Active galactic nuclei AGN are energetic astrophysical sources powered by accretion onto supermassive black holes in galaxies and present unique observational signatures that cover the full electromagnetic spectrum over more than twenty orders of magnitude in frequency. The rich phenomenology of AGN has resulted in a large number of different flavours in the literature that now comprise a complex and confusing AGN zoo. It is increasingly clear that these classifications are only partially related to intrinsic differences between AGN and primarily reflect variations in a relatively small number of astrophysical parameters as well the method by which each class of AGN is selected. Taken together observations in different electromagnetic bands as well as variations over time provide complementary windows on the physics of different substructures in the AGN. In this review we present an overview of AGN multiwavelength properties with the aim of painting their big picture through observations in each electromagnetic band from radio to  rays as well as AGN variability. We address what we can learn from each observational method the impact of selection effects the physics behind the emission at each wavelength and the potential for future studies. To conclude we use these observations to piece together the basic architecture of AGN discuss our current understanding of unification models and highlight some open questions that present opportunities for future observational and theoretical progress.
['Galaxies: active', 'Quasars: supermassive black holes', 'Radio continuum: galaxies', 'Infrared: galaxies', 'X-rays: galaxies', 'Gamma-rays: galaxies', 'Astrophysics - Astrophysics of Galaxies', 'Astrophysics - Cosmology and Nongalactic Astrophysics', 'Astrophysics - High Energy Astrophysical Phenomena']
Active galactic nuclei whats in a name
{"Active Galactic Nuclei: what's in a name?": "P. Padovani GLYPH<1> D. M. Alexander GLYPH<1> R. J. Assef GLYPH<1> B. De Marco GLYPH<1> P. Giommi GLYPH<1> R. C.  \nHickox GLYPH<1> G. T. Richards GLYPH<1> V. Smolˇci´c GLYPH<1> E. Hatziminaoglou GLYPH<1> V. Mainieri GLYPH<1> M. Salvato  \nReceived: June 12, 2017 / Accepted: July 21, 2017  \nAbstract Active Galactic Nuclei (AGN) are energetic astrophysical sources powered by accretion onto supermassive black holes in galaxies, and present unique observational signatures that cover the full electromagnetic spectrum over more than twenty orders of magnitude in frequency. The rich phenomenology of AGN has resulted in a large number of di GLYPH<11> erent 'flavours' in the literature that now comprise a complex and confusing AGN 'zoo'. It is increasingly clear that these classifications are only partially related to intrin-  \nsic di GLYPH<11> erences between AGN, and primarily reflect variations in a relatively small number of astrophysical parameters as well the method by which each class of AGN is selected. Taken together, observations in di GLYPH<11> erent electromagnetic bands as well as variations over time provide complementary windows on the physics of di GLYPH<11> erent sub-structures in the AGN. In this review, we present an overview of AGN multi-wavelength properties with the aim of painting their 'big picture' through observations in each electromagnetic band from radio to GLYPH<13> -rays as well as AGN variability. We address what we can learn from each observational method, the impact of selection e GLYPH<11> ects, the physics behind the emission at each wavelength, and the potential for future studies. To conclude we use these observations to piece together the basic architecture of AGN, discuss our current understanding of unification models, and highlight some open questions that present opportunities for future observational and theoretical progress.  \nKeywords Galaxies: active GLYPH<1> Quasars: supermassive black holes GLYPH<1> Radio continuum: galaxies GLYPH<1> Infrared: galaxies GLYPH<1> X-rays: galaxies GLYPH<1> gamma-rays: galaxies", '1 The Active Galactic Nuclei zoo': "The discovery of quasars (Schmidt, 1963) opened up a whole new branch of astronomy (e.g. D'Onofrio, Marziani, & Sulentic, 2012; Kellermann, 2015, for historical details). Twenty years earlier Seyfert (1943) had reported the presence of broad and strong emission lines in the nuclei of six spiral nebulae (including some by now 'classical' AGN, like NGC 1068 and NGC 4151). However, his work remained largely ignored until Baade & Minkowski (1954) pointed out the similarities between the spectra of the galaxies studied by Seyfert and that of the galaxy they had associated with the Cygnus A radio source.  \nAs implicit in the name, AGN are stronger emitters than the nuclei of 'normal' galaxies. This 'extra' component is unrelated to the nuclear fusion powering stars and is now universally accepted to be connected instead to the presence of an actively accreting central supermassive ( & 10 6 M GLYPH<12> ) black hole (SMBH).  \nAGN have many interesting properties. These include: (1) very high luminosities (up to L bol GLYPH<25> 10 48 erg s GLYPH<0> 1 ), which make them the most powerful non-explosive sources in the Universe and therefore visible up to very high redshifts (currently z = 7 : 1: Mortlock et al., 2011); (2) small emitting regions in most bands, of the order of a milliparsec, as inferred from their rapid variability (e.g. Ulrich, Maraschi, & Urry, 1997), implying high energy densities; (3) strong evolution of their luminosity functions (LFs; e.g. Merloni & Heinz, 2013); (4) detectable emission covering the whole electromagnetic spectrum (this review).  \nThe latter property means that AGN are being discovered in all spectral bands. Di GLYPH<11> erent methods are employed in di GLYPH<11> erent bands to identify these sources but, most importantly, the various wavelength regimes provide di GLYPH<11> erent windows on AGN physics. Namely, the infrared (IR) band is mostly sensitive to obscuring material and dust, the optical / ultraviolet(UV) band is related to emission from the accretion disk, while the X-ray band traces the emission of a (putative) corona. GLYPH<13> -ray and (high flux density) radio samples, on the other hand, preferentially select AGN emitting strong non-thermal (jet [or associated lobe] related) radiation (see Fig. 1) 1 . The surface densities of AGN also vary strongly across the electromagnetic spectrum due to a complex mix of physical processes, selection e GLYPH<11> ects, and technological limitations (as shown in Sect. 8).  \nThe past years have seen a proliferation of AGN classes, which outsiders to the field (but insiders as well!) find mesmerising. A (possibly incomplete) list is given in Tab. 1,  \nTable 1 The AGN zoo: list of AGN classes.  \nThe top part of the table relates to major / classical classes. The last column describes the main properties.  \nWhen these are too complex, it gives a reference to the first paper, which defined the relevant class or, when preceded by 'see', a recent paper, which gives up-to-date details on it. Reference key: 1. Padovani (2016);  \n- 2. Fanaro GLYPH<11> &Riley (1974); 3. Giommi et al. (2012); 4. Weymann, Carswell, & Smith (1981);\n- 5. Ghisellini (2010); 6. O'Dea, Baum, & Stanghellini (1991); 7. Padovani & Giommi (1995);\n- 8. Laing et al. (1994); 9. Heckman & Best (2014); 10. Ho (2008); 11. Osterbrock & Pogge (1985);\n- 12. Sulentic et al. (2002); 13. Osterbrock (1981)  \nFig. 1 A schematic representation of an AGN spectral energy distribution (SED), loosely based on the observed SEDs of non-jetted quasars (e.g. Elvis et al., 1994; Richards et al., 2006a). The black solid curve represents the total emission and the various coloured curves (shifted down for clarity) represent the individual components. The intrinsic shape of the SED in the mm-far infrared (FIR) regime is uncertain; however, it is widely believed to have a minimal contribution (to an overall galaxy SED) compared to star formation (SF), except in the most intrinsically luminous quasars and powerful jetted AGN. The primary emission from the AGN accretion disk peaks in the UV region. The jet SED is also shown for a high synchrotron peaked blazar (HSP, based on the SED of Mrk 421) and a low synchrotron peaked blazar (LSP, based on the SED of 3C 454.3; see Sect. 6.1). Adapted from Harrison (2014). Image credit: C. M. Harrison.  \n<!-- image -->  \nwhich gives the class or acronym in col. (1), its meaning in col. (2), and the main properties or a reference to a relevant paper in col. (3).  \nReality is much simpler, however, as we know that most of these seemingly di GLYPH<11> erent classes are due to changes in only a small number of parameters, namely: orientation (e.g. Antonucci, 1993; Urry & Padovani, 1995; Netzer, 2015), accretion rate (e.g. Heckman & Best, 2014), the presence (or absence) of strong jets (e.g. Padovani, 2016), and possibly the host galaxy and the environment. Sorting out these issues is a pre-requisite to understand AGN physics and the role AGN play in galaxy evolution (e.g. Alexander & Hickox, 2012).  \nTo go beyond taxonomy and paint the AGN 'big picture', which comes out of multi-wavelength surveys, and understand the truly intrinsic and fundamental properties of AGN, the workshop 'Active Galactic Nuclei: what's in a name?' was organised at ESO, Garching, between June 27 and July 1, 2016. This was done by discussing AGN selection and physics in all bands and by addressing:  \n- -the di GLYPH<11> erent types of AGN selected in the various spectral bands;\n- -the similarities and di GLYPH<11> erences they display;\n- -the impact of selection e GLYPH<11> ects on the interpretation of the results;\n- -the physical mechanism(s) behind emission in a given band;\n- -the e GLYPH<11> ective range of black hole (BH) mass ( M BH) and Eddington ratios 2 ( L = L Edd) probed by each selection method;\n- -the possible limitations of current observations and / or facilities.  \nThe workshop consisted of seven di GLYPH<11> erent sessions: radio, IR, optical, X-ray, GLYPH<13> -ray, variability, and multi-frequency. All of the sessions (with the exception of the multi-frequency one) were introduced by a review talk which set the scene, followed by contributed talks, for a total of eighty-six speakers, 48% of whom were women. Sixty-seven posters completed the programme. A summary talk and a discussion  \nsession were held at the end of the workshop 3 . The workshop was very well attended, with 165 participants, covering five continents and thirty-one di GLYPH<11> erent countries; sixty of the participants were students. This review was inspired by the workshop.  \nIn this paper we review our progress in addressing these key issues by discussing radio-, IR-, optical-, X-ray-, GLYPH<13> -ray-, and variability-selected AGN (Sect. 2 - 7). Section 8 summarizes our understanding of AGN and examines some open issues. Throughout this paper, spectral indices are defined by S GLYPH<23> / GLYPH<23> GLYPH<0> GLYPH<11> and the values H 0 = 70 km s GLYPH<0> 1 Mpc GLYPH<0> 1 , GLYPH<10> m = 0 : 27, and GLYPH<10>GLYPH<3> = 0 : 73 have been used. The acronyms of the AGN classes mentioned in this paper are defined in Tab. 1.", '2 Radio-selected AGN': "In this section we describe radio-selected AGN. The types of, and physical mechanisms powering, radio-AGN are outlined in Sect. 2.1. Selection e GLYPH<11> ects are discussed in Sect. 2.2, while the evolution of radio-AGN and future prospects are addressed in Sect. 2.3 and 2.4, respectively. Typical observing frequencies in the radio regime range from about 10 MHz ( GLYPH<21> GLYPH<24> 30 m) up to a few tens of GHz (e.g. 30 GHz, GLYPH<21> = 1 cm). For other recent reviews of radio-selected AGN we refer to Heckman & Best (2014); Padovani (2016); Tadhunter (2016); Smolˇci'c (2016).", '2.1 Physical mechanism(s) and types of AGN selected in the radio': "The dominant emission process in the radio band is synchrotron emission, i.e. radiation by charged particles gyrating at relativistic velocities through magnetic fields 4 . Being non-thermal in origin, this emission is usually parametrized by a power law of the form S GLYPH<23> / GLYPH<23> GLYPH<0> GLYPH<11> where S GLYPH<23> is the flux density [expressed in Jy, mJy, etc.] at frequency GLYPH<23> , and GLYPH<11> is the spectral index. Supernova remnants and processes related to the central SMBH are the main sources of synchrotron radiation in galaxies, resulting in two dominant galaxy populations identified in extragalactic radio continuum surveys, namely star forming galaxies (SFGs) and AGN (e.g. Miley 1980; Condon 1992). The former, being intrinsically weaker radio sources, become more prominent at the faintest radio flux densities (e.g. Wilman et al. 2008; Padovani et al. 2015;  \nPadovani 2016; Smolˇci'c et al. 2017a). We outline here the main classes of radio emitting AGN.  \nFig. 2 Examples of FR I (panel 'a'; 3C 449; Perley, Willis, & Scott 1979), FR II (panel 'b'; 3C 175; Bridle et al. 1994), wide-angle tail (panel 'c'; 3C83.1B; Owen, Burns, & Rudnick 1978), and X-shaped (panel 'd'; 3C 223.1; Dennett-Thorpe et al. 2002) RGs.  \n<!-- image -->", '2.1.1 Radio galaxies': 'Fanaro GLYPH<11> & Riley (1974) di GLYPH<11> erentiated radio galaxies (RGs) into type I and II based on the ratio of the separation of the highest surface brightness regions on opposite sides of the central galaxy, and the extent of the source measured from the lowest surface brightness contour 5 (see Fig. 2). These classes are commonly referred to in the literature as FR I (ratio < 0 : 5) and FR II (ratio > 0 : 5) RGs, where the first (second) are often described as core- (edge-) brightened. They also separate in the radio luminosity vs. optical host galaxy luminosity plane (Ledlow & Owen 1996; see also Fig. 11 in Buttiglione et al. 2010). Recently a third class, FR 0, was suggested by Baldi, Capetti, & Giovannini (2015, see also Baldi & Capetti 2010), which includes RGs sharing the properties of FR Is but lacking prominent extended radio emission, being a factor of GLYPH<24> 30 more core-dominated. Further morphological classes often found in the literature refer to bent or warped appearances of the RGs (e.g. wide-angle tail, narrow-angle tail, X-shaped RGs; see Fig. 2; see also Miley 1980 for a review, and Figs. 6 and 7 therein).', '2.1.2 Flat- and steep-spectrum sources': "When multiple radio continuum frequency observations are available, radio sources are usually separated into two main groups of steep ( GLYPH<11> GLYPH<21> 0 : 5) and flat ( GLYPH<11> < 0 : 5) radio spectrum sources (e.g. Wall 1975; Peacock & Gull 1981; Willott et al. 2001; Kimball & Ivezi'c 2008), which roughly correspond, with some exceptions, to extended and compact sources. They can further be classified as, e.g. USS (e.g. De Breuck et al. 2001), GPS, and CSS sources (see Sadler 2016 and O'Dea 1998 for reviews). FSRQs and BL Lacs, both of which are flat spectrum sources, make up the blazar class, which includes AGN hosting jets oriented at a very small angle ( . 15 GLYPH<0> 20 GLYPH<14> ) with respect to the line of sight (e.g. Urry & Padovani 1995; Giommi, Padovani & Polenta 2013; see also Sect. 6). The two sub-classes main di GLYPH<11> erence lies in their optical spectra, with FSRQs displaying strong, broad emission lines just like standard quasars, and BL Lacs instead showing at most weak emission lines, sometimes exhibiting absorption features, and in many cases being completely featureless. Blazars dominate the bright radio (e.g. Padovani, 2016) and the GLYPH<13> -ray sky (Sect. 6.1). In this respect, we note that a strong radio flux density is one of the most efficient (albeit incomplete) AGN selection criteria: out of the 527 sources with 5 GHz flux density > 1 Jy and j b II j GLYPH<21> 10 GLYPH<14> (Kuehr et al., 1981) only one, M 82, is not an AGN (and only two do not belong to the RG, radio quasar, or blazar classes: M82 and NGC 1068).", '2.1.3 RL and RQ AGN': "One of the most used classifications of radio AGN is their division into RL and RQ AGN. Initially, this distinction was defined in the context of quasars ( M B < GLYPH<0> 23) with the threshold between the two classes set either in: (1) radio flux density or luminosity (e.g. Peacock, Miller, & Longair 1986); (2) or the ratio of radio-to-optical flux density or luminosity (e.g. Schmidt 1970). Radio loudness has since then been defined in di GLYPH<11> erent ways in the literature but in any case these 'classical' definitions apply only to type 1 AGN (Padovani et al., 2011; Bonzini et al., 2013). Following Balokovi'c et al. (2012) the parametrization of radio loudness for type 1 AGN can be summarized as R K = log L radio GLYPH<0> K GLYPH<1> log L GLYPH<1> GLYPH<21> . K = 0 for a simple radio flux density or luminosity threshold (where Lradio may refer to flux density or luminosity measurements at frequencies GLYPH<24> 1 GLYPH<0> 6 GHz in the observed- or rest-frame, respectively; Peacock, Miller, & Longair 1986; Miller, Peacock, & Mead 1990; Ivezi'c et al. 2002), and K = 1 for a threshold in the logarithm of the ratio of flux density or luminosity in the radio band and that within a wavelength range GLYPH<1>GLYPH<21> , which can either be in the optical (e.g. B-band; Kellermann et al. 1989; r-, i-, or z-band; Ivezi'c et al. 2002) or IR (e.g. 24 GLYPH<22> m; Padovani et al. 2011; Bonzini et al. 2013).  \nPadovani (2016) (see also Padovani, 2017) has argued that the distinction between these two types of AGN is not simply a matter of semantics but rather that the two classes represent intrinsically di GLYPH<11> erent objects, with RL AGN emitting a large fraction of their energy non-thermally and in association with powerful relativistic jets, while the multiwavelength emission of RQ AGN is dominated by thermal emission, directly or indirectly related to the accretion disk (see Fig. 1). Moreover, he pointed out that the 'radio-loud / radio-quiet' classes are obsolete, misleading, and inappropriate. Since the major physical di GLYPH<11> erence between these two classes is the presence or lack of strong relativistic jets, which also implies that the two classes reach widely di GLYPH<11> erent maximum photon energies (see his Sect. 2.3 and Fig. 1), we will be using in this review the terms 'jetted' and 'non-jetted' instead of RL and RQ AGN. We discuss this further in Sect.  \n8.  \nNote that, although we know that jetted AGN represent a minority, their exact fraction is still not well determined. The oft-quoted value of GLYPH<25> 15% comes from optically selected samples of quasars (e.g. Kellermann et al., 1989). Padovani (2011), by integrating the radio LFs of jetted and non-jetted AGN, has suggested a much smaller fraction ( < 1%).", '2.1.4 Low- and high-excitation AGN': "The classification of radio AGN into two main classes based on their optical spectroscopic properties goes back to Hine & Longair (1979). They divided the Third Cambridge Catalogue of Radio Sources (3CR) into objects characterized by strong emission lines in their spectra ([O ii ] GLYPH<21> 3727, [O iii ] GLYPH<21> 5007, [Ne ii ] GLYPH<21> 3867), and sources which exhibited either absorption line spectra typical of giant elliptical galaxies (absorption line galaxies hereafter) or weak [O ii ] GLYPH<21> 3727 emission lines. Since then this has been expanded and refined by using also [O iii ] GLYPH<21> 5007 equivalent widths (EWs; e.g. Tadhunter et al. 1998) or high / low excitation / ionization emission line criteria (Laing et al. 1994; Kewley, Groves, Kau GLYPH<11> -mann, & Heckman 2006; Buttiglione et al. 2009, 2010; see Fig 3). In general, objects without and with high-excitation emission lines in their optical spectra are referred to as LEGs and HEGs, respectively. The LEG / HEG classification holds not only for radio selected AGN but applies also to AGN selected in other bands (for which an optical spectroscopic classification is available). More specifically, quasars and Seyferts belong to the HEG category, while LINERs and absorption line galaxies are classified as LEGs (see Fig. 3 and Sect. 4; Baldwin, Phillips, & Terlevich 1981; Veilleux & Osterbrock 1987; Kewley et al. 2001; Kau GLYPH<11> mann et al. 2003a; Kewley, Groves, Kau GLYPH<11> mann, & Heckman 2006. But see Sarzi et al. 2010 for evidence that the nebular emission of most objects in the LINER part of Fig. 3 is not powered by an AGN).  \nFig. 3 Optical spectroscopic diagnostic diagrams (see Kewley et al. 2001; Kau GLYPH<11> mann et al. 2003b; Kewley, Groves, Kau GLYPH<11> mann, & Heckman 2006) that separate emission-line galaxies into star forming, composite galaxies, and Seyfert and LINER AGN. Small grey dots represent galaxies from the Sloan Digital Sky Survey (SDSS) DR4 'main' spectroscopic sample. Large open squares (filled dots) denote z < 0 : 1 Revised Third Cambridge Catalogue of Radio Sources (3CRR; Laing, Riley, & Longair, 1983) RGs independently classified based on their core X-ray emission as systems with radiatively e GLYPH<14> cient (ine GLYPH<14> cient) BH accretion (Evans et al., 2006). c GLYPH<13> AAS. Figure reproduced from Smolˇci'c (2009), Fig. 1, with permission.  \n<!-- image -->  \nFig. 4 From left to right the top panels show the distribution of the observed g GLYPH<0> r colour, 4000 Å break strength, and stellar mass, while the bottom panels show the distribution of the velocity dispersion, GLYPH<27> 4 , proportional to BH mass (Tremaine et al., 2002), and log( L [O iii ] =GLYPH<27> 4 ) proportional to BH accretion rate (in Eddington units; Heckman et al. 2004) for various galaxy populations drawn from the FIRST-NVSSSDSS sample with 0 : 04 < z < 0 : 1 (SFGs: dotted lines and empty histograms; Seyferts: dash-dotted lines and diagonally hatched histograms; absorption line galaxies: dashed lines and vertically hatched histograms; LINERs: full lines and filled histograms). c GLYPH<13> AAS. Figure reproduced from Smolˇci'c (2009), Fig. 2 and 3, with permission.  \n<!-- image -->  \nAs illustrated in Fig. 4 fundamental physical di GLYPH<11> erences between these two types of radio AGN (at z < 1) have been found (e.g. Nagar, Falcke, & Wilson 2005; Evans et al. 2006; Hardcastle, Evans, & Croston 2007; Smolˇci'c et al. 2009; Smolˇci'c 2009; Buttiglione et al. 2010; Best & Heckman  \n2012; Padovani et al. 2015; see also Fig. 6 in Smolˇci'c 2016). Namely, LEGs (LINERs and absorption line systems) have on average redder optical g GLYPH<0> r colours, larger values of the 4000 Å break strength, and higher stellar masses than HEGs (Seyferts; top panel). LEGs are also shown (bottom panel) to exhibit radiatively ine GLYPH<14> cient accretion related to low L = L Edd ( . 0 : 01), possibly fuelled by the hot phase of the inter-galactic medium (IGM), and are typically highly e GLYPH<14> cient in collimated jet production. HEGs accrete in a radiatively e GLYPH<14> cient manner, at high Eddington rates (0 : 01 . L = L Edd . 1), are fuelled by the cold IGM phase, and (on average) less likely to launch collimated jets. From a theoretical aspect, the observed di GLYPH<11> erence in L = L Edd can be related to the switch between a standard accretion, i.e. radiatively e GLYPH<14> cient, geometrically thin (but optically thick) disk accretion flow (Shakura & Sunyaev 1973), and a radiatively ine GLYPH<14> cient, geometrically thick (but optically thin) disk accretion flow (Esin, 1997; Narayan et al., 1998). The switch occurs at accretion rates below a certain L = L Edd ( GLYPH<25> 0 : 01; Rees, Begelman, Blandford, & Phinney 1982; Narayan & Yi 1994; Meier 2002; Fanidakis et al. 2011) as then the decreased accreting gas density lowers the cooling rate, and a substantial amount of heat can be carried along, i.e. advected, rather than irradiated 6 .", '2.1.5 Radio-selected AGN classes and unification': "There is some overlap amongst the classes described above. For example, almost all FR Is are LEGs, while most FR IIs usually display strong emission lines and would thus be classified as HEGs. However, there is no one-to-one correspondence between FR class and emission lines as quite a few FR IIs ( & 20%: e.g. Gendre et al., 2013) have been found to be LEGs (see also Evans et al. 2006; Buttiglione et al. 2010; Mingo et al. 2014). Powerful radio quasars and RGs are generally of the HEG type, while the less powerful (and more common) RGs are mostly LEGs (e.g. Padovani, 2016). 'Classical' non-jetted AGN (i.e. Seyferts and quasars) are always HEGs.  \nMoreover, radio quasars are intrinsically the same sources as some RGs. Namely they are simply FR II / HEG RGs with their jets at an angle . 45 GLYPH<14> with respect to the line of sight (Orr & Browne, 1982; Barthel, 1989; Antonucci, 1993; Urry &Padovani, 1995). The fact that radio quasars display strong and Doppler broadened lines in their optical spectra (with  \nfull width half maximum [FWHM] & 1 ; 000 km s GLYPH<0> 1 ), unlike RGs, requires also the presence of dust in a flattened configuration roughly perpendicular to the jet (see also Sect. 3.1). This so-called 'unification model' explains in a natural way why the (projected) sizes of the jets of RGs are larger than those of quasars (Barthel, 1989).  \nWith regard to FR I / LEGRGs, obscuration towards their nuclei appears to be much smaller than that of their FR II / HEG relatives (e.g. Chiaberge et al., 2002; Evans et al., 2006), which indicates that dust might be not present (see also Sect. 3.2.4). This applies also to the population of FR II / LEG RGs. LEG RGs, therefore, irrespective of their radio morphology, are 'unified' with BL Lacs (e.g. Giommi, Padovani &Polenta, 2013).", '2.1.6 Classification of radio-selected AGN': "The classification of radio-selected AGN is a complex matter, especially so for the faint radio sources routinely studied these days. Getting optical spectra for their counterparts is very time consuming, prohibitively so for the very faint tail [ R & 26] even with 8-10m class telescopes. But even if we had optical spectra for all radio sources, optical-based classification is well known to be prone to obscuration biases (Sect. 4.3) and for this reason spectra need to be complemented with information from multi-wavelength ancillary data. Multi-wavelength methods used in the literature to identify AGN detected also in the radio band include: (1) rest-frame optical colours of the host galaxies, which have been shown to correlate with the galaxies spectral emission line properties (Strateva et al. 2001; Smolˇci'c et al. 2006, 2008; Smolˇci'c 2009; Ilbert et al. 2010); (2) X-ray luminosity ( L X > 10 42 erg s GLYPH<0> 1 ; e.g. Szokoly et al. 2004; see also Sect. 5.2); (3) mid-IR (MIR) colours (e.g. Lacy et al. 2004; Stern et al. 2005; Donley et al. 2012; see also Sect. 3.2.1); (4) multiple component SED fitting using sets of galaxy and AGN templates (Berta et al. 2013; Delvecchio et al. 2014, 2017); (5) excess of radio luminosity relative to a tracer of the SF rate (SFR) in the host galaxy (e.g. far or total IR luminosity; Condon 1992; Del Moro et al. 2013; Delvecchio et al. 2017). A detailed discussion of these methods (and others) can be found in Padovani (2016).", '2.2 Selection e GLYPH<11> ects: SF contribution to the total radio luminosity output': "In the local universe LEGs occupy the red sequence of galaxies, while HEGs are hosted by bluer galaxies, populating the so-called green valley (see Fig. 4 in Smolˇci'c 2009). As, generally, bluer host galaxy colours imply higher SFRs (e.g. Ilbert et al. 2009), in the latter case the observed radio emission could be partially or entirely due to synchrotron radiation generated by supernova remnants, rather than by the  \ncentral SMBH. As the classification of radio AGN often relies on non-radio properties, such as the optical emission line properties or multi-wavelength proxies (Sect. 2.1.6), an a-posteriori assessment of the (SF- or AGN-related) origin of the observed radio emission is needed as X-ray, optical, or IR signatures of an accreting central SMBH do not necessarily imply AGN-related radio emission. Thus, one of the most severe selection e GLYPH<11> ects in the radio band is the contribution of SF-related processes to the total radio power 7 (especially given the limited angular resolution available in many radio continuum surveys).  \nDetailed high angular resolution radio continuum studies often reveal a mixture of SF- and accretion-related radio emission in non-jetted HEGs (e.g. Chi, Barthel, & Garrett 2013; Maini et al. 2016; Herrera Ruiz et al. 2016). For example, Maini et al. (2016) used the Australian Long Baseline Array to search for compact radio cores in four nonjetted AGN located in the Extended Chandra Deep Field -South (E-CDFS). They find that some such sources contain an active AGN that can contribute significantly ( > 50%) to the total radio emission. Herrera Ruiz et al. (2016) studied three non-jetted quasars ( MB < GLYPH<0> 23) in the COSMOS field observed with the Very Large Array (VLA) and the Very Long Baseline Array (VLBA) at 1 : 5 00 and < 20 mas resolutions, respectively. Comparing the core (VLBA) and total (VLA) radio flux densities they infer that 50-75% of the radio emission in these sources is powered by AGN activity. Such high-angular resolution studies are, however, still limited to rather small samples, and to-date the main source of radio emission in the most powerful AGN (i.e. Mi < GLYPH<0> 22) is still debated. While agreement exists that radio emission in jetted quasars is powered by SMBH accretion-related processes (e.g. Miller, Peacock, & Mead 1990), opposing (statistical) evidence can be found in the literature related to the origin of radio emission in non-jetted quasars (the so-called quasar radio loudness dichotomy problem): SF in the host galaxies (Kimball et al., 2011; Condon et al., 2013), or AGN activity (White, Jarvis, Haußler, & Maddox 2015, Zakamska et al. 2016; see also Padovani 2016 for a detailed discussion of this topic).  \nFrom a statistical point of view, studies of radio AGN drawn from large radio-continuum surveys, combined with spectroscopic and / or multi-wavelength data find that ( z < 1) HEGs are much more likely to be associated with SF in their host galaxies, with SFRs at least a factor 3 GLYPH<0> 4 higher than those in LEGs (Hardcastle et al. 2013; see also Gurkan et al. 2015). The inferred statistical contribution of SF-related processes to the observed radio emission in HEGs and LEGs (0 : 04 < z . 0 : 2) is estimated to be GLYPH<24> 60% ( GLYPH<24> 10%) for HEGs (LEGs; Mori'c et al. 2010). Similarly, Bonzini et al.  \n(2015) find that the radio luminosities of non-jetted AGN at z GLYPH<24> 1 : 5 GLYPH<0> 2 in the E-CDFS survey are consistent with the galaxies' SFRs inferred from their FIR luminosities. Identifying AGN in a slightly di GLYPH<11> erent way, Delvecchio et al. (2017) observe that for about 70% of their AGN the radio luminosities are consistent (within 3 GLYPH<27> from the average) with those expected based on the SFR in the host galaxies inferred from the total IR emission (corrected for the AGN component).", '2.3 Cosmic evolution of radio-selected AGN': "Past research has shown that radio AGN evolve via a 'downsizing' e GLYPH<11> ect, i.e. low radio luminosity sources evolve less strongly than high-luminosity ones (e.g. Longair 1966; Willott et al. 2001; Rigby et al. 2015; see also Sect. 5.3 for the Xray perspective). Studies of powerful radio AGN (L1 : 4GHz & 2 GLYPH<2> 10 26 WHz GLYPH<0> 1 ) have found a strong positive density evolution at z . 2, beyond which their comoving volume density declines (Dunlop & Peacock, 1990; Willott et al., 2001). A substantially slower evolution, with a lower redshift ( z GLYPH<24> 1 GLYPH<0> 1 : 5) comoving volume density turnover, has been found for weaker radio AGN (L1 : 4GHz > 2 GLYPH<2> 10 25 WHz GLYPH<0> 1 ; Waddington, Dunlop, Peacock, & Windhorst 2001). Studies of even lower luminosity radio AGN (L1 : 4GHz . 10 25 WHz GLYPH<0> 1 ) find a mild evolution out to z GLYPH<24> 1 (e.g. Smolˇci'c et al. 2009; Sadler et al. 2007; Donoso, Best, & Kau GLYPH<11> mann 2009; Padovani et al. 2011; Smolˇci'c et al. 2017b).  \nThe local radio LFs derived separately for HEGs and LEGshave been presented by e.g. Filho, Barthel, & Ho (2006), Best & Heckman (2012), Gendre et al. (2013), Pracy et al. (2016). While it is clear that HEGs dominate the volume densities at high radio luminosities (L1 : 4GHz > 10 26 WHz GLYPH<0> 1 ; Heckman & Best 2014; Pracy et al. 2016), the slope of the low-luminosity end of the HEG radio LF is still somewhat unclear. Best & Heckman (2012) find a significantly flatter slope than Pracy et al. (2016) 8 , and Filho, Barthel, & Ho (2006) 9 (see Fig. 8 in Pracy et al. 2016). As discussed in Pracy et al. (2016) this is likely due to the di GLYPH<14> culty of disentangling the real contribution of AGN-related radio emission in HEGs within the faint radio luminosity regime, dominated by SFGs. Regardless of the faint end slope, studies out to z GLYPH<24> 1 consistently find that HEGs evolve more rapidly than LEGs. For example, Pracy et al. (2016) find that their LEG population displays little or no evolution over the observed redshift range (0 : 005 < z < 0 : 75), evolving as (1 + z ) 0 : 06 + 0 : 17 GLYPH<0> 0 : 18 [(1 + z ) 0 : 46 + 0 : 22 GLYPH<0> 0 : 24 ] assuming pure density [pure luminosity] evolution, while their HEG population evolves  \nmore rapidly, as (1 + z ) 2 : 93 + 0 : 46 GLYPH<0> 0 : 47 [(1 + z ) 7 : 41 + 0 : 79 GLYPH<0> 1 : 33 ] assuming pure density [pure luminosity] evolution.  \nConstraining the cosmic evolution of the two dominant AGN types detected in the radio band beyond redshift 1 ( z . 6) is not trivial given the di GLYPH<14> culty of: (1) separating the two distinct AGN types so that they can quantitatively be related to the HEG / LEG populations identified via optical spectroscopy at z < 1; (2) isolating the fraction of radio luminosity arising from the AGN (rather than SF in the host galaxy), which is challenging even in the lower ( z < 1) redshift universe. Recently, Padovani et al. (2015) have constrained the cosmic evolution of their selected nonjetted and jetted AGN identified in the E-CDFS survey out to z GLYPH<24> 4. These two populations can qualitatively be roughly related to the HEG and LEG populations respectively (see Bonzini et al. 2013; Padovani et al. 2015). Padovani et al. find a strong evolution, similar to that for SFGs, of their non-jetted sample throughout the redshift range probed, and a peak at z GLYPH<24> 0 : 5 in the number density of their jetted AGN, with a decline at higher redshifts. The first results using the VLA-COSMOS 3 GHz Large Project (Ceraj et al., in prep.), combined with the COSMOS multi-wavelength data (Laigle et al., 2016; Marchesi et al., 2016), yield a stronger cosmic evolution for AGN with the highest bolometric (radiative) luminosities throughout the entire redshift range ( z . 6; and qualitatively broadly consistent with HEG samples), relative to that of the AGN sample with lower bolometric (radiative) luminosities (and qualitatively broadly consistent with LEG samples) 10 . We stress however that both the E-CDFS and COSMOS fields are not large enough to constrain the broad radio luminosity range, encompassing also the rare, highest luminosity AGN (detectable in shallower, wide-area surveys). Hence, for a full, quantitative assessment of the evolution of the AGN radio LF separated into the two types out to high redshift and over a broad luminosity range a combination of surveys with various areal coverages is needed, with access to a robust AGN classifier, and methods to isolate AGN-related radio emission in (low radio luminosity) AGN, that can be uniformly applied throughout the entire redshift range considered.", '2.4 The future of AGN studies in the radio band': 'Studies such as those discussed in the previous section are becoming feasible only now, and will be invigorated with  \nthe onset of the Square Kilometre Array (SKA 11 ), o GLYPH<11> ering an observing window between 50 MHz and 20 GHz extending well into the nanoJy regime with unprecedented versatility, in combination with contemporaneous projects over the entire electromagnetic spectrum (such as, e.g., the Large Synoptic Survey Telescope [LSST], Euclid , the Extended ROentgen Survey with an Imaging Telescope Array (eROSITA), and the James Webb Space Telescope [JWST]).  \nArevolution has in fact started in radio astronomy, which has entered an era of large area surveys reaching flux density limits well below current ones. The Jansky Very Large Array (JVLA 12 ), the LOw Frequency ARray (LOFAR 13 ), the Murchison Widefield Array 14 , are already taking data, and are being joined by the Australian Square Kilometre Array Pathfinder (ASKAP 15 ), MeerKAT 16 , e-MERLIN 17 , and APERTIF 18 . These projects will survey the sky vastly faster than it is possible with existing radio telescopes producing surveys covering large areas of the sky down to fainter flux densities than presently available, as fully detailed in Norris et al. (2013). This, amongst other things, will revolutionise AGNstudies. The Evolutionary Map of the Universe (EMU; Norris et al., 2011), one of the ASKAP surveys, for example, is expected to detect GLYPH<24> 70 million sources, about half of which will likely be AGN una GLYPH<11> ected by the problems of obscuration, which plague the optical (Sect. 4.3) and soft X-ray (Sect. 5.2) bands. Identifying AGN in these new radio surveys, however, will not be straightforward and will require many synergies with facilities in other bands (e.g. Padovani, 2016).', '3 Infrared-selected AGN': 'IR studies have had a strong impact on our understanding of AGN structure, their evolution through cosmic time, and their role in galaxy evolution. In Sect. 3.1 we discuss the mechanisms that give rise to the IR emission in AGN and the advantages of AGN identification in the MIR wavelengths. In Sect. 3.2 we examine in detail how the MIR selection of AGNworks and what the characteristics of the selected samples are. In Sect. 3.3 and 3.4 we explore additional AGN selection criteria that rely on IR observations. Finally, in Sect. 3.5 we analyse the future of AGN studies in the IR in light of upcoming facilities. For the purpose of this section, we divide the IR SED of AGN in three wavelength regimes: the  \n- 14 www.mwatelescope.org\n- 15 www.atnf.csiro.au/projects/askap/\n- 16 www.ska.ac.za/meerkat\n- 17 www.e-merlin.ac.uk  \nnear-IR (NIR; 1 GLYPH<0> 3 GLYPH<22> m), the MIR (3 GLYPH<0> 50 GLYPH<22> m), and the FIR (50 GLYPH<0> 500 GLYPH<22> m).', '3.1 Physical mechanism behind IR emission': "Despite many drawbacks, the 'dusty torus' paradigm has been quite successful in explaining the appearance of a wide variety of AGN. The basis of this paradigm is the presence of dust surrounding the accretion disk on scales larger than that of the broad line region (BLR), with an inner boundary set by the sublimation temperature of the dust grains (Barvainis, 1987). This dust reprocesses the emission of the accretion disk into the IR and dominates the AGN SED from wavelengths longer than GLYPH<24> 1 GLYPH<22> m up to a few tens of micron (see Fig. 1). It plays a fundamental role in the AGN unification scheme (Antonucci, 1993; Urry & Padovani, 1995, see also Sect. 2.1.5), as through polarisation studies it was established that the di GLYPH<11> erence between type 1 and 2 AGN is simply an e GLYPH<11> ect of orientation with respect to the dust. In type 2 AGN the dust obscures the line of sight towards the accretion disk and the BLR and only narrow emission lines can be observed in the optical spectrum (e.g. Antonucci & Miller, 1985; Antonucci, 1993, although see Elitzur & Netzer 2016 for a discussion about possible real type 2 AGN where the di GLYPH<11> erence is not caused by dust obscuration; see also Sect. 5.3).  \nThere is a significant debate in the literature over whether the dust is smoothly distributed in the torus (Pier & Krolik, 1992; Dullemond & van Bemmel, 2005; Fritz, Franceschini, & Hatziminaoglou, 2006), whether it is clumpy in the form of optically and geometrically thick clouds (Krolik & Begelman, 1988; Nenkova, Ivezi'c, & Elitzur, 2002; Nenkova et al., 2008; Elitzur & Shlosman, 2006; Tristram et al., 2007), or a combination of the two (Stalevski et al., 2012; Assef et al., 2013). Observations of the strength of the silicate feature at 9.7 GLYPH<22> m in AGN, for example, seem to favour models where the dust is most prominently clumpy (Nenkova et al., 2008; Nikutta et al., 2009; Hatziminaoglou et al., 2015), but Feltre et al. (2012) has argued that observations are not yet able to discriminate between the di GLYPH<11> erent models. Recent ground-based MIR interferometric observations, on the other hand, suggest that a large proportion of the dust might, instead, reside in the walls of the ionization cone (Asmus, Honig, & Gandhi, 2016, and references therein), at least in a fraction of nearby AGN (L'opezGonzaga et al., 2017). For simplicity and compatibility with the rest of the literature, we will refer to this structure as the 'dusty torus' throughout this section, despite evidence that this dust component may have a significantly more complex distribution (e.g. Nenkova et al., 2008).  \nA number of authors have studied the fraction of linesof-sight that are obscured by the dusty torus, either by comparing the relative fraction of type 1 and 2 AGN at a given  \nredshift, or by modelling the SED of individual objects. Average obscured fractions of 40% to 75% are reported in the literature (see, e.g. Treister et al., 2004; Hatziminaoglou et al., 2009; Assef et al., 2013; Roseboom et al., 2013). However, a single number does not englobe the diversity of AGN in Nature. Some authors have found that the fraction of obscured lines-of-sight diminishes with increasing luminosity of the accretion disk (Ueda et al., 2003; Hasinger, 2004; Simpson, 2005; Hatziminaoglou et al., 2008; Assef et al., 2013; Mateos et al., 2016), an e GLYPH<11> ect typically referred to as the receding torus (Lawrence, 1991), although others have found no evidence of such an e GLYPH<11> ect (Wang & Jiang, 2006; Lawrence & Elvis, 2010; Honig et al., 2011; Lacy et al., 2013; Stalevski et al., 2016, see also Sect. 5.3). Additionally, some authors have found a significant variance in the amount of dust in AGN (e.g. Roseboom et al., 2013), with some showing little to no dust (see Sect. 3.2.4) and some showing very large amounts (e.g. Mateos et al., 2016). Furthermore some authors have found a larger fraction of obscured sources at the highest luminosities (Banerji et al., 2012; Assef et al., 2015), suggesting a more complex scenario, and possibly consistent with models where AGN dust obscuration evolves through time (Sanders et al., 1988; Hopkins et al., 2008).  \nAs already mentioned, the emission of the dusty torus is very prominent in the MIR for both type 1 and type 2 AGN. Dust emission from SF can rival in luminosity the AGN but with typically much cooler temperatures . 40 K (e.g. Magnelli et al., 2012). As significant SF activity is regularly ongoing in the host galaxies of many AGN, it is more likely to dominate the FIR (e.g. Hatziminaoglou et al., 2010). At rest-frame NIR wavelengths, where the AGN emission has a local minimum at the cross-over between the dropping accretion disk emission and the rising dust emission, the stellar 1.6 GLYPH<22> mpeak can severely hamper AGN identification. As the stellar emission drops steeply longward of the 1.6 GLYPH<22> m peak, stellar contamination is less of an issue in the MIR (although see Sect. 3.2.5). Hence, the MIR wavelengths are the optimal IR wavelengths for AGN identification.", '3.2.1 Broad-band MIR AGN identification': "The large sky background and water absorption by the Earth's atmosphere make ground-based MIR observations challenging. Spaceborne telescopes are, therefore, better suited for the identification of large AGN samples. In what follows, we focus solely on selection using space-based broad-band photometry, as they account for the great majority of MIR identified AGN, although most implications and many of the caveats also apply to ground-based and to spectroscopic observations. We explore those further in Sect. 3.4.  \nAnumber of AGN MIR selection criteria have been proposed over the years. The first ones were already developed for the Infrared Astronomical Satellite (IRAS) mission (de Grijp et al., 1985, 1987; Leech et al., 1989), and their number has grown enormously since, with the advent, in the past decade, of the Spitzer Space Telescope (Werner et al. 2004; see, e.g. Lacy et al. 2004; Lacy et al. 2007, 2013; Stern et al. 2005; Hatziminaoglou et al. 2005; Donley et al. 2012), AKARI (Murakami et al., 2007; Oyabu et al., 2011), and the Wide-field Infrared Survey Explorer (WISE: Wright et al. 2010; see, e.g. Stern et al. 2012; Mateos et al. 2012; Wu et al. 2012b; Assef et al. 2013). These selection criteria have typically been calibrated against independent AGN selection methods and rely primarily on colours to separate AGN from stars or galaxies with inactive nuclei, as AGN are expected to be significantly redder in the shorter wavelength MIR bands (e.g. Stern et al., 2005). We note that the latter is not necessarily true for AGN at redshifts where the H GLYPH<11> emission line contaminates the shortest wavelength channels, which can lead to significant biases against 4 . z . 5 AGN in some cases (Richards et al., 2009b; Assef et al., 2010), but is generally true otherwise.  \nAssef et al. (2013) presented an interesting comparison between the WISE- and Spitzerbased 19 selection criteria. These are listed in Table 2 and shown in Fig. 5 20 . Using a sample of large, multi-wavelength, spectroscopically identified AGN they determined how reliable and complete each criterion is. The results are shown for two W2 limiting Vega magnitudes, namely W 2 < 15 : 05 on the left, representative of the shallowest fields in the WISE mission, and W 2 < 17 : 1 on the right, that probes down to a 3 GLYPH<27> depth. Figure 5 shows that shallow and deep surveys need to be analysed separately. For the shallow surveys, most selection criteria recover samples with high reliability and completeness. For deeper surveys, however, the situation is di GLYPH<11> erent. Most selection criteria line up diagonally in the diagram trading completeness for reliability. One should also keep in mind that due to their lower sensitivity, the completeness of selection criteria relying on the W3 and W4 bands is lower than the completeness obtained using criteria derived based on a W2-limited sample. A selection relying on these longer wavelengths can be of particular use in the WISE fields closer to the ecliptic poles, where the sur-  \nvey scan pattern is denser and the shorter wavelength bands reach the confusion limit (e.g. Jarrett et al., 2011).  \n3.2.2 Comparison with general AGN identification at other wavelengths  \nMIR AGN identification is considerably less sensitive to obscuration of the central engine by dust compared to optical identification, as dust opacity is lower at longer wavelengths, and is therefore better for the selection of obscured AGN than optical identification, although its sensitivity to obscured AGN decreases with increasing redshift due to the K-correction (e.g. Assef et al., 2011).  \nAs discussed in Sect. 5.2, X-rays are also sensitive to obscured sources, especially in the harder X-ray energies, which are less a GLYPH<11> ected by neutral hydrogen absorption. The main advantage of the MIR over the X-rays is that the integration times needed for AGN identification are much shorter, and hence allow for faster survey speeds. For example, Gorjian et al. (2008) finds that 97.5% of all sources in the 5 ks integrations of Chandra X-ray Observatory of the XBootes survey (0.5 - 7.0 keV flux > 8 GLYPH<2> 10 GLYPH<0> 15 erg cm GLYPH<0> 2 s GLYPH<0> 1 ; Murray et al., 2005) have counterparts detected in the 90 s integrations of the IRAC Shallow Survey ( f 3 : 6 GLYPH<22> m > 12 : 3 GLYPH<22> Jy; Eisenhardt et al., 2004). Of the X-ray sources without an IR match, 40% might be spurious. Furthermore, MIR identification can find AGN that are hard to detect in the X-rays, either due to obscurations or to intrinsic X-ray faintness (e.g. Stern et al., 2012, see also Sect. 5.2).  \nHowever, MIR identification is a GLYPH<11> ected by contaminants and biases that are only marginally relevant to X-ray or optical selections. In the next sections we discuss these issues, which need to be taken into account when drawing statistical conclusions about the AGN population from MIR selected samples.", '3.2.3 Contaminants': 'As mentioned earlier, AGN selection using MIR broad-bands mostly relies on the typically redder colours of AGN, particularly in the observed 3-5 GLYPH<22> m wavelength range. However, there are a number of di GLYPH<11> erent populations that can mimic the colours of AGN in these bands and will a GLYPH<11> ect most selection criteria, although the extent will depend on each specific selection. At redshift GLYPH<24> 0 : 2, strongly SFGs with powerful polycyclic aromatic hydrocarbon (PAH) emission can have red enough colours to be confused with AGN in some identification schemes (see e.g. Stern et al., 2005; Assef et al., 2010; Hainline et al., 2016). Such galaxies can appear as contaminants in shallow and deep observations (see previous section). As they are uncommon and the co-moving volume is low enough at the respective redshift range, they are typically only a minor contaminant. However, Hainline  \net al. (2016) has recently pointed out that such contaminants can be confused with AGN hosted in dwarf galaxies and hence represent a major problem for their identification (e.g. Satyapal et al., 2014, 2016).  \nFor deeper surveys, the most serious contaminants are high redshift ( z & 1) massive galaxies. At those redshifts the 1.6 GLYPH<22> mstellar bump is shifted into the MIR, and their colours can become red enough to mimic those of AGN in many selection schemes (see Donley et al., 2007; Donley et al., 2012; Yun et al., 2008; Assef et al., 2010; Assef et al., 2013; Mendez et al., 2013). The selection technique developed by Donley et al. (2012) for Spitzer observations is specifically aimed at avoiding these galaxies, resulting in high reliability at faint fluxes although at the cost of completeness. Using W2 magnitude dependent prescriptions, as described in Assef et al. (2013), has the same e GLYPH<11> ect resulting also in high reliability at faint fluxes with a very low completeness level (see Fig. 5).  \nIn addition to extragalactic contaminants, there are a number of Galactic sources that can mimic the colours of AGN in the MIR, such as brown dwarfs or young stellar objects. Brown dwarfs are rare and typically only account for a small fraction of the contaminants but might still a GLYPH<11> ect the identification of high-redshift ( z > 5) AGN (Stern et al., 2007). Young stellar objects also have MIR colours that can be confused with those of AGN (see, e.g. Koenig et al., 2012), and they can be numerous contaminants close to the Galactic plane.', '3.2.4 Dust-free AGN and hot dust poor quasars': "Broad-band MIR AGN selection primarily relies on the detection of the hot dust emission at low and intermediate redshifts. While hot dust emission is rather prominent in most AGN, its ratio to the accretion disk emission (usually described as the torus' apparent covering fraction) shows a wide distribution (see e.g. Roseboom et al., 2013; Mateos et al., 2016; Hern'an-Caballero et al., 2016). Therefore, AGN with low hot dust emission relative to that of their host could escape identification, especially if they reside within luminous hosts. Such objects account for GLYPH<24> 10% of the quasar population selected in the X-rays, optical or MIR (Hao et al., 2010, 2011, but see also Lyu, Rieke, & Shi 2017) and their fraction may be increasing with redshift (Hao et al., 2010; Mor & Trakhtenbrot, 2011; Jun & Im, 2013). According to Hao et al. (2011), their small amount of dust seems to be sufficient to place them to the borders of the Lacy et al. (2004) criteria, but they would be systematically missed by a more stringent selection.  \nMIR selections would of course completely miss dustfree AGN, such as the local analogues of the two sources identified by Jiang et al. (2010) among a sample of 21 z GLYPH<24> 6 quasars observed with Spitzer . Although such analogues  \nTable 2 AGN MIR selection criteria shown in Fig. 5  \nIn all the criteria above, the name of a band represents its magnitude in the Vega system, while fX represents the flux density of band X . Note that [24] refers to the MIPS 24 GLYPH<22> m band Vega magnitude, for which we have assumed a flux density zero point of 7.14 Jy. For empirically calibrated WISE selection criteria we indicate the magnitude range of the calibration sample if one was applied, as the comparison in Figure 5 may be extrapolated to fainter magnitudes in some cases.  \ny Calibrated for galaxies with W1 < 18 : 50 and W2 < 17 : 11.  \nz Calibrated for galaxies with W2 < 15 : 05.  \nGLYPH<3> Calibrated for galaxies with W1 < 18 : 1, W2 < 17 : 2, W3 < 13 : 4.  \nFig. 5 Comparison of completeness and reliability of popular photometric MIR AGN selection criteria, assessed by the test developed by Assef et al. (2013) and discussed in Sect. 3.2.1. The left and right panels show the case of a shallow and deep survey, respectively. The criteria shown correspond to the references listed in Table 2. The red points show the WISE only selection criteria, the blue points show the Spitzer only selection criteria, and the black points show the NIR + Spitzer criteria.  \n<!-- image -->  \nmay not necessarily exist, they might occur more often at lower luminosities. In fact, Elitzur & Shlosman (2006) showed that if the torus is populated by outflowing clouds of material from the accretion disk, at L . 10 42 erg s GLYPH<0> 1 the accretion would be too low to sustain the required outflow rate resulting in the disappearance of the torus. This may apply to some LEG RGs (see also Sect. 2.1.5). A clear case among the observational evidence (e.g. Chiaberge et al., 1999; Maoz et al., 2005; Muller-S'anchez et al., 2013) is the nearby LEG M87, that has been shown to lack the thermal radiation of the torus (Whysong & Antonucci, 2004; Perlman et al., 2007). Such objects would be missed systematically by all MIR selection criteria at low redshifts.", '3.2.5 Eddington Ratios and BH Masses': "The luminosity of the spheroidal component of a galaxy correlates with the mass of its SMBH (at least at relatively low redshifts: e.g. Marconi & Hunt, 2003; Gultekin et al., 2009) and hence with its Eddington limit. The ratio of the specific luminosity of the AGN to that of the host, L GLYPH<23>; AGN = L GLYPH<23>; Host, therefore directly depends on the AGN L = L Edd. In other words, the incompleteness due to host dilution directly translates into a bias of MIR AGN selection against low L = L Edd. Such a bias has been discussed by, e.g., Hickox et al. (2009) (see also Fig. 25) and Mendez et al. (2013), who showed that MIR AGN selection only probes the upper end ( & 1%) of the L = L Edd distribution compared to X-ray selection (this applies also to optically selected AGN: see Sect. 4.5). Quantifying this bias is di GLYPH<14> cult, as it strongly depends on the se-l  \nction function being used, but it needs to be taken into account and the complete selection function needs to be modelled in order to be able to give a physical and statistical interpretation of results based on MIR-selected AGN.  \nAlthough in an indirect manner, this selection e GLYPH<11> ect can also bias the distribution of BH masses in MIR identified AGN. As BH masses correlate only with the luminosity of the host galaxy's spheroidal component, the selection e GLYPH<11> ect discussed above will be stronger in galaxies with important disk or irregular components, as the starlight from them will increase L GLYPH<23>; Host for a fixed BH mass. In other words, AGN in galaxies with disk components need to accrete at higher L = L Edd to be identified by MIR selection techniques. As such non-bulge components are typically more prominent in lower mass galaxies, and these host lower mass BHs (Magorrian et al., 1998), the latter will be systematically underrepresented in MIR AGN samples.", '3.3 Red, reddened and high-redshift AGN': "NIR photometry has also been used to select AGN (e.g. Warren et al., 2000; Francis et al., 2004; Kouzuma & Yamaoka, 2010). Such methods, however, o GLYPH<11> er little gain compared to MIR and optical selection. Nevertheless, NIR has been useful in the identification of red AGN samples, e.g. Glikman et al. (2007) using 2MASS, FIRST and R GLYPH<0> band photometry, as well as the heavily reddened quasars of Banerji et al. (2012, 2015) found in the UKIDSS survey.  \nPopulations of heavily reddened AGN have also been found by means of MIR photometry, often in combination with optical observations. For example, using the colour between the optical R GLYPH<0> band and the MIPS 24 GLYPH<22> m band, Dey et al. (2008) found a new class of objects, dubbed DustObscured Galaxies or DOGs, many of which host heavily reddened AGN (see e.g. Melbourne et al., 2012). Recently Ross et al. (2015) presented a selection of Extremely Red Quasars relying on SDSS and WISE data. Similar is the case of the Hot Dust Obscured galaxies or Hot DOGs (Eisenhardt et al., 2012; Wu et al., 2012a), selected based purely on their WISE colours, for which a number of studies suggest they probe an important stage of galaxy evolution (see e.g. Jones et al., 2014; Assef et al., 2015; Tsai et al., 2015; D'ıaz-Santos et al., 2016).  \nFinally, NIR and MIR wavelengths are very important for the identification of the earliest quasars in the Universe, which are not observable in the optical due to Ly GLYPH<11> forest absorption and the Lyman break. For example, the highest redshift quasar currently known at z = 7 : 1 was found by Mortlock et al. (2011) relying on the IR coverage of the UKIDSS survey, and Ba˜nados et al. (2016) has recently used NIR and MIR observations from 2MASS, VHS and WISE to help in the identification of z > 5 : 6 quasars candidates selected from the optical PanSTARRS 21 survey. Upcoming NIR surveys such as those that will be provided by Euclid and the Wide-Field Infrared Survey Telescope ( WFIRST ) will allow to better probe the quasar population at the earliest cosmic times (see Sect. 3.5).", '3.4 MIR spectroscopy': "MIR spectroscopy, particularly with the InfraRed Spectrograph (IRS; Houck et al. 2004) on board the Spitzer Space Telescope, provided new insights into the physics and classification of AGN. The unambiguous observations of the silicate feature at 9.7 GLYPH<22> m in emission in many known AGN (Hao et al., 2005; Siebenmorgen et al., 2005; Sturm et al., 2005; Buchanan et al., 2006; Shi et al., 2006) came as the long sought confirmation of the unified scheme. At the same time, however, IRS observations indicated that in some cases the source of obscuration resides in the host rather than the torus (e.g. Goulding et al., 2012; Hatziminaoglou et al., 2015).  \nIdentification through MIR spectroscopy is very powerful, allowing to detect obscured AGN components even when the MIR is dominated by the host galaxy. Several classification diagrams have been developed to determine the AGN contribution to an observed spectrum based on certain spectral features, such as high ionisation emission lines like [Ne v ], [Ne ii ] and [O iv ], the EW of PAH features and the strength of the silicate feature at 9.7 GLYPH<22> m(see, e.g. Spoon  \net al., 2007; Armus et al., 2007; Veilleux et al., 2009; Hern'anCaballero & Hatziminaoglou, 2011). A number of techniques have also been developed to model the observed MIR spectra and constrain the AGN and starburst contributions (see e.g. Schweitzer et al., 2008; Nardini et al., 2008; Deo et al., 2009; Feltre et al., 2013).  \nAlthough MIR spectroscopy has had a great impact on our understanding of AGN, the number of objects studied through these techniques is limited when compared to photometric studies, as spectroscopic observations require significantly longer integration times. Ground-based observations are generally limited to the brightest targets due to the e GLYPH<11> ects of the Earth's atmosphere (e.g. Alonso-Herrero et al., 2016), while deeper observations were possible with the IRS during its cryogen-cooled phase. For the most part, such observations were limited to z . 1 luminous IR galaxies (LIRGs), ultraluminous IR galaxies (ULIRGs), and quasars (Hern'an-Caballero & Hatziminaoglou, 2011, and references therein) although a number of higher redshift ULIRGs were also studied by IRS (see e.g. Kirkpatrick et al., 2012). The impact of these techniques will be greatly expanded by the upcoming JWST (Gardner et al. 2006) and Space Infrared Telescope for Cosmology and Astrophysics (SPICA; Nakagawa et al. 2015), that will probe significantly fainter targets and will allow us to select new, currently inaccessible, sets of objects, as discussed next.", '3.5 The future of AGN studies in the IR band': "The upcoming generation of ground-based giant telescopes will significantly expand upon the current NIR and MIR capabilities, as most of them will have significant focus on these wavelengths. The Giant Magellan Telescope (GMT 22 ) is planning on first generation instruments with imaging capabilities from 0.9 to 2.5 GLYPH<22> m and spectroscopic capabilities in the 1-5 GLYPH<22> m range, and its first light is currently expected for 2021. The Thirty Meter Telescope (TMT 23 ) is planning on first-light photometric and spectroscopic instruments in the 0.8-2.5 GLYPH<22> m range, with the goal of extending this range to 28 GLYPH<22> m within its first decade of operations. The first generation instrumentation of the largest of the upcoming giant telescopes, the Extremely Large Telescope (ELT 24 ), will allow for imaging and spectroscopy all the way to 19 GLYPH<22> m. Finally, the University of Tokyo Atacama Observatory (TAO 25 ) 6.5m telescope will focus on the IR, with planned first light instrumentation probing wavelengths as long as 38 GLYPH<22> m.  \nThe only space-based observatories with MIR imaging capabilities currently in operation are Spitzer , whose oper-  \nations have recently been extended until 2019 by the 2016 NASASenior Review, and WISE, whose NEOWISE-R phase is planned to extend until the end of 2017. In the near future, NASA's JWST 26 , expected to launch in 2018, will o GLYPH<11> er unprecedented imaging and spectroscopic capabilities in the 0.6-28.3 GLYPH<22> m wavelength range thanks to its 6.5m diameter primary mirror. Observations with the JWST will probe with high angular resolution a number of targets that are not accessible from the ground, likely having a major impact in our understanding of AGN. The proposed joint JAXA / ESA mission SPICA 27 , that will be launched in 2028 if approved by the two agencies, will have a 2.5m aperture and will provide low-to-high resolution spectroscopy in the wavelength range between 35 and 240 GLYPH<22> m, and imaging capabilities. Finally, the upcoming Euclid and WFIRST missions will have a significant impact in NIR AGN identification by mapping large areas of the sky to very faint depths. Euclid 28 , expected to launch in 2020, will have a 1.2m primary mirror and will survey 15 ; 000 deg 2 of extragalactic sky down to limiting AB magnitudes of 24 in Y , J and H , as well as 24.5 in a very wide optical broad-band. It will also observe a smaller region of 40 deg 2 to limiting AB magnitudes of 26 in the NIR bands and 26.5 in the optical band. The WFIRST mission 29 , expected to launch by 2024, will, on the other hand, have a 2.4m primary mirror and a similar set of bands, and is planned to image 2,227 deg 2 down to a limiting AB magnitude of 26.7 in J (Spergel et al., 2015). Both telescopes will also obtain NIR slitless grism spectroscopy in their survey areas. Through their unique combination of area and depth, both surveys will probe AGN activity during the formation of the first galaxies in the Universe.", '4 Optically-selected AGN': 'This section discusses the selection and properties of opticallyselected AGN as contrasted with investigations at other wavelengths. The focus here is on the more luminous subsets that would typically be classified as quasars or Seyfert 1 galaxies. We will not cover objects like the host-galaxy dominated AGN (Kau GLYPH<11> mann et al., 2003a), the LINERs (Heckman, 1980), or XBONGs (Hornschemeier et al., 2005). While optical surveys are able to identify quantitatively more AGN than other wavelengths (through a combination of area and depth), this size comes with a bias towards brighter, unobscured sources with L = L Edd > 0 : 01 (see Sect. 4.5). Even though optical surveys are not ideal for probing obscured AGN, we discuss how they can guide our search for them. The bias towards unobscured sources in the optical is par-  \ntially mitigated, however, by an increase in information content for the sources that are identified-in the form of physics probed by the combination of optical continuum, absorption, and emission. An example is the ability to estimate the mass of the SMBHs based on the optical / UV emission lines. We discuss the physical mechanisms behind optical emission in Sect. 4.1 and AGN identification, selection effects, information content, and the range of masses (and accretion rates) probed by the optical band in Sect. 4.2 - 4.5. While the redshift / luminosity evolution of optically-selected luminous quasars would seem to be well constrained from today to redshift GLYPH<24> 6, we review evidence suggesting that the Hopkins, Richards, & Hernquist (2007) bolometric LF needs to be updated. How next-generation surveys such as LSST can bridge the evolution of luminous quasars to lowerluminosity AGN (that are typically better probed at other wavelengths) will be addressed in Sect. 4.6. In this section we cover the GLYPH<24> 1 ; 000 GLYPH<0> 8 ; 000 Å range (rest-frame).', '4.1 Physical mechanisms behind optical emission': "AGNare believed to be powered by accretion onto a SMBH, that gives rise to high X-ray-to-optical luminosities, a characteristic rest-frame UV / optical power-law continuum (very distinct from the continuum of non-active galaxies) as well as the so called 'big blue bump', and a break of this continuum blueward of GLYPH<25> 1000 Å (Fig. 1). Many models, usually assuming a geometrically thin, optically thick accretion disk, have been developed in order to explain this emission (e.g. Sun & Malkan, 1989; Laor & Netzer, 1989; Hubeny et al., 2001, and references therein). AGN that have a line of sight to the central engine that is not obscured show broad emission lines with typical gas velocities of a few 1000 km s GLYPH<0> 1 covering a large range in strength and profiles, whose properties correlate with the luminosity of the AGN (e.g. Baldwin, 1997). The source of the broad emission lines is the BLR, believed to be located between the SMBH and the inner wall of the dusty torus (see Sect. 3), with photoionized gas that has been heated by the radiation coming from the accretion disk around the SMBH. Finally, AGN display narrow emission lines, with gas velocities between 300 and 1000 km s GLYPH<0> 1 , originating in the Narrow Line Region (NLR) with sizes GLYPH<25> hundreds of parsec, located above (and below) the plane of the dust.", '4.2 Photometric and spectroscopic identification': "The features described in the previous section are the basis of optical AGN identification, be it photometric or spectroscopic. Broad band photometry is sensitive to the presence of broad emission lines in the various filters as a function of redshift, as they alter the otherwise very typical colours  \nof the AGN that separate them from the stellar locus (see, e.g. Richards et al., 2001, Fig. 4). Narrow band surveys such as COMBO17 (Wolf et al., 2003), ALHAMBRA (Moles et al., 2008), and now J-PAS (Benitez et al., 2014) make use of the spectral features to not only identify AGN but to also estimate their (photometric) redshifts with a precision that reaches below 1% (e.g. Salvato et al., 2009; Hsu et al., 2014), a great improvement with respect to early attempts (Hatziminaoglou, Mathez & Pell'o, 2000). Finally, we are generally reliant on optical spectroscopy to provide confirmation of a source as an AGN and to determine its redshift, while the presence of narrow emission lines in the spectra of galaxies and their ratios are indicative of the presence of an AGN (e.g. Feltre et al., 2016).  \nThe problem with the optical band, as compared to, say, the hard X-rays, is that bright optical sources are not necessarily AGN. The same is true for the radio (Sect. 2.1.2) and IR to some extent (Sect. 3.2)-the brightest sources on the sky have a high probability of being an AGN. This point is illustrated in the comparison of number counts between the X-ray (Lehmer et al., 2012, Fig. 5) and optical (Shanks et al., 2015, Fig. 24): in the optical, stars far outnumber AGN at typical survey depths.  \nOptical selection can make up for this (photometric) uncertainty with sheer numbers. Deep, high-resolution X-ray, IR and radio fields provide a much higher AGN densityup to GLYPH<24> 24 ; 000 deg GLYPH<0> 2 (Sect. 5.1; e.g. Luo et al., 2017, see also Sect. 8), but only over minuscule areas. The density of the largest-area photometric and spectroscopic quasar samples is only GLYPH<24> 150 deg GLYPH<0> 2 , but over a large fraction of the sky, which results in larger samples of AGN overall (e.g. Richards et al., 2009a; D'Abrusco, Longo, & Walton, 2009; Bovy et al., 2011; Flesch, 2015; Brescia, Cavuoti, & Longo, 2015; Pˆaris et al., 2017). Figure 6 shows the growth in quasar numbers with time for both heterogeneous and homogeneous quasar samples. We discuss the impact of future facilities in Sect. 4.6.", '4.3 Selection e GLYPH<11> ects': "Paradoxically, many (optically) unobscured AGN are missed by optical surveys. These are objects whose colours put them in (or close to) the stellar locus. Since luminous quasars are point sources, but are outnumbered by stars in our galaxy by GLYPH<24> 100 : 1 at the SDSS depth, it is very di GLYPH<14> cult to create a complete sample of quasars at certain redshifts-without considerable stellar contamination. The redshifts a GLYPH<11> ected span a large range around z GLYPH<24> 2 : 6 with very low completeness, and a smaller range around z GLYPH<24> 3 : 5 (Richards et al., 2002, 2006b; Worseck & Prochaska, 2011). Even the SDSS-III / BOSS quasar sample is only 60% complete at these redshifts despite being designed to identify 2 : 2 < z < 3 : 5 quasars  \nFig. 6 Number of quasars as a function of time. The dashed line and triangles give the number of quasars in the largest heterogeneous samples to date. The solid line and squares give the largest homogeneous quasar samples (including photometric quasar candidates) to dateextrapolating to 10,000,000 expected AGN for LSST (LSST Science Collaboration et al., 2009). Adapted from Richards et al. (2009a); the 2015 photometric point is from DiPompeo et al. (2015).  \n<!-- image -->  \n(Ross et al., 2013). It is worth noting that most MIR selections have a similar redshift 'hole' over 4 . z . 5 (Sect. 3.2.1) but this can be filled in by using optical and MIR data simultaneously (Richards et al., 2015).  \nLower-luminosity AGN are also a challenge for imagingonly optical surveys (like the Dark Energy Survey [DES 30 ] and LSST 31 ) for the reasons noted above: without spectroscopy, it is di GLYPH<14> cult to distinguish a normal galaxy from an active galaxy. Variability selection may not help all that much for such sources considering that, while the amplitude of variability increases at lower luminosity (Vanden Berk et al., 2004, see also Sect. 7.2.3), the fraction of optical emission from the central engine decreases. Yet this is the population that we most need to probe, especially for comparison to X-ray and MIR samples.  \nThe biggest hole in the selection of AGN via optical photometry is certainly obscured (or type 2) AGN. It does not matter whether the optical obscuration is by a smooth torus or a clumpy one (see Sect. 3.1 for a full list of references on smooth and clumpy distributions): the traditional AGN model has a region where most of the optical emission is obscured. The irony is that a large fraction of known type 2 AGN are still selected in the optical (Zakamska et al., 2003; Reyes et al., 2008; Alexandro GLYPH<11> et al., 2013; Yuan,  \nStrauss, & Zakamska, 2016). This result is due to a combination of e GLYPH<11> ects: the host galaxy is not (always) obscured and both strong emission lines and scattering can result in nonnegligible optical flux producing unusual (or even AGNlike) colours, which can cause them to be identified as potential type 1 sources despite them being type 2.  \nThus the question of the relative fraction of obscured and unobscured AGN is still much debated / investigated (see also Sect. 3.1), particularly as a function of luminosity (e.g. Gilli, Comastri, & Hasinger, 2007; Ueda et al., 2014). Crucially, di GLYPH<11> erences in the definition of 'obscured' between the optical and X-ray (e.g. Hickox et al., 2007) make it more di GLYPH<14> cult than one might imagine to paint a full picture (see also Sect. 5.3).", '4.4 Information content': "In Sect. 3 we saw that IR-detected quasars are relatively unbiased against type 2 AGN, whereas most of the optical light comes from the central accretion disk, which is blocked in these sources. However, while the optical may be missing a crucial component of the AGN zoo in terms of obscured AGN, it more than makes up for that loss in terms of information content of those AGN that are detected. Moreover, the information content in the continuum, emission lines, and absorption lines from optical spectroscopy is particularly rich. For example, BAL quasars (Weymann, Morris, Foltz, & Hewett, 1991) have provided us with direct evidence of winds in AGN systems with outflow velocities extending to tens of thousands km s GLYPH<0> 1 (e.g. Hamann et al., 2011).  \nWhile the BAL sub-class represents only GLYPH<24> 20% of the population of luminous quasars (Hewett & Foltz, 2003), the advent of principal component analysis, both using photometry (Boroson & Green, 1992) and spectroscopy (Francis, Hewett, Foltz, & Cha GLYPH<11> ee, 1992; Yip et al., 2004) and large data sets from SDSS (Schneider et al., 2010; Pˆaris et al., 2017), has enabled the community to treat quasars as diverse systems. For example, Richards et al. (2011) argue that we can learn about winds using emission lines in addition to absorption lines, which potentially turns every quasar into powerful probe of AGN outflows.  \nIndeed, one way to illustrate the diversity of quasars is presented in Fig. 7, which shows how physical trends are manifested in the di GLYPH<11> erent emission lines: quasars with harder spectra have stronger emission lines and less 'blueshift' of the C iv emission line. The probability of a quasar being radio detected or having strong BAL troughs is a strong function of the appearance of these emission lines (Richards et al., 2011). The trends shown in Fig. 7 appear to be related  \nFig. 7 Diversity of UV emission line properties in SDSS quasars. Quadrants refer to the C iv EW-blueshift plane with red objects having low C iv blueshifts and large EW and blue objects having large C iv blueshift and small EW. These correlated features may be indicative of di GLYPH<11> erences in the hardness of the spectral energy distributions (e.g. Leighly, 2004).  \n<!-- image -->  \nto those that define the 'Eigenvector 1' 32 parameter space (Boroson & Green, 1992; Brotherton & Francis, 1999; Sulentic, Marziani, & Dultzin-Hacyan, 2000; Sulentic et al., 2007), which together highlight the great diversity of AGN even when considering only those that are both optically selected and very luminous. Often overlooked is the fact that this diversity has important implications for accurate determination of quasar redshifts (Hewett & Wild, 2010).", '4.5 L = L Edd and M BH': "Arguably the best example of where optical provides additional information content and makes up for selection e GLYPH<11> ects is in our ability to utilise BH mass scaling relations to estimate the masses of the BHs powering quasars (e.g. Vestergaard & Peterson, 2006). Again, this process requires optical spectroscopy 33 . By: (1) knowing the width of the emission lines; (2) assuming that that width is dominated by gravitational e GLYPH<11> ects; (3) having an estimate of the characteristic radius of the emitting gas assuming R / L GLYPH<24> 0 : 5 (Bentz et al., 2009); and (4) calibrating this information against the few dozen objects for which there exists 'reverberation mapping' (Peterson, 1993) data, we can then estimate the masses of the BH in every type 1 quasar.  \nGenerally speaking the types of AGN discussed herein have masses of 10 6 -10 10 M GLYPH<12> and accretion rates (in terms of L = L Edd) of 0.01-1 (Greene & Ho, 2007; Vestergaard et al., 2008; Shen & Kelly, 2012; Trakhtenbrot & Netzer, 2012). See Schulze et al. (2015) for a recent, comprehensive analysis that combines data from the VIMOS-VLT Deep Survey (VVDS), zCOSMOS, and SDSS.  \nScaling relations for estimating the masses of BHs in relatively local AGN (up to z GLYPH<24> 0 : 7) make use of the H GLYPH<12> emission line and are thought to be relatively robust (at the level  \nof GLYPH<24> 0 : 3 dex). Using the Mg ii emission line these scaling relations have been extended to z GLYPH<24> 1 : 9. However, beyond that redshift other broad emission lines need to be used. As such, attempts have been made to calibrate C iv to produce BH mass estimates, though it is becoming clear that the winds discussed above can significantly bias the estimates for highredshift quasars which rely on the C iv emission line (Baskin & Laor, 2005; Richards et al., 2011; Denney, 2012; Shen, 2013). As the sample size of high-redshift quasars with both optical and IR spectroscopic coverage grows, corrections to this scheme might help bringing the BH masses into alignment (e.g. Runnoe et al., 2013; Coatman et al., 2016). However, the uncertainties associated with the determination of SMBHbased on C iv are not solely due to low spectral resolution and / or signal-to-noise ratio (S / N) but rather point towards di GLYPH<11> erences in the physics of the BLR. In other words, either the C iv -emitting gas is non-virialised or objects with low and high FWHM(H GLYPH<12> ) have di GLYPH<11> erent ionisation structure, since the FWHM(C iv ) has only a loose correlation, if any, with FWHM(H GLYPH<12> ) (Denney et al., 2013; Mejia-Restrepo et al., 2016; Coatman et al., 2017).  \n4.6 The evolution with redshift and the impact of future facilities  \nThe SDSS quasar LF (Richards et al., 2006b) was unique not in the redshift range or luminosity that it probed, but rather because it probed such a large range with just one uniform data set with a large number of quasars. One of the shortcomings of the wide, but shallow SDSS work was that it generally only probed the bright end of the LF, whereas narrow, but deep X-ray surveys were better able to probe the faint end. Hopkins, Richards, & Hernquist (2007) combined the best of both worlds from various multi-wavelength surveys to create a bolometric LF.  \nRecent works, however (e.g. Assef et al., 2011; Ross et al., 2013; McGreer et al., 2013), have shown that the evolution of the break luminosity (where the slope of the LF changes rapidly) may be very di GLYPH<11> erent from that predicted by Hopkins, Richards, & Hernquist (2007) and that the faintest SDSS quasars might start probing the faint end (rather than the bright end, as was assumed) of the LF at high z . What is needed here are both deeper surveys in the optical and wider surveys in the X-ray (Sect. 5.4), or similarly deep / wide NIR surveys (Sect. 3.5). But even without new data there is a decade of observations that could be incorporated into an updated bolometric LF.  \nImproving our knowledge of the quasar LF has consequences beyond the study of quasars: it also has important consequences for reionisation in the early Universe. For example, the results of McGreer et al. (2013) and Glikman et al. (2011) suggest photoionisation rates at z > 4 that do not fully agree.  \nIt is important to understand that the bias in the optical band is towards the high luminosity end of the AGN distribution, i.e. bona fide quasars. In part that is because that is the population that optical surveys themselves are biased to. However, current and upcoming experiments like PanSTARRS 34 , DES, and LSST (will) probe to fainter limits that are more compatible with the lower-luminosity AGN (where the host emission is more comparable to the central engine) that surveys at other wavelengths most commonly identify. These new optical surveys will help complete a multi-wavelength bridge that will allow AGN astronomers to more fully sample luminosity-redshift space across the full electromagnetic spectrum, as illustrated by LaMassa et al. (2016, Fig. 14).", '5 X-ray-selected AGN': 'We discuss in this section X-ray-selected AGN. The physical mechanism behind X-ray emission is examined in Sect. 5.1, while Sect. 5.2 deals with AGN selection and its challenges. Sect. 5.3 reviews the types of AGN selected in the X-ray band, the range of M BH and L = L Edd they sample, and their evolution, while Sect. 5.4 gives an overview of the future of this field. In this review we define the X-ray band as covering the energy range of 0.2-200 keV.', '5.1 Physical mechanism behind X-ray emission': "X-ray observations provide a near complete selection of AGN with low contamination from non-AGN systems. The primary reasons for this are: (1) X-ray emission from AGN appears to be (near) universal; (2) X-rays are able to penetrate through large column densities of gas and dust (particularly at high X-ray energies); (3) X-ray emission from hostgalaxy processes are typically weak when compared to the AGN (see also Sect. 1.1 of Brandt & Alexander, 2015). On the basis of these advantages, the deepest blank-field cosmic X-ray surveys have identified the largest reliable AGN source density to date ( GLYPH<25> 24,000 deg GLYPH<0> 2 ; Lehmer et al. 2012; Luo et al. 2017 and Sect. 8).  \nThe intrinsic X-ray emission from AGN is due to processes related to the accretion disk (see Mushotzky, Done, & Pounds 1993; Done 2010; Gilfanov & Merloni 2014 for reviews; note that in jetted AGN the jet can make a major contribution in the X-ray band as well) 35 . The primary  \nprocess is thought to be inverse Compton scattering of the accretion-disk photons to X-ray energies via the accretiondisk 'corona' (see Fig. 1; this is generally depicted as an atmosphere above the inner accretion disk, though its exact geometry is unknown). However, thermal X-ray emission due to the inner regions of the accretion disk can also be produced at the lowest X-ray energies (e.g. Sobolewska, Siemiginowska, & ˙ Zycki, 2004). The X-ray emission is then modified due to the interaction with matter in the nuclear region (e.g. reflection, scattering, and photo-electric absorption of photons from the accretion disk and / or the obscuring AGN torus: see Sect. 3.1). The relative strength of these components can vary quite significantly from source to source, mostly due to di GLYPH<11> erences in the geometry and inclination angle of the torus to the line of sight, leading to a broad range of X-ray spectral shapes. The intrinsic X-ray emission from the 'corona' is tightly connected to the accretion-disk emission (as parameterised by GLYPH<11> OX; e.g. Ste GLYPH<11> en et al. 2006; Lusso & Risaliti 2016) for almost all systems (for exceptions see, e.g. Wu et al. 2011; Luo et al. 2014), demonstrating a causal relationship and showing that X-ray emission from AGN is (near) universal.  \nAlarge number of X-ray observatories have been launched since the first pioneering rocket flights of the 1960s (see Giacconi 2009 for a review). The majority of the results presented here have been obtained from the most sensitive Xray observatories in operation, all of which employ grazingincidence optics to focus X-ray photons and achieve high sensitivity at high spatial resolution: Chandra , XMM-Newton , and NuSTAR . Chandra (launched July 1999; Weisskopf et al. 2002) provides up-to sub-arcsecond imaging at GLYPH<25> 0.38 keV with su GLYPH<14> cient collecting area for high S / N X-ray spectra of bright X-ray sources. The low background, high spatial resolution, and good collecting area allows Chandra to detect sources three orders of magnitude fainter than previous-generation X-ray observatories. XMM-Newton (launched December 1999; Jansen et al. 2001) provides lower spatial resolution imaging than Chandra ( GLYPH<25> 5 00 FWHM)over GLYPH<25> 0.2-12 keV but with substantially larger collecting area, allowing for higher S / NX-ray spectra of bright X-ray sources than Chandra . NuSTAR (launched June 2012; Harrison et al. 2013) provides lower spatial resolution imaging than Chandra and XMM-Newton ( GLYPH<25> 18 00 FWHM and GLYPH<25> 58 00 halfpower diameter) but is sensitive to much higher energy photons ( GLYPH<25> 3-79 keV). In comparison to previous generation observatories with sensitivity at > 10 keV NuSTAR is able to detect sources two orders of magnitude fainter.  \nFig. 8 X-ray luminosity versus redshift for sources detected in a selection of blank-field cosmic surveys undertaken with Swift -BAT (red), ASCA (magenta), XMM-Newton (blue), and Chandra (cyan and black). The open and filled symbols indicate X-ray unabsorbed ( N H < 10 22 cm GLYPH<0> 2 ) and X-ray absorbed ( N H > 10 22 cm GLYPH<0> 2 ) systems, respectively. c GLYPH<13> AAS. Figure reproduced from Ueda et al. (2014), Fig. 3, with permission.  \n<!-- image -->", '5.2 Selection of AGN in the X-ray band: identification challenges': "The (near) universality of X-ray emission from AGN, the high penetrating power of X-rays, and the low contamination from host-galaxy emission, mean that AGN selection e GLYPH<11> ects at X-ray energies are generally modest, particularly at high energies (rest-frame energies > 10 keV). Fig. 8 demonstrates the broad L Xz plane coverage for AGN selected from blank-field cosmic X-ray surveys: AGN with L X > 10 44 erg s GLYPH<0> 1 , L X = 10 42 -10 44 erg s GLYPH<0> 1 , and L X < 10 42 erg s GLYPH<0> 1 are typically classified as high luminosity (broadly corresponding to 'quasars'), moderate luminosity (broadly corresponding to 'Seyfert galaxies'), and LLAGN respectively.  \nFor the majority of AGN, the most significant selection e GLYPH<11> ect is that of absorption, which is a function of rest-frame X-ray energy: lower energy X-rays are more easily absorbed than higher energy X-rays (Wilms, Allen, & McCray 2000). The impact of varying amounts of absorption on the detection of X-ray photons for a z = 0 AGN from a selection of X-ray observatories is shown in Fig. 9. The e GLYPH<11> ect of absorption on the fraction of X-ray detected counts is clear for all of the X-ray observatories but is only significant at > 10 keV for heavily obscured AGN ( N H > 3 GLYPH<2> 10 23 cm GLYPH<0> 2 ). Since an increase in redshift leads to an increase in the rest-frame energies probed within a given observed-frame band, the e GLYPH<11> ect of absorption is less significant at high redshift than low redshift. However, CT AGN (i.e. AGN where the absorbing column density exceeds the inverse of the Thomson scattering  \nFig. 9 The impact of varying amounts of absorption on the fraction of X-ray detected counts (with respect to the case for no absorption) for an AGN at z = 0 for a variety of X-ray observatories: ROSAT (grey; GLYPH<25> 0.2-2.4 keV), eROSITA (burgundy; GLYPH<25> 0.2-5 keV), Chandra (red; GLYPH<25> 0.3-8 keV), XMM-Newton (green; GLYPH<25> 0.2-12 keV), NuSTAR (blue: GLYPH<25> 3-79 keV), and Swift -BAT (black: GLYPH<25> 14-195 keV). A cuto GLYPH<11> power law with GLYPH<0> = 1 : 9 and E c > 200 keV has been assumed. c GLYPH<13> AAS. Figure reproduced from Koss et al. (2016), Fig. 2, with permission.  \n<!-- image -->  \ncross section: N H > 1 =GLYPH<27> T > 1 : 5 GLYPH<2> 10 24 cm GLYPH<0> 2 ) are challenging to detect even at high rest-frame energies due to Compton recoil and subsequent absorption of the X-ray photons (see Comastri 2004 for a review). Other wavebands that are less sensitive to the e GLYPH<11> ects of heavy obscuration (e.g. the radio and IR wavebands; see Sects. 2 and 3) will be less biased towards the detection of CT AGN. However, the unambiguous identification of the signatures of CT absorption and the measurement of absorbing column densities requires X-ray observations. This is most e GLYPH<11> ectively achieved from broadband X-ray spectral fitting (i.e. the combination of [ideally simultaneous] data from, for example, NuSTAR and Chandra or XMM-Newton ), which can break the degeneracy between the contributions from various X-ray emitting components (e.g. photo-electric absorption; reflection; scattering; Balokovi'c et al. 2014; Del Moro et al. 2014; Gandhi et al. 2014; Akylas et al. 2016).  \nFor AGN with low observed X-ray luminosities (e.g. intrinsically LLAGN, including LEGs, or heavily obscured AGN), the host galaxy can start to contaminate the emission from the AGN, leading to challenges in the identification and characterisation of the AGN. The dominant hostgalaxy phenomenon at X-ray energies is commonly referred to as X-ray binaries (see Fabbiano 2006 and Remillard & McClintock 2006 for reviews). The emission from X-ray binaries is due to mass accretion onto a degenerate star (neutron star or BH) from a companion star in a binary system: X-ray binaries are sub-classified into low-mass X-ray binaries (LMXBs) and high-mass X-ray binaries (HMXBs), depending on the mass of the companion star. The emission  \nfrom LMXBs is closely tied to the stellar mass of the galaxy and can reach L X GLYPH<25> 10 41 erg s GLYPH<0> 1 for a massive galaxy of GLYPH<25> 10 11 M GLYPH<12> (e.g. Lehmer et al. 2010; Boroson, Kim, & Fabbiano 2011) while the emission from HMXBs is closely tied to the SFR and can reach L X GLYPH<25> 3 GLYPH<2> 10 42 erg s GLYPH<0> 1 for an extreme SFG with a SFR of GLYPH<25> 1000 M GLYPH<12> yr GLYPH<0> 1 (e.g. Lehmer et al. 2010; Mineo, Gilfanov, & Sunyaev 2012a). To accurately identify or characterise the AGN requires taking account of both of these X-ray binary components. However, since the X-ray emission from host-galaxy processes rarely exceeds L X > 10 42 erg s GLYPH<0> 1 , and has not been known to exceed L X > 10 43 erg s GLYPH<0> 1 (e.g. Alexander et al. 2005; Wang et al. 2013), an X-ray source with L X > 10 42 erg s GLYPH<0> 1 is likely to be an AGN. Furthermore, the integrated emission from a population of X-ray binaries is mostly produced at low energies ( < 10 keV) and therefore AGN can be more reliably identified and characterised at higher energies (see Sect. 2.3 of Brandt & Alexander, 2015, for a list of additional criteria to identify X-ray emission from an AGN).  \nAnother potential component of non-AGN contamination at X-ray energies is emission from hot gas, either from the host galaxy or a galaxy cluster. The hot-gas component can be up-to L X GLYPH<25> 10 41 -10 42 erg s GLYPH<0> 1 from galaxies (e.g. Boroson, Kim, & Fabbiano 2011; Mineo, Gilfanov, & Sunyaev 2012b) and can be as high as L X GLYPH<25> 10 44 -10 45 erg s GLYPH<0> 1 in the cores of massive galaxy clusters (e.g. Stanek et al. 2006; Ebeling et al. 2010). However, since the X-ray emission from the hot gas is thermal, it is mostly produced at low energies ( < 2-5 keV) and therefore the AGN can be more reliably identified and characterised at higher energies, even in the most massive galaxy cluster cores.  \nOnthe basis of the aforementioned factors, it is clear that X-ray observations provide an e GLYPH<14> cient and reliable selection of the overall AGN population. Furthermore, the modest Xray selection biases are well understood and can be reliably modelled to allow for robust measurements on the evolution of AGN and the growth of BHs (e.g. Gilli, Comastri, & Hasinger 2007; Georgantopoulos et al. 2013; Ueda et al. 2014; Aird et al. 2015; Buchner et al. 2015; Miyaji et al. 2015; Merloni 2016). However, significant uncertainties remain on the contributions to the cosmic BH growth from LLAGN and CT AGN. Various complementary approaches can be utilised to make further progress. For example, combining constraints in the X-ray band with AGN and hostgalaxy measurements in other wavebands (e.g. IR and radio wavelengths) to assess the expected strength of the AGN and host-galaxy components at X-ray energies (e.g. Alexander et al. 2008; Gandhi et al. 2009; Georgantopoulos et al. 2011; Del Moro et al. 2013, 2016; Asmus et al. 2015) or utilising high spatial resolution X-ray imaging and spectroscopy to directly identify the AGN and host-galaxy components in nearby low-luminosity systems (e.g. Annuar et al. 2015, 2017; Ricci et al. 2016).  \n<!-- image -->  \nFig. 10 Distribution of absorbing column densities for X-ray selected AGN from the INTEGRAL observatory (20-100 keV) with type 1 (optically unobscured; top) and type 2 (optically obscured; bottom) optical spectral signatures. The dashed bins indicate column density upper limits and the dashed lines indicate the typical adopted column density threshold between X-ray absorbed and unabsorbed AGN. Figure reproduced from Malizia et al. (2012), Fig. 5, with permission. c GLYPH<13> The Authors.  \n<!-- image -->", '5.3 Selection of AGN in the X-ray band: AGN types, M BH, L = L Edd, and cosmic evolution': "Essentially all types of AGN are selected at X-ray energies: absorbed and unabsorbed AGN of low, moderate, and high luminosity (see Fig. 8). Overall there is also good agreement between the optical and X-ray signatures of absorption (e.g. Malizia et al. 2012; Merloni et al. 2014; Burtscher et al. 2016): the majority ( > 80-90%) of optical type 1 AGN are X-ray unabsorbed ( N H < 10 22 cm GLYPH<0> 2 ) while the majority ( > 80-90%) of optical type 2 AGN are X-ray absorbed ( N H > 10 22 cm GLYPH<0> 2 ; see Fig. 10). Careful consideration of the thresholds in the classification of X-ray and optical absorbed and unabsorbed AGN can provide even closer agreement (Burtscher et al. 2016). The overall consistency between the X-ray and optical absorption indicators provide some of the strongest observational support for the basic unified AGN model (e.g. Antonucci 1993; Urry & Padovani 1995).  \nHowever, the clear disagreements between absorption indicators for a small subset of the AGN population (e.g. X-ray unabsorbed type 2 AGN and X-ray absorbed type 1 AGN; e.g. Panessa & Bassani 2002; Bianchi et al. 2012) also provide interesting insight on the overall universality of the basic unified model (see Netzer 2015 for a review). Time-series observations have shown that the X-ray and optical spectral properties of AGN can vary on relatively short  \nFig. 11 Specific accretion rate (a proxy for L = L Edd) distributions for X-ray selected AGN at z = 0 : 2 GLYPH<0> 1 : 2 residing in a range of host galaxy types dividing the sample into four populations according to their epoch-normalized specific SFRs (quiescent galaxies with low SFR, quiescent galaxies with higher SFR, SFGs below the star-forming main sequence (MS), and SFGs above the star-forming MS). c GLYPH<13> AAS. Figure reproduced from Azadi et al. (2015), Fig. 12, with permission.  \n<!-- image -->  \ntimescales as a result of changes in the absorbing column density along the line of sight (e.g. Risaliti, Elvis, & Nicastro 2002; Risaliti et al. 2005; Matt, Guainazzi, & Maiolino 2003; MacLeod et al. 2016; Ruan et al. 2016; see also Sect. 7.1.3). Therefore, some of the occasional disagreements between absorption indicators are due to non-simultaneous Xray and optical observations; however, AGN variability does not explain the di GLYPH<11> erences for all cases and some AGN appear to genuinely depart from the basic unified model (see also Sect. 3.1).  \nDue to the (near) universality of X-ray emission from AGN, its production should not be inherently biased towards specific ranges in M BH and L = L Edd. Indeed, X-ray emission has been detected from AGN with a broad range of M BH out to high redshifts ( GLYPH<25> 10 5 -10 9 M GLYPH<12> ; e.g. Hickox et al. 2009; Page et al. 2014; Baldassare et al. 2015; Chen et al. 2017). Despite the lack of an intrinsic bias towards detecting lowmass BHs at X-ray energies, the majority of the AGN detected in blank-field cosmic X-ray surveys are nevertheless found to reside in massive galaxies (stellar masses > 10 10 M GLYPH<12> implying M BH > 10 7 M GLYPH<12> ; e.g. Brusa et al. 2009; Hickox et al. 2009; Xue et al. 2010; see Brandt & Alexander 2015 for a review). However, the deficiency of X-ray AGN in low-mass galaxies (i.e., a low AGN fraction) appears to be due to selection e GLYPH<11> ects: for a fixed X-ray flux limit (i.e. a luminosity limit at a given redshift), the probability of detecting a low L = L Edd AGN with a massive BH is significantly higher than a high L = L Edd AGN with a low-mass BH (e.g. Aird et al.  \n,  \nFig. 12 Space density versus redshift for AGN selected across a wide range in X-ray luminosity. The symbols indicate the data for AGN from Miyaji et al. (2015) in di GLYPH<11> erent X-ray luminosity bins while the curves and shaded regions indicate the models for the evolution of X-ray selected AGN from Aird et al. (2015). Figure reproduced from Aird et al. (2015), Fig. 18, with permission. c GLYPH<13> The Authors.  \n<!-- image -->  \n2012; Bongiorno et al. 2012). Taking account of these observational biases, the distribution of L = L Edd for X-ray AGN appears to be broadly consistent with a power law and is largely mass independent (e.g. Aird et al. 2012; Bongiorno et al. 2012). However, there is evidence for di GLYPH<11> erences in the normalisation (and potentially the shape) of the L = L Edd distribution between quiescent and star-forming host galaxies (e.g. Aird et al. 2012; Azadi et al. 2015; see Fig. 11).  \nBlank-field cosmic X-ray surveys have provided some of the most detailed and sensitive constraints on the evolution of the AGN population. It is now clear from a large suite of studies that the evolution in the space density of X-ray selected AGN is dependent on luminosity: moderateluminosity AGN peak at z GLYPH<25> 0.5-1 while high-luminosity AGNpeak at z GLYPH<25> 2-3 (e.g. Ueda et al. 2014; Aird et al. 2015; Buchner et al. 2015; Miyaji et al. 2015); see Fig. 12. This luminosity dependent evolution is commonly referred to as 'AGN downsizing' (see also Sect. 2.3) and, to first order, is likely to be driven by the availability of a cold-gas supply in the vicinity of the accreting BH; however, the processes that influence the availability of the gas are likely to be manifold (e.g. SF; AGN and stellar feedback; large-scale environment; see Alexander & Hickox 2012 for a general review). In terms of the cosmic BH growth (essentially the product of the space density and AGN luminosity), the majority has occurred at z GLYPH<25> 1-2, with broadly similar amounts of growth at z < 1 and z > 2: high-luminosity AGN dominate the BH  \ngrowth density at z > 1 : 5 ( L X GLYPH<25> 10 44 -10 45 erg s GLYPH<0> 1 AGNcontribute the majority) while moderate-luminosity AGN dominate at z < 0 : 5 ( L X GLYPH<25> 10 43 -10 44 erg s GLYPH<0> 1 AGNcontribute the majority).  \nThe fraction of X-ray absorbed AGN is found to be a function of luminosity, with a decreasing fraction towards higher X-ray luminosities, and appears to also increase with redshift (e.g. La Franca et al. 2005; Ueda et al. 2014; Aird et al. 2015; Buchner et al. 2015; but see also Sect. 3.1 for IRselected AGN). The redshift evolution in absorption may be a consequence of the luminosity dependent X-ray absorbed AGN fraction shifting to higher luminosities at higher redshifts (e.g. Aird et al. 2015; Buchner et al. 2015). These results suggest that the covering factor of the obscuring material (i.e. the AGN torus) might change as a function of luminosity and redshift; however, it is currently unclear what drives this behaviour.", '5.4 The future of AGN studies in the X-ray band': "We now look towards the scientific gains that can be anticipated from several future X-ray facilities; see Sect. 6.4 of Brandt & Alexander (2015) for a more detailed discussion of these observatories and other proposed X-ray facilities.  \neROSITA 36 (Merloni et al. 2012) is a joint Russian-German mission planned for launch in 2018. The principle objective of eROSITA is to undertake a sensitive all-sky survey, achieving sensitivity limits GLYPH<25> 20 and GLYPH<25> 200 times deeper than ROSAT (0.5-2 keV; Voges et al. 1999) and HEAO 1 A2 (2-10 keV; Piccinotti et al. 1982), respectively. The great advance that eROSITA will provide over the more sensitive Chandra and XMM-Newton observatories is huge AGN statistics ( GLYPH<25> 3 million AGN out to z GLYPH<25> 6), e GLYPH<11> ectively providing an X-ray equivalent of the SDSS (York et al. 2000) or WISE, to explore the cosmic growth of BHs and large-scale structure at X-ray energies.  \nThe Advanced Telescope for High ENergy Astrophysics ( Athena 37 ; Nandra et al. 2013) is an ESA-led mission planned for launch in 2028. Athena will be a revolutionary generalpurpose X-ray observatory with a wide field of view (FoV; 40 0 GLYPH<2> 40 0 ), large collecting area (2 m 2 at 1 keV), good spatial resolution (5 00 ), and excellent spectral resolution (2.5 eV). Athena has many key scientific aims but, from the point of view of this review, two of the main advances will come from: (1) excellent-quality X-ray spectroscopy (both in terms of unprecedented sensitivity and spectral resolution), to elucidate the physics of AGN activity (e.g. Cappi et al. 2013; Dovciak et al. 2013); (2) unsurpassed sensitivity for widedeep blank-field cosmic surveys, to construct a near-complete  \ncensus of AGN activity out to z GLYPH<25> 1-3 and identify moderately luminous AGN out to z GLYPH<25> 6-10 (down to L X GLYPH<25> 10 43 erg s GLYPH<0> 1 ; e.g. Aird et al. 2013; Georgakakis et al. 2013).  \nFinally, the X-ray Imaging Polarimetry Explorer (XIPE 38 ; So GLYPH<14> tta et al. 2016) is a new mission concept selected by ESA in 2015 to undergo a 2 year-long assessment phase in the context of the Cosmic Vision competition. XIPE is dedicated to undertake temporally, spatially, and spectrally resolved X-ray polarimetry. From the point of view of AGN the polarised emission is expected to be due to the scattering and reflection of photons and to originate in the vicinity of the accretion disk, the absorbing region (the AGN torus), and larger-scale ionisation 'cones'. Therefore, XIPE will provide unique physical insight on the geometry and connections between these di GLYPH<11> erent regions (Goosmann & Matt 2011).", '6 GLYPH<13> -ray-selected AGN': "We discuss in this section GLYPH<13> -ray-selected AGN. The GLYPH<13> -ray band is conventionally split into the High Energy (HE) band, between 100 MeV and GLYPH<24> 100 GeV, and the Very High Energy (VHE) band, covering the GLYPH<24> 50 GeV to GLYPH<24> 10 TeV range. The types of AGN selected, their SEDs, and the physical mechanism(s) behind GLYPH<13> -ray emission are detailed in Sect. 6.1, while GLYPH<13> -ray detectors are described in Sect. 6.2. Sects. 6.3 and Sect. 6.4 deal with the HE and VHE bands respectively, while Sect. 6.5 addresses the blazar population and its contribution to the GLYPH<13> -ray background. Sect. 6.6 discusses selection biases and, finally, Sect. 6.7 addresses the future of this field.  \n6.1 GLYPH<13> -ray AGN, their SEDs, and physical mechanism(s) behind GLYPH<13> -ray emission  \nThe GLYPH<13> -ray band is the most energetic part of the electromagnetic spectrum and, as such, is beyond the reach of most astronomical sources. This applies also to most types of extragalactic objects, including the non-jetted AGN detected in large numbers in IR, optical, and X-ray surveys thanks to the radiation resulting from accretion onto the central SMBH (Sects. 3, 4, and 5; see Fig. 1).  \nBlazars, despite being intrinsically very rare (orders of magnitude less abundant than non-jetted AGN of the same optical magnitude), dominate the extragalactic GLYPH<13> -ray sky, which include also a few other AGN, mostly nearby RGs (blazars are also prevalent in the bright radio sky: Sect. 2.1.2). Nonjetted AGN have not been detected in the GLYPH<13> -rays 39 (Acker-  \nmann et al., 2012a). The power output of blazars covers the entire electromagnetic spectrum and is dominated by nonthermal, blue-shifted, and Doppler boosted radiation arising in a relativistic jet pointed in the direction of the observer (e.g. Urry & Padovani, 1995, see also Sect. 2.1.5). It is because of this intense non-thermal emission, and the very special geometrical conditions, that blazars reach the most extreme parts of the electromagnetic spectrum with fluxes well above the sensitivity of the instruments operating today. Blazars, as discussed in Sect. 2.1.2, are further divided into two subgroups defined by their optical spectra, i.e. BL Lacs and FSRQs.  \nFig. 13 The SED of the BL Lac Mrk 421. Strong and variable emission is present at all energies, from the radio band to GLYPH<13> -rays. Variability is most pronounced in the X-rays and GLYPH<13> -rays where the two SED components peak. The green line indicated by the arrow represents the expected emission from a typical blazar host galaxy. A hard spectrum is present in the HE band with variability of approximately a factor 50 in the 200 MeV (light green), 1 GeV (orange) and 10 GeV (purple) data. The GLYPH<13> -ray SED peaks in the VHE band, where large variability is also present. VHE data are from Bartoli et al. (2011); Biteau & Williams (2015); Aharonian et al. (2005); Chandra et al. (2010); Sharma et al. (2015); Amenomori et al. (2003); Albert et al. (2007). The SEDs here and in Fig. 14 have been generated using the SED builder tool of the ASI Science Data Center (ASDC), available at tools.asdc.asi.it/SED , while the light curves have been produced at the ICRANet site of Yerevan as part of a collaboration with ASDC, using Fermi public software and archival data.  \n<!-- image -->  \nThe SED of blazars (see Figs. 13 and 14 for two examples of well known objects) covers the entire electromagnetic spectrum, from radio waves to GLYPH<13> -ray energies, and is characterized by a typical 'double humped' shape (in a GLYPH<23> L ( GLYPH<23> ) vs. GLYPH<23> [or GLYPH<23> f ( GLYPH<23> ) vs. GLYPH<23> ] space). The low energy component, peaking between the IR and the X-ray band, is generally attributed to synchrotron radiation produced by relativistic electrons moving in a magnetic field. Sources where this component peaks at low energies ( GLYPH<23> synch peak < 10 14 Hz) are called LSPs, while objects with SED peaking at high energies ( GLYPH<23> synch peak > 10 15 Hz) are called HSPS (Padovani & Giommi, 1995; Abdo et al., 2010). Objects with GLYPH<23> synch peak located at intermediate energies are called ISPs.  \nFig. 14 The SED of the FSRQ 3C 273. The strong and highly variable non-thermal radiation from the jet encompasses the entire electromagnetic spectrum, but is not dominant in the optical-UV and the soft Xray bands (indicated by the blue circle), where most of the emission is due to accretion onto the SMBH and to the BLR. The GLYPH<13> -ray spectrum is steep with extremely high variable intensity (up to a factor of 10,000: see the light green, orange and purple light curves at 0.2, 1.0 and 10.0 GeV, respectively) in the HE band, while very little or nothing is present in the VHE band.  \n<!-- image -->  \nThe nature of the second SED component, that extends well into the GLYPH<13> -ray band, is still debated as two alternative (or complementary) interpretations are being considered. In leptonic models (e.g. Maraschi, Ghisellini & Celotti, 1992) the emission is explained as inverse Compton scattering between the electrons in the jet and their own synchrotron emission (synchrotron self-Compton) or an external photon field (external inverse Compton). In hadronic scenarios (e.g. Bottcher et al., 2013) GLYPH<13> -rays are instead assumed to originate from high-energy protons either loosing energy through synchrotron emission (Aharonian, 2000) or through photo-meson interactions (Mannheim, 1993). In this case blazars would also be neutrino emitters (from the decay of charged pions) extending their SEDs outside the electromagnetic spectrum into newly explored multi-messenger scenarios, which might even include cosmic rays (CRs) (e.g. Padovani et al., 2016; Resconi et al., 2017).  \nFigures 13 and 14 show the SEDs of the HSP BL Lac Mrk 421 and of the LSP FSRQ 3C 273 built using large amounts of archival data from many space- and ground-based observatories covering almost all frequencies and a time span of several years. The HE and VHE GLYPH<13> -ray bands are highlighted. A clear di GLYPH<11> erence in the GLYPH<13> -ray emission of the two objects is apparent: a flat spectrum in the HE band extending to VHE energies for Mrk 421, a steep spectrum in the HE band with almost no emission in the VHE band for 3C 273. Strong variability, another defining characteristics of blazars, is clearly visible in both objects at all energies, with the largest amplitude occurring in the X-rays for Mrk 421 and in the GLYPH<13> -ray band for 3C 273.", '6.2 GLYPH<13> -ray detectors': 'Di GLYPH<11> erent GLYPH<13> -ray detectors operate in di GLYPH<11> erent bands. The HE band is where GLYPH<13> -rays are detected in electron pair-conversion telescopes. These instruments operate in space and are characterized by a very large FoV (thousands of square degrees; e.g. Tavani et al., 2009; Atwood et al., 2009). The VHE band is where the present detection capability is provided by Imaging Atmospheric Cherenkov Telescopes (IACTs) and Extensive Air Shower (EAS) observatories (e.g. DeNaurois &Mazin, 2015). These instruments observe from the ground the particle showers that are produced by the impact of VHE GLYPH<13> -ray photons on the top layers of the atmosphere, either through the Cherenkov light they generate, or via the direct detection of the charged particles in the shower. The small overlap between the two bands (between 50 and 100 GeV) allows for inter-calibration between space and groundbased observatories. This is particularly important as this is where spectral breaks occur in the most extreme astrophysical sources.', '6.3 The HE band': "Currently four GLYPH<13> -ray space telescopes or instruments sensitive to photons in the 100 MeV - 100 GeV band are operational: the 'Astro-rivelatore Gamma a Immagini LEggero' (AGILE), which was launched in 2007 and is the oldest in operation, Fermi (launched in 2008), the Alpha Magnetic Spectrometer (AMS-2, launched in 2011), and the DArk Matter Particle Explorer (DAMPE, launched in 2015). Published results or publicly available data are, however, so far available only from AGILE and Fermi . The other facilities, although sensitive to cosmic GLYPH<13> -rays, have di GLYPH<11> erent prime objectives, such as the detailed measurement of charged CRs and dark matter, and have not contributed to the GLYPH<13> -ray astronomy literature so far.  \nThe best sensitivity is provided by the Large Area Telescope on board Fermi ( Fermi -LAT, Atwood et al., 2009), which is approximately two orders of magnitude more sensitive than the previous generation of GLYPH<13> -ray telescopes like the Energetic Gamma Ray Experiment Telescope (EGRET) on board of the Compton Gamma Ray Observatory (Thompson et al., 1993).  \nThe size of the point spread function and the e GLYPH<11> ective area of Fermi -LAT strongly depend on energy, resulting in a sensitivity limit that significantly depends on the intrinsic source spectrum 40 . This has a strong impact on the blazar types that are detected in di GLYPH<11> erent GLYPH<13> -ray bands, introducing selection biases, as discussed below (Sect. 6.6).", '6.3.1 AGN in the HE GLYPH<13> -ray band': "Two main approaches have been followed to produce catalogues of GLYPH<13> -ray sources in the HE band. In the one adopted by the project teams the detection is based on GLYPH<13> -ray data only and is therefore 'blind' with respect to any additional information about astrophysical sources. For this reason they use conservative statistical thresholds (e.g. AGILE: Pittori et al. 2009; Fermi -LAT 0,1,2,3FGL: Acero et al. 2015, and references therein, where the numbers denote the n-th Fermi -LATsource catalogue; Fermi 1,2,3FHL: The Fermi-LAT Collaboration 2017, and references therein, where the numbers denote the n-th catalogue of hard sources). Other lists have instead been obtained by searching for GLYPH<13> -ray excesses at the positions of previously known blazars, or blazar candidates (e.g. Arsioli & Chang, 2017; Arsioli, Giommi & Polenta, 2017) in Fermi -LAT archival data. The two approaches are complementary as they make use of di GLYPH<11> erent information in the application of the statistical detection methods, use different thresholds and integration times, and are sensitive in di GLYPH<11> erent ways to source confusion, a problem that is becoming an issue as the sensitivity improves after many years of Fermi -LAT data.  \nFig. 15 The third catalogue of AGN detected by the Fermi -LAT (3LAC; Ackermann et al., 2015b) plotted in Galactic coordinates. FSRQs (all of the LSP type) are plotted as red filled circles, BL Lacs (mostly of the HSP type) are shown as blue points; green filled circles represent blazars of uncertain type.  \n<!-- image -->  \nThe largest catalogue of GLYPH<13> -ray sources published so far, the 3FGL, is based on the first 4 years of Fermi -LAT data and includes 3033 objects. Outside the Galactic plane almost all GLYPH<13> -ray detections that have been associated to known objects are jetted AGN, the large majority of them being blazars with only a handful of RGs.  \nFigure 15 shows a plot in Galactic coordinates of the subsample of 1563 high Galactic latitude ( j b j > 10 GLYPH<14> ) sources in the 3FGL catalogue that have been firmly associated with AGN (Ackermann et al., 2015b). This includes 415 FSRQs (all of the LSP type), 657 BL Lacs (mostly of the HSP type), and 402 blazars of uncertain type (assumed to be blazars be-  \ncause of their radio to GLYPH<13> -ray SED but with no optical spectrum yet available to classify them as FSRQs or BL Lacs).  \nAn example of the second approach to the detection of GLYPH<13> -ray sources is the Brazil ICRANet Gamma-ray Blazar catalogue (1BIBG; Arsioli & Chang, 2017) where the authors report 150 new GLYPH<13> -ray sources in the sample of multi-frequency selected Second WISE High Synchrotron Peaked (2WHSP) blazars.  \nA comprehensive list of AGN detected by Fermi , compiled at the ASDC from all published catalogues and other publications, is available on-line 41 . At the time of writing it includes 1959 distinct sources, 536 of which are FSRQs, 687 are BL Lacs, 15 are RGs, and 75 are AGN of unknown type.", '6.4 The VHE band': 'The VHE GLYPH<13> -ray band is where currently operating IACTs and EAS are sensitive, with Fermi -LAT also partly covering this band up to GLYPH<24> 2 TeV. Indeed, the largest catalogue of VHE sources, the 3FHL (The Fermi-LAT Collaboration, 2017), is based on Fermi -LAT data.  \nThis energy region is particularly challenging for AGN observations as VHE GLYPH<13> -rays are subject to pair production interactions with the extragalactic background light (EBL; Ackermann et al., 2012c) causing strong flux attenuations that are energy and redshift dependent, thus modifying the observed spectra and limiting the horizon to the relatively low redshift Universe.  \nThe present generation of IACTs (e.g. MAGIC, H.E.S.S., VERITAS) and the upcoming Cherenkov Telescope Array (CTA) are characterized by relatively small FoV (a few square degrees), and very good sensitivity. IACTs are excellent instruments for detecting fast variability, catching flaring states, and measure the status of the object during the (typically few hours) of observations. Several years of observations led to the detection of many blazars, especially during large flares, often following pointings triggered by high states discovered in other wavebands.  \nWater Cherenkov / EAS detectors (e.g. HAWK, ARGO, TIBET, and the future Large High Altitude Air Shower Observatory [LHAASO]) are instead characterized by a large FoV(thousands of square degrees), moderate sensitivity, and operate nearly 100% of the time (day and night). These observatories are well suited to carry out long-integration surveys of large parts of the sky, with typical output being fluxes averaged over long integration periods or the discovery of strong flares in bright objects.', '6.4.1 AGN in the VHE GLYPH<13> -ray band': 'The main lists of objects in this energy band detected by IACTs are available on-line 42 as interactive tables that are updated periodically as new sources are detected. At present they include approximately 180 sources distributed in the Galaxy as shown in Fig. 16. These samples do not represent uniform surveys of the VHE sky as they only include sources detected during pointings of known sources, often during flaring states. Only a fraction of the high Galactic latitude sky has been observed so far.  \nAt high Galactic latitudes almost all sources in VHE catalogues are blazars, the majority of which (50 sources) are of the HSP or ISP type, while only 8 are of the LSP type (6 FSRQs and 2 BL Lacs); two of these, namely S3 0218 + 35 and PKS1441 + 25, are located at z > 0 : 9, a remarkably high value for this energy band. Four RGs are also detected (Centaurus A, NGC 1275, PKS 0625 GLYPH<0> 35, and M 87).  \nThe 2FHL catalogue (Ackermann et al., 2016a) is based on 80 months of Fermi -LAT data and is a real full sky survey compiled with photons having energies between 50 GeV and 2 TeV. It includes 360 sources, many more that those detected by IATCs. In fact only about 25% of 2FHL sources were previously detected by Cherenkov telescopes. Similarly to the Fermi -3FGL catalogue o GLYPH<11> the Galactic plane nearly all sources are blazars. However, in this case BL Lacs of the HSP type are the large majority; only 10 FSRQs have been found so far. This di GLYPH<11> erence with respect to the HE band is easily explained as due to the much steeper GLYPH<13> -ray spectral slope of FRSQs (all of which are LSPs) and to EBL absorption that further steepens and reduces the intensity of the spectrum of the more distant FSRQs.  \nFig. 16 The sample of GLYPH<13> -ray sources detected in the VHE band as reported in TeVCat at the time of writing plotted in Galactic coordinates. Red and black points represent extragalactic and Galactic plus unidentified sources respectively.  \n<!-- image -->  \nTo complement the 2FHL sample, and in an e GLYPH<11> ort to construct a much larger list of targets for VHE observations, Chang et al. (2017) assembled the 2WHSP catalogue, a very large sample of confirmed and candidate blazars of the HSP type that are expected to emit in the VHE band. The sample was selected using radio, IR (WISE), optical, and X-ray survey data, imposing that the SED of the candidates is similar to that of known HSP blazars, which are the most abundant type of AGN found in the VHE band. The 2WHSP sample includes 1691 sources and is available on-line 43 . The already mentioned study by Arsioli & Chang (2017), who found 150 GLYPH<13> -ray detections that were never reported before using over 7 years of Fermi -LAT data, confirms that 2WHSP blazars indeed constitute a very good reservoir of candidate VHE GLYPH<13> -ray sources for the next generation of detectors such as CTA and LHAASO.  \n6.5 Blazar population properties and contribution to the GLYPH<13> -ray extragalactic background  \nThe large samples that can be assembled from Fermi -LAT catalogues and other publications have been used to determine the population properties of blazars such as the GLYPH<13> -ray number counts, the LF and cosmological evolution for both BLLacs and FSRQs (Abdo et al., 2010b; Ajello et al., 2015).  \nAjello et al. (2015) found that the blazar GLYPH<13> -ray LF can be represented by a broken power law and that its evolution with redshift is strong for all types of evolution models (luminosity, density and luminosity dependent density evolution) considered. By integrating the best fit LF, taking into account the estimated amount of cosmological evolution, the distribution of blazar spectral slopes and EBL attenuation, the authors estimated the contribution of AGN to the extragalactic GLYPH<13> -ray background (EBG, Ackermann et al., 2015a). The results show that the integrated emission from blazars and RGs can explain both the intensity and the spectral shape of the extragalactic background in the 100 MeV 820 GeV energy band. In particular, above 100 GeV a very large fraction of the EGB is due to HSP blazars with SED similar to that shown in Fig. 13. The fact that AGN are responsible for most, if not all, of the EGB is particularly important also because it leaves little room to the contribution of di GLYPH<11> use components such as GLYPH<13> -rays from the annihilation of dark matter particles and from the interaction of ultra HE CRs with the cosmic microwave background.  \n6.6 Blazars and selection biases in the GLYPH<13> -ray and other energy bands  \nThe complex broad-band SEDs of blazars result from the superposition of many spectral components, such as the double  \nhumped non-thermal emission, light from the host galaxy, the BLR, and the accretion onto the SMBH. This mix, combined with di GLYPH<11> erent viewing angles and a wide range of maximum particle acceleration energies leads to SEDs with largely di GLYPH<11> erent shapes, causing very strong selection effects when looking at blazars in widely separated regions of the electromagnetic spectrum. For instance, blazars selected at radio or microwave frequencies are mostly of the FSRQ / LSP type, whereas X-ray selection leads to samples largely dominated by BL Lacs of the HSP type. In the GLYPH<13> -ray band selection e GLYPH<11> ects are not less important, especially because the sensitivity of Fermi -LAT strongly depends on the spectral slope of the detected sources: steep GLYPH<13> -ray spectra FSRQs / LSPs (like 3C 273, see Fig. 14) are therefore detected less e GLYPH<14> ciently than hard GLYPH<13> -ray spectra HSP BL Lacs (e.g. Fig. 13), leading to percentages of the two blazar types that do not represent the real cosmic abundance. The GLYPH<24> 40 to GLYPH<24> 60 % mix between FSRQs and BL Lacs in the 3LAC sample and the over 95% of HSP BL Lacs in the 2FHL catalogue are just the result of this e GLYPH<11> ect in the HE and VHE GLYPH<13> -ray energy bands. To understand the intrinsic population properties of blazars is therefore essential to control all the selection biases. To this purpose Giommi, Padovani and collaborators published a series of papers (Giommi et al., 2012; Giommi, Padovani & Polenta, 2013; Padovani & Giommi, 2015; Giommi & Padovani, 2015), where, through a detailed Monte Carlo approach, called the blazar simplified view (BSV), they showed that the widely di GLYPH<11> erent statistical population properties of blazars observed in the radio, X-ray and GLYPH<13> -ray bands can be reproduced in detail starting from simple minimal assumptions. In particular, the BSV correctly predicts the di GLYPH<11> erent composition of GLYPH<13> -ray catalogues in the HE and VHE bands, including percentages of FSRQs / LSPs and BL Lacs / HSPs, spectral slopes, redshift distributions, and contribution to the EGB.', '6.7 The future of AGN studies in the GLYPH<13> -ray band': "Building on the technology of current generation IACTs, CTA 44 will be ten times more sensitive and will have unprecedented accuracy in its detection of VHE GLYPH<13> rays, with more than 100 telescopes located in the northern and southern hemispheres covering the 20 GeV - 300 TeV energy range. Construction should start in 2018, with the first telescopes on site in 2019. CTA will provide a systematic approach to blazar studies, as our knowledge of VHE GLYPH<13> -ray emission from blazars is very biased and patchy, since many of them have been detected only because they were in outburst (Sect. 6.4).  \nFig. 17 The comparison of this plot with that of Fig.16 illustrates the rapid evolution of the VHE sky. VHE sources detected by IACTs are shown as black dots as in Fig. 16, those from the Fermi 2FHLcatalogue (E > 50 GeV) are shown as orange filled circles, while blazars in the 2WHSP sample that are predicted by Eq. 1 to be VHE emitters with intensity larger than the sensitivity of current IACTs and that of CTA, appear as large and small green circles, respectively.  \n<!-- image -->  \nLHAASO 45 (LHAASO Collaboration, 2016) is a new generation instrument, to be built at 4410 metres of altitude in the Sichuan province of China, with the aim of studying with unprecedented sensitivity the energy spectrum, the elemental composition and the anisotropy of CRs in the energy range between 10 12 and 10 17 eV, as well as to act simultaneously as a wide aperture ( GLYPH<24> 2 sr), continuously-operated GLYPH<13> -ray telescope in the energy range between 100 GeV and 1 PeV.  \nIn the BSV paper dedicated to the VHE GLYPH<13> -ray band Padovani & Giommi (2015) estimated the number of blazars of the FSRQ and BL Lac type and their redshift distributions expected in future deep VHE surveys. The expectations are largely consistent with the 2FHL catalogue (Ackermann et al., 2016b), which suggests that the BSV might also be a reliable predictor of the average VHE sky that will be probed by the upcoming large new VHE facilities like CTA and LHAASO.  \nA study based on the subset of 2WHSP and 2FHL commonsources, shows that the average (EBL unabsorbed) VHE flux F(E > 50 GeV) of HSP blazars can be predicted with an uncertainty of the order of a factor two based on the shape and intensity of their SED synchrotron component. The following preliminary relationship  \nF ( E > 50 GeV ) GLYPH<25> 2 GLYPH<2> 10 11 S peak flux10 ( GLYPH<0> 0 : 154 Log ( GLYPH<23> synch peak) GLYPH<0> 8 : 03) (1)  \ngives F(E > 50 GeV), the VHE flux in units of photons cm GLYPH<0> 2 s GLYPH<0> 1 , as a function of Speak flux, which is the flux at the peak of the SED synchrotron hump in units of erg cm GLYPH<0> 2 s GLYPH<0> 1 and of GLYPH<23> synch peak in units of Hz.  \nTo emphasize the rapid evolution of the VHE AGN sky, Fig. 17 shows the distribution of the currently known and predicted VHE AGN in galactic coordinates, including TevCAT sources and Fermi 2FHL objects. 2WHSP sources that  \nFig. 18 Multiwavelength light curves of the non-jetted AGN MR 2251 GLYPH<0> 178. From top to bottom: 2 GLYPH<0> 10 keV X-rays from RXTE ; B band Wise Observatory data in blue open circles and B band SMARTS data in pink filled circles; V band SMARTS data, and R band Wise Observatory data. Figure reproduced from Ar'evalo et al. 2008, Fig.1, with permission. c GLYPH<13> The Authors.  \n<!-- image -->  \ndate [MJD  \n50000]  \nare predicted (on the basis of Eq. 1) to be at or above the sensitivity of current IACTs and also detectable by the future CTA are also shown.", '7 Variability-selected AGN': 'Wediscuss in this section variability-selected AGN. An overview of AGN variability in the local Universe is given in Sect. 7.1, while Sect. 7.2 deals with AGN variability in extragalactic surveys. The future of this field is discussed in Sect. 7.3.', '7.1 An overview of AGN variability in the local Universe': 'Variability of the emitted multi-wavelength (from radio to GLYPH<13> -ray) radiation has been recognized as one of the main characteristics of AGN as a class (e.g. Angione 1973; Marshall, Warwick, & Pounds 1981). Therefore, just like other diagnostics, variability can be used as a tool to select AGN in extragalactic surveys.  \nAGN display erratic, aperiodic flux variability over a wide range of timescales (from years to minutes). The distribution of AGN variability power (i.e. the power spectral density [PSD] defined as the squared amplitude of the flux, e.g. Uttley, McHardy, & Papadakis 2002) over timescales (or, equivalently, temporal frequencies) strongly depends on the observing waveband. In other words, for example, much faster variability is observed in the X-ray band than in the optical band, where the same variability amplitude is reached  \nonly over longer timescales (Fig. 18). The minimum timescale of variability measured in a given waveband provides us with an estimate of the linear size of the source component emitting in that waveband (e.g. Terrell 1967). The Xray band is where some of the most rapid (hours-minutes), largest-amplitude flux variations are measured. This variability is thought to originate in the innermost regions of the accretion flow (corona and inner disk). Moreover, it is responsible for driving (at least part of) the variability from the outer accretion disk, observed at longer wavelengths (UV and optical). Processes occurring in the jet can also contribute to the observed AGN variability (e.g. shocks or bulk injection of new particles; Marscher & Gear 1985; Bottcher &Dermer 2010). Variability associated with the jet can dominate in the radio-toGLYPH<13> -ray bands in jetted AGN (e.g. MaxMoerbeck et al. 2014; see also Sect. 6.1 and Figs. 13 and 14). These variations may ultimately originate from stochastic instabilities within the accretion flow (Malzac 2014). However, whether and how accretion-driven variability is transferred into the jet is not definitely known. In the following we will focus on discussing variability directly associated with the accretion process.  \nNote that one can indirectly probe AGN variability on much longer timescales by studying powerful past events in nearby galaxies through studies of extended emission line regions. These can then trace the history of AGN emission over the light travel time from the nucleus to the gas (typically 10 4 GLYPH<0> 10 5 years: e.g. Dadina et al., 2010; Keel et al., 2012; Gagne et al., 2014; Davies, Schirmer, & Turner, 2015).', '7.1.1 X-ray variability': "The availability of long-term monitoring and continuous sampling X-ray observations has allowed us to make significant progress towards a good characterization of X-ray variability in low-redshift AGN. These studies played a key role in our general understanding of AGN variability.  \nThe main property of AGN variability is its 'red noise' character, namely the occurrence of larger amplitude variations on longer timescales. This property became evident from early EXOSAT long-looks (e.g. Lawrence et al. 1987). The more recent long monitorings performed by the Rossi X-ray Timing Explorer ( RXTE ) enabled a detailed characterization of the X-ray PSD. Particularly when combined with continuous but shorter X-ray observations (e.g. by XMMNewton ) they allowed sampling AGN variability over a broad range of timescales (from several years to seconds, Fig. 19, left panel). These studies revealed that the X-ray PSD of AGN has a universal shape, characterized by a steep (spectral index GLYPH<24> GLYPH<0> 2) high-frequency (i.e. short-timescales) slope. Moreover, they showed that in many AGN the PSD flattens out to a slope of GLYPH<24> GLYPH<0> 1 below a characteristic frequency, dubbed 'break frequency', GLYPH<23> b (e.g. Edelson & Nandra 1999;  \nFig. 19 Left panel: X-ray PSDs from combined RXTE and XMM-Newton observations of NGC 4051 (filled circles) and NGC 3516 (open squares), and comparison with the PSD of the BHXRB Cygnus X-1 in di GLYPH<11> erent accretion states. Figure reproduced from McHardy et al. 2004, Fig. 18, with permission. Right panel: The scaling of the X-ray PSD break (expressed in terms of timescale 1 =GLYPH<23> b ) as a function of M BH in a sample of AGN observed by XMM-Newton . Open and filled circles are Narrow Line Seyferts, squares are Seyfert 1s, the green star is a Seyfert 2, the red star is Cygnus X-1. The continuous and dashed lines show the best-fitting linear model and the GLYPH<6> 1 dex region around this model. Figure reproduced from Gonz'alez-Mart'ın & Vaughan 2012, Fig. 5, with permission.  \n<!-- image -->  \nUttley, McHardy, & Papadakis 2002). Apart from this characteristic frequency, the PSD of AGN is mostly featureless over several decades in frequency 46 . The existence of a break in the PSD is indicative of GLYPH<23> b corresponding to a physical timescale of the flow at some characteristic radius. There are a number of fundamental physical timescales that might be associated with the timescales of accretion flow variability (e.g. Treves, Maraschi, & Abramowicz 1988). However, these timescales depend also on some unknown parameters such as the viscosity and scale-height of the disk. Therefore, it is di GLYPH<14> cult to unequivocally associate GLYPH<23> b with one of these timescales. Nonetheless, all the above mentioned timescales depend linearly on M BH. Early indications that also GLYPH<23> b scales (inversely) with M BH were reported in several studies (Edelson & Nandra 1999; McHardy et al. 2004) and finally confirmed by McHardy et al. (2006, see also Kording et al. 2007), who showed that the correlation becomes tighter after correcting for the accretion rate / bolometric luminosity. Although the exact functional dependence on the accretion rate / bolometric luminosity is currently debated (e.g. Gonz'alezMart'ın & Vaughan 2012; Ponti et al. 2012), it is widely accepted that stellar-mass BHs in X-ray binary systems (BHXRBs) lie on the extension of the GLYPH<23> b GLYPH<0> M BH relation, which holds for SMBHs (Fig. 19, right panel; a similar scaling occurs also in accreting neutron stars and white dwarfs: Kording et al. 2007 and Scaringi et al. 2015). Overall, the striking similarities of the X-ray timing properties of AGN and BHXRBs suggest the existence of a common physical process driving the observed variability.", '7.1.2 UV / optical variability': "The UV / optical emission of AGN displays highly correlated variability, as expected if produced in the same physical region, the accretion disk. A detailed characterization of UV / -optical variability is made di GLYPH<14> cult by the sparse and irregular sampling of ground-based observations, as well as the relatively long timescales associated with the regions of the disk emitting at these wavelengths (days-months). In recent years, dedicated ground-based campaigns (e.g. S'anchez et al. 2016, Caplar et al. 2017), the use of new powerful analysis approaches (Kelly et al. 2014), and the increasing exploitation of data from space observatories ( Kepler and Swift ; e.g. Smith et al. 2015) are opening the way to detailed studies of UV / optical variability of AGN. These studies have been revealing properties significantly di GLYPH<11> erent from those characterizing X-ray variability (e.g. Mushotzky et al. 2011, Simm et al. 2016), including steeper PSD high-frequency slopes (ranging between GLYPH<24> GLYPH<0> 3 and GLYPH<0> 4) and the detection of the PSD break at systematically longer timescales than expected from X-rays ( GLYPH<24> 100 GLYPH<0> 300 days) with no clear dependence on M BH.  \nAnimportant breakthrough in the understanding of UV / -optical variability came from the detection of inter-band, red lags (i.e. with longer wavelengths lagging behind shorter wavelengths) on day or sub-day timescales (e.g. Sergeev et al. 2005). These lags are too short to be explained by some form of outwards di GLYPH<11> usion in the flow. Therefore, heating from a central X-ray source is considered the most plausible mechanism. Indeed, the derived lag amplitude-wavelength dependence is consistent with that expected from reprocessing of X-rays in a standard disk (e.g. Cackett, Horne, & Winkler 2007; Edelson et al. 2015). In this scenario the lags are dominated by the light crossing time from the X-ray  \nsource to the region of the disk emitting at a given wavelength, with longer (red) wavelengths coming from larger radii, thus producing longer lags. Recent analyses of simultaneous X-ray, UV / optical, and IR observations confirmed the disk reprocessing hypothesis, and extended it to explain also the variable emission from the surrounding dusty torus (e.g. McHardy et al. 2014; Vazquez et al. 2015).  \nReprocessing of variable X-ray photons in the UV / optical emitting regions of the disk explains why, on timescales of hours-to-days, AGN are more variable in the X-rays than in the UV / optical. However, the availability of long X-ray observations and simultaneous optical monitoring has allowed the extension of these studies to longer timescales, revealing that on month-to-year timescales variations in the optical are more intense than in the X-rays (e.g. Ar'evalo et al. 2009; Breedt et al. 2010; Uttley et al. 2003). This behaviour cannot be explained by X-ray reprocessing only, but it requires some additional source of intrinsic disk variability dominating on long timescales (Sect. 7.1.3).", '7.1.3 What does variability tell us about the driving physical mechanism?': "The X-ray PSD of AGN has been extensively studied to gather information about the driving physical mechanism. However, the sole analysis and modelization of the PSD has not led to a clear identification of the underlying process. Indeed, most of the originally proposed models (such as shot-noise models: e.g. Lehto 1989) had di GLYPH<14> culties in explaining other X-ray timing properties of both AGN and BHXRBs, such as the observed 'rms-flux' relation, whose existence was first shown by Uttley & McHardy (2001) and later confirmed by several studies (e.g. Vaughan et al. 2003; Gaskell 2004; McHardy et al. 2004). This relation indicates that the absolute amplitude of X-ray variability (rms, e.g. Vaughan et al. 2003) is linearly correlated with the flux level, meaning that the source is more variable when it is brighter. The existence of an rms-flux relation implies that the underlying physical process is multiplicative and that the longterm variations should modulate the short-term variations (Gaskell 2004; Uttley, McHardy, & Vaughan 2005).  \nSuch findings argue against models (such as additive shot-noise models) invoking the presence of independent flares or active regions. Rather, it appears that the class of 'propagating-fluctuation' models, first introduced by Lyubarskii (1997), are more suitable to explain a vast range of X-ray timing properties, including the rms-flux relation (Ar'evalo &Uttley 2006; Ingram & van der Klis 2013). These models assume the emergence of local perturbations of disk parameters triggering variations of the accretion rate, with long timescale perturbations produced at larger radii. If the timescale of the perturbations is longer than the radial di GLYPH<11> usion time, the perturbations can propagate inward, combin-  \nng multiplicatively with perturbations produced at smaller radii, and reach the innermost zones where most of the energy is released (e.g. Churazov, Gilfanov, & Revnivtsev 2001; Hogg & Reynolds 2016).  \nThese models can explain the presence of large amplitude X-ray variability on a wide range of timescales, even orders of magnitude longer than the viscous-timescale of the compact X-ray emitting regions of the flow. Moreover, the perturbations produced throughout the disk could be responsible for driving intrinsic UV / optical disk variability (Uttley et al., 2003). This component would explain the excess longtimescales optical variability detected in some AGN (Sect. 7.1.2). Propagating-fluctuation models are also invoked to explain the common detection of 'hard' X-ray lags (timedelays of the hard X-ray band variations with respect to soft X-ray band variations) in both AGN and BHXRBs (e.g. Miyamoto et al. 1988; McHardy et al. 2004; Uttley et al. 2011; De Marco et al., 2013, 2015). These lags have large amplitudes, typically of the order of 1% of the variability timescale. By interpreting the lags as due to light-travel time e GLYPH<11> ects, the inferred size of the emitting regions would be too large ( GLYPH<24> 10 3 gravitational radii) to be plausible (e.g. Nowak et al. 1999). However, if due to the slower, viscous propagation in the flow the large lags can be easily recovered in standard disk-corona geometries (e.g. Kotov, Churazov, & Gilfanov 2001; Ar'evalo & Uttley 2006).  \nVariations of photoelectric absorption, e.g. associated with temporary obscuration of the central engine as a consequence of gas clouds located in the BLR or the torus crossing the observer's line of sight can also contribute to the observed AGN variability (Risaliti et al. 2011; Cappi et al. 2016). However, this is unlikely to be responsible for the bulk of it, as several arguments and observational evidences rather favour an intrinsic origin. These include: the ubiquity of AGN variability; the universal shape of the PSD; the scaling of characteristic timescales with M BH; the similarities of timing properties in AGN and BHXRBs; the fact that the inner / outer disk and the BLR directly respond to continuum variations as inferred from results of X-ray (Fabian et al. 2009; Zoghbi et al. 2012; De Marco et al. 2013; Kara et al. 2016) and UV / optical reverberation mapping (e.g. Peterson et al. 2004; Edelson et al. 2015). Moreover, recent studies of long-term ( GLYPH<24> 15 years) X-ray variability of distant AGN ( z = 0 : 6 GLYPH<0> 3 : 1: Yang et al., 2016) showed that intrinsic Xray variability prevails over absorption variability (see also Hern'andez-Garc'ıa et al. 2015; Soldi et al. 2014), further supporting this conclusion.", '7.2.1 Selecting AGN by variability': 'Extragalactic surveys are typically characterized by uneven sampling, with large gaps between consecutive cycles. This makes PSD techniques unsuitable for studying variability in these datasets. The identification of variable sources requires assessing whether the variability observed between observations exceeds the variations due to statistical fluctuations. This is usually done by computing the quantity X 2 = P Nobs i = 1 ( xi GLYPH<0> ¯ x ) 2 =GLYPH<27> 2 err ; i , where xi denotes the photon flux (e.g. Lanzuisi et al. 2014; De Cicco et al. 2015; Simm et al. 2016; Kozłowski et al. 2016) during each observation, ¯ x is the average photon flux, and GLYPH<27> 2 err ; i is the measurement error. The X 2 statistics tends to a GLYPH<31> 2 distribution for large photon fluxes (in a low-photon flux regime assessing whether a source is significantly variable requires carrying out MonteCarlo simulations; e.g. Paolillo et al. 2004; Young et al. 2012). Thus, the ability to detect significant variability in single sources depends on the error of each measurement. At a given source flux and exposure, this in turn depends on the collecting area of the detector and the background contribution, which a GLYPH<11> ects the uncertainty on the flux measurements (e.g. Lanzuisi et al. 2014).  \nSelection on the basis of variability can return a relatively high number of AGN candidates. The latest estimates from optical variability over a temporal baseline of 3 years (De Cicco et al. 2017, in prep.) are 275 deg GLYPH<0> 2 AGN at a magnitude limit r < 23. This corresponds to GLYPH<24> 48% completeness with respect to X-ray confirmed AGN at the depth reached in the COSMOS field (Fig. 20, left panel). However, the resulting AGN density strongly depends on the characteristics of the survey - mainly the spanned temporal baseline and sampling cadence, the observing wavelength, the depth of the single exposures - as well as on the AGN type. Some of these aspects are discussed in Sect. 7.2.2.', '7.2.2 Selection e GLYPH<11> ects': "As the bulk of AGN variability appears to be intrinsically associated with the accretion process, any AGN can in principle be selected by variability provided a significant fraction of the emission from the nucleus is directly observable. This requirement makes the X-ray band particularly suitable for the identification of AGN, independently of their classification, thanks to the penetrating power of X-rays and the relatively weak host galaxy emission (Sect. 5.2). As a matter of fact, the number of X-ray variable AGN appears to be type-independent (see Fig. 20, right panel), with X-ray variable type 2 AGN typically showing less variability at longer wavelengths and on similar time scales (e.g. Lanzuisi et al. 2014, Hern'andez-Garc'ıa et al. 2015). Indeed, in the opti-  \nband the completeness of AGN samples selected through variability decreases significantly for type 2 AGN (De Cicco et al. 2015 estimate 25% and 6% completeness respectively for type 1 and type 2 AGN over a temporal baseline of 5 months), while in the X-ray band it is similar for the two classes (e.g. GLYPH<24> 40% and GLYPH<24> 32% completeness respectively for type 1 and type 2 AGN, Lanzuisi et al. 2014). Nonetheless, it is important to note that high column densities of circumnuclear absorbing material can significantly a GLYPH<11> ect the fraction of detected X-ray variable AGN, e.g. as a consequence of the increased contribution from a large scale, constant reflector (Paolillo et al. 2004; Hern'andez-Garc'ıa et al. 2015).  \nX-ray variability is also suitable for identifying LLAGN, which are missed by other selection criteria (Young et al. 2012). Systematic X-ray variability studies showed that, given good statistics, variability can be detected in a high fraction of AGN (e.g. 80 GLYPH<0> 90% Paolillo et al. 2004; Lanzuisi et al. 2014; Soldi et al. 2014; Yang et al. 2016) independently of the optical classification of the object or its radio loudness (note that in jetted AGN the X-ray variability can contain a very significant contribution from the jet: e.g. Lichti et al. 2008; see also Figs. 13 and 14).  \nThe e GLYPH<11> ectiveness of variability as a tool to select AGN is strongly related to the temporal baseline spanned by the observations and the depth of a single frame. Indeed, given the red-noise character of the PSD of AGN, the ability of detecting variability is higher at longer timescales (see Fig. 20, left panel), particularly when the low-frequency part of the PSD below GLYPH<23> b is sampled. In the X-ray band, GLYPH<23> b scales inversely with M BH and directly with the accretion rate / bolometric luminosity (but see discussion in Sect. 7.1.1), thus the sampling of longer timescales also allows detection of variability over a wider range of M BH and L = L Edd. In the UV / optical this scaling is not clearly observed (Simm et al. 2016), but the break is measured at systematically longer timescales than in the X-rays (Sect. 7.1.2). Therefore, the longer the maximum sampled timescales, the higher the detection fraction and, at least as far as the X-rays are concerned, the larger the range of M BH and L = L Edd probed. Note that time dilation e GLYPH<11> ects reduce the e GLYPH<11> ective range of sampled timescales. Therefore, given a total exposure time, the more distant a quasar is the more likely it is to intercept the highfrequency part of the PSD, where the variability power drops rapidly, thus making detection of variability more di GLYPH<14> cult and limited by statistics.", '7.2.3 Variability dependence on luminosity and redshift': "In the presence of uneven, gappy data, variability can be quantified using the so-called normalized excess variance ( GLYPH<27> 2 NXV ; e.g. Nandra et al. 1997; Vaughan et al. 2003; Ponti et al. 2012; see also Kelly et al. 2014), which provides an estimate of the amplitude of intrinsic source variability over the  \n<!-- image -->  \nFig. 20 Left panel: Fraction of optically variable AGN in the VST-SUDARE / VOICE survey of the COSMOS field as a function of temporal baseline. Figure reproduced from De Cicco et al. 2017, in prep., with permission. Right panel: Distribution of X-ray variability index V (which parametrizes the confidence level of variability) for sources selected from the XMM-COSMOS survey divided by class. The dashed vertical line marks the value V = 1.3 used to discriminate between variable and non-variable sources. Sources with V > 1.3 are intrinsically variable at the 95% confidence level. c GLYPH<13> AAS. Figure reproduced from Lanzuisi et al. 2014, Fig. 5, with permission.  \n<!-- image -->  \nsampled timescales. Biases associated with measurements of GLYPH<27> 2 NXV have been extensively studied by Allevato et al. (2013, see also Almaini et al. 2000). These biases can be greatly reduced choosing an appropriate observing strategy (e.g. planning observations separated by constant temporal gaps), while 'ensemble' GLYPH<27> 2 NXV estimates (i.e. obtained by averaging over single GLYPH<27> 2 NXV estimates from multiple light curves of the same source, or from single light curves of many sources with similar properties) should be preferred.  \nDeriving a reliable estimate of GLYPH<27> 2 NXV is important in order to properly analyze global variability properties of different AGN classes, to study correlations with fundamental parameters, and to investigate the evolution of variability with redshift. These studies have shown that variability is anti-correlated with luminosity in several wavebands (e.g. in the X-rays: Ponti et al. 2012; Lanzuisi et al. 2014 and references therein; in the optical / MIR: Hook et al. 1994; Kelly, Bechtold, & Siemiginowska 2009; MacLeod et al. 2010; Zuo et al. 2012; Kozłowski et al. 2016; Simm et al. 2016). The origin of this anti-correlation is currently unknown, but, at least in the X-rays and on relatively short timescales (shorter than GLYPH<24> 1 =GLYPH<23> b ), this correlation seems to be the byproduct of a more fundamental anti-correlation of variability with M BH ultimately driven by the scaling of the PSD break (e.g. Czerny et al. 2001; Papadakis 2004; O'Neill et al. 2005; Nikołajuk et al. 2006; Zhou et al. 2010; Ponti et al. 2012; Lanzuisi et al. 2014). The GLYPH<27> 2 NXV -M BH relation is very tight, with an estimated scatter of the order of the uncertainties on M BH (Zhou et al. 2010; Ponti et al. 2012). These findings reinforce early suggestions that GLYPH<27> 2 NXV could be used to estimate M BH (Czerny et al. 2001; Nikołajuk, Papadakis, & Czerny, 2004; Nikołajuk et al., 2006, Gierli'nski, Nikołajuk, & Czerny 2008).  \nSeveral studies also showed that both X-ray and optical variability tend to be stronger at higher redshifts, but this appears to be a consequence of selection e GLYPH<11> ects (e.g. Cid Fernandes, Aretxaga, & Terlevich 1996; Almaini et al. 2000; Manners, Almaini, & Lawrence 2002; Paolillo et al. 2004; Lanzuisi et al. 2014; Morganson et al. 2014; Simm et al. 2016; Yang et al. 2016; Paolillo et al. 2017). Therefore, to date there are no clear indications of an evolution of AGN variability with redshift.", '7.3 The future of AGN variability studies': 'Variability is a defining property of AGN, therefore a fundamental tool to understand the AGN engine and map its close environments. Due to its diagnostic power and complementarity to other probes, variability is gaining increasing importance in the census of the AGN population. The recognized relevance of AGN variability studies is mirrored by the growing number of future missions and facilities that include the investigation of the variable Universe amongst their science goals. Among these is eROSITA (Merloni et al. 2012; see also Sect. 5.4), due to launch in spring 2018. During its four years of operation eROSITA will perform a deep survey of the entire sky at X-ray wavelengths. The planned monitoring strategy (eight all-sky surveys and a cadence of six months, with the ecliptic poles being monitored at higher pace) will provide repeated observations of the same portions of the sky. Ultimately, this will allow sampling AGN X-ray variability over time scales from 250 s (corresponding to the daily eROSITA exposure) up to 4 years (corresponding to the scheduled duration of the survey phase). Based on AGNX-ray variability characteristics and scaling properties (Sect. 7.1.1), eROSITA is expected to detect around 60,000  \nvariable AGN in the full sky (and many more overall: Sect. 5.4).  \nIn the far future, Athena (Nandra et al. 2013; see also Sect. 5.4) is expected to greatly advance our knowledge of AGN X-ray variability. Thanks to its large collecting area, the sensitivity of X-ray variability measurements will be significantly enhanced. This will have a great impact on our understanding of the accretion process variability, it will allow the mapping of the close environments of AGN and will assess the role of AGN winds and outflows and their influence on the observed X-ray variability properties.  \nThe exploration of the transient and variable sky is one of the driving science theme of several future facilities that will operate at longer wavelengths. In the optical band these include the Zwicky Transient Facility (ZTF 47 ), a high-cadence, 3-year, time-domain survey, starting in summer 2017. However, the currently most ambitious planned survey in the optical band is the LSST, starting operations in 2022 (LSST Science Collaboration et al. 2009). LSST is designed to uniformly observe an area of GLYPH<24> 20 ; 000 deg 2 , with about 50 GLYPH<0> 200 visits per source for each of the six filters, over an operation period of ten years. This cadence will probe optical variability on time scales ranging between 1 minute and one decade, allowing selection of tens of millions of AGN and the construction of highly-complete catalogues with minimum contamination. Finally, variability studies of radio-emitting AGN will be one of the main science goals of the SKA (Sect. 2.4), which is expected to provide a deluge of AGN radio variability information.', '8 Summary': "This review highlights the extraordinary diversity of observational signatures produced by growing SMBHs, and illustrates the challenges of placing all these observations into a coherent picture. AGN are complex systems exhibiting a wide range of phenomena, and di GLYPH<11> erent classes of AGN can be selected across the full range of the electromagnetic spectrum (Fig. 21). The e GLYPH<14> ciency of selection of AGN in various wavebands is the result of: (1) variations in the underlying physical properties of AGN; (2) observational capabilities; (3) selection e GLYPH<11> ects.  \nThe first consideration relates to physical e GLYPH<11> ects (introduced in Sect. 1 and discussed throughout this review). The most straightforward of these is the presence or absence of a strong relativistic jet, leading to the distinction between jetted and non-jetted AGN as discussed in Sect. 2. As detailed in Sect. 2.1.3 and shown in Fig. 21, the latter class is fainter in the radio and absent in the GLYPH<13> -ray band (Sect. 6), highlighting how AGN selection can be a GLYPH<11> ected by variations in the physical properties of di GLYPH<11> erent AGN populations. Other  \nFig. 21 The largest AGN surface density over the whole electromagnetic spectrum. Black filled points refer to all AGN, open red points are for non-jetted AGN. The latter are actually directly measured only in the radio band, while in the NIR to X-ray bands they have been derived by simply subtracting 10% from the total values. Non-jetted AGN have not been detected in the GLYPH<13> -ray band. The blue square indicates variability selected AGN (Sect. 7.2). Updated from Fig. 11 of Padovani (2016), where one can find the references to the relevant samples and facilities, to include variability selected AGN and the results of the CDFS 7 Ms sample (Luo et al., 2017).  \n<!-- image -->  \nphysical e GLYPH<11> ects include changes in the accretion flow with L = L Edd (which can modify the shape of the intrinsic SED, in particular the relative outputs in the optical / UV and Xray bands; e.g. Vasudevan & Fabian 2009; Yuan & Narayan 2014), and obscuration by gas and dust that can highly suppress emission in the NIR through soft X-rays (Sects. 3 5).  \nSecond, observations in some wavebands are more sensitive than others relative to the typical AGN SED. For example, the current generation of radio telescopes (Sect. 2) can probe AGN with far smaller bolometric fluxes, compared to contemporary GLYPH<13> -ray observatories (Sect. 6), yielding a far higher surface density of detected AGN.  \nThird, AGN selection techniques (due to luminosity, colour, morphology, variability, etc.) have di GLYPH<11> erent levels of e GLYPH<14> ciency in di GLYPH<11> erent wavebands. Of particular importance is the relative emission of the AGN compared to its host galaxy. At wavelengths at which stellar processes in the host galaxy can be particularly luminous (e.g. optical, IR, and to some extent the radio), it is challenging to select extremely faint AGN even in the deepest observations (although welldesigned techniques using colours or emission line charac-  \nteristics can help minimize contamination). By contrast, host contamination is particularly low in the X-ray band (Sect. 5), and cutting-edge X-ray observatories are capable of extremely deep observations. Simple X-ray luminosity selection can therefore probe AGN at very faint fluxes, leading the detected AGN surface density to be highest in this band (Fig. 21).  \nWe note that by multiplying the largest entry in Fig. 21 by the area of the sky we estimate that there are at least GLYPH<25> 1 billion AGN in the Universe that could be detected with current technology. This number needs to be compared with the number of currently known AGN, of the order of a million (Fig. 6), which shows the exciting potential for discovery in future AGN surveys (as detailed in Sects. 2.4, 3.5, 4.6, 5.4, 6.7, and 7.3). We can also compare it with the number of currently observable galaxies in the Universe, GLYPH<25> 200 billion (Conselice et al., 2016), indicating that bright AGN are found in approximately 1% of galaxies.  \nTable 3 summarizes the selection biases and key capabilities (in other words, the weaknesses and the strengths) in di GLYPH<11> erent bands, as described above and in detail throughout this review. Despite the significant di GLYPH<11> erences between AGNclasses detected in some bands, the observations highlighted in this review illustrate that AGN share some common components over a wide dynamic range (up to 12 orders of magnitude) in physical scales. In what follows, we will describe this basic 'architecture' of an AGN in the context of the observational signatures described in the review. We will then discuss our present understanding of AGN unification models, highlighting the need for a more complex picture than the classic 'strict' unification, and discussing the importance of understanding relevant timescales in interpreting observations. Finally, we will present a broad framework for an emerging picture of AGN and their host galaxies in light of the exciting recent advances such as those presented in this review and will conclude by highlighting some future prospects and open questions.", '8.1 Fitting together the components of an AGN': "Based on the current observational knowledge of AGN as discussed throughout this review, we can now assemble the di GLYPH<11> erent components, covering a wide range of physical scales, that together make up the complete picture of the AGN phenomenon.  \nBlack hole ( 10 GLYPH<0> 7 -10 GLYPH<0> 3 pc)The fundamental element common to all AGN is of course the central BH itself. Astrophysical BHs are simple objects whose only distinguishing characteristics are mass and spin, but as we have seen throughout this review, these two parameters are critically important in determining the observable features of an AGN. It is a nearly universal feature of AGN selection that more massive BHs are easier to detect, because the mass of the  \nBH sets the Eddington limit, and so massive BHs are more luminous at a given L = L Edd (Sect. 3.2.5 and 5.3). (The exception here is selection via X-ray variability, for which characteristic frequencies vary inversely with M BH, so that detecting more massive BHs requires longer timescale observations, as described in Sect. 7.1.1.) The e GLYPH<11> ects of BH spin are far more di GLYPH<14> cult to understand observationally, but rapidly spinning BHs may have accretion disks that extend closer to the event horizon, producing a bluer SED (see below) with a higher radiative e GLYPH<14> ciency, and may influence the ability of accreting BHs to launch relativistic jets and radiation linedriven winds.(e.g. Tchekhovskoy et al., 2011; Narayan et al., 2014).  \nAccretion flow ( 10 GLYPH<0> 7 -1 pc)The accretion flow onto the BH is the ultimate energy source in AGN and the most important component in determining their observational characteristics. Indeed, turning a normal galaxy into an AGN merely requires a SMBH accreting at a relatively high accretion rate. There is compelling theoretical and observational evidence that the structure of the flow changes with L = L Edd (e.g. Narayan & Yi, 1994; Vasudevan & Fabian, 2009; Yuan & Narayan, 2014), with higher L = L Edd systems producing stronger emission from an optically-thick accretion disk in the optical and UV (e.g. Slone & Netzer, 2012; Netzer & Trakhtenbrot, 2014; Capellupo et al., 2015; Castell'o-Mor, Netzer, & Kaspi, 2016; Bertemes et al., 2016) and stronger radiation line-driven winds (e.g. Laor & Davis, 2014).  \nThe structure of the flow also appears to influence emission from the magnetic corona (with lower L = L Edd systems having stronger X-rays relative to the disk emission: Sect. 5.1) and is also connected to the launching of relativistic jets, with luminous radio emission observed to be more common in lower L = L Edd systems (see references in Sect. 2). Changes in the accretion flow are also the source of the bulk of observed variability in AGN. As discussed in Sect. 7, the variability is observed over a wide range of timescales from the optical to the X-rays, likely corresponding to characteristic (e.g. viscous) time scales at various radii in the accretion disk (although there is also some interplay due to reprocessing of emission from di GLYPH<11> erent regions). The nature of the variability changes with L = L Edd further illustrating the dependence on the structure of the flow.  \nTorus ( 1 -10 pc)The putative torus of gas and dust surrounding the central engine in the AGN is critical to understanding two key observational phenomena: emission from the AGN in the IR, and obscuration of the accretion disk and corona emission (see also Netzer 2015 for a review). As discussed in Sect. 3.1, the majority of the MIR light from luminous AGN is emission from hot dust. The geometric distribution (smooth or clumpy, axisymmetric or polar) and kinematics (static, inflowing, or outflowing) of the dusty material are however still uncertain, as is their connection to the accretion flow on larger and smaller scales. At minimum,  \nTable 3 A multi-wavelength overview of AGN highlighting the di GLYPH<11> erent selection biases (weaknesses) and key capabilities (strengths). The definitions of some of the terms used in the bias and capability columns are as follows: E GLYPH<14> ciency : ability to identify a large number of AGN with relative small total exposure times (this is thus a combination of the nature of AGN emission and the capabilities of current telescopes in a given band). Reliability : the fraction of sources that are identified as AGN using typical criteria that are truly AGN. Completeness : the ability to detect as much as possible of the full underlying population of AGN.  \nit is now well-established that the structure of the torus is not universal but vary significantly for AGN types and even within an individual class (Sect. 3.2.4). This variation in the dusty torus also has implications for AGN obscuration, as the covering factors of obscuring material can di GLYPH<11> er significantly for di GLYPH<11> erent AGN, and variations in torus structure can a GLYPH<11> ect the observed column densities, extent, and time variability of the obscuration. We can ultimately conclude that the dusty torus is a common component of AGN that is critical for understanding observations, but its physical nature is uncertain, variable, and complex.  \nJet ( 10 GLYPH<0> 7 -10 6 pc)Another important but poorly understood component of the AGN phenomenon is the presence and strength of a relativistic jet. Jets dominate the emission from AGN in the GLYPH<13> -rays and often in the radio band (as discussed in Sects. 2 and 6), and can make important contributions in the X-rays and (in the case of blazars) across the whole SED. The structure and orientation of the jet can influence a range of rich observational phenomena, particularly in the radio and GLYPH<13> -rays; indeed the majority of the AGN classes presented in Tab. 1 relate in some way to the presence of a jet. However, despite jet emission being among the best- (and earliest-) studied aspects of AGN, the physical nature of AGN jets and the prevalence of relativistic outflows, particularly low-luminosity jets on small scales, remain uncertain.  \nHost galaxy and dark matter halo ( 10 -10 6 pc)In understanding the observational signatures of AGN it is essential to account for the host galaxies and large-scale structures in which the BHs reside (see Hickox et al. 2016 for a review). One important consideration is the e GLYPH<11> ect of host galaxy dilution (or equivalently, 'contamination') on AGN selection, which are spelled out in detail in this review, particularly in the radio, IR, optical, and X-ray bands (Sects. 2  \n- 5). In all cases, this contamination leads to uncertainties in the population of faint AGN. It also produces a bias in AGN selection toward higher L = L Edd, an e GLYPH<11> ect which is strongest in the IR and optical bands, and serves as motivation for observations at high angular resolution that can separate the AGN emission from the stellar processes in the surrounding galaxy (e.g. Gandhi et al., 2009; Simmons et al., 2011). The properties of gas in host galaxies can also have a physical influence on the fueling and emission from AGN. Some AGN obscuration originates on galaxy scales much larger than the putative dusty torus (e.g. Chen et al., 2015; Buchner et al., 2017), and connections between physical AGN properties (for example the distinction between HEG and LEG line classifications, indicating di GLYPH<11> erent L = L Edd: Sect. 2.1.4) and the stellar populations of host galaxies indicate that the gas supply for BH accretion can be connected to the largerscale reservoir from which stars form in the host galaxy (e.g. Hickox et al., 2009; Smolˇci'c et al., 2009; Smolˇci'c, 2009; Azadi et al., 2015). Finally, the interaction between AGN and gas in surrounding dark matter halos can have important e GLYPH<11> ects on observed phenomena, particularly with hot spots, lobes, and wide-angle tails in large-scale relativistic jets (e.g. Hardcastle, 2015).", '8.2 Unification and the importance of timescales': "Piecing together our current understanding of the various components of an AGN and their observational signatures, we can begin to re-assess the extent to which the full AGN population can be explained by a 'unified' model that reduces the complex AGN 'zoo' described in Sect. 1 (Tab. 1) to a relatively small set of parameters.  \nIn the most straightforward 'strict' unified model, the only parameter is orientation relative to an axisymmetric  \nFig. 22 Observational signatures in a 'weak' unification model with two parameters (radiative e GLYPH<14> ciency [related to L = L Edd], and relativistic jet strength), showing the classes associated with each broad range in this parameter space. This schematic illustrates the need for parameters beyond orientation to explain the wide range of AGN properties. A theme that emerges throughout this review is that these classifications do not represent distinct groups of AGN, but rather general regions in a continuous distribution of AGN properties. Adapted from schematic by P. Hopkins.  \n<!-- image -->  \ndusty torus and relativistic jet (Antonucci, 1993; Urry & Padovani, 1995). In broad terms this model has been remarkably successful in connecting type 1 and 2 Seyferts, and FSRQs and HEGs. In addition to the presence or absence broad lines, orientation can also help explain the details of the line profiles; for example, Shen & Ho (2014) suggest FWHM(H GLYPH<12> ) is more of an indicator of orientation than mass. However, the evidence presented in this review and elsewhere (see Netzer 2015 for a comprehensive overview) suggests that a picture based primarily on orientation and obscuring material is incomplete. While the structure of AGN clearly deviates from spherical symmetry and so there is some orientation dependence on observed properties, other parameters also have key e GLYPH<11> ects. Of particular importance is L = L Edd, which can change the structure and emission properties of the accretion flow and thus the SED shape and excitation properties of surrounding gas (Sect. 8.1), and can also impact the detectability of AGN over emission from the host galaxy.  \nEven at a fixed L = L Edd, the structure of the AGN is not universal. For example, the dusty torus can have a range of covering factors (producing a statistical di GLYPH<11> erence in the intrinsic properties of objects that are observed to be type 2 as opposed to type 1: Sect. 3.2.4), and the strength of a relativistic jet can vary, yielding very di GLYPH<11> erent multi-wavelength signatures particularly in the radio and GLYPH<13> -rays (as discussed in Sects. 2 and 6). Further, obscuration of the AGN or dilu-  \ntion of stellar processes can be produced in the host galaxy, independent of the small-scale orientation of the central engine (e.g. Chen et al., 2015; Buchner et al., 2017). A more complete 'weak' unified model is one in which all these components ( L = L Edd, torus covering factor, jet strength, and host galaxy properties as well as orientation) come together to produce the observed signatures of an AGN. A schematic showing the e GLYPH<11> ects of just two of these parameters, BH accretion rate (BHAR) and jet strength, is shown in Fig. 22. An important distinction is that these parameters, as well as the others described above, comprise a continuous distribution. Therefore the separate AGN classes sample di GLYPH<11> erent parts of this distribution rather than representing truly distinct populations, extending the picture for the dominance of radio jets presented by Padovani (2016).  \nIt is also important to note that the parameters that determine AGN properties will naturally be expected to vary with time. This has motivated another sort of 'unification', in which AGN represent the same underlying objects viewed at di GLYPH<11> erent points in their evolution. One example of this is the classic merger evolution scenario, in which a galaxy merger triggers gas flows that fuel an AGN, starting o GLYPH<11> obscured until feedback clear the surroundings of the black hole producing an unobscured object (e.g. Sanders et al., 1988; Hopkins et al., 2008). While there is compelling evidence for time evolution in some cases (for example large-scale radio jets are likely to have evolved from more compact relativistic outflows) it is challenging to construct a successful unification picture based on time evolution alone. This difficulty arises from the relative time and spatial scales: while galaxy evolution processes can take 10 8 years or more and on scales of kpc, variations in nuclear structures, gas flows, and BHARs can occur on timescales many orders of magnitude shorter (e.g. Hickox et al. 2014; Fig. 23) as evidenced by hydrodynamic simulations (e.g. Novak et al., 2011) and AGNlight echoes (Keel et al., 2012; Schawinski et al., 2015) that point toward large-amplitude fluctuations in AGN luminosity on timescales of GLYPH<24> 10 5 -10 6 years. Thus an AGN cannot directly 'know' about a galaxy merger or other processes that happen on large galactic scales. While there may be some connection between galaxy-scale processes and the instantaneous observed signatures of an AGN, these will be primarily statistical in nature (e.g. Hickox et al., 2009; Goulding et al., 2014; Azadi et al., 2015).", '8.3 The emerging technicolor picture': "With this reasoning in mind, there is emerging a general picture to describe the 'technicolor' properties of AGN and their host galaxies that is based on the statistical relationships between BH and galaxy evolution. In this picture, BHARs are broadly correlated with the supply of gas (and thus SFR)  \nFig. 23 An illustration of the stochastic fluctuations in AGN accretion rates (taken from the hydro simulations of Novak et al. 2011) on timescales shorter than those for typical galaxy evolution processes. This schematic highlights the weak connection between the instantaneous properties of the AGN and the evolution of the larger host galaxy. c GLYPH<13> AAS. Figure reproduced from Hickox et al. (2014), Fig. 1, with permission.  \n<!-- image -->  \nFig. 24 The range of physical processes involved with BH fuelling, in di GLYPH<11> erent regimes of BHAR and gas supply in the host galaxy. Many observed properties of AGN can be attributed to the di GLYPH<11> erent physics operating in these various regimes. Adapted from schematic by P. Hopkins.  \n<!-- image -->  \nin the centres of galaxies, but can vary dramatically over several orders of magnitude in response to processes (instabilities, feedback, etc.) that occur on small scales. A schematic showing the range of physical processes involved in di GLYPH<11> erent regimes of BHAR and a galaxy's central gas supply is shown in Fig. 24.  \nThe key point is that any type of galaxy can in principle host AGN with a wide range of observational signatures, but broad correlations between gas supply and BHAR introduce some important general trends (e.g. high L = L Edd, IR-selected  \nAGN being found in SFGs, while low L = L Edd LERGs are found primarily in passive galaxies; Fig. 25).", '8.4 The future and open questions': "There are exciting prospects for future progress in studies of AGN over the coming decades. Many of the potential breakthroughs come from new observational resources, in particular observations at high resolution and sensitivity. On the theoretical side, increasingly sophisticated and complex simulations of AGN will inform the nature of the central engine and of AGN feedback. Here we briefly discuss each of these avenues for progress, and conclude with a survey of interesting open questions in the field.  \nNewobservations at high resolution and sensitivity.One critical observational capability in studying the AGN central engine is the ability to directly resolve the relevant small scales with correspondingly high sensitivity. Recently, NIR adaptive optics and particularly interferometric observations have provided new insights about the structure of the AGN torus (Sect. 3.1). ALMA is already resolving the innermost parts of nearby AGN, such as NGC 1068 (Gallimore et al., 2016; Garc'ıa-Burillo et al., 2016; Imanishi, Nakanishi, & Izumi, 2016) and NGC 1097 (Hatziminaoglou et al. in prep., Izumi et al. in prep.) down to a few parsec scales, providing new insights into the dynamics near the SMBH by resolving its sphere of influence, the existence of the torus and the feeding of the SMBH, and is promising more groundbreaking results once the high frequency bands are o GLYPH<11> ered in the longest baselines ( GLYPH<24> 16km). ALMA, in collaboration with the Global mm-Very Large Baseline Interferometry (VLBI) Array 48 and the Event Horizon Telescope 49 consortia, is also trying to directly observe for the first time the immediate environment of the SMBH in, amongst others, M 87, OJ 287, and Cen A, with angular resolution comparable to the event horizon, as part of the Cycle 4 mm-VLBI campaign, building on previous work (e.g. Johnson et al., 2015; Fish et al., 2016). With the launch of JWST and the advent of > 30m class ground-based telescopes, we will see a dramatic improvement in the ability to study the morphologies and spectral properties of the central engine on small scales. In the radio and submm, advances in interferometry (including along Earth-scale baselines) have the potential to bring further insights into the nature of AGN jet acceleration, mechanical feedback, and gas content and kinematics. Planned or large space missions or concepts in the X-rays (e.g. Athena , Lynx 50 ) and optical / UV (e.g. HabEx 51 , LUVOIR 52 ), along with a range of other potential missions  \nFig. 25 Left panel: L = L Edd distributions for radio, IR, and X-ray selected AGN. Adapted from Hickox et al. (2009), where one can find details on the area and depth of each survey. Right panel: Aschematic picture for evolution of galaxies and their observed AGN classes, based on observations of AGN populations to z GLYPH<24> 1. All galaxies appear to begin as star-forming blue-cloud systems and end as passive red-sequence sources, once their dark matter halos have grown su GLYPH<14> ciently. However, we show that those galaxies hosting IR, X-ray, and / or radio AGN appear to follow a similar evolutionary path: radiatively e GLYPH<14> cient rapid BH growth (IR / X-ray AGN) appears to be linked with those galaxies with large supplies of cool gas, while mechanically dominated (radio) accretion is associated with passive galaxies, which may also be responsible for preventing late SF. The red and green stars represent schematically the subset of galaxies that are observed as IR- and X-ray bright AGN, respectively, in the di GLYPH<11> erent phases of evolution. c GLYPH<13> AAS. Figure reproduced from Goulding et al. (2014), Fig. 7, with permission.  \n<!-- image -->  \n(some of which are discussed throughout this review), will enable the study of AGN phenomena with high sensitivity and spectral and / or spatial resolution.  \nLarge sky survey data sets.All areas of astronomy are being revolutionized by increasingly larger and deeper sky surveys at all wavelengths, and this flood of data has the potential for major breakthroughs in our understanding of AGN. As shown in Fig. 21, X-ray surveys are the most efficient for detecting a high surface density of AGN with minimal host galaxy contamination. The next major X-ray survey will be the eRosita All Sky Survey (eRASS) by the eROSITA instrument (Sect. 5.4), which will detect GLYPH<25> 3 million AGN over most of the sky, with ground-based optical spectroscopic follow-up from multiple planned surveys. Further deep, wide surveys with Athena , Lynx , and other future X-ray missions would probe large numbers of AGN over a wider parameter space in redshift and luminosity.  \nIn the optical and NIR, the Euclid and WFIRST satellite missions will perform wide-area surveys characterizing millions of AGN (Sect. 3.5 and 4.6), while dedicated groundbased surveys (for example from the LSST, the Subaru Prime Focus Spectrograph 53 , and the Multi Object Optical and Nearinfrared Spectrograph for the VLT [MOONS] 54 ) will build  \non the legacy of ongoing surveys (for example DES and SDSS-IV). At longer wavelengths, the growing number of sensitive, wide-area radio telescopes (leading ultimately toward the SKA) will provide increasing numbers (in the tens of millions: Sect. 2.4) of radio-selected AGN across most of the sky. Together, these surveys will produce massive data sets with huge statistical samples of images, spectra, and time variability of AGN over a wide range in redshift and luminosity, and will enable statistical analyses of AGN with precision comparable to what is currently possible for 'normal' galaxies. Harnessing these large data sets represents a major challenge and opportunity for the future of AGN science.  \nHydrodynamic simulations.Major theoretical challenges in understanding the AGN arise from the complexity of the physical processes involved and the enormous dynamic range in the relevant physical scales. With continual advances in computing power and improvements in astrophysical codes, theorists will continue to approach the ultimate goal of resolving the physics of AGN on all the scales described in Sect. 8.1, the structure and kinematics of the torus and central engine (e.g. Chan & Krolik, 2016; Namekata & Umemura, 2016; Wada, Schartmann, & Meijerink, 2016), the physics of the inner accretion flow and the launching of winds and relativistic jets (e.g. Tchekhovskoy, 2015; Waters & Proga, 2016), and the impact of this feedback on host galaxies and  \nhalos (e.g. Dubois et al., 2016; McAlpine et al., 2017; Weinberger et al., 2017). Coupled with an improved understanding of the underlying physics, emission mechanisms, and prescriptions for radiative transfer (e.g. Jud et al., 2017; Hopkins et al., 2017), these simulations will be critical for interpreting the high-resolution, high-sensitivity observations described above.  \nForward modelling of selection e GLYPH<11> ects.As discussed in depth throughout this review, an important di GLYPH<14> culty in piecing together the AGN population is understanding the wide array of selection e GLYPH<11> ects due to physical variation among AGN, host galaxy contamination, and observational limitation. Many previous studies have attempted to invert these selection e GLYPH<11> ects to recover the intrinsic AGN population studied in a particular waveband. However, with a proliferation of multi-wavelength data on large samples of AGN, it is increasingly challenging to successfully account for selection e GLYPH<11> ects across multiple bands simultaneously. There is therefore great potential for progress from forward -modelling these e GLYPH<11> ects by producing a simulated population of AGN with various physical characteristics (e.g. luminosities, redshifts, L = L Edd, dust obscuration, and host galaxy properties) and then producing simulated SEDs and other observables for direct comparisons to data (for recent examples of this method see Jones et al. 2016).  \nThis approach is made particularly powerful in combination with large hydrodynamic or semi-analytic simulations of galaxy formation (for just a few examples, see Hirschmann et al., 2014; Schaye et al., 2015; Dubois et al., 2016; Di Matteo et al., 2017), which provide realistic populations of galaxies that enable a robust accounting for host contamination and connections between AGN and galaxy properties. This forward-modelling approach, informed by a better understanding of AGN physics and future high-resolution and high-sensitivity AGN observations, will move us closer to a complete 'unification' of AGN that can account for the properties of the large AGN populations to be discovered in the next generation of surveys.  \nThese exciting observational and theoretical resources in the coming decades will be critical in answering the many interesting open questions that remain about the AGN phenomenon. Following the structure of this review, we discuss some outstanding problems related to AGN observed using each technique, plus general questions regarding the full AGN population:  \n- -Radio: What is the physical driver of AGN outflows, and in particular relativistic jets? How does the nature of these outflows change as a function of BH mass and accretion rate, and what processes (for example spin) explain the existence of jetted AGN that otherwise look (almost) identical to non-jetted AGN?\n- -IR: What is the composition, geometry, and morphology of the AGN torus, and how is its structure related to the accretion flow and / or AGN feedback?\n- -Optical: What is the physics of AGN emission lines and how can they be used to probe the physics of outflows? What are the emission line characteristics of high-redshift obscured quasars, and why are these currently rare in optical surveys?\n- -X-rays: What is the origin, geometrical configuration, and energy source of the corona? How do the AGN detected in X-ray surveys (which are the most e GLYPH<14> cient method for uncovering AGN) trace the underlying full population of AGN?\n- -GLYPH<13> -rays: What is the connection between GLYPH<13> -ray emission from AGN and high-energy particles (neutrinos and CRs), and how can these observations constrain theoretical models for particle acceleration in AGN?\n- -Variability: What is the physical driver of AGN variability as observed in di GLYPH<11> erent wavebands? Can X-ray variability be used as an independent indicator of BH mass?\n- -General: What is the complete census of the AGN population as observed at all wavebands (and those still undetected)? How does the cosmic history of BH accretion, as traced by the complete AGN population, compare to the history of SF? What are the physical connections between the evolution of BHs and that of their host galaxies and halos, and are these driven by common sources of gas, feedback processes, or other e GLYPH<11> ects?  \nIn summary, the future of AGN studies is very bright and we will soon be flooded with exciting new data. We need to be ready to extract as much information as possible from these observations by asking the right questions and using the appropriate tools, so that we can most e GLYPH<11> ectively piece together the physical nature of AGN and uncover the full cosmic evolution of growing black holes.  \nAcknowledgements We thank the participants of the AGN Workshop 'Active Galactic Nuclei: what's in a name?' (see full list at www.eso. org/sci/meetings/2016/AGN2016/participants.html ) for their presentations, Lisa Kewley, John Silverman, and Sylvain Veilleux for their role in the SOC, Phil Hopkins for his summary talk, Chris Harrison for producing Fig. 1, and Sarah Gallagher, Darshan Kakkad, Andrea Merloni, Kevin Schawinski, and an anonymous referee for reading the paper and providing helpful comments. DMA thanks the Science and Technology Facilities Council (STFC) for support through grant ST / L00075X / 1, and James Aird and Bret Lehmer for useful critical feedback. RJA was supported by FONDECYT grant number 1151408. BDM thanks D. De Cicco for helpful discussions and acknowledges support from the European Union's Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement No. 665778 via the Polish National Science Center grant Polonez UMO-2016 / 21 / P / ST9 / 04025. 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