Context. Gaia Data Release 2 provides highprecision astrometry and threeband photometry for about 1.3 billion sources over the full sky. The precision accuracy and homogeneity of both astrometry and photometry are unprecedented. BR  Aims We highlight the power of the Gaia DR2 in studying many fine structures of the HertzsprungRussell diagram HRD. Gaia allows us to present many different HRDs depending in particular on stellar population selections. We do not aim here for completeness in terms of types of stars or stellar evolutionary aspects. Instead we have chosen several illustrative examples. BR  Methods We describe some of the selections that can be made in Gaia DR2 to highlight the main structures of the Gaia HRDs. We select both field and cluster open and globular stars compare the observations with previous classifications and with stellar evolutionary tracks and we present variations of the Gaia HRD with age metallicity and kinematics. Late stages of stellar evolution such as hot subdwarfs postAGB stars planetary nebulae and white dwarfs are also analysed as well as lowmass brown dwarf objects. BR  Results The Gaia HRDs are unprecedented in both precision and coverage of the various Milky Way stellar populations and stellar evolutionary phases. Many fine structures of the HRDs are presented. The clear split of the white dwarf sequence into hydrogen and helium white dwarfs is presented for the first time in an HRD. The relation between kinematics and the HRD is nicely illustrated. Two different populations in a classical kinematic selection of the halo are unambiguously identified in the HRD. Membership and mean parameters for a selected list of open clusters are provided. They allow drawing very detailed cluster sequences highlighting fine structures and providing extremely precise empirical isochrones that will lead to more insight in stellar physics. BR  Conclusions Gaia DR2 demonstrates the potential of combining precise astrometry and photometry for large samples for studies in stellar evolution and stellar population and opens an entire new area for HRDbased studies. P The full Table A.1 is only available at the CDS via anonymous ftp to A hrefhttpcdsarc.ustrasbg.frhttpcdsarc.ustrasbg.frA A hrefhttpcdsarc.ustrasbg.frhttp130.79.128.5A or via A hrefhttpcdsarc.ustrasbg.frvizbinqcatJAA616A10httpcdsarc.ustrasbg.frvizbinqcatJAA616A10A
['parallaxes', 'Hertzsprung-Russell and C-M diagrams', 'solar neighborhood', 'stars: evolution', 'Astrophysics - Solar and Stellar Astrophysics', 'Astrophysics - Astrophysics of Galaxies']
Gaia Data Release 2. Observational HertzsprungRussell diagrams
{'Gaia Data Release 2: Observational Hertzsprung-Russell diagrams ?': "Gaia Collaboration, C. Babusiaux 1 ; 2 , F. van Leeuwen 3 , M.A. Barstow 4 , C. Jordi 5 , A. Vallenari 6 , D. Bossini 6 , A. Bressan 7 , T. Cantat-Gaudin 6 ; 5 , M. van Leeuwen 3 , A.G.A. Brown 8 , T. Prusti 9 , J.H.J. de Bruijne 9 , C.A.L. Bailer-Jones 10 , M. Biermann 11 , D.W. Evans 3 , L. Eyer 12 , F. Jansen 13 , S.A. Klioner 14 , U. Lammers 15 , L. Lindegren 16 , X. Luri 5 , F. Mignard 17 , C. Panem 18 , D. Pourbaix 19 ; 20 , S. Randich 21 , P. Sartoretti 2 , H.I. Siddiqui 22 , C. Soubiran 23 , N.A. Walton 3 , F. Arenou 2 , U. Bastian 11 , M. Cropper 24 , R. Drimmel 25 , D. Katz 2 , M.G. Lattanzi 25 , J. Bakker 15 , C. Cacciari 26 , J. Castañeda 5 , L. Chaoul 18 , N. Cheek 27 , F. De Angeli 3 , C. Fabricius 5 , R. Guerra 15 , B. Holl 12 , E. Masana 5 , R. Messineo 28 , N. Mowlavi 12 , K. Nienartowicz 29 , P. Panuzzo 2 , J. Portell 5 , M. Riello 3 , G.M. Seabroke 24 , P. Tanga 17 , F. Thévenin 17 , G. Gracia-Abril 30 ; 11 , G. Comoretto 22 , M. Garcia-Reinaldos 15 , D. Teyssier 22 , M. Altmann 11 ; 31 , R. Andrae 10 , M. Audard 12 , I. Bellas-Velidis 32 , K. Benson 24 , J. Berthier 33 , R. Blomme 34 , P. Burgess 3 , G. Busso 3 , B. Carry 17 ; 33 , A. Cellino 25 , G. Clementini 26 , M. Clotet 5 , O. Creevey 17 , M. Davidson 35 , J. De Ridder 36 , L. Delchambre 37 , A. Dell'Oro 21 , C. Ducourant 23 , J. Fernández-Hernández 38 , M. Fouesneau 10 , Y. Frémat 34 , L. Galluccio 17 , M. García-Torres 39 , J. González-Núñez 27 ; 40 , J.J. González-Vidal 5 , E. Gosset 37 ; 20 , L.P. Guy 29 ; 41 , J.-L. Halbwachs 42 , N.C. Hambly 35 , D.L. Harrison 3 ; 43 , J. Hernández 15 , D. Hestro GLYPH<11> er 33 , S.T. Hodgkin 3 , A. Hutton 44 , G. Jasniewicz 45 , A. Jean-Antoine-Piccolo 18 , S. Jordan 11 , A.J. Korn 46 , A. Krone-Martins 47 , A.C. Lanzafame 48 ; 49 , T. Lebzelter 50 , W. Lö GLYPH<15> er 11 , M. Manteiga 51 ; 52 , P.M. Marrese 53 ; 54 , J.M. Martín-Fleitas 44 , A. Moitinho 47 , A. Mora 44 , K. Muinonen 55 ; 56 , J. Osinde 57 , E. Pancino 21 ; 54 , T. Pauwels 34 , J.-M. Petit 58 , A. Recio-Blanco 17 , P.J. Richards 59 , L. Rimoldini 29 , A.C. Robin 58 , L.M. Sarro 60 , C. Siopis 19 , M. Smith 24 , A. Sozzetti 25 , M. Süveges 10 , J. Torra 5 , W. van Reeven 44 , U. Abbas 25 , A. Abreu Aramburu 61 , S. Accart 62 , C. Aerts 36 ; 63 , G. Altavilla 53 ; 54 ; 26 , M.A. Álvarez 51 , R. Alvarez 15 , J. Alves 50 , R.I. Anderson 64 ; 12 , A.H. Andrei 65 ; 66 ; 31 , E. Anglada Varela 38 , E. Antiche 5 , T. Antoja 9 ; 5 , B. Arcay 51 , T.L. Astraatmadja 10 ; 67 , N. Bach 44 , S.G. Baker 24 , L. Balaguer-Núñez 5 , P. Balm 22 , C. Barache 31 , C. Barata 47 , D. Barbato 68 ; 25 , F. Barblan 12 , P.S. Barklem 46 , D. Barrado 69 , M. Barros 47 , S. Bartholomé Muñoz 5 , J.-L. Bassilana 62 , U. Becciani 49 , M. Bellazzini 26 , A. Berihuete 70 , S. Bertone 25 ; 31 ; 71 , L. Bianchi 72 , O. Bienaymé 42 , S. Blanco-Cuaresma 12 ; 23 ; 73 , T. Boch 42 , C. Boeche 6 , A. Bombrun 74 , R. Borrachero 5 , S. Bouquillon 31 , G. Bourda 23 , A. Bragaglia 26 , L. Bramante 28 , M.A. Breddels 75 , N. Brouillet 23 , T. Brüsemeister 11 , E. Brugaletta 49 , B. Bucciarelli 25 , A. Burlacu 18 , D. Busonero 25 , A.G. Butkevich 14 , R. Buzzi 25 , E. Ca GLYPH<11> au 2 , R. Cancelliere 76 , G. Cannizzaro 77 ; 63 , R. Carballo 78 , T. Carlucci 31 , J.M. Carrasco 5 , L. Casamiquela 5 , M. Castellani 53 , A. Castro-Ginard 5 , P. Charlot 23 , L. Chemin 79 , A. Chiavassa 17 , G. Cocozza 26 , G. Costigan 8 , S. Cowell 3 , F. Crifo 2 , M. Crosta 25 , C. Crowley 74 , J. Cuypers y 34 , C. Dafonte 51 , Y. Damerdji 37 ; 80 , A. Dapergolas 32 , P. David 33 , M. David 81 , P. de Laverny 17 , F. De Luise 82 , R. De March 28 , D. de Martino 83 , R. de Souza 84 , A. de Torres 74 , J. Debosscher 36 , E. del Pozo 44 , M. Delbo 17 , A. Delgado 3 , H.E. Delgado 60 , S. Diakite 58 , C. Diener 3 , E. Distefano 49 , C. Dolding 24 , P. Drazinos 85 , J. Durán 57 , B. Edvardsson 46 , H. Enke 86 , K. Eriksson 46 , P. Esquej 87 , G. Eynard Bontemps 18 , C. Fabre 88 , M. Fabrizio 53 ; 54 , S. Faigler 89 , A.J. Falcão 90 , M. Farràs Casas 5 , L. Federici 26 , G. Fedorets 55 , P. Fernique 42 , F. Figueras 5 , F. Filippi 28 , K. Findeisen 2 , A. Fonti 28 , E. Fraile 87 , M. Fraser 3 ; 91 , B. Frézouls 18 , M. Gai 25 , S. Galleti 26 , D. Garabato 51 , F. García-Sedano 60 , A. Garofalo 92 ; 26 , N. Garralda 5 , A. Gavel 46 , P. Gavras 2 ; 32 ; 85 , J. Gerssen 86 , R. Geyer 14 , P. Giacobbe 25 , G. Gilmore 3 , S. Girona 93 , G. Giu GLYPH<11> rida 54 ; 53 , F. Glass 12 , M. Gomes 47 , M. Granvik 55 ; 94 , A. Gueguen 2 ; 95 , A. Guerrier 62 , J. Guiraud 18 , R. Gutiérrez-Sánchez 22 , R. Haigron 2 , D. Hatzidimitriou 85 ; 32 , M. Hauser 11 ; 10 , M. Haywood 2 , U. Heiter 46 , A. Helmi 75 , J. Heu 2 , T. Hilger 14 , D. Hobbs 16 , W. Hofmann 11 , G. Holland 3 , H.E. Huckle 24 , A. Hypki 8 ; 96 , V. Icardi 28 , K. Janßen 86 , G. Jevardat de Fombelle 29 , P.G. Jonker 77 ; 63 , Á.L. Juhász 97 ; 98 , F. Julbe 5 , A. Karampelas 85 ; 99 , A. Kewley 3 , J. Klar 86 , A. Kochoska 100 ; 101 , R. Kohley 15 , K. Kolenberg 102 ; 36 ; 73 , M. Kontizas 85 , E. Kontizas 32 , S.E. Koposov 3 ; 103 , G. Kordopatis 17 , Z. Kostrzewa-Rutkowska 77 ; 63 , P. Koubsky 104 , S. Lambert 31 , A.F. Lanza 49 , Y. Lasne 62 , J.-B. Lavigne 62 , Y. Le Fustec 105 , C. Le Poncin-Lafitte 31 , Y. Lebreton 2 ; 106 , S. Leccia 83 , N. Leclerc 2 , I. Lecoeur-Taibi 29 , H. Lenhardt 11 , F. Leroux 62 , S. Liao 25 ; 107 ; 108 , E. Licata 72 , H.E.P. Lindstrøm 109 ; 110 , T.A. Lister 111 , E. Livanou 85 , A. Lobel 34 , M. López 69 , S. Managau 62 , R.G. Mann 35 , G. Mantelet 11 , O. Marchal 2 , J.M. Marchant 112 , M. Marconi 83 , S. Marinoni 53 ; 54 , G. Marschalkó 97 ; 113 , D.J. Marshall 114 , M. Martino 28 , G. Marton 97 , N. Mary 62 , D. Massari 75 , G. Matijeviˇc 86 , T. Mazeh 89 , P.J. McMillan 16 , S. Messina 49 , D. Michalik 16 , N.R. Millar 3 , D. Molina 5 , R. Molinaro 83 ,  \nL. Molnár 97 , P. Montegri GLYPH<11> o 26 , R. Mor 5 , R. Morbidelli 25 , T. Morel 37 , D. Morris 35 , A.F. Mulone 28 , T. Muraveva 26 , I. Musella 83 , G. Nelemans 63 ; 36 , L. Nicastro 26 , L. Noval 62 , W. O'Mullane 15 ; 41 , C. Ordénovic 17 , D. Ordóñez-Blanco 29 , P. Osborne 3 , C. Pagani 4 , I. Pagano 49 , F. Pailler 18 , H. Palacin 62 , L. Palaversa 3 ; 12 , A. Panahi 89 , M. Pawlak 115 ; 116 , A.M. Piersimoni 82 , F.-X. Pineau 42 , E. Plachy 97 , G. Plum 2 , E. Poggio 68 ; 25 , E. Poujoulet 117 , A. Prša 101 , L. Pulone 53 , E. Racero 27 , S. Ragaini 26 , N. Rambaux 33 , M. Ramos-Lerate 118 , S. Regibo 36 , C. Reylé 58 , F. Riclet 18 , V. Ripepi 83 , A. Riva 25 , A. Rivard 62 , G. Rixon 3 , T. Roegiers 119 , M. Roelens 12 , M. Romero-Gómez 5 , N. Rowell 35 , F. Royer 2 , L. Ruiz-Dern 2 , G. Sadowski 19 , T. Sagristà Sellés 11 , J. Sahlmann 15 ; 120 , J. Salgado 121 , E. Salguero 38 , N. Sanna 21 , T. Santana-Ros 96 , M. Sarasso 25 , H. Savietto 122 , M. Schultheis 17 , E. Sciacca 49 , M. Segol 123 , J.C. Segovia 27 , D. Ségransan 12 , I-C. Shih 2 , L. Siltala 55 ; 124 , A.F. Silva 47 , R.L. Smart 25 , K.W. Smith 10 , E. Solano 69 ; 125 , F. Solitro 28 , R. Sordo 6 , S. Soria Nieto 5 , J. Souchay 31 , A. Spagna 25 , F. Spoto 17 ; 33 , U. Stampa 11 , I.A. Steele 112 , H. Steidelmüller 14 , C.A. Stephenson 22 , H. Stoev 126 , F.F. Suess 3 , J. Surdej 37 , L. Szabados 97 , E. Szegedi-Elek 97 , D. Tapiador 127 ; 128 , F. Taris 31 , G. Tauran 62 , M.B. Taylor 129 , R. Teixeira 84 , D. Terrett 59 , P. Teyssandier 31 , W. Thuillot 33 , A. Titarenko 17 , F. Torra Clotet 130 , C. Turon 2 , A. Ulla 131 , E. Utrilla 44 , S. Uzzi 28 , M. Vaillant 62 , G. Valentini 82 , V. Valette 18 , A. van Elteren 8 , E. Van Hemelryck 34 , M. Vaschetto 28 , A. Vecchiato 25 , J. Veljanoski 75 , Y. Viala 2 , D. Vicente 93 , S. Vogt 119 , C. von Essen 132 , H. Voss 5 , V. Votruba 104 , S. Voutsinas 35 , G. Walmsley 18 , M. Weiler 5 , O. Wertz 133 , T. Wevers 3 ; 63 , Ł. Wyrzykowski 3 ; 115 , A. Yoldas 3 , M. Žerjal 100 ; 134 , H. Ziaeepour 58 , J. Zorec 135 , S. Zschocke 14 , S. Zucker 136 , C. Zurbach 45 , and T. Zwitter 100  \n(A GLYPH<14> liations can be found after the references)  \nReceived ; accepted", 'ABSTRACT': 'Context. Gaia Data Release 2 provides high-precision astrometry and three-band photometry for about 1.3 billion sources over the full sky. The precision, accuracy, and homogeneity of both astrometry and photometry are unprecedented.  \nAims. We highlight the power of the Gaia DR2 in studying many fine structures of the Hertzsprung-Russell diagram (HRD). Gaia allows us to present many di GLYPH<11> erent HRDs, depending in particular on stellar population selections. We do not aim here for completeness in terms of types of stars or stellar evolutionary aspects. Instead, we have chosen several illustrative examples.  \nMethods. We describe some of the selections that can be made in Gaia DR2 to highlight the main structures of the Gaia HRDs. We select both field and cluster (open and globular) stars, compare the observations with previous classifications and with stellar evolutionary tracks, and we present variations of the Gaia HRD with age, metallicity, and kinematics. Late stages of stellar evolution such as hot subdwarfs, post-AGB stars, planetary nebulae, and white dwarfs are also analysed, as well as low-mass brown dwarf objects.  \nResults. The Gaia HRDs are unprecedented in both precision and coverage of the various Milky Way stellar populations and stellar evolutionary phases. Many fine structures of the HRDs are presented. The clear split of the white dwarf sequence into hydrogen and helium white dwarfs is presented for the first time in an HRD. The relation between kinematics and the HRD is nicely illustrated. Two di GLYPH<11> erent populations in a classical kinematic selection of the halo are unambiguously identified in the HRD. Membership and mean parameters for a selected list of open clusters are provided. They allow drawing very detailed cluster sequences, highlighting fine structures, and providing extremely precise empirical isochrones that will lead to more insight in stellar physics.  \nConclusions. Gaia DR2 demonstrates the potential of combining precise astrometry and photometry for large samples for studies in stellar evolution and stellar population and opens an entire new area for HRD-based studies.  \nKey words. parallaxes - Hertzsprung-Russell and C-M diagrams - solar neighbourhood - Stars: evolution', '1. Introduction': 'The Hertzsprung-Russell diagram (HRD) is one of the most important tools in stellar studies. It illustrates empirically the relationship between stellar spectral type (or temperature or colour index) and luminosity (or absolute magnitude). The position of a star in the HRD is mainly given by its initial mass, chemical composition, and age, but e GLYPH<11> ects such as rotation, stellar wind, magnetic field, detailed chemical abundance, over-shooting, and non-local thermal equilibrium also play a role. Therefore, the detailed HRD features are important to constrain stellar structure and evolutionary studies as well as stellar atmosphere modelling. Up to now, a proper understanding of the physical process in the stellar interior and the exact contribution of each of the e GLYPH<11> ects mentioned are missing because we lack large precise and homo-  \ngeneous samples that cover the full HRD. Moreover, a precise HRD provides a great framework for exploring stellar populations and stellar systems.  \nUp to now, the most complete solar neighbourhood empirical HRD could be obtained by combining the Hipparcos data (Perryman et al. 1995) with nearby stellar catalogues to provide the faint end (e.g. Gliese & Jahreiß 1991; Henry & Jao 2015). Clusters provide empirical HRDs for a range of ages and metal contents and are therefore widely used in stellar evolution studies. To be conclusive, they need homogeneous photometry for inter-comparisons and astrometry for good memberships.  \nWith its global census of the whole sky, homogeneous astrometry, and photometry of unprecedented accuracy, Gaia DR2 is setting a new major step in stellar, galactic, and extragalactic studies. It provides position, trigonometric parallax, and proper motion as well as three broad-band magnitudes ( G , G BP, and G RP) for more than a billion objects brighter than G GLYPH<24> 20, plus radial velocity for sources brighter than G RVS GLYPH<24> 12 mag and pho-  \ntometry for variable stars (Gaia Collaboration et al. 2018a). The amount, exquisite quality, and homogeneity of the data allows reaching a level of detail in the HRDs that has never been reached before. The number of open clusters with accurate parallax information is unprecedented, and new open clusters or associations will be discovered. Gaia DR2 provides absolute parallax for faint red dwarfs and the faintest white dwarfs for the first time.  \nThis paper is one of the papers accompanying the Gaia DR2 release. The following papers describe the data used here: Gaia Collaboration et al. (2018a) for an overview, Lindegren et al. (2018) for the astrometry, Evans et al. (2018) for the photometry, and Arenou et al. (2018) for the global validation. Someone interested in this HRD paper may also be interested in the variability in the HRD described in Gaia Collaboration et al. (2018b), in the first attempt to derive an HRD using temperatures and luminosities from the Gaia DR2 data of Andrae et al. (2018), in the kinematics of the globular clusters discussed in Gaia Collaboration et al. (2018c), and in the field kinematics presented in Gaia Collaboration et al. (2018d).  \nIn this paper, Sect. 2 presents a global description of how we built the Gaia HRDs of both field and cluster stars, the filters that we applied, and the handling of the extinction. In Sect. 3 we present our selection of cluster data; the handling of the globular clusters is detailed in Gaia Collaboration et al. (2018c) and the handling of the open clusters is detailed in Appendix A. Section 4 discusses the main structures of the Gaia DR2 HRD. The level of the details of the white dwarf sequence is so new that it leads to a more intense discussion, which we present in a separate Sect. 5. In Sect. 6 we compare clusters with a set of isochrones. In Sect. 7 we study the variation of the Gaia HRDs with kinematics. We finally conclude in Sect. 8.', '2. Building the Gaia HRDs': 'This paper presents the power of the Gaia DR2 astrometry and photometry in studying fine structures of the HRD. For this, we selected the most precise data, without trying to reach completeness. In practice, this means selecting the most precise parallax and photometry, but also handling the extinction rigorously. This can no longer be neglected with the depth of the Gaia precise data in this release.', '2.1. Data filtering': 'The Gaia DR2is unprecedented in both the quality and the quantity of its astrometric and photometric data. Still, this is an intermediate data release without a full implementation of the complexity of the processing for an optimal usage of the data. A detailed description of the astrometric and photometric features is given in Lindegren et al. (2018) and Evans et al. (2018), respectively, and Arenou et al. (2018) provides a global validation of them. Here we highlight the features that are important to be taken into account in building Gaia DR2 HRDs and present the filters we applied in this paper.  \nConcerning the astrometric content (Lindegren et al. 2018), the median uncertainty for the bright source ( G < 14 mag) parallax is 0.03 mas. The systematics are lower than 0.1 mas, and the parallax zeropoint error is about 0.03 mas. Significant correlations at small spatial scale between the astrometric parameters are also observed. Concerning the photometric content (Evans et al. 2018), the precision at G = 12 is around 1 mmag in the three passbands, with systematics at the level of 10 mmag.  \nLindegren et al. (2018) described that a five-parameter solution is accepted only if at least six visibility periods are used (e.g. the number of groups of observations separated from other groups by a gap of at least four days, the parameter is named visibility\\_periods\\_used in the Gaia archive). The observations need to be well spread out in time to provide reliable fiveparameter solutions. Here we applied a stronger filter on this parameter: visibility\\_periods\\_used > 8 . This removes strong outliers, in particular at the faint end of the local HRD (Arenou et al. 2018). It also leads to more incompleteness, but this is not an issue for this paper.  \nThe astrometric excess noise is the extra noise that must be postulated to explain the scatter of residuals in the astrometric solution. When it is high, it either means that the astrometric solution has failed and / or that the studied object is in a multiple system for which the single-star solution is not reliable. Without filtering on the astrometric excess noise, artefacts are present in particular between the white dwarf and the main sequence in the Gaia HRDs. Some of those stars are genuine binaries, but the majority are artefacts (Arenou et al. 2018). To still see the imprint of genuine binaries on the HRD while removing most of the artefacts, we adopted the filter proposed in Appendix C of Lindegren et al. (2018): p GLYPH<31> 2 = ( GLYPH<23> 0 GLYPH<0> 5) < 1 : 2 max(1 ; exp( GLYPH<0> 0 : 2( G GLYPH<0> 19 : 5)) with GLYPH<31> 2 and GLYPH<23> 0 given as astrometric\\_chi2\\_al and astrometric\\_n\\_good\\_obs\\_al, respectively, in the Gaia archive. A similar clean-up of the HRD is obtained by the astrometric\\_excess\\_noise < 1 criterion, but this is less optimised for the bright stars because of the degrees of freedom (DOF) issue (Lindegren et al. 2018, Appendix A).  \nWe built the Gaia HRDs by simply estimating the absolute Gaia magnitude in the G band for individual stars using MG = G + 5 + 5 log 10 ( $= 1000 : ), with $ the parallax in milliarcseconds (plus the extinction, see next section). This is valid only when the relative precision on the parallax is lower than about 20% (Luri et al. 2018). We aim here to examine the fine structures in the HRD revealed by Gaia and therefore adopt a 10% relative precision criterion, which corresponds to an uncertainty on MG smaller than 0.22 mag: parallax\\_over\\_error > 10 .  \nSimilarly, we apply filters on the relative flux error on the G , G BP, and G RP photometry: phot\\_g\\_mean\\_flux\\_over\\_error > 50 ( GLYPH<27> G < 0 : 022 mag), phot\\_rp\\_mean\\_flux\\_over\\_error > 20, and phot\\_bp\\_mean\\_flux\\_over\\_error > 20 ( GLYPH<27> GXP < 0 : 054 mag). These criteria may remove variable stars, which are specifically studied in Gaia Collaboration et al. (2018b).  \nThe processing of the photometric data in DR2 has not treated blends in the windows of the blue and red photometers (BP and RP). As a consequence, the measured BP and RP fluxes may include the contribution of flux from nearby sources, the highest impact being in sky areas of high stellar density, such as the inner regions of globular clusters, the Magellanic Clouds, or the Galactic Bulge. During the validation process, misdeterminations of the local background have also been identified. In some cases, this background is due to nearby bright sources with long wings of the point spread function that have not been properly subtracted. In other cases, the background has a solar type spectrum, which indicates that the modelling of the background flux is not good enough. The faint sources are most strongly a GLYPH<11> ected. For details, see Evans et al. (2018) and Arenou et al. (2018). Here, we have limited our analysis to the sources within the empirically defined locus of the ( IBP + IRP ) = IG fluxes ratio as a function of G BP GLYPH<0> G RP colour: phot\\_bp\\_rp\\_excess\\_factor > 1 : 0 + 0 : 015 ( G BP GLYPH<0> G RP) 2 and phot\\_bp\\_rp\\_excess\\_factor < 1 : 3 + 0 : 06 ( G BP GLYPH<0> G RP) 2 . The Gaia  \nFig. 1. Full Gaia colour-magnitude diagram of sources with the filters described in Sect. 2.1 applied (65,921,112 stars). The colour scale represents the square root of the relative density of stars.  \n<!-- image -->  \narchive query combining all the filters presented here is provided in Appendix B.', '2.2. Extinction': 'The dust that is present along the line of sight towards the stars leads to a dimming and reddening of their observed light. In the full colour - absolute magnitude diagram presented in Fig. 1, the e GLYPH<11> ect of the extinction is particularly striking for the red clump. The de-reddened HRD using the extinction provided together with DR2 is presented in Andrae et al. (2018). To study the fine structures of the Gaia HRD for field stars, we selected here only low-extinction stars. High galactic latitude and close-by stars located within the local bubble (the reddening is almost negligible within GLYPH<24> 60 pc of the Sun (Lallement et al. 2003)) are a GLYPH<11> ected less from the extinction, and we did not apply further selection for them. To select low-extinction stars away from these simple cases, we followed Ruiz-Dern et al. (2018) and used the 3D extinction map of Capitanio et al. (2017) 1 , which is particularly well adapted to finding holes in the interstellar medium and to select field stars with E ( B GLYPH<0> V ) < 0 : 015.  \nFor globular clusters we used literature extinction values (Sect. 3.3), while for open clusters, they are derived together with the ages (Sect. 3.2). Detailed comparisons of these global cluster extinctions with those that can be derived from the extinctions provided by Gaia DR2 can be found in Arenou et al. (2018). To transform the global cluster extinction easily into the Gaia passbands while taking into account the extinction coe GLYPH<14> -cients dependency on colour and extinction itself in these large passbands (e.g. Jordi et al. 2010), we used the same formulae as Danielski et al. (2018) to compute the extinction coe GLYPH<14> cients  \nkX = AX = A 0: kX = c 1 + c 2( GBP GLYPH<0> GRP )0 + c 3( GBP GLYPH<0> GRP ) 2 0 + c 4( GBP GLYPH<0> GRP ) 3 0 + c 5 A 0 + c 6 A 2 0 + c 7( GBP GLYPH<0> GRP )0 A 0 :  \n(1)  \nAs in Danielski et al. (2018), this formula was fitted on a grid of extinctions convolving the latest Gaia passbands presented in Evans et al. (2018) with Kurucz spectra (Castelli & Kurucz 2003) and the Fitzpatrick & Massa (2007) extinction law for 3500 K < T e GLYPH<11> < 10000 K by steps of 250 K, 0.01 < A 0 < 5 mag by steps of 0.01 mag and two surfaces gravities: log g = 2 : 5 and 4. The resulting coe GLYPH<14> cients are provided in Table 1. We assume in the following A 0 = 3 : 1 E ( B GLYPH<0> V ).  \nSome clusters show high di GLYPH<11> erential extinction across their field, which broadens their colour-magnitude diagrams. These clusters have been discarded from this analysis.', '3. Cluster data': 'Star clusters can provide observational isochrones for a range of ages and chemical compositions. Most suitable are clusters with low and uniform reddening values and whose magnitude range is wide, which would limit our sample to the nearest clusters. Such a sample would, however, present a rather limited range in age and chemical composition.', '3.1. Membership and astrometric solutions': "Two types of astrometric solutions were applied. The first type is applicable to nearby clusters. For the second Gaia data release, the nearby 'limit' was set at 250 pc. Within this limit, the parallax and proper motion data for the individual cluster members are su GLYPH<14> ciently accurate to reflect the e GLYPH<11> ects of projection along the line of sight, thus enabling the 3D reconstruction of the cluster. This is further described in Appendix A.1.  \nFor these nearby clusters, the size of the cluster relative to its distance will contribute a significant level of scatter to the HRD if parallaxes for individual cluster members are not taken into account. With a relative accuracy of about 1% in the parallax measurement, an error contribution of around 0.02 in the absolute magnitude is possible. For a large portion of the Gaia photometry, the uncertainties are about 5 to 10 times lower, making the parallax measurement still the main contributor to the uncertainty in the absolute magnitude. The range of di GLYPH<11> erences in parallax between the cluster centre and an individual cluster member depends on the ratio of the cluster radius over the cluster distance. At a radius of 15 pc, the 1% level is found for a cluster at 1.5 kpc, or a parallax of 0.67 mas. In Gaia DR2, formal uncertainties on the parallaxes may reach levels of just lower than 10 GLYPH<22> as, but the overall uncertainty from localised systematics is about 0.025 mas. If this value is considered the 1% uncertainty level, then a resolution of a cluster along the line of sight, using Gaia DR2, becomes possible for clusters within 400 pc, and realistic for clusters within about 250 pc.  \nFor clusters at larger distances, the mean cluster proper motion and parallax are derived directly from the observed astrometric parameters for the individual cluster members. The details of this procedure are presented in Appendix A.2.", '3.2. Selection of open clusters': "Our sample of open clusters consists of the mostly well-defined and fairly rich clusters within 250 pc, and a selection of mainly  \nFig. 2. Composite HRD for 32 open clusters, coloured according to log(age), using the extinction and distance moduli as determined from the Gaia data (Table 2).  \n<!-- image -->  \nFig. 3. Composite HRD for 14 globular clusters, coloured according to metallicity (Table 3).  \n<!-- image -->  \nTable 1. Parameters used to derive the Gaia extinction coe GLYPH<14> cients as a function of colour and extinction (Eq. 1).  \nrich clusters at larger distances, covering a wider range of ages, mostly up to 1.5 kpc, with a few additional clusters at larger distances where these might supply additional information at more extreme ages. For very young clusters, the definition of the cluster is not always clear, as the youngest systems are mostly found embedded in OB associations, producing large samples of similar proper motions and parallaxes. Very few clusters appear to survive to an 'old age', but those that do are generally rich, allowing good membership determination. The final selection consists of 9 clusters within 250 pc, and 37 clusters up to 5.3 kpc. Of the latter group, only 23 were finally used for construction of the colour-magnitude diagram; these clusters are listed together with the 9 nearby clusters in Table 2. For the remaining 14 clusters, the colour-magnitude diagrams appeared to be too much a GLYPH<11> ected by interstellar reddening variations. More details on the astrometric solutions are provided in Appendix A; the solutions are presented for the nearby clusters in Table A.3 and for the more distant clusters in Table A.4. Figure 2 shows the combined HRD of these clusters, coloured according to their ages as provided in Table 2. The main-sequence turn-o GLYPH<11> and red clump evolution with age is clearly visible. The age di GLYPH<11> erence is also shown for lower mass stars, the youngest stars lie slightly above the main sequence of the others. The white dwarf sequence is also visible.", '3.3. Selection of globular clusters': 'The details of selecting globular clusters are presented in Gaia Collaboration et al. (2018c). A major issue for the globular cluster data is the uncertainties on the parallaxes that result from the systematics, which is in most cases about one order of magnitude larger than the standard uncertainties on the mean parallax determinations for the globular clusters. The implication of this is that the parallaxes as determined with the Gaia data cannot be used to derive the distance moduli needed to prepare the composite HRD for the globular clusters. Instead, we had to rely on distances as quoted in the literature, for which we used the tables (2010 edition) provided online by Harris (1996). The inevitable drawback is that these distances and reddening values have been obtained through isochrone fitting, and the application of these values to the Gaia data will provide only limited new information. The main advantage is the possibility of comparing the HRDs of all globular clusters within a single, accurate photometric system. The combined HRD for 14 globular clusters is shown in Fig. 3, the summary data for these clusters is presented in Table 3. The photometric data originate predominantly from the outskirts of the clusters, as in the cluster centres the crowding often a GLYPH<11> ects the colour index determination. Figure 3 shows the blue horizontal branch populated with the metal-poor clusters and the move of the giant branch towards the blue with decreasing metallicity.  \nAn interesting comparison can be made between the most metal-rich well-populated globular cluster of our sample, 47 Tuc (NGC 104), and one of the oldest open clusters, M67 (NGC 2682) (Fig. 4). This provides the closest comparison between the HRDs of an open and a globular cluster. Most open  \nTable 2. Overview of reference values used in constructing the composite HRD for open clusters (Figure 2).  \nNotes. Distance moduli (DM) as derived from the Gaia astrometry; ages and reddening values as derived from Gaia photometry (see Sect. 6), with distances fixed on astrometric determinations; metallicities from Netopil et al. (2016); Memb: the number of members with Gaia photometric data after application of the photometric filters.  \nclusters are much younger, while most globular clusters are much less metal rich.', '4. Details of the Gaia HRDs': 'In the following, several field star HRDs are presented. Unless otherwise stated, the filters presented in Sect. 2.1, including the E ( B GLYPH<0> V ) < 0 : 015 mag criteria, were applied. The HRDs use a red colour scale that represents the square root of the density of stars. The Gaia DR2 HRD of the low-extinction stars is represented in Fig. 5. The approximate equivalent temperature and luminosity to the G BP GLYPH<0> G RP colour and the absolute Gaia MG magni-  \nTable 3. Reference data for 14 globular clusters used in the construction of the combined HRD (Figure 3).  \nNotes. Data on distance moduli (DM), [Fe / H] and E(B GLYPH<0> V) from Harris (1996), 2010 edition, (1): Dotter et al. (2010), (2) Denissenkov et al. (2017), (3) Powalka et al. (2017) for age estimates. Memb: cluster members with photometry after application of photometric filters.  \nFig. 4. Comparison between the HRDs of 47 Tuc (NGC 104, Age = 12.75 Gyr, [Fe / H] = -0.72), one of the most metal-rich globular clusters (magenta dots), and M 67 (NGC 2682, Age = 3.47 Gyr, [Fe / H] = 0.03), one of the oldest open clusters (blue dots).  \n<!-- image -->  \ntude provided in the figure were determined using the PARSEC isochrones (Marigo et al. 2017) for main-sequence stars.  \nFigure 6 shows the local Gaia HRDs using several cuts in parallax, still with the filters of Sect. 2.1, but without the need to apply the E ( B GLYPH<0> V ) < 0 : 015 mag extinction criteria, as these sources mostly lie within the local bubble.', '4.1. Main sequence': 'The main sequence is very thin, both in fields and in clusters. This is very clearly visible in Fig. 7, which shows the HRDs of the Hyades and Praesepe clusters (ages GLYPH<24> 700 Myr), which accurately overlap, as has previously been noticed in van Leeuwen (2009) and confirmed in Gaia Collaboration et al. (2017). This figure shows the very narrow sequence described by the stars in both clusters, as well as the scattering of double stars up to 0.75 magnitudes above the main sequence. The remaining width of the main sequence is still largely explained as due to the uncer-  \nFig. 5. Gaia HRD of sources with low extinction ( E ( B GLYPH<0> V ) < 0 : 015 mag) satisfying the filters described in Sect. 2.1 (4,276,690 stars). The colour scale represents the square root of the density of stars. Approximate temperature and luminosity equivalents for main-sequence stars are provided at the top and right axis, respectively, to guide the eye.  \n<!-- image -->  \ntainties in the parallax of the individual stars, and the underlying main sequence is likely to be even narrower.  \nThe binary sequence spread is visible throughout the main sequence (Figs. 5 and 6), and most clearly in open clusters (Fig. 7, see also Sect. 6). It is most preeminent for field stars below MG = 13. Figure 8 shows the main-sequence fiducial of the local HRD shifted by 0.753 mag, which corresponds to two identical stars in an unresolved binary system observed with the same colour but twice the luminosity of the equivalent single star. See Hurley & Tout (1998), for instance, for a discussion of this strong sequence. Binaries with a main-sequence primary and a giant companion would lie much higher in the diagram, while binaries with a late-type main-sequence primary and a white dwarf companion lie between the white dwarf and the main sequence, as is shown in Fig. 5, for example.  \nThe main sequence is thicker between 10 < MG < 13 (Figs. 2, 5, 6). The youngest main-sequence stars lie on the upper part of the main sequence (in blue in Fig. 2). The subdwarfs, which are metal-poor stars associated with the halo, are visible in the lower part of the local HRD (in red in Fig. 2, see also Sect. 7).  \nThe main-sequence turn-o GLYPH<11> variation with age is clearly illustrated in Fig. 2, and the variation with metallicity is shown in Fig. 3. Blue stragglers are also visible over the main-sequence turn-o GLYPH<11> (Figs. 4).  \nBetween the main sequence and the subgiants lies a tail of stars around MG = 4 and G BP GLYPH<0> G RP = 1.5. These stars shows  \n<!-- image -->  \n<!-- image -->  \nFig. 6. Solar neighbourhood Gaia HRDs for a) $ > 40 mas (25 pc, 3,724 stars), b) $ > 20 mas (50 pc, 29,683 stars), and c) $ > 10 mas (100 pc, 212,728 stars).  \n<!-- image -->  \nFig. 7. Extract of the HRD for the Hyades and Praesepe clusters, showing the detailed agreement between the main sequences of the two clusters, the narrowness of the combined main sequence, and a scattering of double stars up to 0.75 mag above the main sequence.  \n<!-- image -->  \nvariability and may be associated with RS Canum Venaticorum variables, which are close binary stars (Gaia Collaboration et al. 2018b).', '4.2. Brown dwarfs': 'To study the location of the low-mass objects in the Gaia HRD, we used the Gaia ultracool dwarf sample (GUCDS) compiled by Smart et al. (2017). It includes 1886 brown dwarfs (BD) of L, T, and Y types, although a substantial fraction of them are too faint for Gaia . We note that the authors found 328 BDs in common with the Gaia DR1 catalogue (Gaia Collaboration et al. 2016).  \nThe crossmatch between the 2MASS catalogue (Skrutskie et al. 2006) and Gaia DR2 provided within the Gaia archive (Marrese et al. 2018) has been used to identify GUCDS entries. The resulting sample includes 601 BDs. Of these, 527 have fiveparameter solutions (coordinates, proper motions, and parallax) and full photometry ( G , GBP , and GRP ). Most of these BDs have parallaxes higher than 4 mas (equivalent to 250 pc in distance)  \nFig. 8. Same as Fig. 6c, overlaid in blue with the median fiducial and in green with the same fiducial shifted by -0.753 mag, corresponding to an unresolved binary system of two identical stars.  \n<!-- image -->  \nand relative parallax errors smaller than 25%. They also have astrometric excess noise larger than 1 mas and a high ( IBP + IRP ) = IG flux ratio. They are faint red objects with very low flux in the BP wavelength range of their spectrum. Any background underestimation causes the measured BP flux to increase to more than it should be, yielding high flux ratios, the highest ratios are derived for the faintest BDs. The filters presented in Sect. 2.1 therefore did not allow us to retain them.  \nFig. 9. a): Gaia HRD of the stars with $ > 10 mas with adapted photometric filters (see text, 240,703 stars) overlaid with all cross-matched GUCDS (Smart et al. 2017) stars with GLYPH<27>$ =$ < 10% in blue (M type), green (L type), and red (T type). Pink squares are added around stars with tangential velocity V T > 200 km s GLYPH<0> 1 . b) BT-Settl tracks (Bara GLYPH<11> e et al. 2015) of solar metallicity for masses from 0.01 M GLYPH<12> to 0.08 M GLYPH<12> in steps of 0.01 (the upper tracks correspond to lower masses) plus in pink the same tracks for [M / H] = -1.0. Panels c) and d): Same diagrams using the 2MASS colours.  \n<!-- image -->  \nWe accordingly adapted our filters for the background stars of Fig. 9. We plot the HRD using the G GLYPH<0> G RP colour instead of G BP GLYPH<0> G RP because of the poor quality of G BP for these faint red sources. We applied the same astrometric filters as for Fig. 6c, but we did not filter the fluxes ratio or the G BP photometric uncertainties. More dispersion is present in this diagram than in Fig. 6c because of this missing filter, but the faint red sources we study here are represented better.  \nThe 470 BDs for which DR2 provides parallaxes better than 10%, and the G and G RP magnitudes are overlaid in Fig. 9 without any filtering. The sequence of BDs follows the sequence of low-mass stars. The absolute magnitudes of four stars are too bright, most probably because of a cross-match issue. In Fig. 9a the M-, L- and T-type BDs are sorted according to the classification in GUCDS. There are 21, 443, and 7 of each type, respectively. We also present in Fig. 9c the corresponding HRD using 2MASS colours with the 2MASS photometric quality flag AAA (applied to background and GUCDS stars). Figures 9b,d includes BT-Settl tracks 2 (Bara GLYPH<11> e et al. 2015) for  \nmasses < 0 : 08 M GLYPH<12> that were computed using the nominal Gaia passbands. With the Gaia G GLYPH<0> G RP colour, the sequence of M, L, T types is continuous and relatively thin. Conversely, the spread in the near-infrared is larger and the L / T transition feature is strongly seen with a shift of J GLYPH<0> Ks to the blue, which is due to a drastic change in the brown dwarf cloud properties (e.g. Saumon & Marley 2008). Some GUCDS L-type stars with very blue 2MASS colours seem at first sight intriguing, but their location might be consistent with metal-poor tracks (Fig. 9d). Following Faherty et al. (2009), we studied their kinematics, which are indeed consistent with the halo kinematic cut of the tangential velocity V T > 200 km s GLYPH<0> 1 (see Sect. 7). A kinematic selection of the global HRD as done in Sect. 7 but using the 2MASS colours confirms the blue tail of the bottom of the main sequence in the near-infrared for the halo kinematic selection.', '4.3. Giant branch': 'The clusters clearly illustrate the change in global shape of the giant branch with age and metallicity (Figs. 2 and 3). For field stars, there are fewer giants than dwarfs in the first 100 pc. To  \nFig. 10. Gaia HRD of low-extinction nearby giants: $ > 2 mas (500 pc), E ( B GLYPH<0> V ) < 0 : 015 and MG < 2 : 5 (29288 stars), with labels to the features discussed in the text.  \n<!-- image -->  \nobserve the field giant branch in more detail, we therefore extended our selection to 500 pc with the low-extinction selection ( E ( B GLYPH<0> V ) < 0 : 015, see Sect. 2.2) for Fig. 10.  \nThe most prominent feature of the giant branch is the Red Clump (RC in Fig. 10, around G BP GLYPH<0> G RP = 1 : 2, MG = 0 : 5 mag). It corresponds to low-mass stars that burn helium in their core (e.g. Girardi 2016). The colour of core-helium burning stars is strongly dependent on metallicity and age. The more metal-rich, the redder, which leads to this red clump feature in the local HRD. For more metal-poor populations, these stars are bluer and lead to the horizontal-branch (HB) feature that is clearly visible in globular clusters (Fig. 11).  \nThe secondary red clump (SRC in Fig. 10, around G BP GLYPH<0> G RP = 1 : 1, MG = 0 : 6) is more extended in its bluest part to fainter magnitudes than the red clump. It corresponds to younger more massive red clump stars (Girardi 1999) and is therefore mostly visible in the local HRD (Fig. 6c). Core-helium burning stars that are even more massive are more luminous than the red clump and lie still on the blue part of it, leading to a vertical structure that is sometimes called the Vertical Red Clump (VRC in Fig. 10).  \nOnthe red side and fainter than the clump lies the RGB bump (RGBB in Fig. 10). This bump is caused by a brief interruption of the stellar luminosity increase as a star evolves on the red giant branch by burning its hydrogen shell, which creates an accumulation of stars at this HRD position (e.g. Christensen-Dalsgaard 2015). Its luminosity changes more with metallicity and age than the red clump. Brighter than the red clump, at MG GLYPH<24> GLYPH<0> 0 : 5, lies the AGB bump (AGBB in Fig. 10), which corresponds to the start of the asymptotic giant branch (AGB) where stars are burning their helium shell (e.g. Gallart 1998). The AGB bump is much less densely populated than the RGB bump. It is also clearly visible in the HRD of 47 Tuc (Fig. 11a).  \nThe globular clusters in Fig. 11 clearly illustrate the diversity of the HB morphology. Some have predominantly blue HB (NGC 6397), some just red HB (NGC 104), and some a mixed HB showing bimodal distribution (NGC 5272 and NGC 6362). The HB morphology is explained in the framework of the multiple populations; it is regulated by age, metallicity, and first / second generation abundances (Carretta et al. 2009). NGC 6362 is the least massive globular that presents multiple  \npopulations. Mucciarelli et al. (2016) concluded that most of the stars that populate the red HB are Na poor and belong to the first generation, while the blue side of the HB is populated by the Na-rich stars belonging to the second generation. The same kind of correlation is shown in general by the globular clusters. We quote among others the studies of 47 Tuc (Gratton et al. 2013) and NGC 6397 (Carretta et al. 2009). The role of the He abundances is still under discussion (Valcarce et al. 2016; Marino et al. 2014). He-enhanced stars are indeed expected to populate the blue side of the instability strip because they are still O depleted and Na enhanced, as observed in the second-generation stars. How significant the He enhancement is is still unclear.  \nFigure 3 shows that the globular cluster HB can extend towards the extreme horizontal branch (EHB) region. They are in the same region of the HRD as the hot subdwarfs, which creates a clump at MG = 4 and G BP GLYPH<0> G RP = -0.5 that is well visible in Fig. 1 and Fig. 5. These stars are also nicely characterised in terms of variability, including binary-induced variability, in Gaia Collaboration et al. (2018b). These hot subdwarfs are considered to be red giants that lost their outer hydrogen layers before the core began to fuse helium, which might be due to the interaction with a low-mass companion, although other processes might be at play (e.g. Heber 2009). Gaia will allow detailed studies of the di GLYPH<11> erences between cluster and field hot subdwarfs.', '4.4. Planetary nebulae': 'At the end of the AGB phase, the star has lost most of its hydrogen envelope. The gas expands while the central star first grows hotter at constant luminosity, contracting and fusing hydrogen in the shell around its core (post-AGB phase), then it slowly cools when the hydrogen shell is exhausted, to reach the white dwarf phase. This planetary nebulae phase is very short, about 10,000 years, and is therefore quite di GLYPH<14> cult to observe in the HRD. The Gaia DR2 contains many observations of nearby planetary nebulae as their expanding gas create excess flux over the mean sky background that triggers the on-board detection. We here wish to follow the route of the central star in the HRD. While some central planetary nebula stars are visible in the Galactic Pole HRD (Fig. 12), post-AGB stars are too rare to appear in this diagram. We used catalogue compilations to highlight the position of the two types in the Gaia HRD.  \nWe used the Kerber et al. (2003) catalogue of Galactic planetary nebulae, selecting only sources classified as central stars that are clearly separated from the nebula. With a cross-match radius of 1 00 and using all our filter criteria of Sect. 2.1, only four stars remain. We therefore relaxed the extinction criteria to E ( B GLYPH<0> V ) < 0 : 05 and the parallax relative uncertainty to GLYPH<27>$ =$ < 20%, leading to 23 stars.  \nFor post-AGB stars, we used the catalogue of Szczerba et al. (2007) and the 2MASS identifier provided for the cross-match. Weselected only stars that are classified as very likely post-AGB objects. Here we also relaxed the extinction criteria to E ( B GLYPH<0> V ) < 0 : 05 and the parallax relative uncertainty to GLYPH<27>$ =$ < 20%, leading to 11 stars.  \nWhile some outliers are seen in Fig. 12, either due to crossmatch or misclassification issues, the global position of these stars in the HRD closely follows the expected track from the AGBto the white dwarf sequence. We note that this path crosses the hot subdwarf region we discussed in the previous section.  \nFig. 11. Several globular clusters selected to show a clearly defined and very di GLYPH<11> erent horizontal branch, sorted by decreasing metallicity. a) NGC 104 (47 Tuc), b) NGC 6362, c) NGC 5272, and d) NGC 6397.  \n<!-- image -->  \nFig. 12. North Galactic Pole HRD ( b > 50 GLYPH<14> , 2,077,925 stars) with literature central planetary nebula stars (blue) and post-AGB stars (magenta).  \n<!-- image -->', '5. White dwarfs': 'The Sloan Digital Sky Survey (SDSS, Ahn et al. 2012) has produced the largest spectroscopic catalogue of white dwarfs so far (e.g. Kleinman et al. 2013). This data set has greatly aided our understanding of white dwarf classification and evolution. For example, it has allowed determining the white dwarf mass distribution for large statistical samples of di GLYPH<11> erent white dwarf spectral types. However, much of this work is model dependent and relies upon theoretical mass-radius relationships and stellar atmosphere models, whose precision has only been tested in a limited way. These tests have been limited by the relatively small number of white dwarfs for which accurate parallaxes are available (e.g. Provencal et al. 1998) and by the precision of the parallaxes for these faint stars. This work was updated using the Gaia DR1 catalogue (Tremblay et al. 2017), which included  \nFig. 13. Gaia HRD of white dwarfs with GLYPH<27>$ =$ < 5% (26,264 stars), with letter labels to the features discussed in the text.  \n<!-- image -->  \nmore stars, but the uncertainties remain too large to constrain the theoretical mass-radius relations. Only in a few cases, where the white dwarf resides in a binary system, have mass radius measurements begun to approach the accuracy required to constrain the core composition and H layer mass of individual stars (e.g. Barstow et al. 2005; Parsons et al. 2017; Joyce et al. 2017). Even then, some of these white dwarfs may not be representative of the general population because common envelope evolution may have caused them to depart from the normal white dwarf evolutionary paths.  \nThe publication of Gaia DR2 presents the opportunity to apply accurate parallaxes, with uncertainties of 1% or smaller, to the study of white dwarf stars. The availability of these data, coupled with the accurate Gaia photometry, yields the absolute magnitude, with which the white dwarfs can be clearly located in the expected region of the HRD (Figs. 5, 6). Figure 13 shows the white dwarf region of the HRD alone. This sample was selected with G BP GLYPH<0> G RP < 2 and G GLYPH<0> 10 + 5 log 10 $ > 10 + 2 : 6 ( G BP GLYPH<0> G RP) and by applying the filters described in Sect. 2, including the low-extinction E ( B GLYPH<0> V ) < 0 : 015 criterion, but with a stronger  \nFig. 15. SDSS white dwarfs (5,237 stars) with evolutionary models. Mu is computed using the SDSS u magnitude and the Gaia parallax. Magenta: 0.6 M GLYPH<12> pure H; green dashed: 0.8 M GLYPH<12> pure H; and blue : 0.6 M GLYPH<12> pure He.  \n<!-- image -->  \n<!-- image -->  \nFig. 14. Gaia HRD of white dwarfs with GLYPH<27>$ =$ < 5% and GLYPH<27> GBP < 0 : 01 and GLYPH<27> GRP < 0 : 01 (5,781 stars) overlaid with white dwarf evolutionary models. Magenta: 0.6 M GLYPH<12> pure H; green dashed: 0.8 M GLYPH<12> pure H; and blue: 0.6 M GLYPH<12> pure He. a): HRD. b): Colour-colour diagram.  \n<!-- image -->  \nconstraint on the parallax relative uncertainty of 5%. This yields a catalogue of 26,264 objects. We overplot in Fig. 14 white dwarf evolutionary models 3 for C / O cores (Holberg & Bergeron 2006; Kowalski & Saumon 2006; Tremblay et al. 2011; Bergeron et al. 2011) with colours computed using the revised Gaia DR2 passbands (Evans et al. 2018).  \nSeveral features are clearly visible in Fig. 13. First there is a clear main concentration of stars that is distributed continuously from left to right in the diagram (A) and coincides with the 0.6 M GLYPH<12> hydrogen evolutionary tracks (in magenta). This is expected because the white dwarf mass distribution peaks very strongly near 0.6 M GLYPH<12> (Kleinman et al. 2013). Interestingly, the concentration of white dwarfs departs from the cooling tracks towards the red end of the sequence.  \nJust below the main 0.6 M GLYPH<12> concentration of white dwarfs is a second, separate concentration (B) that seems to be separate from the 0.6 M GLYPH<12> peak at G BP GLYPH<0> G RP GLYPH<24> GLYPH<0> 0 : 1 before again merging by G BP GLYPH<0> G RP GLYPH<24> 0 : 8. At the maximum separation, this concentration is roughly aligned with the 0.8 M GLYPH<12> hydrogen white dwarf cooling track (in green), which is not expected. While the SDSS mass distribution (Kleinman et al. 2013) shows a significant upper tail that extends through 0.8 M GLYPH<12> and up to almost 1.2 M GLYPH<12> , there is no evidence for a minimum between 0.6 and 0.8 M GLYPH<12> like that seen in Fig. 14a. A mass di GLYPH<11> erence should therefore not lead to this feature. However, for a given mass, the evolutionary tracks for di GLYPH<11> erent compositions (DA: hydrogen and DB: helium) and envelope masses are virtually coincident at the resolution of Fig. 14 in the theoretical tracks, leading to no direct interpretation from the tracks in the HRD alone, but we describe below a di GLYPH<11> erent view from the colour-colour relation and the SDSS comparison.  \nA third, weaker concentration of white dwarfs in Fig. 13 lies below the main groups (Q) . It does not follow an obvious evolutionary constant mass curve, which would be parallel to those shown in the plot. Beginning at approximately MG = 13 and G BP GLYPH<0> G RP = GLYPH<0> 0 : 3, it follows a shallower curve that converges with the other concentrations near G BP GLYPH<0> G RP = 0 : 2.  \nWhite dwarfs are also seen to lie above the main concentration A . This can be explained as a mix between natural white dwarf mass distributions and binarity (see Fig. 8).  \nSelecting only the most precise G BP and G RP photometry ( GLYPH<27> G BP < 0 : 01 and GLYPH<27> G RP < 0 : 01), we examined the colour-colour relation in Fig. 14b. The sequence is also split into two parts in this diagram. We verified that the two splits coincide, meaning that the stars in the lower part of Fig. 14a lie in the upper part of Fig. 14b. The mass is not expected to lead to significant differences in this colour-colour diagram, and the theoretical tracks coincide with the observed splits, pointing towards a di GLYPH<11> erence between helium and hydrogen white dwarfs. It also recalls the split in the SDSS colour-colour diagram (Harris et al. 2003).  \nWhile Gaia identifies white dwarfs based on their location on the HRD, SDSS white dwarfs were identified spectroscopically, providing further information on the spectral type, T e GLYPH<11> , and log g as well as a classification. Therefore we cross-matched the two data sets to better understand the features observed in Fig. 14.  \nWe obtained a catalogue of spectroscopically identified SDSS white dwarfs from the Montreal White Dwarf Database 4 (Dufour et al. 2017) by downloading the whole catalogue and then filtering for SDSS identifier, which yielded 28,797 objects. Using the SDSS cross-match provided in the Gaia archive (Marrese et al. 2018), we found that there are 22,802 objects in common and 5,237 satisfying all the filters described in Sect. 2.1 and with single-star spectral type information. Figure 15 shows the SDSS u GLYPH<0> g colour magnitude for the sample with the absolute u magnitude calculated using the Gaia parallax. The distribution is clearly bifurcated. Evolutionary tracks for H and He atmospheres (0.6 M GLYPH<12> ) are overplotted in the figure, indicating that this is due to the di GLYPH<11> erent atmospheric compositions. The Gaia counterparts of these SDSS white dwarfs are quite faint, and therefore the features seen in Fig. 14a are less well visible in this sample because of the larger noise in the parallaxes and the colours. Still, it allowed us to verify that the split of the SDSS white dwarfs corresponds to the location of the Gaia splits in Fig. 14. The narrower filter bands of SDSS are more sensitive to atmospheric compositions than the broad BP and RP Gaia bands. In particular, the u -band fluxes of H-rich DA white dwarfs are suppressed by the Balmer jump at 364.6 nm, which reddens the colours of these stars. The Balmer jump is in the wavelength range where the Gaia filters calibrated for DR2 di GLYPH<11> er most from the nominal filters (Evans et al. 2018), which explains the importance of using tracks that are updated to the DR2 filters for the white dwarf studies instead of the nominal tracks provided by Carrasco et al. (2014).  \nFigure 16 shows the colour-magnitude diagrams in the Gaia and SDSS photometry bands, overlaid with the white dwarfs for specific spectral types. The locations of the various spectral types correspond well to the expected colours arising from their e GLYPH<11> ective temperatures. For example, DQ (carbon), DZ (metal rich), and DC (no strong lines) stars are confined to the red end of the colour-magnitude diagram, while the DO stars (ionised helium) all lie at the blue end. DAs cover the whole diagram. Interestingly, in Fig. 16b, a significant number of classified DA white dwarfs appears to occupy the He-rich atmosphere branch that is indicated by the evolutionary track in Fig. 15. The weaker Q concentration seems to include stars of all types except for DO and DZ. However, the most numerous components are the DA and DQs.', '6. Cluster as stellar parameter templates': 'Clusters have long been considered as benchmarks with regard to the determination of the stellar properties. Open cluster stars share common properties, such as age and chemical abundances. The level of homogeneity of open clusters has been assessed in several papers (Cantat-Gaudin et al. 2014; Bovy 2016). By means of a high-precision di GLYPH<11> erential abundance analysis, the Hyades have been proved to be chemically in-homogeneous at the 0.02 dex level (Liu et al. 2016) at maximum. Until now, the study of clusters was hampered by the disk field contamination. This in turn results in di GLYPH<14> cult membership determination, and in highly uncertain parameters (Netopil et al. 2015). Distance and age, together with chemical abundances, are the fundamen-  \nFig. 16. SDSS white dwarfs per spectral type (DA: hydrogen; DB: neutral helium; DO: ionised helium; DQ: carbon; DZ: metal rich; and DC: no strong lines). panel a): Gaia photometry, panel b): SDSS photometry.  \n<!-- image -->  \ntal properties for a meaningful description of the disk characteristics. Their study complements the field population studies that are based on Galactic surveys. Globular clusters are fundamental tools for studying the properties of low-mass stars and the early chemical evolution of the Galaxy. Now Gaia DR2 data bring us into a completely new domain. High-accuracy parallaxes and exquisite photometry make the comparison with theoretical isochrones very fruitful, based on which, stellar properties can be defined. A detailed discussion of the uncertainties of stellar models is beyond the scope of this paper. Here we would like to recall that e GLYPH<11> ects such as convection in the stellar core, mass loss, rotation, and magnetic fields are still poorly constrained and are often only parametrised in stellar models (Bell 2016; Pasetto et al. 2016; Weiss & Heners 2013). Although very significant, seismic predictions depend on our poor knowledge of the relevant physics (Miglio et al. 2015). A calibration of these e GLYPH<11> ects on star cluster photometry is mandatory and will complement asteroseismology as a tool for testing stellar physics and will ultimately improve stellar models. In Table 2 we present the ages and the extinction values derived by isochrone fitting for the sample of open clusters discussed in this paper. The uncertainties are GLYPH<1> (log(age)) + 0 : 14 GLYPH<0> 0 : 22 , + 0 : 11 GLYPH<0> 0 : 13 , + 0 : 08 GLYPH<0> 0 : 06 for 6 < log(age) GLYPH<20> 7, 7 < log(age) GLYPH<20> 8, log(age) > 8 ; respectively, and GLYPH<1> E ( B GLYPH<0> R ) = 0 : 04. Here we made use of PARSEC isochrones (Chen et al. 2014) for metallicities Z = 0 : 017 and  \n<!-- image -->  \nFig. 17. HRDs of nearby clusters compared with PARSEC isochrones (see text for details) of the Pleiades (a), Praesepe (b), Coma Ber (c), Hyades (d), Alpha Per (e), and Blanco 1 (f). Praesepe, Hyades, and Alpha Per are fitted with Z = 0 : 02, while the others are reproduced using Z = 0 : 017.  \n<!-- image -->  \nZ = 0 : 020 updated to the latest transmission curve calibrated on Gaia DR2 data (Evans et al. 2018) 5 . Praesepe, Hyades, Alpha Per, and NGC 6475 were fitted with Z = 0 : 02 (Gaia Collab-  \noration et al. 2017; Kharchenko et al. 2015), while the others were reproduced using Z = 0 : 017. This gave a relatively poor fit for clusters that are known to have sub-solar metallicity, such as NGC 2158, which has [Fe / H] = -0.25 (Kharchenko et al. 2015). The PARSEC solar value is Z = 0 : 015. This version of the PARSEC tracks makes use of a modified relation between the e GLYPH<11> ec-  \nFigure 18 presents the comparison of two distant clusters, NGC 2682 (M67) and NGC 2447, with PARSEC isochrones. M 67 is one of the best-studied star clusters. It has a metallicity near solar, an accessible distance of about 1028 pc with low reddening (Taylor 2007), and an age close to solar ( GLYPH<24> 4 Gyr). It is a very highly populated object that includes over 1000 members from main-sequence dwarfs, a well-populated subgiant and red giant branch, white dwarfs, blue stragglers, sub-subgiants, X-ray sources, and cataclysmic variables. Gaia identifies 1526 members. It was observed by almost all the most relevant spectroscopic surveys ( Gaia -ESO, APOGEE, WIYN, etc.). Astero-  \n<!-- image -->  \nFig. 18. HRDs of two distant clusters compared with PARSEC isochrones (see text for details): M67 (NGC 2682) (a), and NGC 2447(b).  \n<!-- image -->  \nFig. 19. HRD of the globular cluster 47 Tuc compared with PARSEC isochrones (see text for details). The inner region (radius < 10 arcmin, e.g. three times the half-light radius) is shown in green, while the external regions are plotted in blue. A maximum radius of 1.1 degrees was used.  \n<!-- image -->  \ntive temperature and Rosseland mean optical depth GLYPH<28> across the atmosphere that is derived from PHOENIX (Allard et al. 2012) and in particular from the set of BT-Settl models. With this modified relation, introduced to better reproduce the observed massradius relation in nearby low mass stars (Chen et al. 2014), the models provide a good representation of the colour distribution of very low mass stars in several passbands.  \nFigure 17 shows the HRD of a few nearby open clusters compared with PARSEC isochrones. The distance modulus (Table 2) was used, and the extinction was not corrected in the photometry, but was applied on the isochrones.  \nThe fits are remarkably good in the upper and lower main sequence. The high quality of Gaia photometry produces welldefined features, very clean main sequences, and a clear definition of the binary sequence. The agreement for the Pleiades is particularly remarkable. In spite of the impressively good agreement across a range of several magnitudes, at about MG GLYPH<24> 10 ; the model predictions and the observed main sequence still disagree. The slope of the theoretical main sequence initially seems  \nto be slightly steeper than the observed main sequence, while at even lower magnitudes, the slope of the observed main sequence becomes steeper than the predicted main sequence. The latter effect might be due to the background subtraction, which becomes challenging at these faint magnitudes (Evans et al. 2018; Arenou et al. 2018). Instead, the initial steepening of the isochrones, which is also observed in other clusters in Fig. 17, might indicate that the adopted boundary conditions in the domain of very low mass stars in PARSEC need a further small revision. It is well known that current models and the colour transformations fail to reproduce the main sequence in the very low mass regime (Bell 2016), and the data gathered by Gaia will certainly help to overcome this long-standing problem.  \nThe age determination of Blanco 1 deserves further comments. Blanco 1 has a slightly super-solar metallicity [Fe = H] = + 0 : 04 GLYPH<6> 0 : 04 (Ford et al. 2005). Previous age determination placed Blanco 1 in the age range log(age) = 8 : 0 GLYPH<0> 8 : 17 (Moraux et al. 2007). A determination of the lithium depletion boundary on very low mass stars gives log(age) = 8 : 06 GLYPH<6> 0 : 13 when a correction for magnetic activity is applied (Juarez et al. 2014). From the main-sequence turno GLYPH<11> , we obtain log(age) = 8 : 30. However, fitting the main-sequence turno GLYPH<11> in such an inconspicuous cluster might not lead to correct results, since the initial mass function disfavours higher mass stars. Using the lithium depletion boundary age of log(age) of 8 : 06 GLYPH<6> 0 : 04, we reproduce the lower main sequence, with a marginal fit to the upper main sequence. Similar considerations apply to the Pleiades, whose log(age) is in the range 8 : 04 GLYPH<6> 0 : 03 - 8 : 10 GLYPH<6> 0 : 06 and is derived from the lithium depletion boundary or from eclipsing binaries (for a recent discussion, see David et al. 2016). Using the lithium depletion boundary age of 8 : 04 GLYPH<6> 0 : 06, we can reproduce the main sequence with PARSEC isochrones.  \nseismologic data are available from the Kepler 2 mission (Stello et al. 2016). M67 is a cornerstone of stellar astrophysics, and it is a calibrator of age determination via gyrochronology (Barnes et al. 2016). Its turn-o GLYPH<11> mass is very close to the critical mass for the onset of core convection. For this reason, the cluster is especially interesting for this specific regime of stellar models and their dependence on di GLYPH<11> erent parameters such as nuclear reaction rate and solar abundances. The main-sequence termination presents a distinctive hook and a gap just above it. These features are used to distinguish between di GLYPH<11> usive and non-di GLYPH<11> usive evolutionary models. Atomic di GLYPH<11> usion is very important for the morphology of isochrones in the vicinity of the turn-o GLYPH<11> . The hook feature traces the rapid contraction phase that occurs at central H exhaustion in those stars that have convective cores during their main-sequence phase. This hook is located at somewhat higher luminosities and cooler temperatures when di GLYPH<11> usive processes are included (Michaud et al. 2004). Gaia photometry and parallax place the location of these features very precisely in the HRD. PARSEC isochrones, including overshoot and diffusion, reproduce the main-sequence slope and termination point reasonably well, although additional overshoot calibration might be necessary. A population of blue stragglers, a few yellow giants, and two sub-subgiants are clearly visible among the members. The binary star sequence in M67 is clearly defined as well.  \nNGC 2447 is a younger object with an age of 0.55 Gyr and almost solar metallicity. Previous photometry is relatively poor (Clariá et al. 2005). In Gaia DR2, photometry and membership of the cluster stand out very clearly. PARSEC isochrones reproduce the main sequence very well, while the red clump colour is slightly redder.  \nFigure 19 presents the HRD of the globular cluster 47 Tuc (see Table 3), which is one prominent example of multiple populations in globular clusters. Hubble Space Telescope (HST) photometry in the blue passbands has revealed a double main sequence (Milone et al. 2012) and distinct subgiant branches (Anderson et al. 2009). These components are not visible in the highaccuracy Gaia photometry, since bluer colours would be necessary. 47 Tuc has a relatively high average metallicity of [Fe / H] = -0.72. We fit it with PARSEC isochrones with Z = 0 : 0056, Y = 0 : 25. Since no alpha-enhanced tracks are available in the PARSEC data set, we use the Salaris et al. (1993) relation to account for the enhancement.', '7. Variation of the HRD with kinematics': 'Thin disk, thick disk, and halo have di GLYPH<11> erent age and metallicity distributions as well as kinematics. The Gaia HRD is therefore expected to vary with the kinematics properties. For stars with radial velocities, we apply classical cuts to broadly kinematically select thin-disk ( V tot < 50 km s GLYPH<0> 1 ), thickdisk (70 < V tot < 180 km s GLYPH<0> 1 ), and halo stars ( V tot > 200 km s GLYPH<0> 1 ) (e.g. Bensby et al. 2014), using U , V , W computed within the framework of Gaia Collaboration et al. (2018d), in which a global Toomre diagram is presented. This sample with radial velocities is limited to bright stars. To probe deeper into the HRD, we also made a selection using only tangential velocities, which we computed with V T = 4 : 74 =$ q GLYPH<22> 2 GLYPH<11> GLYPH<3> + GLYPH<22> 2 GLYPH<14> . We roughly adapted our kinematic cut to the fact that we now only have two components of the velocity instead of three: we used V T < 40 km s GLYPH<0> 1 for the thin disk and 60 < V T < 150 km s GLYPH<0> 1 for the thick disk, but still V T > 200 km s GLYPH<0> 1 for the halo. To all our samples we also applied the E ( B GLYPH<0> V ) < 0 : 015 selection criterion. The results are presented in Fig. 20 and Fig. 21. We note that hot star radial veloci-  \nties are not included in Gaia DR2 (Sartoretti et al. 2018), which explains why they are missing in Fig. 20.  \nThe left figures associated with the thin disk show the same main features typical of a young population as the local HRD of Fig. 6: young hot main-sequence stars are present (Fig. 21a), the secondary red clump as well as the AGB bump is visible (Fig. 20a), and the turn-o GLYPH<11> region is di GLYPH<11> usely populated. The middle figures associated with the thick disk show a more localised turn-o GLYPH<11> typical of an intermediate to old population. The median locus of the main sequence is similar to the thin-disk selection. The right figures associated with the halo show an extended horizontal branch, typical of old metal-poor populations, but also two very distinct main sequences and turn-o GLYPH<11> s. We note the presence of the halo white dwarfs.  \nWe study the kinematic selection associated with the halo in Fig. 22 in more detail. The two main-sequence turn-o GLYPH<11> s are shifted by GLYPH<24> 0.1 mag in colour. The red main-sequence turn-o GLYPH<11> is shifted by GLYPH<24> 0.05 mag from the thick-disk kinematic selection main sequence (green line in Fig. 22a). Comparison with isochrones clearly identifies the distinct main sequences as being driven by a metallicity di GLYPH<11> erence of about 1 dex. To further confirm this, we cross-matched our selection with the APOGEE DR14 catalogue (Holtzman et al. 2015) using their 2MASS ID and the 2MASS cross-match provided in the Gaia archive (Marrese et al. 2018). There are 184 stars in common, 1168 if we relax the low-extinction criteria that mostly confine our HRD selection to the galactic poles. The metallicity distribution is indeed double-peaked, with peak metallicities of -1.3 and -0.5 dex. We superimpose in Fig. 22 the corresponding PARSEC isochrones using the Salaris et al. (1993) formula for the mean GLYPH<11> enhancement of 0.23 for [M / H] = -1.3 and -0.5 and ages of 13 and 11 Gyr, respectively. While the extent of the horizontal branch does not correspond to the isochrones used here, it can be compared to the empirical horizontal branches of the globular clusters presented in Fig. 11.  \nThis bimodal metallicity distribution in the kinematic selection of the halo may recall the globular cluster bimodal metallicity distribution with the same peaks at [Fe / H] GLYPH<24> -0.5 and [Fe / H] GLYPH<24> -1.5 (e.g. Zinn 1985), the more metal-rich part being associated with the thick disk and bulge. We verified with the globular cluster kinematics provided in Gaia Collaboration et al. (2018c) that 80% of these globular clusters indeed fall into our halo kinematic selection, independently of their metallicity. The -0.5 dex peak also recalls the bulge metal-poor component (e.g. Hill et al. 2011). However, it seems to be di GLYPH<11> erent from the double halo found at larger distances (Carollo et al. 2007; de Jong et al. 2010): while their inner-halo component at GLYPH<24> -1.6 could correspond to our metal-poor component, their metal-poor component is at metallicity GLYPH<24> -2.2 and is found in the outer Galaxy. This duality in the metallicity distribution of the kinematically selected halo stars has also been found using TGAS data with RAVE and APOGEE (Bonaca et al. 2017). Half of the stars are also found to have [M / H] > -1 dex with a dynamically selected halo sample in TGAS / RAVE by Posti et al. (2017).  \nThe GLYPH<11> abundances of this APOGEE sample (Fig. 22b) let us recover the two sequences described by Nissen & Schuster (2010) using an equivalent kinematic selection. We adjusted a median spline to the main sequence of the high-velocity HRD and present the velocity distribution of the stars on either side of this median spline in Fig. 22c. The magenta sequence looks like a velocity distribution tail towards high velocities, while the blue sequence has a flat velocity distribution. We do not see any difference in the sky distribution of these components, most probably because the sky distribution is fully dominated by our sample  \nFig. 20. Gaia HRDs with kinematic selections based on the total velocity: a) V tot < 50 km s GLYPH<0> 1 (275,595 stars), b) 70 < V tot < 180 km s GLYPH<0> 1 (116,198 stars), and c) V tot > 200 km s GLYPH<0> 1 (4,461 stars).  \n<!-- image -->  \nFig. 21. Gaia HRDs with kinematic selections based on the tangential velocity: a) V T < 40 km s GLYPH<0> 1 (1,893,677 stars), b) 60 < V T < 150 km s GLYPH<0> 1 (1,303,558 stars), and c) V T > 200 km s GLYPH<0> 1 (64,727 stars).  \n<!-- image -->  \nselection criteria. All these tests and comparisons with the literature seem to indicate a very di GLYPH<11> erent formation scenario for the two components of this kinematic selection of the halo.', '8. Summary': "The unprecedented all-sky precise and homogeneous astrometric and photometric content of Gaia DR2 allows us to see fine structures in both field star and cluster Hertzsprung-Russell diagrams to an extent that has never been reached before. We have described the main filtering of the data that is required for this purpose and provided membership for a selection of open clusters covering a wide range of ages.  \nThe variations with age and metallicity are clearly illustrated by the main sequence and the giant branches of a large set of open and globular clusters and kinematically selected stellar populations. The main sequence for nearby stars is extremely thin, for field and cluster stars both, with a clear scattering of  \ndouble stars up to 0.75 magnitude visible above the main sequence. Gaia DR2 provides a very unique view of the bottom of the main sequence down to the brown dwarf regime, including L-type and halo BDs. We also see the post-AGB stars and the central stars of planetary nebulae, which follow the expected tracks down to the white dwarf sequence, as well as hot subdwarfs.  \nThe split in the white dwarf sequence between hydrogen and helium white dwarfs, which was first detected in the SDSS colour-colour diagrams, is visible for the first time in an HRD, with very thin sequences that agree with the strong peak of their mass distribution around 0.6 M GLYPH<12> .  \nKinematic selections clearly show the change in HRDs with stellar populations. It highlights the strong bimodality of the HRD of the classical halo kinematic selection, and gives evidence of two very di GLYPH<11> erent populations within this selection.  \nAll the features in the Gaia HRDs chiefly agree in general with the theoretical stellar evolution models. The di GLYPH<11> erences that  \n<!-- image -->  \n<!-- image -->  \nFig. 22. a) Same as Fig. 21c (kinematic selection V T > 200 km s GLYPH<0> 1 ) overlaid with PARSEC isochrones for [M / H] = GLYPH<0> 1 : 3, age = 13 Gyr (blue), and [M / H] = GLYPH<0> 0 : 5, age = 11 Gyr (magenta) and [ GLYPH<11> / Fe] = 0 : 23; green line: median spline fit to the main sequence of the thick-disk kinematic selection (Fig. 21b). b) [ GLYPH<11> / Fe] vs. [Fe / H] of the corresponding APOGEE stars without extinction criterion applied. c) Density distribution of the tangential velocity V T on the blue and red sides of a median spline main-sequence fit.  \n<!-- image -->  \nare observed for the faintest brown dwarfs, the white dwarf hydrogen / helium split, or the very fine structures of the open cluster main sequences, for example, are expected to bring new insight into stellar physics.  \nNumerous studies by the community are expected on the Gaia HRD. For example, rare stages of evolution will be extracted from the archive, together with more clusters, and detailed comparisons with di GLYPH<11> erent stellar evolution models will be made. The completeness of the data is a di GLYPH<14> cult question that we did not discuss here, but that will be studied by the community as it is a very important issue, in particular for determining the local volume density and all the studies of the initial mass function and stellar evolution lifetimes.  \nThe next Gaia release, DR3, will again be a new step for stellar studies. This will be achieved not only by the increase in completeness, precision, and accuracy of the data, but also by the additional spectrophotometry and spectroscopy, together with the binarity information that will be provided.  \nAcknowledgements. We thank Pierre Bergeron for providing the WD tracks in the Gaia DR2 passbands. This work presents results from the European Space Agency (ESA) space mission Gaia . Gaia data are being processed by the Gaia Data Processing and Analysis Consortium (DPAC). Funding for the DPAC is provided by national institutions, in particular the institutions partic-  \nipating in the Gaia MultiLateral Agreement (MLA). The Gaia mission website is https://www.cosmos.esa.int/gaia . The Gaia archive website is https://archives.esac.esa.int/gaia . The Gaia mission and data processing have financially been supported by, in alphabetical order by country: the Algerian Centre de Recherche en Astronomie, Astrophysique et Géophysique of Bouzareah Observatory; the Austrian Fonds zur Förderung der wissenschaftlichen Forschung (FWF) Hertha Firnberg Programme through grants T359, P20046, and P23737; the BELgian federal Science Policy O GLYPH<14> ce (BELSPO) through various PROgramme de Développement d'Expériences scientifiques (PRODEX) grants and the Polish Academy of Sciences - Fonds Wetenschappelijk Onderzoek through grant VS.091.16N; the Brazil-France exchange programmes Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP) and Coordenação de Aperfeicoamento de Pessoal de Nível Superior (CAPES) - Comité Français d'Evaluation de la Coopération Universitaire et Scientifique avec le Brésil (COFECUB); the Chilean Dirección de Gestión de la Investigación (DGI) at the University of Antofagasta and the Comité Mixto ESO-Chile; the National Science Foundation of China (NSFC) through grants 11573054 and 11703065; the Czech-Republic Ministry of Education, Youth, and Sports through grant LG 15010, the Czech Space O GLYPH<14> ce through ESA PECS contract 98058, and Charles University Prague through grant PRIMUS / SCI / 17; the Danish Ministry of Science; the Estonian Ministry of Education and Research through grant IUT40-1; the European Commission's Sixth Framework Programme through the European Leadership in Space Astrometry ( https://www.cosmos.esa. int/web/gaia/elsa-rtn-programme ELSA) Marie Curie Research Training Network (MRTN-CT-2006-033481), through Marie Curie project PIOF-GA2009-255267 (Space AsteroSeismology & RR Lyrae stars, SAS-RRL), and through a Marie Curie Transfer-of-Knowledge (ToK) fellowship (MTKD-CT2004-014188); the European Commission's Seventh Framework Programme through grant FP7-606740 (FP7-SPACE-2013-1) for the Gaia European Network for Improved data User Services (GENIUS) and through grant 264895 for the Gaia Research for European Astronomy Training ( https://www.cosmos. esa.int/web/gaia/great-programme GREAT-ITN) network; the European Research Council (ERC) through grants 320360 and 647208 and through the European Union's Horizon 2020 research and innovation programme through grants 670519 (Mixing and Angular Momentum tranSport of massIvE stars MAMSIE) and 687378 (Small Bodies: Near and Far); the European Science Foundation (ESF), in the framework of the Gaia Research for European Astronomy Training Research Network Programme ( https://www.cosmos.esa. int/web/gaia/great-programme GREAT-ESF); the European Space Agency (ESA) in the framework of the Gaia project, through the Plan for European Cooperating States (PECS) programme through grants for Slovenia, through contracts C98090 and 4000106398 / 12 / NL / KML for Hungary, and through contract 4000115263 / 15 / NL / IB for Germany; the European Union (EU) through a European Regional Development Fund (ERDF) for Galicia, Spain; the Academy of Finland and the Magnus Ehrnrooth Foundation; the French Centre National de la Recherche Scientifique (CNRS) through action 'Défi MASTODONS', the Centre National d'Etudes Spatiales (CNES), the L'Agence Nationale de la Recherche (ANR) 'Investissements d'avenir' Initiatives D'EXcellence (IDEX) programme Paris Sciences et Lettres (PSL GLYPH<3> ) through grant ANR-10-IDEX0001-02, the ANR 'Défi de tous les savoirs' (DS10) programme through grant ANR-15-CE31-0007 for project 'Modelling the Milky Way in the Gaia era' (MOD4Gaia), the Région Aquitaine, the Université de Bordeaux, and the Utinam Institute of the Université de Franche-Comté, supported by the Région de Franche-Comté and the Institut des Sciences de l'Univers (INSU); the German Aerospace Agency (Deutsches Zentrum für Luft- und Raumfahrt e.V., DLR) through grants 50QG0501, 50QG0601, 50QG0602, 50QG0701, 50QG0901, 50QG1001, 50QG1101, 50QG1401, 50QG1402, 50QG1403, and 50QG1404 and the Centre for Information Services and High Performance Computing (ZIH) at the Technische Universität (TU) Dresden for generous allocations of computer time; the Hungarian Academy of Sciences through the Lendület Programme LP2014-17 and the János Bolyai Research Scholarship (L. Molnár and E. Plachy) and the Hungarian National Research, Development, and Innovation O GLYPH<14> ce through grants NKFIH K-115709, PD-116175, and PD-121203; the Science Foundation Ireland (SFI) through a Royal Society - SFI University Research Fellowship (M. Fraser); the Israel Science Foundation (ISF) through grant 848 / 16; the Agenzia Spaziale Italiana (ASI) through contracts I / 037 / 08 / 0, I / 058 / 10 / 0, 2014-025-R.0, and 2014-025-R.1.2015 to the Italian Istituto Nazionale di Astrofisica (INAF), contract 2014-049-R.0 / 1 / 2 to INAF dedicated to the Space Science Data Centre (SSDC, formerly known as the ASI Sciece Data Centre, ASDC), and contracts I / 008 / 10 / 0, 2013 / 030 / I.0, 2013030-I.0.1-2015, and 2016-17-I.0 to the Aerospace Logistics Technology Engineering Company (ALTEC S.p.A.), and INAF; the Netherlands Organisation for Scientific Research (NWO) through grant NWO-M-614.061.414 and through a VICI grant (A. Helmi) and the Netherlands Research School for Astronomy (NOVA); the Polish National Science Centre through HARMONIA grant 2015 / 18 / M / ST9 / 00544 and ETIUDA grants 2016 / 20 / S / ST9 / 00162 and 2016 / 20 / T / ST9 / 00170; the Portugese Fundação para a Ciência e a Tecnologia (FCT) through grant SFRH / BPD / 74697 / 2010; the Strategic Programmes UID / FIS / 00099 / 2013 for CENTRA and UID / EEA / 00066 / 2013 for UNINOVA;  \nthe Slovenian Research Agency through grant P1-0188; the Spanish Ministry of Economy (MINECO / FEDER, UE) through grants ESP2014-55996-C2-1-R, ESP2014-55996-C2-2-R, ESP2016-80079-C2-1-R, and ESP2016-80079-C2-2R, the Spanish Ministerio de Economía, Industria y Competitividad through grant AyA2014-55216, the Spanish Ministerio de Educación, Cultura y Deporte (MECD) through grant FPU16 / 03827, the Institute of Cosmos Sciences University of Barcelona (ICCUB, Unidad de Excelencia 'María de Maeztu') through grant MDM-2014-0369, the Xunta de Galicia and the Centros Singulares de Investigación de Galicia for the period 2016-2019 through the Centro de Investigación en Tecnologías de la Información y las Comunicaciones (CITIC), the Red Española de Supercomputación (RES) computer resources at MareNostrum, and the Barcelona Supercomputing Centre - Centro Nacional de Supercomputación (BSC-CNS) through activities AECT-2016-1-0006, AECT2016-2-0013, AECT-2016-3-0011, and AECT-2017-1-0020; the Swedish National Space Board (SNSB / Rymdstyrelsen); the Swiss State Secretariat for Education, Research, and Innovation through the ESA PRODEX programme, the Mesures d'Accompagnement, the Swiss Activités Nationales Complémentaires, and the Swiss National Science Foundation; the United Kingdom Rutherford Appleton Laboratory, the United Kingdom Science and Technology Facilities Council (STFC) through grant ST / L006553 / 1, the United Kingdom Space Agency (UKSA) through grant ST / N000641 / 1 and ST / N001117 / 1, as well as a Particle Physics and Astronomy Research Council Grant PP / C503703 / 1. This publication has made use of SIMBAD and VizieR, both operated at the Centre de Données astronomiques de Strasbourg (CDS, http: // cds.u-strasbg.fr / ). This publication has made use of data products from the Two Micron All Sky Survey, which is a joint project of the University of Massachusetts and the Infrared Processing and Analysis Center / California Institute of Technology, funded by the National Aeronautics and Space Administration and the National Science Foundation. This publication has made use of data products from SDSS-III. The Funding for SDSS-III has been provided by the Alfred P. Sloan Foundation, the Participating Institutions, the National Science Foundation, and the U.S. Department of Energy O GLYPH<14> ce of Science. The SDSS-III web site is http: // www.sdss3.org / . SDSS-III is managed by the Astrophysical Research Consortium for the Participating Institutions of the SDSS-III Collaboration.", 'References': 'Ahn, C. P., Alexandro GLYPH<11>  \n, R., Allende Prieto, C., et al. 2012, ApJS, 203, 21  \n- Allard, F., Homeier, D., & Freytag, B. 2012, Philosophical Transactions of the Royal Society of London Series A, 370, 2765\n- Anderson, J., Piotto, G., King, I. R., Bedin, L. R., & Guhathakurta, P. 2009, ApJ, 697, L58\n- Andrae, R., Fouesneau, M., Creevey, O., et al. 2018, A&A, this volume, DPACP43: astrophysical parameters\n- Arenou, F., Luri, X., Babusiaux, C., & et al. 2018, A&A, this volume, DPACP39: Catalogue validation  \nBara  \nGLYPH<11>  \ne, I., Homeier, D., Allard, F., & Chabrier, G. 2015, A&A, 577, A42  \n- Barnes, S. A., Weingrill, J., Fritzewski, D., Strassmeier, K. G., & Platais, I. 2016,\n- ApJ, 823, 16 Barstow, M. A., Bond, H. E., Holberg, J. B., et al. 2005, MNRAS, 362, 1134 Bell, C. P. M. 2016, in 19th Cambridge Workshop on Cool Stars, Stellar Systems, and the Sun (CS19), 102\n- Bensby, T., Feltzing, S., & Oey, M. S. 2014, A&A, 562, A71  \nBergeron, P., Wesemael, F., Dufour, P., et al. 2011, ApJ, 737, 28  \n- Bonaca, A., Conroy, C., Wetzel, A., Hopkins, P. F., & Kereš, D. 2017, ApJ, 845, 101  \nBovy, J. 2016, ApJ, 817, 49  \nCantat-Gaudin, T., Vallenari, A., Zaggia, S., et al. 2014, A&A, 569, A17  \nCapitanio, L., Lallement, R., Vergely, J. L., Elyajouri, M., & Monreal-Ibero, A.  \n2017, A&A, 606, A65  \nCarollo, D., Beers, T. C., Lee, Y. S., et al. 2007, Nature, 450, 1020  \n- Carrasco, J. M., Catalán, S., Jordi, C., et al. 2014, A&A, 565, A11\n- Carretta, E., Bragaglia, A., Gratton, R. G., et al. 2009, A&A, 505, 117  \nCastelli, F. & Kurucz, R. L. 2003, in IAU Symposium, Vol. 210, Modelling of  \nStellar Atmospheres, ed. N. Piskunov, W. W. Weiss, & D. F. Gray, A20  \nChen, Y., Girardi, L., Bressan, A., et al. 2014, MNRAS, 444, 2525  \n- Christensen-Dalsgaard, J. 2015, MNRAS, 453, 666\n- Clariá, J. J., Piatti, A. E., Lapasset, E., & Parisi, M. C. 2005, Baltic Astronomy, 14, 301\n- Conrad, C., Scholz, R.-D., Kharchenko, N. V., et al. 2014, A&A, 562, A54 Danielski, C., Babusiaux, C., Ruiz-Dern, L., Sartoretti, P., & Arenou, F. 2018, ArXiv e-prints, 1802.01670  \nDavid, T. J., Conroy, K. E., Hillenbrand, L. A., et al. 2016, AJ, 151, 112  \nde Jong, J. T. A., Yanny, B., Rix, H.-W., et al. 2010, ApJ, 714, 663  \n- Denissenkov, P. A., VandenBerg, D. A., Kopacki, G., & Ferguson, J. W. 2017, ApJ, 849, 159\n- Dotter, A., Sarajedini, A., Anderson, J., et al. 2010, ApJ, 708, 698\n- Dufour, P., Blouin, S., Coutu, S., et al. 2017, in Astronomical Society of the Pacific Conference Series, Vol. 509, 20th European White Dwarf Workshop, ed. P.-E. Tremblay, B. Gaensicke, & T. Marsh, 3\n- Evans, D., Riello, M., De Angeli, F., et al. 2018, A&A, this volume, DPACP-40: photometric validation  \nFaherty, J. K., Burgasser, A. J., Cruz, K. L., et al. 2009, AJ, 137, 1  \nFitzpatrick, E. L. & Massa, D. 2007, ApJ, 663, 320  \n- Ford, A., Je GLYPH<11> ries, R. D., & Smalley, B. 2005, MNRAS, 364, 272\n- Gaia Collaboration, Brown, A., Vallenari, A., et al. 2018a, A&A, this volume, DPACP-36: DR2 overview\n- Gaia Collaboration, Brown, A. G. A., Vallenari, A., et al. 2016, A&A, 595, A2 Gaia Collaboration, Eyer, L., & et al. 2018b, A&A, this volume, DPACP-35: variable stars in the CMD\n- Gaia Collaboration, Helmi, A., van Leeuwen, F., et al. 2018c, A&A, this volume, DPACP-34: kinematics of globular clusters and dwarf galaxies  \nGaia Collaboration, Katz, D., Antoja, T., Romero-Gómez, M., & et al. 2018d,  \n- A&A, this volume, DPACP-33: Mapping the Milky Way kinematic structure Gaia Collaboration, van Leeuwen, F., Vallenari, A., et al. 2017, A&A, 601, A19 Gallart, C. 1998, ApJ, 495, L43\n- Girardi, L. 1999, MNRAS, 308, 818  \nGirardi, L. 2016, ARA&A, 54, 95  \n- Gliese, W. & Jahreiß, H. 1991, Preliminary Version of the Third Catalogue of Nearby Stars, Tech. rep.\n- Gratton, R. G., Lucatello, S., Sollima, A., et al. 2013, A&A, 549, A41\n- Harris, H. C., Liebert, J., Kleinman, S. J., et al. 2003, AJ, 126, 1023\n- Harris, W. E. 1996, AJ, 112, 1487  \nHeber, U. 2009, ARA&A, 47, 211  \n- Henry, T. J. & Jao, W.-C. 2015, IAU General Assembly, 22, 2253773  \nHill, V., Lecureur, A., Gómez, A., et al. 2011, A&A, 534, A80  \n- Holberg, J. B. & Bergeron, P. 2006, AJ, 132, 1221  \nHoltzman, J. A., Shetrone, M., Johnson, J. A., et al. 2015, AJ, 150, 148  \nHurley, J. & Tout, C. A. 1998, MNRAS, 300, 977  \n- Jordi, C., Gebran, M., Carrasco, J. M., et al. 2010, A&A, 523, A48\n- Joyce, S. R. G., Barstow, M. A., Casewell, S. L., Holberg, J. B., & Bond, H. E. 2017, in Astronomical Society of the Pacific Conference Series, Vol. 509, 20th European White Dwarf Workshop, ed. P.-E. Tremblay, B. Gaensicke, & T. Marsh, 389\n- Juarez, A. J., Cargile, P. A., James, D. J., & Stassun, K. G. 2014, ApJ, 795, 143 Kerber, F., Mignani, R. P., Guglielmetti, F., & Wicenec, A. 2003, A&A, 408, 1029\n- Kharchenko, N. V., Piskunov, A. E., Röser, S., Schilbach, E., & Scholz, R.-D. 2005, A&A, 438, 1163\n- Kharchenko, N. V., Piskunov, A. E., Schilbach, E., Roeser, S., & Scholz, R.-D. 2015, VizieR Online Data Catalog, 358\n- Kleinman, S. J., Kepler, S. O., Koester, D., et al. 2013, ApJS, 204, 5  \nKowalski, P. M. & Saumon, D. 2006, ApJ, 651, L137  \n- Lallement, R., Welsh, B. Y., Vergely, J. L., Crifo, F., & Sfeir, D. 2003, A&A, 411, 447\n- Lindegren, L., Hernández, J., Bombrun, A., Klioner, S., & Bastian, U. 2018, A&A, this volume, DPACP-51: The astrometric solution\n- Liu, F., Yong, D., Asplund, M., Ramírez, I., & Meléndez, J. 2016, MNRAS, 457, 3934  \nLoktin, A. V. & Beshenov, G. V. 2003, Astronomy Reports, 47, 6  \n- Luri, X., Brown, A., Sarro, L., et al. 2018, A&A, this volume, DPACP-38: handling astrometric data\n- Marigo, P., Girardi, L., Bressan, A., et al. 2017, ApJ, 835, 77\n- Marino, A. F., Milone, A. P., Przybilla, N., et al. 2014, MNRAS, 437, 1609\n- Marrese, P., Marinoni, S., Fabrizio, M., & Altavilla, G. 2018, A&A, this volume, DPACP-41: cross-match with external catalogues\n- Michaud, G., Richard, O., Richer, J., & VandenBerg, D. A. 2004, ApJ, 606, 452 Miglio, A., Brogaard, K., & Handberg, R. 2015, IAU General Assembly, 22, 2251619\n- Milone, A. P., Piotto, G., Bedin, L. R., et al. 2012, ApJ, 744, 58\n- Moraux, E., Bouvier, J., Stau GLYPH<11> er, J. R., Barrado y Navascués, D., & Cuillandre, J.-C. 2007, A&A, 471, 499\n- Mucciarelli, A., Dalessandro, E., Massari, D., et al. 2016, ApJ, 824, 73\n- Netopil, M., Paunzen, E., & Carraro, G. 2015, A&A, 582, A19\n- Netopil, M., Paunzen, E., Heiter, U., & Soubiran, C. 2016, A&A, 585, A150\n- Nissen, P. E. & Schuster, W. J. 2010, A&A, 511, L10\n- Parsons, S. G., Gänsicke, B. T., Marsh, T. R., et al. 2017, MNRAS, 470, 4473\n- Pasetto, S., Chiosi, C., Chiosi, E., Cropper, M., & Weiss, A. 2016, MNRAS, 459, 3182\n- Perryman, M. A. C., Lindegren, L., Kovalevsky, J., et al. 1995, A&A, 304, 69 Posti, L., Helmi, A., Veljanoski, J., & Breddels, M. 2017, ArXiv e-prints, 1711.04766\n- Powalka, M., Lançon, A., Puzia, T. H., et al. 2017, ApJ, 844, 104\n- Provencal, J. L., Shipman, H. L., Høg, E., & Thejll, P. 1998, ApJ, 494, 759  \nRuiz-Dern, L., Babusiaux, C., Arenou, F., Turon, C., & Lallement, R. 2018,', 'A&A, 609, A116': "Salaris, M., Chie GLYPH<14> , A., & Straniero, O. 1993, ApJ, 414, 580  \nSartoretti, P., Katz, D., Cropper, M., et al. 2018, A&A, this volume, DPACP-47: Spectroscopic data processing  \nSaumon, D. & Marley, M. S. 2008, ApJ, 689, 1327  \nSchlegel, D. J., Finkbeiner, D. P., & Davis, M. 1998, ApJ, 500, 525  \nSkrutskie, M. F., Cutri, R. M., Stiening, R., et al. 2006, AJ, 131, 1163  \nSmart, R. L., Marocco, F., Caballero, J. A., et al. 2017, MNRAS, 469, 401  \nStello, D., Vanderburg, A., Casagrande, L., et al. 2016, ApJ, 832, 133  \nSzczerba, R., Siódmiak, N., Stasi'nska, G., & Borkowski, J. 2007, A&A, 469, 799  \nTaylor, B. J. 2007, AJ, 133, 370  \nTremblay, P.-E., Gentile-Fusillo, N., Raddi, R., et al. 2017, MNRAS, 465, 2849  \nTremblay, P.-E., Ludwig, H.-G., Ste GLYPH<11> en, M., Bergeron, P., & Freytag, B. 2011, A&A, 531, L19  \nValcarce, A. A. R., Catelan, M., Alonso-García, J., Contreras Ramos, R., & Alves, S. 2016, A&A, 589, A126  \nvan Leeuwen, F. 2009, A&A, 497, 209  \nWeiss, A. & Heners, N. 2013, in European Physical Journal Web of Conferences, Vol. 43, European Physical Journal Web of Conferences, 01002  \nZinn, R. 1985, ApJ, 293, 424  \n- 1 Univ. Grenoble Alpes, CNRS, IPAG, 38000 Grenoble, France\n- 2 GEPI, Observatoire de Paris, Université PSL, CNRS, 5 Place Jules Janssen, 92190 Meudon, France\n- 3 Institute of Astronomy, University of Cambridge, Madingley Road, Cambridge CB3 0HA, United Kingdom\n- 4 Leicester Institute of Space and Earth Observation and Department of Physics and Astronomy, University of Leicester, University Road, Leicester LE1 7RH, United Kingdom\n- 5 Institut de Ciències del Cosmos, Universitat de Barcelona (IEECUB), Martí i Franquès 1, 08028 Barcelona, Spain\n- 6 INAF - Osservatorio astronomico di Padova, Vicolo Osservatorio 5, 35122 Padova, Italy\n- 7 SISSA - Scuola Internazionale Superiore di Studi Avanzati, via Bonomea 265, 34136 Trieste, Italy\n- 8 Leiden Observatory, Leiden University, Niels Bohrweg 2, 2333 CA Leiden, The Netherlands\n- 9 Science Support O GLYPH<14> ce, Directorate of Science, European Space Research and Technology Centre (ESA / ESTEC), Keplerlaan 1, 2201AZ, Noordwijk, The Netherlands\n- 10 Max Planck Institute for Astronomy, Königstuhl 17, 69117 Heidelberg, Germany\n- 11 Astronomisches Rechen-Institut, Zentrum für Astronomie der Universität Heidelberg, Mönchhofstr. 12-14, 69120 Heidelberg, Germany\n- 12 Department of Astronomy, University of Geneva, Chemin des Maillettes 51, 1290 Versoix, Switzerland\n- 13 Mission Operations Division, Operations Department, Directorate of Science, European Space Research and Technology Centre  \nArticle number, page 20 of 28  \n- (ESA / ESTEC), Keplerlaan 1, 2201 AZ, Noordwijk, The Netherlands\n- 14 Lohrmann Observatory, Technische Universität Dresden, Mommsenstraße 13, 01062 Dresden, Germany\n- 15 European Space Astronomy Centre (ESA / ESAC), Camino bajo del Castillo, s / n, Urbanizacion Villafranca del Castillo, Villanueva de la Cañada, 28692 Madrid, Spain\n- 16 Lund Observatory, Department of Astronomy and Theoretical Physics, Lund University, Box 43, 22100 Lund, Sweden\n- 17 Université Côte d'Azur, Observatoire de la Côte d'Azur, CNRS, Laboratoire Lagrange, Bd de l'Observatoire, CS 34229, 06304 Nice Cedex 4, France\n- 18 CNESCentre Spatial de Toulouse, 18 avenue Edouard Belin, 31401 Toulouse Cedex 9, France\n- 19 Institut d'Astronomie et d'Astrophysique, Université Libre de Bruxelles CP 226, Boulevard du Triomphe, 1050 Brussels, Belgium\n- 20 F.R.S.-FNRS, Rue d'Egmont 5, 1000 Brussels, Belgium\n- 21 INAF - Osservatorio Astrofisico di Arcetri, Largo Enrico Fermi 5, 50125 Firenze, Italy\n- 22 Telespazio Vega UK Ltd for ESA / ESAC, Camino bajo del Castillo, s / n, Urbanizacion Villafranca del Castillo, Villanueva de la Cañada, 28692 Madrid, Spain\n- 23 Laboratoire d'astrophysique de Bordeaux, Univ. Bordeaux, CNRS, B18N, allée Geo GLYPH<11> roy Saint-Hilaire, 33615 Pessac, France\n- 24 Mullard Space Science Laboratory, University College London, Holmbury St Mary, Dorking, Surrey RH5 6NT, United Kingdom\n- 25 INAF - Osservatorio Astrofisico di Torino, via Osservatorio 20, 10025 Pino Torinese (TO), Italy\n- 26 INAF - Osservatorio di Astrofisica e Scienza dello Spazio di Bologna, via Piero Gobetti 93 / 3, 40129 Bologna, Italy\n- 27 Serco Gestión de Negocios for ESA / ESAC, Camino bajo del Castillo, s / n, Urbanizacion Villafranca del Castillo, Villanueva de la Cañada, 28692 Madrid, Spain\n- 28 ALTEC S.p.a, Corso Marche, 79,10146 Torino, Italy\n- 29 Department of Astronomy, University of Geneva, Chemin d'Ecogia 16, 1290 Versoix, Switzerland\n- 30 Gaia DPAC Project O GLYPH<14> ce, ESAC, Camino bajo del Castillo, s / n, Urbanizacion Villafranca del Castillo, Villanueva de la Cañada, 28692 Madrid, Spain\n- 31 SYRTE, Observatoire de Paris, Université PSL, CNRS, Sorbonne Université, LNE, 61 avenue de l'Observatoire 75014 Paris, France\n- 32 National Observatory of Athens, I. Metaxa and Vas. Pavlou, Palaia Penteli, 15236 Athens, Greece\n- 33 IMCCE, Observatoire de Paris, Université PSL, CNRS, Sorbonne Université, Univ. Lille, 77 av. Denfert-Rochereau, 75014 Paris, France\n- 34 Royal Observatory of Belgium, Ringlaan 3, 1180 Brussels, Belgium\n- 35 Institute for Astronomy, University of Edinburgh, Royal Observatory, Blackford Hill, Edinburgh EH9 3HJ, United Kingdom\n- 36 Instituut voor Sterrenkunde, KU Leuven, Celestijnenlaan 200D, 3001 Leuven, Belgium\n- 37 Institut d'Astrophysique et de Géophysique, Université de Liège, 19c, Allée du 6 Août, B-4000 Liège, Belgium\n- 38 ATG Europe for ESA / ESAC, Camino bajo del Castillo, s / n, Urbanizacion Villafranca del Castillo, Villanueva de la Cañada, 28692 Madrid, Spain\n- 39 Área de Lenguajes y Sistemas Informáticos, Universidad Pablo de Olavide, Ctra. de Utrera, km 1. 41013, Sevilla, Spain\n- 40 ETSE Telecomunicación, Universidade de Vigo, Campus LagoasMarcosende, 36310 Vigo, Galicia, Spain\n- 41 Large Synoptic Survey Telescope, 950 N. Cherry Avenue, Tucson, AZ 85719, USA\n- 42 Observatoire Astronomique de Strasbourg, Université de Strasbourg, CNRS, UMR 7550, 11 rue de l'Université, 67000 Strasbourg, France\n- 43 Kavli Institute for Cosmology, University of Cambridge, Madingley Road, Cambride CB3 0HA, United Kingdom\n- 44 Aurora Technology for ESA / ESAC, Camino bajo del Castillo, s / n, Urbanizacion Villafranca del Castillo, Villanueva de la Cañada, 28692 Madrid, Spain\n- 45 Laboratoire Univers et Particules de Montpellier, Université Montpellier, Place Eugène Bataillon, CC72, 34095 Montpellier Cedex 05, France\n- 46 Department of Physics and Astronomy, Division of Astronomy and Space Physics, Uppsala University, Box 516, 75120 Uppsala, Sweden\n- 47 CENTRA, Universidade de Lisboa, FCUL, Campo Grande, Edif.  \nTable A.1. Membership data for the open clusters. Only the first three lines with data for members of the Praesepe cluster are presented here. For the more distant clusters, the last two columns are not included. The astrometric and photometric extra filters presented in Sect. 2.1 and used in the figures of this paper are not applied in this table. The full table will be available in electronic form at the CDS.  \nFig. A.1. Maximum radius in degrees in DR2 for the 46 open clusters as a function of parallax. The two diagonal lines represent maximum radii of 10 (bottom) and 20 (top) pc.  \n<!-- image -->", 'Appendix A.1: Nearby clusters': 'The nearby clusters were analysed with the method described and applied to the Hyades cluster in the first Gaia data release (Gaia Collaboration et al. 2017). By combining the information from the measured proper motions and parallaxes for individual cluster members, it is possible to derive a higher precision measurement for the relative parallax of these cluster members. The proper motion observed for an individual cluster member represents the local projection on the sky of the baricentric velocity of the cluster. It is therefore a GLYPH<11> ected by the angular separation on the sky of the member star from the projection of the cluster centre and the baricentric distance of the star, again relative to that of the cluster centre. Similarly, the measured parallax for the star can be significantly di GLYPH<11> erent from the mean parallax of the cluster.  \nThe primary aim of the present paper is to provide highprecision HRDs, for which these accurate relative parallaxes contribute important information by reducing the actual di GLYPH<11> erential distance modulus variations of cluster members. The effectiveness of this procedure is limited by the amplitude of the proper motion of the cluster centre and the ratio of the diameter over the distance of the cluster. The standard uncertainties in the individual parallaxes and proper motions of the cluster members in the second Gaia data release allow for this procedure to be applied for clusters within 250 pc. Table A.1 shows an example of an extract from the cluster member files produced for each of the nine clusters treated in this way.  \nFig. A.2. Surface-density profile for the Pleiades cluster, based on 1332 identified cluster members.  \n<!-- image -->  \nNine clusters within 250 pc from the Sun were analysed as nearby clusters. The analysis is iterative, and consists of two elements: 1. determinations of the space velocity vector at the cluster centre, and 2. determination of the cluster centre. A first selection is made of stars contained in a sphere with a radius of around 15 pc around the assumed centre of the cluster. A summary of the observed radii for the nearby and more distant clusters is shown in Fig. A.1. The radius can be adjusted based on the derived surface density distribution (Fig. A.2), where the outermost radius is set at the point beyond which the density of contaminating field stars starts to dominate. The selected stars are further filtered on their agreement between the observed proper motion and the predicted projection of the assumed space motion at the 3D position of the star, using the measured stellar parallax, and taking into account the uncertainties on the observed proper motion and parallax. The solution for the space motion follows Eq. A13 in Gaia Collaboration et al. (2017). Although it is in principle possible to solve also for the radial velocity using only the astrometric data, this e GLYPH<11> ectively only works for the Hyades cluster. Instead, a single equation for the observed radial velocity of the cluster was added, where the observed radial velocity is based on the weighted mean of the Gaia radial velocities of cluster members for which these data are available.  \nTo stabilise the solution, it is important to align the coordinate system with the line of sight towards the cluster centre, minimising the mixing of the contributions from the proper motions and the additional information from the radial velocity. The solution for the space motion does provide an estimate of the radial velocity component, but except for the Hyades and Coma Ber, this is largely dominated by the radial velocity value and its accuracy that is used as input to the solution. Small di GLYPH<11> erences are therefore seen between the radial velocities as presented in Table A.2 (as directly derived from the Gaia spectroscopic data) and in Table A.3 (the summary data for the nine clusters in this selection), where the astrometric information on the radial velocity is also taken into account. Figure A.3 shows an example of the level of agreement between the di GLYPH<11> erential parallax and proper motion values in the cluster IC 2602. In Fig. A.4 we also  \nFig. A.3. Comparison between the directly measured parallaxes and the parallaxes obtained by including the relative proper motion data, for the cluster IC 2602. The clear linear relation shows the good agreement between proper motion and parallax o GLYPH<11> sets from the mean cluster values.  \n<!-- image -->  \nTable A.2. Mean radial velocity values as derived from the Gaia spectroscopic data for nearby clusters.Notes. Columns: 1. Cluster name; 2: weighted-mean radial velocity in km s GLYPH<0> 1 ; 3. standard uncertainty on radial velocity; 4. unit-weight standard deviation of mean velocity solution; and 5. number of observations in mean velocity solution.  \nshow an example of the 3D distribution maps for this cluster; maps like this were prepared for all nearby clusters.  \nNext to the astrometric data, the second Gaia data release also presents radial velocity measurements for a magnitudelimited sample. The radial velocities were compared with the projection of the cluster space velocity at the position of each star for which these data are available. This is particularly relevant for stars in the Hyades cluster, where the projection e GLYPH<11> ects of the radial velocity can be of the order of several km s GLYPH<0> 1 . Table A.2 presents the results for the nine nearby clusters.  \nFigure A.5 shows the di GLYPH<11> erences (observed GLYPH<0> predicted, where the predicted value is based on the local projection of the space velocity of the cluster) in the radial velocities for 191 stars in the Hyades cluster. Only stars for which the colour index G BP GLYPH<0> G RP is greater than 0.4 mag were used. The results for all 9 nearby clusters are shown in Table A.2.', 'Appendix A.2: More distant open clusters': "For the more distant clusters, a selection was made of 37 relatively rich clusters, generally only little reddened, and as far as possible, covering a spread in ages and chemical composition (Fig. A.6). These clusters were all analysed in a combined solution of the mean parallax and proper motion from the observed astrometric data of the member stars. This is an iterative procedure, where cluster membership determination is based on the solution for the astrometric parameters of the cluster. The combined solution for the astrometric parameters of a cluster takes into account noise contributions from three sources:  \n- 1. the covariance matrix of the astrometric solution for each star;\n- 2. the internal velocity dispersion of the cluster, a GLYPH<11> ecting the dispersion of the proper motions;\n- 3. the e GLYPH<11> ect of the cluster size relative to its distance, which\n- (a) is reflected in a dispersion on the parallaxes of the cluster members;\n- (b) is reflected in a dispersion in proper motions in the direction of, and scaled by, the cluster proper motion.  \nWhen we assume that the velocity distribution is isotropic within the measurement accuracy, then the second of these noise contributions will be diagonal. The first and third may also contain significant o GLYPH<11> -diagonal elements. Given a cluster parallax of $ c , a cluster proper motion of ( GLYPH<22>GLYPH<11>; c ; GLYPH<22>GLYPH<14>; c ), and an average relative dispersion in the parallaxes of the cluster stars of GLYPH<27>$ =$ = GLYPH<27> R = R (where R is the distance to the cluster centre), the contribution to the dispersion in the proper motions of the cluster stars scales with the relative dispersion of the parallaxes and the proper motions of the cluster:  \nGLYPH<27>GLYPH<22>GLYPH<11>;  \ns  \n=  \nj  \nGLYPH<22>GLYPH<11>;  \nc  \nj GLYPH<2>  \nGLYPH<27>$ =$  \n(A.1)  \nGLYPH<27>GLYPH<22>GLYPH<14>; s = j GLYPH<22>GLYPH<14>; c j GLYPH<2> GLYPH<27>$ =$: (A.2)  \nFor most of the clusters with distances beyond 250 pc, this contribution will be small to very small relative to other contributions. Figure A.7 shows the overall relation between parallaxe and proper motion amplitudes for the selection of clusters we used.  \nThe contributions are summed into a single noise matrix, of which an upper-triangular square root is used to normalise the observation equations that describe the cluster proper motion and parallax as a function of the observed proper motions and parallaxes of the individual cluster members.  \nTable A.4 presents an overview of the astrometric solutions for 37 open clusters, with mean radial velocities when available in the Gaia data. We note that some clusters are not included in Table 2 because their colour-magnitude diagrams are too disturbed by interstellar extinction (see an illustration of the differential extinction e GLYPH<11> ect in Fig. A.8). The proper motions are compared with those presented by Loktin & Beshenov (2003) in Fig. A.9, and they agree well overall, but there is also an indication that errors on the data presented in Loktin & Beshenov (2003) are underestimated. In the same figure the comparison between the parallaxes as derived from the DR2 data and parallax values derived from photometric distances as (mostly) presented in Kharchenko et al. (2005) are shown, and again generally agree well (see also the validation with more clusters in Arenou et al. 2018). The systematic di GLYPH<11> erence of 0.029 mas, which can be observed for globular clusters (Gaia Collaboration et al. 2018c), is too small to be noticed here (Fig. A.10), but the calibration noise on the DR2 parallaxes (0.025 mas), obtained in the same study,  \nFig. A.4. Distribution of stars in IC 2602 in galactic rectangular coordinates, showing the flattening in the Z (galactic pole) direction.  \n<!-- image -->  \nTable A.3. Space velocity fitting results for nearby clusters  \nNotes. Columns: 1. Cluster identifiers; 2 to 4 U', V' and W' velocity components in the equatorial system; 5. U'V' error correlation (top) V'W' error correlation (bottom); 6. U'W' error correlation (top), applied internal velocity dispersion in km s GLYPH<0> 1 (bottom); 7. unit-weight standard deviation of solution (top), number of stars (bottom); 8. Coordinates of the convergent point; 9. parallax (mas); 10. radial velocity (km s GLYPH<0> 1 ); 11. proper motion in right ascension; and 12. proper motion in declination.  \nis significantly larger than the standard uncertainties on the mean cluster parallaxes and is therefore the main contributor to the uncertainties on the cluster parallaxes. In most cases, however, this amounts to less than 1% in error on the parallax, or 0.02 mag in distance modulus.  \nThe maximum radius for each cluster was determined from the contrast between the cluster and the field stars in the proper motion and parallax domain. In practice, this means that the density of field stars for which the combined information on the parallax and proper motion, combined with uncertainties and error correlations, leaves a significant possibility for a field star to be a cluster member. When the surface density of these field stars becomes similar to the surface density of the cluster stars, we  \nhave reached the maximum radius for the cluster in this particular data set and parameter space. It is well possible, however, that for a catalogue with higher accuracies on the astrometric parameters for the fainter stars in particular, this limit will be found still farther away from the cluster centre. Radial velocities for the clusters, mostly as given in Kharchenko et al. (2005) or Conrad et al. (2014), were compared with the mean radial velocities as derived from the Gaia DR2 data. A limited spectral range was used, for which there is clear consistency of the radial velocity measurements. The summary of the results is shown in Fig. A.9 and generally agrees well (see also the validation with more clusters in Arenou et al. 2018). The largest discrepancies  \nFig. A.5. Di GLYPH<11> erences between the predicted and observed radial velocities in the Hyades cluster as a function of G magnitude.  \n<!-- image -->  \nare found for NGC 2516 (RAVE measurements in Conrad et al. 2014) and Trumpler 2 (Kharchenko et al. 2005).", 'Gaia Collaboration et al.: Gaia Data Release 2: Observational Hertzsprung-Russell diagrams': 'Fig. A.6. Distributions over age and composition for stars in the 32 open clusters selected for the composite HRD, including the nearby clusters.  \n<!-- image -->  \nFig. A.7. Comparison between the parallaxes and proper motions for the 37 open clusters. The upper and lower diagonal lines represent tangential velocities of 40 and 5 km s GLYPH<0> 1 , respectively.  \n<!-- image -->  \nFig. A.8. Colour-magnitude diagram of NGC 2477, with each star colour-coded by the value of integrated extinction in the catalogue of Schlegel et al. (1998).  \n<!-- image -->', 'A & A proofs: manuscript no. DR2HRD': 'Fig. A.9. Comparisons with values quoted in literature (see text) for (top) proper motions in right ascension, proper motions in declination, (bottom) parallaxes, and radial velocities for 37 open clusters with distances beyond 250 pc.  \n<!-- image -->  \nFig. A.10. Standard uncertainties on the mean cluster parallax determinations. The curves represent the 100 and 500 GLYPH<27> significance levels when only the standard uncertainties are considered.  \n<!-- image -->  \nTable A.4. Overview of the results for open clusters with distances beyond 250 pc  \nTable A.4 - continued from previous page', 'Appendix B: Gaia archive query': 'The Gaia archive 6 query corresponding to the filters described in Sect. 2.1 is the following (selecting here the first five stars):  \nSELECT TOP 5 phot\\_g\\_mean\\_mag+5*log10(parallax)-10 AS mg, bp\\_rp FROM gaiadr2.gaia\\_source  \nWHERE parallax\\_over\\_error > 10  \nAND phot\\_g\\_mean\\_flux\\_over\\_error>50  \nAND phot\\_rp\\_mean\\_flux\\_over\\_error>20  \nAND phot\\_bp\\_mean\\_flux\\_over\\_error>20  \nAND phot\\_bp\\_rp\\_excess\\_factor < 1.3+0.06*power(phot\\_bp\\_mean\\_mag-phot\\_rp\\_mean\\_mag,2)  \nAND phot\\_bp\\_rp\\_excess\\_factor > 1.0+0.015*power(phot\\_bp\\_mean\\_mag-phot\\_rp\\_mean\\_mag,2)  \nAND visibility\\_periods\\_used>8  \nAND astrometric\\_chi2\\_al/(astrometric\\_n\\_good\\_obs\\_al-5)<1.44*greatest(1,exp(-0.4*(phot\\_g\\_mean\\_mag-19.5)))'}