We present an overview of the James Webb Space Telescope JWST Advanced Deep Extragalactic Survey JADES an ambitious program of infrared imaging and spectroscopy in the GOODSS and GOODSN deep fields designed to study galaxy evolution from high redshift to cosmic noon. JADES uses about 770 hours of Cycle 1 guaranteed time largely from the NearInfrared Camera NIRCam and NearInfrared Spectrograph NIRSpec instrument teams. In GOODSS in and around the Hubble Ultra Deep Field and Chandra Deep Field South JADES produces a deep imaging region of 45 arcmin2 with an average of 130 hrs of exposure time spread over 9 NIRCam filters. This is extended at medium depth in GOODSS and GOODSN with NIRCam imaging of 175 arcmin2 with an average exposure time of 20 hrs spread over 810 filters. In both fields we conduct extensive NIRSpec multiobject spectroscopy including 2 deep pointings of 55 hrs exposure time 14 medium pointings of 12 hrs and 15 shallower pointings of 4 hrs targeting over 5000 HST and JWSTdetected faint sources with 5 low medium and highresolution dispersers covering 0.65.3 microns. Finally JADES extends redward via coordinated parallels with the JWST MidInfrared Instrument MIRI featuring 9 arcmin2 with 43 hours of exposure at 7.7 microns and twice that area with 26.5 hours of exposure at 12.8 microns For nearly 30 years the GOODSS and GOODSN fields have been developed as the premier deep fields on the sky JADES is now providing a compelling start on the JWST legacy in these fields.
['Astrophysics - Astrophysics of Galaxies']
Overview of the JWST Advanced Deep Extragalactic Survey JADES
{'Overview of the JWST Advanced Deep Extragalactic Survey (JADES)': "Daniel J. Eisenstein, 1 Chris Willott, 2 Stacey Alberts, 3 Santiago Arribas , 4 Nina Bonaventura, 5, 6, 3 Andrew J. Bunker, 7 Alex J. Cameron, 7 Stefano Carniani, 8 Stephane Charlot, 9 Emma Curtis-Lake, 10 Francesco D'Eugenio, 11, 12 Pierre Ferruit, 13 Giovanna Giardino, 14 Kevin Hainline, 3 Ryan Hausen, 15 Peter Jakobsen, 5, 6 Benjamin D. Johnson, 1 Roberto Maiolino, 11, 12, 16 Marcia Rieke, 3 George Rieke, 17 Hans-Walter Rix, 18 Brant Robertson, 19 Daniel P. Stark, 3 Sandro Tacchella, 11, 12 Christina C. Williams, 20 Christopher N. A. Willmer, 3 William M. Baker, 11, 12 Stefi Baum, 21 Rachana Bhatawdekar, 22, 23 Kristan Boyett, 24, 25 Zuyi Chen, 3 Jacopo Chevallard, 7 Chiara Circosta, 26 Mirko Curti, 27, 11, 12 A. Lola Danhaive, 11 Christa DeCoursey, 3 Ryan Endsley, 28 Anna de Graaff, 18 Alan Dressler, 29 Eiichi Egami, 3 Jakob M. Helton, 3 Raphael E. Hviding, 3 Zhiyuan Ji, 3 Gareth C. Jones, 7 Nimisha Kumari, 30 Nora Lutzgendorf, 31 Isaac Laseter, 32 Tobias J. Looser, 11 Jianwei Lyu, 3 Michael V. Maseda, 32 Erica Nelson, 33 Eleonora Parlanti, 8 Michele Perna, 4 D'avid Pusk'as, 11, 12 Tim Rawle, 34 Bruno Rodr'ıguez Del Pino, 4 Lester Sandles, 11, 12 Aayush Saxena, 7, 16 Jan Scholtz, 11, 12 Katherine Sharpe, 1 Irene Shivaei, 3 Maddie S. Silcock, 35 Charlotte Simmonds, 11, 12 Maya Skarbinski, 1 Renske Smit, 36 Meredith Stone, 3 Katherine A. Suess, 19, 37 Fengwu Sun, 3 Mengtao Tang, 3 Michael W. Topping, 3 Hannah Ubler, 11, 12 Natalia C. Villanueva, 1 Imaan E. B. Wallace, 7 Lily Whitler, 3 Joris Witstok, 11, 12 and Charity Woodrum 3  \n1 Center for Astrophysics | Harvard & Smithsonian, 60 Garden St., Cambridge MA 02138 USA 2 NRC Herzberg, 5071 West Saanich Rd, Victoria, BC V9E 2E7, Canada  \n3 Steward Observatory, University of Arizona, 933 N. Cherry Avenue, Tucson AZ 85721 USA  \nCentro de Astrobiolog'ıa (CAB), CSIC-INTA, Cra. de Ajalvir Km. 4, 28850- Torrej'on de Ardoz, Madrid, Spain  \n5 Cosmic Dawn Center (DAWN), Copenhagen, Denmark  \n- 6 Niels Bohr Institute, University of Copenhagen, Jagtvej 128, DK-2200, Copenhagen, Denmark  \nDepartment of Physics, University of Oxford, Denys Wilkinson Building, Keble Road, Oxford OX1 3RH, UK  \n7  \n8 Scuola Normale Superiore, Piazza dei Cavalieri 7, I-56126 Pisa, Italy  \nSorbonne Universit'e, CNRS, UMR 7095, Institut d'Astrophysique de Paris, 98 bis bd Arago, 75014 Paris, France  \n9  \nCentre for Astrophysics Research, Department of Physics, Astronomy and Mathematics, University of Hertfordshire, Hatfield AL10  \n9AB, UK  \n11 Kavli Institute for Cosmology, University of Cambridge, Madingley Road, Cambridge CB3 0HA, UK  \n12 Cavendish Laboratory, University of Cambridge, 19 JJ Thomson Avenue, Cambridge CB3 0HE, UK  \n- 13 European Space Agency, European Space Astronomy Centre, Camino Bajo del Castillo s/n, 28692 Villafranca del Castillo, Madrid, Spain  \n14 ATG Europe for the European Space Agency, ESTEC, Noordwijk, The Netherlands  \n15  \nDepartment of Physics and Astronomy, The Johns Hopkins University, 3400 N. Charles St., Baltimore, MD 21218  \n16  \nDepartment of Physics and Astronomy, University College London, Gower Street, London WC1E 6BT, UK  \n17 Steward Observatory and Dept of Planetary Sciences, University of Arizona 933 N. Cherry Avenue Tucson AZ 85721 USA 18 Max-Planck-Institut fur Astronomie, Konigstuhl 17, D-69117, Heidelberg, Germany  \nDepartment of Astronomy and Astrophysics University of California, Santa Cruz, 1156 High Street, Santa Cruz CA 96054 USA  \n20  \nNSF's National Optical-Infrared Astronomy Research Laboratory, 950 North Cherry Avenue, Tucson, AZ 85719 USA  \n21  \nDepartment of Physics and Astronomy, University of Manitoba, Winnipeg, MB R3T 2N2, Canada  \n- 22 European Space Agency (ESA), European Space Astronomy Centre (ESAC), Camino Bajo del Castillo s/n, 28692 Villanueva de la Ca˜nada, Madrid, Spain  \n23 European Space Agency, ESA/ESTEC, Keplerlaan 1, 2201 AZ Noordwijk, NL  \n24 School of Physics, University of Melbourne, Parkville 3010, VIC, Australia  \n25 ARC Centre of Excellence for All Sky Astrophysics in 3 Dimensions (ASTRO 3D), Australia  \n26 European Space Agency (ESA), European Space Astronomy Centre (ESAC), Camino Bajo del Castillo s/n, 28692 Villanueva de la Ca˜nada, Madrid, Spain  \n27 European Southern Observatory, Karl-Schwarzschild-Strasse 2, 85748 Garching, Germany  \n28 Department of Astronomy, University of Texas, Austin, TX 78712 USA  \n29 The Observatories of the Carnegie Institution for Science, 813 Santa Barbara St., Pasadena, CA 91101  \nAURA for European Space Agency, Space Telescope Science Institute, 3700 San Martin Drive. Baltimore, MD, 21210  \n31 European Space Agency, Space Telescope Science Institute, Baltimore, Maryland, US  \n- 32 Department of Astronomy, University of Wisconsin-Madison, 475 N. Charter St., Madison, WI 53706 USA  \n33 Department for Astrophysical and Planetary Science, University of Colorado, Boulder, CO 80309 USA  \n10  \n19  \n30  \n4  \n- 34 European Space Agency (ESA), European Space Astronomy Centre (ESAC), Camino Bajo del Castillo s/n, 28692 Villafranca del Castillo, Madrid, Spain\n- 35 Centre for Astrophysics Research, Department of Physics, Astronomy and Mathematics, University of Hertfordshire, Hatfield AL10 9AB, UK  \n- 37  \nKavli Institute for Particle Astrophysics and Cosmology and Department of Physics, Stanford University, Stanford, CA 94305 USA", 'ABSTRACT': 'We present an overview of the James Webb Space Telescope (JWST) Advanced Deep Extragalactic Survey (JADES), an ambitious program of infrared imaging and spectroscopy in the GOODS-S and GOODS-N deep fields, designed to study galaxy evolution from high redshift to cosmic noon. JADES uses about 770 hours of Cycle 1 guaranteed time largely from the Near-Infrared Camera (NIRCam) and Near-Infrared Spectrograph (NIRSpec) instrument teams. In GOODS-S, in and around the Hubble Ultra Deep Field and Chandra Deep Field South, JADES produces a deep imaging region of ∼ 45 arcmin 2 with an average of 130 hrs of exposure time spread over 9 NIRCam filters. This is extended at medium depth in GOODS-S and GOODS-N with NIRCam imaging of ∼ 175 arcmin 2 with an average exposure time of 20 hrs spread over 8-10 filters. In both fields, we conduct extensive NIRSpec multi-object spectroscopy, including 2 deep pointings of 55 hrs exposure time, 14 medium pointings of ∼ 12 hrs, and 15 shallower pointings of ∼ 4 hrs, targeting over 5000 HST and JWST-detected faint sources with 5 low, medium, and high-resolution dispersers covering 0.6-5.3 µ m. Finally, JADES extends redward via coordinated parallels with the JWST Mid-Infrared Instrument (MIRI), featuring ∼ 9 arcmin 2 with 43 hours of exposure at 7.7 µ m and twice that area with 2-6.5 hours of exposure at 12.8 µ m. For nearly 30 years, the GOODS-S and GOODS-N fields have been developed as the premier deep fields on the sky; JADES is now providing a compelling start on the JWST legacy in these fields.  \nKeywords: early universe - galaxies: evolution - galaxies: high-redshift', '1. INTRODUCTION': 'The James Webb Space Telescope (JWST) is revolutionizing the study of galaxy evolution by giving us unprecedented access to deep, sharp, and nuanced infrared imaging and spectroscopy. Designed to push the redshift frontier and bring the early growth of galaxies into clear focus, the telescope is performing at, or even better than, expectations (Rigby et al. 2023). JWST takes marvelous advantage of the faintness of the zodiacal foregrounds at 2-10 µ m and state-of-the-art infrared detectors to unlock the rest-frame optical at redshifts z > 4, combining large collecting area and diffractionlimited imaging. Exploiting this telescope are ambitious multi-purpose instruments (Gardner et al. 2023) that give us dozens of selectable filters, exquisite slitless, integral-field or multi-object spectroscopy (MOS) and multiple coronagraphs.  \nUnraveling the physics of high-redshift galaxies will require the combination of many different kinds of observations. While there are important observations of rare, extreme phenomena, many goals in studying the general population are well served by deep-sky general surveys, as each image contains an unbiased superposition of all epochs of galaxy evolution. Of course, low  \nredshifts are best served by wider, shallower data, but great depth is required to identify and characterize highredshift galaxies.  \nThe Hubble Deep Field was a dramatic advance in this regard. It boldly unveiled the high-redshift Universe in a single multi-color blank-field image (Williams et al. 1996; Ferguson et al. 2000). Since then, such surveys have been vigorously pursued, utilizing virtually every high-sensitivity narrow-field telescope. This field and that of the Chandra Deep Field South (Giacconi et al. 2002) were broadened out to form the Great Observatories Origins Deep Survey (GOODS Giavalisco et al. 2004), utilizing the new opportunities of the HST Advanced Camera for Surveys (ACS) and Spitzer infrared telescope to partner with deep Chandra X-ray imaging (Luo et al. 2008). Soon after, the Hubble Ultra Deep Field (HUDF) was sited in the heart of GOODS-S (Beckwith et al. 2006). It has since become the standard bearer of deep fields, pushing into the epoch of reionization by leveraging exceptional optical and infrared Hubble Space Telescope imaging, e.g., the UDF09 (Bouwens et al. 2010) and UDF12 programs (Ellis et al. 2013), with tremendous investments across the electromagnetic spectrum from many other imaging and spectroscopic facilities.  \nJWST is designed to pursue such surveys; the telescope provides exquisite image quality and depth, but it moves slowly enough that deep fields are operationally favored. Every pointing of practical depth reveals tens of thousands of galaxies, including many at z > 6 where the intergalactic medium (IGM) completely blocks optical light. Further, JWST provides a novel opportunity to conduct detailed faint multi-object spectroscopy beyond 2 µ m, where critical rest-optical lines are shifted at high redshift. Numerous projects have already been approved to start this work, which we expect will be one of the enduring legacies of the telescope (Robertson 2022).  \nHere, we describe the JWST Advanced Deep Extragalactic Survey (JADES), a collaboration of the NearInfrared Camera (NIRCam) and Near-Infrared Spectrograph (NIRSpec) Instrument Development Teams. The plans to conduct deep-field imaging and spectroscopy were featured in the original instrument proposals, with the intent to devote a substantial amount of guaranteed time to this topic. In 2015, the teams joined to form a larger and more coordinated project, now called JADES, to focus on the exceptional opportunities of JWST onto the GOODS-S and GOODS-N fields. In doing so, it became possible to carry out a project with fewer compromises: deep and wide enough to support the geometry of the instrument footprints and utilize efficient parallel observations, with robust well-dithered imaging and spectroscopy in many filters and several dispersion modes.  \nAt about 770 hours of observing time plus coordinated parallels, JADES is the largest program operating in JWST Cycle 1 and is a very large investment of instrument team guaranteed time. The time was roughly evenly split between the NIRCam and NIRSpec GTO budgets, with a supplementary contribution from the MIRI-US team. By applying the experience of the teams that designed and commissioned the instruments, we aim to provide an exquisite legacy data set for these deep fields.  \nIn this overview paper, we describe the scientific motivations and resulting survey design of JADES, providing an overview of how we developed our strategy to maximize performance in both imaging and spectroscopy in the targeted fields. Subsequent papers will describe the imaging data reduction and spectroscopic target selection, as well as the first data release centered on the HUDF (Bunker et al. 2023a; Rieke et al. 2023a).', '2.1. Motivations': "The sensitivity and instrumentation of JWST provide a singular opportunity to study the evolution of galaxies from the earliest epochs ≲ 300 Myr after the Big Bang, through the Epoch of Reionization during the first billion years of cosmic history, and on to Cosmic High Noon where the stellar mass and black hole mass densities of the universe were well-established. Unlike all other previous studies of high-redshift (i.e., z > 3) galaxy populations where only rest-frame ultraviolet spectral properties have been accessible, JWST enables for the first time, via its instruments NIRCam (Rieke et al. 2023b), NIRSpec (Jakobsen et al. 2022; Ferruit et al. 2022), NIRISS (Doyon et al. 2023) and MIRI (Wright et al. 2023), photometry and spectroscopy extending from blueward of the Lyman break to redward of the Balmer/4000 ˚ A break region. In this section we describe how our view of the Universe before the launch of JWST shaped the design of JADES and how early JWST observations support our decisions.  \nAt the earliest times in cosmic history (e.g., < 500 Myr), the first abundant population of star-forming galaxies developed. Galaxy formation is a self-regulated process, and the ways in which early galaxies respond to the rapid accretion and cooling of gas greatly affects their bulk properties like luminosity and size. Through perseverance in HST imaging surveys, a handful of galaxies at z ∼ 10 -11 were discovered (Coe et al. 2013; Oesch et al. 2016), enabling a first glance at the primitive galaxy formation process.  \nJWST has the sensitivity and the required array of infrared filters to identify galaxies selected in rest-frame ultraviolet (UV) at z > 12, farther than any tentative HST detections. Hundreds of hours of NIRCam multifilter imaging will yield sufficient source counts to measure the UV luminosity function evolution out to z ∼ 10 and beyond. JADES includes medium-band filters in the NIRCam long wave channel that can help identify and distinguish high-z candidates from dusty, strong emission line sources at lower redshifts e.g. Zavala et al. 2023; Fujimoto et al. 2022; Arrabal Haro et al. 2023). The most distant galaxies will inevitably be very faint and these NIRCam discoveries will require very long integrations with the NIRSpec low-resolution prism for redshift confirmation, especially at redshifts z > 10 where the strongest optical lines are redshifted beyond the NIRSpec range (Robertson et al. 2023a; Curtis-Lake et al. 2023).  \nExtending redder than Hubble and reaching many magnitudes deeper than ever achieved with Spitzer,  \nJWST greatly improves our census of the early Universe, tracing the growth of galaxies at this early epoch. Combining the SFR and stellar masses derived from spectralenergy distributions (SED) spanning the rest-UV and optical, NIRCam and MIRI imaging allow estimates of the stellar birthrate of galaxies out to z ∼ 10 and can deliver our earliest constraints on the efficiency of galaxy formation (e.g. Labbe et al. 2022; Endsley et al. 2022; Tacchella et al. 2023). Stellar masses measured at z ∼ 10 allow us to infer a bulk star formation rate to z ≳ 12 (given the minimum ∼ 100 Myr timescale typically required for the development of strong restframe optical breaks; Whitler et al. 2023a; Dressler et al. 2023). Rest-UV emission lines, such as [CIV](1549 ˚ A), HeII(1640 ˚ A), OIII](1663 ˚ A) and CIII](1909 ˚ A), are accessible to NIRSpec to the highest redshifts to measure the physical properties of nebular gas and infer their sources of ionization (Bunker et al. 2023b; Hsiao et al. 2023; Tang et al. 2023). Our window into early galaxies with JWST becomes dramatically richer at just slightly later times ( z ∼ 8 -9) where NIRSpec can measure the rest-frame optical strong lines (e.g., [OII], [NeIII], H β , [OIII], and even H α at z < 7) and both the Lyman and Balmer/4000 ˚ A breaks (Cameron et al. 2023; Sanders et al. 2023; Reddy et al. 2023a; Tang et al. 2023). NIRCam imaging in medium and wide filters can measure these breaks and strong lines, and given enough filters can differentiate between the two (Endsley et al. 2022; Williams et al. 2023; Withers et al. 2023).  \nFrom previous surveys of the cosmic microwave background, quasars and galaxies, we know that these epochs experience the first important contributions of galaxies to the cosmic reionization process (Planck Collaboration et al. 2020; Fan et al. 2022; Robertson et al. 2022). Here, JWSTsimultaneously constrains the evolving rest-frame UV galaxy luminosity density and provides information on the hardness of the ionizing continuum and the escape fraction of Lyman continuum photons (Simmonds et al. 2023; Mascia et al. 2023; Endsley et al. 2022; Donnan et al. 2023; Bouwens et al. 2023). These measurements will result in a more accurate 'balancing of the budget' for cosmic reionization, where we weigh the cosmic ionization rate against the recombination of the intergalactic hydrogen in determining the evolving bulk IGM neutrality. Mapping with spectra the 'Lymanα disappearance', measuring the evolving fraction of UVdropout selected galaxies that show (or not) Lymanα emission, can track how the increased IGM neutrality at earlier times extinguishes observed line emission in progressively more of the sources (Stark et al. 2010; Fontana et al. 2010; Pentericci et al. 2014; Mason et al. 2018; Ouchi et al. 2020; Jones et al. 2023). Correlating the  \ntransmission of Lymanα with photometric or spectroscopic measurements of environment can provide further insight into the topology of ionized bubbles during this epoch (Tang et al. 2023; Witstok et al. 2023a; Endsley et al. 2023; Jung et al. 2023; Lu et al. 2023; Whitler et al. 2023b).  \nRest-frame optical line spectroscopy at z ∼ 6-9 dramatically extends our knowledge of the chemical enrichment of galaxies and reveals the physical conditions in the warm interstellar medium of early star-forming galaxies. Line excitation diagrams provide insights into the ionization state of the star-forming ISM in these systems; NIRSpec allows to apply these diagnostics in an entirely new redshift regime (e.g., Cameron et al. 2023; Sanders et al. 2023; Reddy et al. 2023a), connecting them with the properties of the exciting stellar populations. Via the combined measures of star formation rate in the rest-UV, stellar mass in the rest-optical, and metallicity from nebular lines we can explore whether the fundamental metallicity and mass-metallicity relations are already in place after only ∼ 1 billion years of cosmic history (Curti et al. 2023; Nakajima et al. 2023).  \nJWST is revealing the emergence of morphological structures at z > 2 through superb infrared imaging (Robertson et al. 2023b; Kartaltepe et al. 2023; Ferreira et al. 2022a,b; Jacobs et al. 2023; Huertas-Company et al. 2023; Magnelli et al. 2023; Baker et al. 2023). JWST can resolve these galaxies from the rest-UV to the rest-optical, providing spatially-resolved measures of color gradients and stellar population properties, vastly outperforming HST (e.g. Figure 1). We can distinguish the clumpy UV-bright morphology from the rest-optical light on a galaxy-by-galaxy basis, and thereby constrain the role of large-scale gravitational instability in setting galaxy structures at z ∼ 2 -3. NIRSpec spectroscopy with the medium- or high-resolution gratings will connect these morphological measures to the dynamics of the galaxies, and through measuring outflows further constrain the role of feedback in shaping these maturing galaxies.  \nHST has found compact red galaxies at z = 2, but JWST's angular resolution, sensitivity and redder bands are proving revolutionary to explore old stellar populations and their morphology at z > 3 (Carnall et al. 2023; Ji et al. 2023, Suess et al. in prep). With NIRCam imaging, including medium filters, Balmer and D 4000 breaks can be cleanly picked out. Spectroscopy at R = 100 with the NIRSpec prism provides precise redshifts and break strengths, but higher resolution spectroscopy enables more detailed constraints on SFH and abundances at z > 3 -4, an era that prior to JWST was prohibitive or impossible to study, but critical to our understand-  \n<!-- image -->  \nFigure 1. A grand design spiral at redshift 2 revealed in JADES imaging in GOODS-S. ( left ) The JWST NIRCam image combining F090W, F200W, and F444W filters in the Deep Prime region of program 1180. ( right ) The HST ACS F850LP image, where this star-forming galaxy is all but invisible.  \n<!-- image -->  \ning of why and how galaxies stop forming stars (Carnall et al. 2023; Nanayakkara et al. 2022). The importance of burstiness in the evolution of galaxies is now becoming clear with several examples of z > 5 galaxies undergoing 'mini-quenching' episodes (Looser et al. 2023b; Strait et al. 2023). Additional evidence for burstiness is now becoming apparent in statistical samples of NIRCam SEDs (Endsley et al. 2023; Dressler et al. 2023).  \nDust attenuation and reddening in the rest-frame UV and optical spectra and SEDs of galaxies strongly affect the inferred physical quantities, so it is important to study the underlying dust properties. JWST opens a new window to identify and characterize obscured populations that were completely missed by even the deepest Spitzer and HST surveys. ALMA has revealed that such hidden galaxies likely contribute significantly to the cosmic star formation rate density at 3 < z < 8 (e.g. Williams et al. 2019; Fudamoto et al. 2021; Algera et al. 2023), and early JWST data is supporting this finding (Barrufet et al. 2023). The stellar SEDs and morphologies of dust obscured galaxies at z > 3 can now be characterized in detail for the first time (G'omezGuijarro et al. 2023; Nelson et al. 2022; P'erez-Gonz'alez et al. 2023). JWST is indicating that massive galaxies have non-negligible dust content at high-redshift, pointing to efficient production mechanisms even out to z ∼ 8 (McKinney et al. 2023; Akins et al. 2023). The combina-  \nof multi-band NIRCam photometry and multi-line NIRSpec spectroscopy offers the opportunity to tackle these issues through SED-fitting and through line diagnostics such as the Paschen and Balmer decrements and 2200 ˚ A bump (e.g., Witstok et al. 2023b; Shapley et al. 2023; Reddy et al. 2023b; Sandles et al. 2023).  \nThe intimate connection between the growth of galaxies and their supermassive black holes can be traced back to the earliest epochs with deep JWST imaging and spectroscopy. Active galactic nuclei (AGN) are being discovered via their pointlike morphology (particularly in the redder bands, e.g. Labbe et al. 2022; Furtak et al. 2022), broad wings of Balmer emission lines (e.g. Figure 2) and highly-ionized narrow lines (Kocevski et al. 2023; Harikane et al. 2023; Maiolino et al. 2023; Scholtz et al. 2023; Larson et al. 2023). In most cases these AGN are not detectable even by very deep Chandra or JVLA imaging, putting JWST at the forefront of the quest for the earliest supermassive black holes. With JADES we obtain deep NIRCam and MIRI imaging plus deep NIRSpec spectrocopy to discover these previously hidden AGN and investigate the evolving relationship between supermassive black holes and their host galaxies.  \nThroughout these epochs, the development of the galaxy populations remains tightly connected with the structure formation process in our ΛCDM cosmology  \n<!-- image -->  \n<!-- image -->  \nFigure 2. Example spectra for the z = 4 . 65 galaxy JADES-GS+53.13284-27.80185 (ID=00008083) from the JADES Deep/HST observations. The upper panel shows the low-resolution prism spectrum (total integration time 10 5 seconds). This spectrum reveals many emission lines and high S/N continuum. However, some emission lines are blended or have low equivalent width, motivating the acquisition of grating spectra for most of the galaxies with prism spectra in JADES. The rms uncertainty is shown in the gray shaded spectrum at the bottom of the plot. The lower-left panel shows the JADES Deep imaging data of this galaxy with an overlay of the position of the microshutters during the three nods. The green color of the galaxy indicates [OIII] and H β line emission dominating in the F277W filter. For the angular scale, we remind that the individual microshutters are 0.2 '' by 0.46 '' . The lower-right panel shows the H α spectra obtained with the medium G395M and high G395H resolution gratings. Both these spectra reveal a broad ( σ = 800kms -1 ) emission line from a low-luminosity AGN broad line region (Maiolino et al., in prep.). However, the G395H grating is required to spectrally resolve the narrow line emission from the galaxy itself (observed σ = 65kms -1 , compared to instrumental line spread function σ = 30kms -1 ; de Graaff et al. (in prep.)).  \n<!-- image -->  \nuniverse. The rates of star formation, stellar population aging, merging, and dynamical and morphological transformation are ultimately manifestations of the growth of dark matter halos. JWST is providing a new context for understanding the connection between galaxy and dark matter structure formation by aiming to discover the earliest galaxies that form in rare peaks of the density field, establishing both the SFR-halo mass and stellar mass-halo mass relations out to z ∼ 10, watching the emergence of dynamically cold galactic structures, and by observing the assembly of the first massive galaxies that form primarily through dissipationless  \nmergers. The new spectroscopic capabilities allow us to identify physically-associated galaxies in the early universe rather than just projected overdensities (Kashino et al. 2022; Helton et al. 2023; Morishita et al. 2023) and enable us to distinguish between how central and satellite galaxies evolve further back in time than has previously been possible. The combination of area and depth allow for clustering analyses down to very faint magnitudes on spectroscopically-informed samples with well-constrained redshift selection functions. This combination will also address critical gaps in our knowledge of environmentally-driven galaxy evolution. The key  \nepochs of stellar growth and the subsequent quenching in groups and (proto-)clusters likely often occur in a dust-obscured phase (see Alberts & Noble 2022, for a review), necessitating rest-frame near- and mid-infrared observations that are robust against extinction and directly probe obscured activity. In all, JWST allows a more physically complete view of galaxy formation that builds directly from the underlying ΛCDM framework.  \nWe stress that most if not all of these science drivers require a substantial survey volume, not just depth. We aim to slice the galaxy samples in a variety of parameters for inter-comparison. Going deep may (slowly) reveal the less luminous galaxies, but we need to gather sufficient samples of the L ∗ and brighter ones as well. Rare phases, such as AGN and extreme starbursts, can be important for the evolutionary story. Large-scale structure is prominent even at high redshifts because galaxies are extremely biased tracers of the underlying density field. On the scale of one NIRCam or NIRSpec MOS pointing, this can cause the fluctuations in the number of objects, particularly those from the most massive halos, to vary substantially (Steinhardt et al. 2021). Larger surveys allow one to measure more accurate luminosity functions, but also to potentially measure the clustering amplitude itself, which bears on the mass of the host halos as well as on possible Mpc-scale environmental drivers in galaxy evolution.  \nThe above science cases can all be addressed efficiently through a deep extragalactic survey. Typical high-redshift galaxies are common on the sky but very faint. The scientific exploitation of images is necessarily broad simply because of projection of the line of sight, but this is also true for efficient use of multi-object spectroscopy. Since the advent of the Hubble Deep Field, the community has been focusing its resources onto a small number of deep fields, so that the synergies between different types of data can be best exploited. Our survey follows this same logic.", '2.2. Opportunities of a Combined Imaging & Spectroscopy Program': 'As the combination of imaging and spectroscopy is a key driver of our coordinated parallel strategy, we want to stress that JWST imaging and spectroscopy reinforce each other in numerous critical ways.  \nFirst, one has the obvious aspect that imaging and spectroscopy constrain different physical properties of the galaxies, which we seek to combine.  \nSecond, having accurate redshifts is important for the interpretation of imaging in terms of luminosities, restframe colors, and proper sizes. For example, the conversion of SEDs to stellar masses and star formation  \nhistories can easily be degenerate with redshift uncertainty. Spectroscopy is the gold standard for redshifts, and JWST has sufficient sensitivity and multiplex to provide spectroscopic redshifts for thousands of galaxies all the way to z > 10. Moreover, our program is providing large training samples for the photometric redshift methods that will supply redshifts for the rest of the imaging sample.  \nThird, there are technical synergies. NIRCam broadband filters in the rest-frame optical can have substantial contribution from very strong emission lines, as illustrated by the recent JWST results (Cameron et al. 2023; Matthee et al. 2022). NIRSpec spectroscopy is providing the location and fluxes of these lines, enabling us to subtract them to accurately measure the continuum SED. This is important for the estimation of stellar population age distributions. We will do this subtraction directly in thousands of objects, but also measure the trends and variations needed to model the purely photometric samples.  \nNIRCam, in turn, is important for NIRSpec MOS to understand its slit losses, background subtraction, and to aid in the interpretation of emission line kinematics. Unlike ground-based slit masks, the NIRSpec micro-shutter array (MSA) provides a fixed grid of slits. Galaxies will fall at various registrations relative to those slits and with a range of sizes. Achieving accurate line flux calibration requires the imaging to provide a model of this. Further, NIRSpec MOS background subtraction requires the subtraction of neighboring shutters; only NIRCam can provide a deep 2-5 µ m probe of contaminating objects in these shutters. Eventually, we expect that the sharp NIRCam images will provide morphological templates for more ambitious extraction of undersampled NIRSpec spectra, going beyond just summing along the spatial direction of a slit.  \nFourth, JWST imaging can allow more efficient target selection for NIRSpec MOS spectroscopy of rare populations. While HST can provide Lyman-dropout selection for UV bright targets, the longer wavelength coverage of JWST yields much improved photometric redshifts for redder objects. NIRCam medium-band imaging can isolate objects with strong rest-frame optical line emission that can then be targeted for line profile studies with the NIRSpec gratings.  \nFinally, there are more subtle astrophysical synergies. For strong line emitters, the high S/N and the excellent angular resolution of NIRCam provides, via the comparison of different filters, measurements of size and morphology of the line emission relative to the stellar light. NIRCam imaging can reveal color gradients to be correlated with spectral properties. For spatially extended  \ngalaxies, one can even connect these to resolved spectral variations along the slits.  \nWe note that while the combination of imaging and spectroscopy is critically important, it is not the case that one requires spectroscopy for every imaging object. Rather one intends to use the spectroscopy to build models of the trends, so that one can perform statistical work on the non-spectroscopic sample.', '3.1. Field Selection': 'JADES seeks to combine deep multi-band imaging and spectroscopy in pursuit of the science goals described in § 2. It is designed to bring NIRCam and NIRSpec MOS together on a common region of the sky, while covering substantial areas in two different fields in order to increase the statistical reach for rare objects and sample large-scale structure.  \nWe observe two fields in JADES, to avoid concern that the large-scale structure of highly biased tracers and the radiation transport of reionization could make any one field peculiar and limit confidence in any unusual results. Further, we wanted to spread the observing around the year to ease the constraints on scheduling such a large program. Of course, even more fields would better mitigate the concerns about cosmic variance, but this would limit the depth and area of each.  \nThe choice of location was driven by the availability of deep pan-chromatic imaging and spectroscopy, as the study of galaxy evolution draws on a wide range of such input. This led us clearly to the GOODS-South and GOODS-North fields, which have received huge investments of telescope time over the past 25 years from essentially every facility that bears on the high-redshift Universe.  \nGOODS-South, home of the Chandra Deep Field South and the Hubble Ultra Deep Field as well as very deep ALMA (Walter et al. 2016; Dunlop et al. 2017; Franco et al. 2018; Hatsukade et al. 2018) and JVLA data (Rujopakarn et al. 2016; Alberts et al. 2020), is the preeminent deep field on the sky. We chose this as the primary field for JADES and focused the majority of the observing time there. GOODS-North, home of the Hubble Deep Field and exceptionally deep Chandra data, was chosen as the second field.  \nBy placing JADES in the legacy GOODS fields, we seek to augment the rich HST community data products with a comprehensive set of JWST imaging and spectroscopy. The GOODS (Giavalisco et al. 2004), CANDELS (Grogin et al. 2011; Koekemoer et al. 2011), and UDF (Beckwith et al. 2006; Ellis et al. 2013; Illingworth et al. 2013) data have been reduced and released as com-  \nponents of the Hubble Legacy Fields (HLF Illingworth et al. 2016; Whitaker et al. 2019a). The HLF reductions provide an excellent matched set of HST images in multiple ACS and WFC3 bands for use with the JADES JWST NIRCam imaging. We also utilize astrometric registration to Gaia performed by G. Brammer (private communication) using the methods of Kokorev et al. (2022) and grizli 1 .', '3.2. Tiers and Geometrical Constraints': "JADES is built as a two-layer wedding cake, with Deep portions of both imaging and spectroscopy, flanked by larger Medium depth regions. Bringing imaging and spectroscopy to bear on the same targets, while making efficient use of coordinated parallel observations, are driving goals of the survey design. Here we begin to describe these considerations.  \nThe differing on-sky geometries of the NIRCam and NIRSpec instruments mean that these two cannot be efficiently overlapped with a single pointing of NIRCam. It takes at least a 2x2 mosaic of NIRCam to produce a filled area large enough to cover one NIRSpec MOS pointing. Further, the ability to use two instruments at once is an important opportunity to increase the science return, but the angular separation between the instantaneous fields of the instruments drives one to a large field. We note that, as a consequence of the visibility constraints, neither of the JADES fields allows JWST to return at a 180 · position angle, so as to swap the instrument locations. Instead, we have to construct an adequately sized mosaic, and choose the parallels to maximize the science return. Most of the MIRI parallel data and the NIRSpec MOS parallel data falls on NIRCam imaging, and nearly all of the NIRSpec parallel data falls on the GOODS/CANDELS HST imaging.  \nWe placed the Deep portion of JADES in GOODS-S, while the Medium data are in both fields. We considered placing Deep pointings in GOODS-N, but as full support of the NIRSpec MOS footprint requires 4 NIRCam pointings, this would have become overly expensive.  \nThe NIRCam data in JADES fall into 4 categories. There are contiguous portions in regular mosaics, of both deep and medium variety; we call these 'Prime'. Other portions occur as parallel exposures to NIRSpec MOS pointings, whose positions are therefore dictated by the location and position angle of the spectroscopy; we call these 'Parallel'. Again, these come in deep and medium variety.  \nIn detail, ten of the Medium-depth Prime NIRCam exposures were taken with NIRSpec in parallel, but the structure of JWST coordinated parallel observations is that NIRSpec is formally prime in the planning tool. We refer to NIRCam as prime (and NIRSpec as parallel) despite this, because the exact pointing and exposure times were being dictated by the NIRCam science goals.  \nOther NIRCam pointings were taken with MIRI in parallel; these yield Deep and Medium MIRI imaging.  \nThe JADES NIRSpec MOS data fall into 3 tiers. One tier comprises two deep pointings, one scheduled early in the program and targeted without JWST imaging, the other scheduled at the end and targeted from the JADES imaging. These are called Deep/HST and Deep/JWST, respectively. Then there are two tiers of medium depth. One named Medium/JWST is targeted from JADES imaging, the other named Medium/HST has target selection prior to JWST imaging and is somewhat shallower. All of the NIRSpec MOS data is taken with NIRCam in parallel.  \nThe Medium-depth designs with both NIRCam and NIRSpec MOS are shaped heavily by a desire to take well-dithered data, with at least 6 pixel locations to provide robustness to bad pixels and the undersampled point-spread function, and to use long enough exposures to keep observatory overheads low (these concerns are easily satisfied with the Deep data). Hence, even this flanking data is quite deep in comparison to pre-JWST opportunities. Because of the full use of coordinated parallel observations, we paid particular attention to minimizing the data rate for telemetry, typically utilizing the DEEP8 readout pattern for NIRCam and SLOW readouts for MIRI. This kept the program to about 2 GB/hr of data volume.  \nAlthough JADES was designed to be observed in a single year, over-scheduling in Cycle 1 resulted in it being scheduled over 18 months. In particular, the large investment in GOODS-S was spread over two observing seasons. This led to some reoptimization relative to the original design, induced by exact position angles, instrument problems for some observations, and further on-orbit appreciation of science opportunities. We will focus in this paper on the observed program, making only passing mention of the original layout.", '3.3. JADES Footprint': 'The footprint of the JADES survey is shown in Figures 3 for GOODS-S and 4 for GOODS-N. As the geometry is complicated with the various overlapping footprints, we include separate images of each major portion of the survey. We stress that portions of the GOODS-S footprint are provisional: the position angle and exact  \nlocation of most of the Medium/JWST NIRSpec and parallel NIRCam data have not been confirmed yet, and observational hiccups may yet occur.  \nIn GOODS-S, one can see how the primary Deep portion of the survey, centered on the UDF, and the Medium portion to the west support each other with coordinated parallel observations. For instance, the MIRI parallels are largely partnered with NIRCam imaging, including the first NIRCam Deep Parallel. We also generate NIRSpec Medium/HST parallels that fall back on the UDF, providing high-multiplex spectroscopy for our Deep imaging. Finally, the NIRSpec Medium/JWST and Deep/JWST pointing create NIRCam parallels that fan out to create more imaging area.  \nIn GOODS-N, the area of the prime survey is a little smaller, which makes it harder to fully utilize the parallels. We do utilize the NIRCam Medium Prime fields to cover the HDF and provide imaging for the initial NIRSpec Medium/HST spectroscopy as well as targets for the Medium/JWST followup. The parallels from that later spectroscopy produce NIRCam images that cover additional GOODS/CANDELS imaging. Two of the NIRCam prime pointings did not have MIRI or NIRSpec parallels that would fall on NIRCam imaging or GOODS; we opted to use MIRI, to be partnered with HST CANDELS imaging and perhaps future NIRCam data.  \nA major constraint on the layout of the survey comes from the intention to be able to conduct NIRSpec followup of NIRCam-selected targets within a single observing window. We judged that 60 days would be the minimum separation of these visits, and therefore that it is needed to perform the NIRCam imaging early in the window and the NIRSpec follow-up late in the window. In GOODS-N, this plan is what has been scheduled. Unfortunately, our GOODS-S observations ended up split over two years, and we are seeking to use more optimal position angles (PA) and observing windows in the second year.  \nIn GOODS-S, the year 1 NIRCam Deep Prime imaging was taken at V3 PA = 298.56 · , in early October 2022. The year 1 Medium Prime imaging was taken a week later at V3 PA = 308 · . The first NIRSpec Deep/HST pointing followed at V3 PA = 321 · . When we return in year 2, we will seek to match the Deep Prime and Medium Prime position angles to those of year 1. The position angles of the year 2 follow-up spectroscopy are assigned but might change, and the exact locations will depend on the location of high-priority targets.  \nIn GOODS-N, we observed the NIRCam Medium Prime data at PA = 241 · in early February 2023. The  \nDec (ICRS)  \nFigure 3. Layout of the JADES observations in the GOODS-South field. JADES observations with NIRCam, NIRSpec MOS, and MIRI are shown as colored shaded regions. Higher opacity indicates higher exposure time for NIRCam and MIRI or overlapping MSA pointings for NIRSpec. Dithers and nods smaller than 2 arcseconds are not plotted. For NIRCam, only the SW quadrants are shown for clarity. For NIRSpec, only the active area of the MSA that was used for target placement, excluding regions that lead to truncated prism spectra, is shown. Some of the observations yet to be made in Cycle 2 (NIRSpec Deep/JWST and most Medium/JWST and their associated NIRCam parallels) have positions and orientations that are still to be defined based on scheduling. Outlines of other surveys, including the HST/ACS UDF and CANDELS, are shown with black and olive green curves. The smaller sub-panels show the same information split by instrument for clarity because it can be difficult to see the details when all observations are plotted together. The NIRCam sub-plot in upper-right additionally includes field outlines for the public JWST Cycle 1 NIRCam imaging from the JEMS, FRESCO and NGDEEEP programs.  \n<!-- image -->  \nJADES GOODS-South Field Layout  \nJADES GOODS-North Field Layout  \nFigure 4. Layout of the JADES observations in the GOODS-North field. Details as in Figure 3. GOODS-North data collection is nearly complete, so this figure is nearly final. Only the southern-most of the Medium/JWST pointings remains, due to a guide-star acquisition failure; this pointing will be repeated at an unknown location and position angle. The NIRCam sub-plot in the upper-right additionally includes the outlines of the public JWST Cycle 1 NIRCam imaging from the FRESCO program.  \n<!-- image -->  \nNIRSpec Medium/JWST data then followed in early May, at PA = 150.48 · . Due to a fault with acquiring guide stars, one observation was skipped and had to be redesigned and observed at PA = 132 . 93 · .', '3.4. Other Overlapping JWST Data': "The GOODS fields, UDF, and HDF have of course been observed by other programs in JWST Cycle 1. Here we briefly describe programs whose data overlap JADES. Figures 3 and 4 show the JADES NIRCam footprint with overlays with some of these and other programs. We surely expect this list to grow in future cycles!  \nThe First Reionization Epoch Spectroscopic Complete program (FRESCO, PI: Oesch, Program 1895, Oesch et al. 2023) conducted NIRCam F444W slitless spectroscopy (2 hr depth), paired with F182M and F210M medium-band imaging (1 hr each). These 8-pointing mosaics in GOODS-S and GOODS-N overlap heavily with JADES. FRESCO has proven to be highly complementary to JADES, as the strong emission lines are imaged as excesses in JADES photometry and then redshifts are obtained in FRESCO. The additional mediumband imaging, while shallower than JADES, provides more spectral resolution on mid-redshift galaxies.  \nThe JWST Extragalactic Medium-band Survey (JEMS; PIs: Williams, Tacchella, & Maseda; Program 1963, Williams et al. 2023) observed one pointing on the UDF in F182M, F210M, F430M, F460M, and F480M, with 4-8 hrs/filter. This dataset heavily overlaps with JADES, providing additional filters with compelling depth. In addition, JEMS conducted a NIRISS parallel in F430M and F480M, about half of which overlaps JADES NIRCam imaging.  \nBetween these two, we note that F182M and F210M will be available for a notable portion of JADES. We have co-reduced JEMS and FRESCO NIRCam imaging with JADES, and include these data in JADES photometric catalogs.  \nIn addition to FRESCO's wider medium-depth slitless spectroscopy, the Next Generation Deep Extragalactic Exploratory Public survey (NGDEEP, PI: Finkelstein, Program 2079) is producing very deep NIRISS slitless spectroscopy on the UDF (Bagley et al. 2023). We expect that these programs will complement the deeper but targeted NIRSpec MOS spectroscopy. The NGDEEP NIRCam imaging parallel falls off the JADES footprint, to the south-east.  \nThere is also other deep MIRI GTO imaging in GOODS-S. Program 1283 (PI: Oestlin) is observing one extremely deep pointing in the UDF, reaching 49 hrs in F560W. The NIRISS parallel from this pointing falls  \nat the southern edge of JADES NIRCam imaging. For wider MIRI coverage, program 1207 (PI: G. Rieke) is observing 15 pointings in 8 filters, all overlapping the JADES NIRCam imaging.  \nThe push for deep imaging and spectroscopy in GOODS-S will continue in Cycle 2 with an approved GO program 3215 (PI: Eisenstein) that will return to the footprint of the JADES 1210 program to add very deep NIRCam imaging in six medium bands-F162M, F182M, F210M, F250M, F300M, and F335M-to refine the search for z > 15 Lyman dropouts. At the same time, ultra-deep NIRSpec MOS spectroscopy will be obtained on top of the JADES Deep Prime imaging.  \nFinally, there are several other NIRSpec programs in the fields. Two examples are program 2674 (PI: Arrabal Haro), which conducted NIRSpec MOS and coordinated NIRCam imaging in GOODS-N that will complement the JADES footprint, and program 2198 (PI: Barrufet), which conducted NIRSpec MOS and NIRCam pre-imaging on two fields in GOODS-S. Other spectroscopic programs are the GTO NIRSpec WIDE MOS survey from programs 1211 and 1212 (PI: Luetzgendorf) and IFU program 1216 (PI: Luetzgendorf). Additional NIRCam pure-parallel imaging overlapping both fields is being obtained by the PANORAMIC program (PI: Williams, Program 2514).", '4. NIRCAM OBSERVATIONS': 'In this section, we detail the JADES NIRCam imaging. We begin by describing the details of the four categories of NIRCam imaging: Deep Prime, Medium Prime, Deep Parallel, and Medium Parallel. We then discuss cross-cutting aspects: filter selection, data quality, and a summary of depths.', '4.1. NIRCam Deep Prime': "In the heart of GOODS-S centered on the UDF, we observe 4 NIRCam fields to image a 4 . 4 ' by 6 . 1 ' rectangular field. A pair of NIRCam pointings is offset by ∼ 61 . 5 '' in V2 so as to cover the NIRCam inter-module gap, and each pointing contains many exposures including offsets in V3 to cover the shortwave chip gap. This pattern is then repeated in the second pair of pointings, offset in V3 leaving only a small overlap with the first pair. We size this offset to the height of the long-wave (LW) footprint, as this is slightly smaller than the shortwave (SW) footprint. We note that the mosaic was laid out for V3 PA of 300 · but observed at 298.56 · , causing a small cosmetic deviation from a rectangular layout.  \nWe use the DEEP8 readout pattern with 7 groups, yielding individual exposure times of 1375 seconds. DEEP8 was used to reduce the data volume, but will  \n<!-- image -->  \nFigure 5. A small portion of the Hubble Ultra Deep Field, comparing HST and JWST imaging. ( left ) The F160W image from HST WFC3, from the Hubble Legacy Field reduction of Whitaker et al. (2019b), with an exposure time of about 65 hrs. This is the single deepest H-band image taken with HST. ( right ) The F150W JWST NIRCam image from the first year of JADES with an exposure time of about 10 hours. The superior depth and image quality of JWST is clear.  \n<!-- image -->  \nTable 1. Overview of the NIRCam Deep imaging in GOODS-S in different filters, listing the number of separate exposures and the total exposure time per pointing, in ksec. We note that some pointings overlap, doubling the depth, and that many Deep pointings also overlap with Medium, further increasing the depth.  \nyield somewhat worse recovery from cosmic rays than a MEDIUM choice would have. In total, each pointing utilizes 114 such exposures, each with a SW and LW filter choice. Because each pointing includes more than 2 days of exposure time, we must split the observations into 3 visits. The first two use 9-point subpixel dithers  \n(and no primary dither), each with 5 filter pairs, yielding 45 exposures. These two visits are offset in V3 by ∼ 5 '' to step over the SW chip gap. The third visit uses a mosaic of two pointings, each with 4-point subpixel dithers and 3 filter pairs, so 24 total exposures. The mosaic is designed with a row overlap chosen to result in the same V3 step and with the pointing chosen to result in the same footprint as the first two visits. Due to a mistake in correcting for a small PA shift, the third visit of pointing 2 is offset mildly, 3 '' , from the exact overlap. All filters are included in both 9-point subpixel dither visits and therefore most points in the image are observed by at least 18 different NIRCam pixels (9 if the location falls in the SW chip gap in one of the visits).  \nThese observations are all taken with MIRI in coordinated parallel, the results of which will be described in § 6. Because of this, in the first season, we selected the subpixel dither based on F770W stepsizes. Having inspected these results, we concluded that a mildly larger stepsize would be better for background subtraction; we therefore changed to the F1500W dither pattern in year 2.  \nWe utilize 9 filters in the Deep Prime pointings: F090W, F115W, F150W, and F200W on the SW arm, and F277W, F335M, F356W, F410M, and F444W on the LW arm. The exposure times per filter are listed in Table 1. It is important to note that about over a  \nthird of the total field is covered by two of the pointings, doubling the total exposure times. Because of the importance of high-redshift dropouts, we slant the SW exposure times toward the F115W and F150W filters, while on the LW side we favor the longer filters where the zodiacal background is reducing the sensitivity. A comparison of the imaging we obtained in the NIRCam Deep Prime with that from the HUDF HST imaging is shown in Fig. 5.  \nAlthough JADES was designed to be observed in one year, Cycle 1 scheduling constraints caused the program to be split. We opted to observe all 4 pointings in each year. In year 1, all pointings were observed with one of the 9-point dither visits, and two were observed with the 4-point dithers. This will be repeated in year 2, completing the observing. Unfortunately, this segmentation also caused a delay in the spectroscopic followup of the Deep imaging. However, it does create an opportunity to consider year-scale time variation in this nearly 25 arcmin 2 deep field.  \nIn total, this part of the JADES program was an investment of 229 hours and resulted in 174 open-shutter hours of data, a utilization of 76%.", '4.2. NIRCam Medium Prime': "To provide shallower flanking coverage and increase the area available for NIRSpec MOS targeting, JADES includes 18 pointings in (mostly) regular mosaics yielding contiguous coverage to medium depth. 7 of these are in GOODS-N and 11 in GOODS-S. Because of the footprint, 8 of the pointings have MIRI in parallel, while 10 have NIRSpec MOS in parallel. In most cases, the pointings are paired with a 62 '' step in V2 so as to fill a long rectangle covering the inter-module gap, with some double coverage. In detail, the step is chosen to match the width of one SW chip, so that the pointings cover the V3-parallel chip gap of their partner.  \nCycle 1 scheduling constraints caused half of the Medium Prime time in GOODS-S to be delayed until fall 2023. We opted to observe in 2022 the six pointings of the mosaic that did not overlap the NIRCam Deep Prime field, so that most of the prime area could be observed in fall 2022, including the footprint of the deep MIRI parallels. These pointings also provided NIRSpec MOS parallels on and around the UDF. The GOODS-S mosaic was designed for and observed at v3PA of 308 · . The small PA difference from the Deep Prime mosaic was included to make the program more easily schedulable.  \nFor these six pointings, the filters are as in Deep Prime save for omission of F335M. Each of the 8 filters received 6 exposures, falling on 6 different pixels. The  \nfilter pair of F115W and F444W received 1159 second exposures using DEEP8 and 6 groups. The other three filter pairings receive 945 second exposures; these use DEEP8 with 5 groups to reduce data volume. Unfortunately, one pointing failed due to shorts in the NIRSpec MSA; this one will be repeated in fall 2023. Another pointing had half of the LW imaging impacted by the shorts; we opted to accept this one and adjust a future pointing to compensate.  \nAfter this start, and in view of the ongoing scheduling of the NIRCam parallel observations, we opted to make some minor adjustments. We had originally planned for 19 Medium pointings, but we decided to remove one pointing in GOODS-S and compress certain exposure times in GOODS-N in order to add F335M back into filter set for 11 of the 12 remaining pointings, pairing with a second exposure of F115W. We also had to adjust times to balance the program within its allocation, due to small on-orbit alterations in the parallel observation timing model. The detailed exposure times are presented in Table 2 for GOODS-S and Table 3 for GOODSN. Most exposures use the DEEP8 readout mode, but the shorter ones use MEDIUM8. In GOODS-S, relative to the original grid, we removed one pointing that overlapped the Deep Prime imaging and mildly compressed the time on a second that filled only a small gap between Deep and the rest of Medium. We then took the northern most row and displaced one pointing to compensate for the short-impacted year 1 pointing, and the other pointing to fill more of the gap between Deep Prime and the expected location of future Parallel imaging. In GOODS-N, we decreased the time in the 3 pointings with MIRI parallels; in one case we were unable to include F335M.  \nFor the 7 pointings in GOODS-N, we pack four of them tightly in V2 to cover the intermodule gap. The other three have no intermodule coverage, and we further have chosen these to have less exposure time, as the MIRI parallels are more flexible than the NIRSpec MOS parallels. The northern portion of the mosaic is therefore somewhat shallower, but able to cover more of our early NIRSpec Medium/HST data. We decided that it was more important to maintain a 6-fold dither than to insist on a filled footprint, expecting that this field will likely attract larger coverage in future Cycles. The mosaic was designed and observed at v3PA of 241 · .  \nRegarding the dither strategy, when operated with MIRI parallels, we use 3 dithers with the INTRAMODULEX pattern and 2-point subdithers. These were based on the MIRI F1800W PSF in GOODS-N and F2100W in GOODS-S, chosen to increase the dither step size for background subtraction. This dither uses small  \nTable 2. Overview of the NIRCam GOODS-S Medium imaging in different filters, listing the number of separate exposures and the total exposure time per pointing, in ksec. We note that some pointings overlap, increasing depth. Pointing 4 (observation 22) with MIRI parallels is shorter than the others to balance the time within the allocation; this pointing is substantially overlapped by the Deep Prime mosaic. Pointing 25 of the NS-HST set lost half of the LW exposure time to illumination from a short circuit in NIRSpec.  \nTable 3. Overview of the NIRCam GOODS-N Medium imaging in different filters, listing the number of separate exposures and the total exposure time per pointing, in ksec. We note that some pointings overlap, increasing depth. Pointing 3 (observation 3) with MIRI parallels is shorter than the other two to balance the time within the allocation. Pointings 4-7 are with NS-HST, while pointings 8-11 are with NS-JWST.  \nsteps at 45-degrees in V2 and V3, stepping over both SW chip gaps in each. Hence most points in the chip gaps receive 4 SW exposures; only small overlaps from the cross in the middle generate only 2. We remind that in most cases, the center of each arm is covered by the other pointing in the pair.  \nWhen operated with NIRSpec parallels, the strategy is mildly different. Here, we split the 6 exposures into two sets of 3. Each triplet is a different MSA design with largely independent targets, to be described further in § 5. In each triplet, NIRSpec will execute its 3-step nod along the slits of the MSA. We note that these steps are  \nroughly at 45 · on the NIRCam pixel grid. For the next triplet, we step the central pointing purely in the V3 direction by an amount to cover the V2-parallel chip gap. The V3-parallel gap is not covered within this pointing, but usually will be by the partner in the mosaic.  \nIn summary, this part of JADES was an investment of 195 hours, 123 in GOODS-S and 72 in GOODS-N, resulting in 131 open-shutter hours (with the formally prime instrument), a utilization of 67%.  \nFigure 6. A small portion of JADES NIRCam GOODS-S imaging, combining F090W, F200W, and F444W filters in the Deep Parallel region of program 1210. This image shows the great diversity of galaxies revealed in every JWST image, with a wide variety of colors and morphologies. North is up.  \n<!-- image -->  \nIn GOODS-S, JADES executes two long NIRSpec MOS pointings ( § 5), each of 200 ks open-shutter spectroscopy. Each of these is used to make a long NIRCam parallel exposure, the location of which depends on the position angle and observing window, which in turn was subject to the programmatic constraints of the NIRSpec targeting.  \nIt turned out, fortuitously, that the first of these pointings was at a position angle (V3PA of 321 · ) that caused the NIRCam parallel to fall on top of the deep MIRI parallels produced by the NIRCam Deep Prime program.  \nThe second pointing needs to be later in the observing window so that the targets resulting from the analysis of the full NIRCam data set can be used. We are designing this for v3PA of 53 · , which will place the NIRCam parallel north of the Deep Prime field, near the location of the first Medium/JWST parallel. The exact placement will depend on the location of the most interesting high-redshift candidates in the Deep Prime field.  \nEach of these two deep fields use the same nine filters as the Deep Prime program. We also use the same DEEP8 readout mode with 7 groups, yielding 1375 second integrations. Each field uses 144 such integrations for a total of 55 hours of open-shutter imaging, indeed mildly deeper than a single Deep Prime pointing (but without the overlaps of the mosaic). The exposure time per filter is shown in Table 1.  \nOne limitation of these data is that NIRSpec only employs 9 dither locations, 3 nod locations in each of 3 different slit configurations. We were careful to arrange that each filter is observed at least twice at every location. In detail, the NIRSpec exposures are just over twice as long as the NIRCam integration, so each nod position results in a pair of back-to-back otherwise identical NIRCam integrations, 72 in all. We note that the dither pattern is set by the geometry of the NIRSpec MSA and therefore not tuned to the pixel scale of NIRCam; that said, the steps are not commensurate with the NIRCam pixel scale and so the intra-pixel behavior is sampled.  \nAnother limitation is that the 3 MSA configurations in NIRSpec are stepped only a short distance ∼ 0.8 '' , to limit the effects of distortions across the MSA. This means that the data set does not fill the SW chip gaps. On the flip side, the data maximize depth in the region that is covered. An example of the superb quality obtained in this program is shown in Figure 6.", '4.4. NIRCam Medium Parallel': 'JADES executes twelve medium-depth NIRSpec MOS pointings, 4 in GOODS-N and 8 in GOODS-S, to be described in § 5. Each of these produces a NIRCam coordinated parallel observation, with a total of 45 exposures. The exposure times are given in Tables 2 and 3.  \nAs these parallel fields were at risk to fall off of the HST GOODS and CANDELS imaging, depending on the final position angles, we opted to include the F070W filter in addition to the nine filters used in the Deep imaging. This improves isolation of z ∼ 5 . 5 Lyman α dropouts.  \nAs with the NIRSpec Deep program, these observations also use 9 closely spaced dither pointings, via 3 nod locations in each of 3 slit configurations. The SW chip gaps are not covered. We ensure that each NIRCam filter is observed in at least 2 of the 3 slits and hence at 6 dither locations. 2 of the 3 slits have all ten filters observed; the remaining one is missing F070W, F200W, F335M, and F356W. Therefore, the area covered by all ten filters is reduced by a tiny amount.  \nAs the prime spectroscopy will be placed on the NIRCam Prime mosaic, these Medium parallels in both GOODS-S and GOODS-N fall almost entirely outside of the NIRCam Prime footprint, thereby providing a substantial amount of additional area at medium depth. In GOODS-N, we observed at v3PA of 150.48 · and 132.92 · , placing the new imaging on the northeastern portion of the HST GOODS-N field. Because of the location of high-priority spectroscopic targets, these do not form a regular grid, but they are close enough to map a sizable near-contiguous region. By coincidence, the orientation of NIRCam in this Parallel imaging is almost 90 · rotated from the Prime imaging, leaving an obvious pattern for future observations to fill in the gap between the two. Unfortunately, a guide-star acquisition failure caused Observation 8 to be skipped, requiring a replan (Obs 98) that was observed a few weeks later with 18 · of rotation relative to the other three pointings.  \nIn GOODS-S, we will spread the spectroscopic pointings over the full Medium mosaic. In the original plan, these would all have been late in the first observing window, but given the scheduling delay, we are opting to spread them out. The first field (observation 1) was observed on January 12-13, 2023, at a V3PA of 56.17 · . The other 7 will be observed in late 2023, likely at a range of position angles. Here, we assume V3 PA of 30 · for display and summary purposes. The exact parallel footprints cannot be specified until the targets are in hand, and may move substantially.', '4.5. Comments on Filter Selection': 'Early on in the design of JADES, we recognized that the strong increase in zodiacal emission longward of 4.5 µ m would increase the background in F444W, such that F410M could be competitive despite its narrower bandpass. We therefore opted to include both filters to increase the resolution of the spectral energy dis-  \nribution. This is particularly important because of the strong rest-optical emission lines expected in some high-redshift galaxies, as indicated by Spitzer imaging and now confirmed with early JWST spectroscopy. The spacing of the H α +[NII] and H β +[OIII] complexes is such that only one can fall into F444W at any given redshift, and including F410M means that the comparison will separate the line from continuum emission at most redshifts (with ambiguity if the lines fall on the shoulder of the filter curves). This separation is important for stellar population modeling, as we want to measure the rest-optical continuum color relative to the ultraviolet.  \nAs we studied this, we concluded that F335M and F356W offered a similar opportunity and that the likelihood of strong H α or H β +[OIII] emission recommended splitting this exposure time as well. This has been borne out in practice: we have found the abilty to isolate strong emission lines at 3-5 µ mto be very useful and interesting. In addition to the lines themselves, the extra spectral resolution helps to isolate the Balmer jump at high redshift and to measure the rest-optical continuum.  \nWhere possible, we observe F277W somewhat longer than F356W because of the extra coverage from F335M. We also chose to slant the exposure time toward making F115W deeper, emphasizing the selection of z > 9 candidates.  \nIn summary, we have found the NIRCam coverage in the nine base bands to be highly effective for photometric redshifts. For example, at z ≈ 7, one observes the Lyman α drop in F090W and H β +[OIII] in the longest bands.', '4.6. Data Quality Caveats': "While a detailed description of the data reduction and performance will be left for later papers (Robertson et al., in prep.; Tacchella et al., in prep.), we here describe some issues that we have already seen and that might be of interest to other users.  \nOur observing was split into many separate visits rather than long campaigns, and we encountered substantial persistence at the start of some visits, left over from the immediately preceding program. These signals last for several hours and will require detailed modeling. The effect is more severe on the SW chips A3, B3, and B4; the other SW and both LW chips are much milder.  \nMost dramatically, in the Deep program, observations 7 and 10, were observed immediately after observations of the bright Trapezium nebula, leaving substantial diffuse emission over portions of SW chips A3, B3, and A4. This is most severe in the F090W filter (the first used), but there are faint traces in the next filter (F115W), 3.5 hours later.  \nWe stress that the persistence is not simply coming from bright stars in the previous images, but the change in the diffuse background illumination level from the previous program. This greatly increases the affected area, particularly in A3 and B4. The decay time for A3 is particularly long. Observation 4 in 1181 shows a similar morphology of persistence incurred by a change in the background level relative to the previous program.  \nWe also see persistence in A3 in visits following wavefront sensing operations, creating a moderate-size ( ∼ 100 pixel across) hexagonal image. While such sensing is common, the reference star is planned to fall on a consistent part of the chip. We hope that the frequent reoccurence of this signal will allow that area of the chip to be particularly well characterized. 1180 observations 15 and 27 are affected by this.  \nWe have also seen a case (1180 observation 18) in which a bright star happened to fall on the NIRCam field during the preceding MIRI observation, even though NIRCam was not being used in parallel. NIRCam is typically left open to the sky when not used. One can see the imprint of the whole MIRI dither pattern, as well as the trail when the telescope slewed away from the field.  \nOf course, these regions do also incur persistence from brighter sources in our own observations. For instance, in 1181 observation 2, there is a bright star in the bad portion of A3 that creates a recurrent glow in all 6 dither locations.  \nMitigating these persistent signals is particularly vexing when one is using a small-angle dither, as a pixel may never find a blank-sky location away from a larger galaxy. We are therefore increasing our sub-pixel dither selection in the remainder of our observations. However, this is not always possible when observing jointly with NIRSpec. We caution that we have not yet considered the effect of persistence on our photometry, but in the worst regions of these chips, we believe this should be studied. By construction, the dither pattern is repeated between filters, so the persistence from the first filter will affect the next.  \nLike many NIRCam observations, we occasionally have noticeable illumination of the SW detector through an off-axis stray-light path, producing the so-called 'wisps'. These affect F200W and F150W most strongly. While these signals are known to modulate in amplitude due to the brightness of stars in the source region on the sky, we have found that the exact morphology of the pattern also varies within our program. We are still analyzing this, but hope that a low-dimensional set of templates will suffice to remove them.  \nWe have found it very helpful to visualize the calibrated exposures of a dither sequence in animations, fixed in pixel coordinates so that the true objects move and the detector artifacts stay still.  \nWe have found it easier to disentagle persistence from wisps when F090W or F115W are observed first in a visit, so that the persistence has decayed away before the wisp-affected F150W and F200W bands are observed.  \nWe now turn to rarer problems. The second half of one pointing (observation 30) of the Medium Prime mosaic in GOODS-S had to be skipped due to an on-board issue unrelated to our program. There was not enough time in the observing window (constrained by the spectroscopic coordinated parallel) to try again. Fortunately, this pointing is at the edge of the mosaic. The first half of this same pointing had its LW data badly contaminated by a glowing short circuit in the NIRSpec MSA. We will repeat this entire pointing in October 2023 to complete the 6-dither coverage.  \nOne half of another pointing (observation 25, first 4 dither sequences) was also affected by the NIRSpec glowing short (Rawle et al. 2022). In this case, because the location of the field was favorable to access in a different way in the year 2 observing, we opted not to repeat this imaging location but instead combine the NIRSpec re-do with another pointing.  \nIn both of these cases, we found that the LW data were badly affected. The background was roughly doubled, but further there are many patterns of concentric rings, with spacing depending on wavelength, likely due to some diffractive pattern from where the light from NIRSpec has bounced off of the tertiary mirror. As the short circuit is apparently not particularly hot, the effect on SW is much less and we think this data is usable. There are a handful of faintly detected rings in F200W, chips A1, A2, A4, and B4.  \nNext, in the 3 deep visits of 1210, we find an enigmatic set of arcsecond-scale blobs near an edge of B3. These are bright in the second visit, but detectable in the other two. They are therefore not due to persistence, and we are confident they are not astrophysical as they do not appear in 1180 images of the same region. The morphology is very different from a wisp.  \nSome of our exposures have a plume of what appears to be scattered light in a corner of B4. We hypothesize that this may be due to a bright star striking the chip mask, as the signal changes slightly between the three visits of 1210, which move only at the arcsecond level, suggesting a well-focused source. However, we also see it in observations 27, 28, 29, and 30 of 1180, so it seems that the cause is not particularly rare.", '4.7. NIRCam Imaging Depth': "As shown in Figures 3 and 4, the NIRCam pointings often overlap, so that the survey is deeper than what appears in Table 1-3. Further, the depth varies because of the geometry of these overlaps. To provide a useful summary of the NIRCam program, we divide the footprint into 3 disjoint regions: Deepest, Deep, and Medium. Deepest refers to the area where two or more of the Deep Prime pointings overlap. Deep refers to the remainder of the area of the Deep Prime and Parallel fields. Medium refers to the rest of the area, including both GOODS-S and GOODS-N. In each case, we add up all of the exposure time in each filter, including the contribution of Medium pointings to the Deep regions, along with a corresponding point source depth from the Exposure Time Calculator. These areas and averages are approximate, as we do not yet have the final exposure locations and have not used an exact weight map, which would include the detailed impact of the dithers on the boundaries and the impact of bad pixels. We also remind that the exposure times do vary within the regions; for example, the northern portion of GOODS-N is shallower by a factor of 2-3 in exposure time than the bulk of the Medium region. Nevertheless, these summaries are reasonable averages for forecasts and contextual comparisons.  \nWe then convert the representative exposure times to anticipated 10σ depths for background-limited 0 . 2 '' diameter apertures with point source aperture corrections. We do this by using the first pointing of 1286, as a representative and currently non-overlapped Medium pointing. The aperture error is derived from measuring many such apertures in blank regions of the mosaic and computing the rms in bands of exposure time. We note that the Deep survey was observed with longer exposure times and usually lower zodiacal background level, which will make it slightly deeper than the scaling from this 1286 pointing. However, the final mosaic will have mildly lower effective exposure time due to bad pixels and cosmic rays.  \nWe remind that the Deep area is all in GOODS-S, while the medium area is split approximately evenly between GOODS-S and GOODS-N. The average depths in GOODS-N is mildly shallower than in GOODS-S, but the two fields are sufficiently similar that we do not separate them for this summary.  \nIn Figure 7, we show a visualization of the estimated depth of the JADES, JEMS, and FRESCO NIRCam and JADES MIRI imaging, along with the estimates for HST ACS and WFC3 imaging (Whitaker et al. 2019b) in the HUDF and CANDELS fields that JADES overlaps. We have measured the JEMS and FRESCO depths in the  \nFigure 7. Depth versus Wavelength for JADES and other data sets. Black, blue, and red solid squares show the 10σ point source depth for JADES Deepest, Deep, and Medium NIRCam data, using the variation in 0.2 '' blank-sky apertures. Purple and magenta circles show the depth of the JEMS and FRESCO medium-band imaging. Horizontal ranges show the filter widths. The JADES Deep and Medium MIRI depths are shown with grey and pink points on the right. The 0.2 '' aperture is mildly too small for the HST WFC3 image quality, causing these estimates of depth to be too optimistic by 0.1-0.2 mag compared to larger apertures. Comparison is shown (dark and light green) to the depths measured in the same method from the Hubble Legacy Field (Whitaker et al. 2019b) mosaics, separating the single HUDF pointing from the broader CANDELS region. The HUDF ACS (WFC3) footprint is 11 (4.7) square arcminutes, comparable to the area of the Deepest JADES data. The CANDELS area exceeds the JADES Medium area. JADES improves over even the HUDF in area and spatial resolution, and at wavelengths longward of 1.6 µ m, the gains in depth and resolution are immense.  \n<!-- image -->  \nsame manner as that of JADES, using our own reductions of these data. One sees that the JADES imaging is comparable in depth in the deepest HUDF data, which covered only a single HST pointing. One also sees that the ratio of optical ACS to infrared JADES depth is less favorable in the broader CANDELS region compared to that of the HUDF.", '5. NIRSPEC OBSERVATIONS': "As introduced in § 3, the JADES NIRSpec MOS data fall into 3 tiers: Deep, Medium/JWST, and Medium/HST. All 3 tiers use the low-resolution prism as well as several gratings, with grating spectra available for most of the prism targets. Table 5 provides a summary of disperser configurations and exposure times for each tier. This section presents some of the features common to all tiers before describing each tier separately.  \nTable 4. A Summary of Average Exposure Times and Depths in the NIRCam Deep and Medium Surveys. The 6 Deep pointings cover a total footprint of ∼ 45 arcmin 2 , with ∼ 9 of these being double-covered and marked as Deepest. The 31 Medium pointings are anticipated to cover a total additional footprint of ∼ 175 arcmin 2 exclusive of the Deep footprint. Within each, we compute the average exposure time per filter, including the contribution of Medium to the deeper regions. We then present the 10σ 0 . 2 '' diameter aperture depth, including point source aperture correction, for these average exposure times, scaling from observed errors in the first observed pointing of 1286 as described in the text. a The F070W filter is used in only a subset of Medium pointings, covering an area of ∼ 76 arcmin 2 . We quote the average exposure time and depth in this smaller area. b The F335M filter is not used in some Medium pointings, so that this filter covers a Medium footprint of ∼ 134 arcmin 2 . We quote the average exposure time and depth in that smaller region.  \nEach of the NIRSpec gratings are used with a matching long-pass filter to prevent overlap of first order spectra by higher orders. For the band 1 G140M grating there are two available filters; F070LP and F100LP. F100LP blocks all light below 1 µ m, thereby ensuring no second order overlap within the nominal spectral range up to 1.8 µ m. F070LP allows through light at > 0 . 7 µ m, so it has the advantage of enabling observation in the range 0.7 to 1.0 µ m. This corresponds to the wavelength of the Lymanα transition at redshifts of 4.8 to 7.2, bridging the epoch of the end of cosmic reionization (Robertson 2022). Therefore we chose to use the F070LP filter for all the JADES G140M spectroscopy. We accept that there will be second order overlap from the sky, increasing the sky background at > 1 . 4 µ m, and from galaxies at redshifts below 7 that have flux in this wavelength region. However, much like the overlapping grating spectra allowed by our MSA configurations described in the following subsection, this increased continuum flux will have little impact on our emission line measurements from the G140M spectra.", '5.1. MSA Configuration Design': "JADES designed its NIRSpec multi-object observations using the tool eMPT (Bonaventura et al. 2023) that provided key features beyond what was found in the baseline tools for MSA design. In particular, eMPT allowed us to:  \n- 1. Constrain the NIRSpec pointings to a rigid mosaic of NIRCam fields, once the position angle is specified.\n- 2. Impose a detailed prioritization system for our targets and have complete control over the order in which each class of targets is attempted placed on the MSA at a given pointing.\n- 3. Optimize repeated observations across multiple overlapping MSA designs to maximize exposure time on the highest priority targets.\n- 4. Identify and eliminate beforehand targets having contaminating objects falling within their (nodded) slitlets.\n- 5. Avoid the use of shutters leading to prism spectra truncated by the NIRSpec detector gap or contaminated by the spectra of failed open shutters.\n- 6. Enable overlap of the grating spectra (except for some high priority targets whose grating spectra are protected from overlap) to maximize the gratings multiplexing, while keeping those of the prism distinct.\n- 7. Open additional blank-sky shutters that disperse onto unused detector real estate to support master background subtraction.  \nTo do this, eMPT contains the full NIRSpec model of the astrometric distortions and multi-shutter geometry  \nand constraints, from which it can accurately predict how given astrometric positions will fall onto shutters, whether those shutters are available to use, and where the resulting spectra will fall on the detectors (and thereby whether they will overlap). The code thereby revealed the detailed outcome of each target, with which one can proceed to accept targets in complex priority orders. After this process determines which shutters were to be opened, the final optimal pointings and matching MSA masks were imported into the standard APT/MPT workflow for further execution.  \nThe MSA shutters are on a rigid grid, and the opaque regions between the shutters block enough light from compact sources that one typically chooses to retain only the fraction of targets that are sufficiently well centered in their shutters. Not all shutters function properly with 22 failed open that always disperse light onto the detector and 17.5% of the unvignetted shutters that are permanently closed (Boker et al. 2023). Our MSA masks require a 3-shutter-high slitlet for nodding and background subtraction. Locations where one can open a 3-shutter-high slitlet are therefore limited by this MSA operability leading to the concept of a 'viable slitlet' map. In all the JADES tiers we perform MSA reconfigurations with small (always < 10 and mostly < 1 arcsec) offsets where we attempt to obtain spectra of at least the highest priority targets in multiple configurations. Simulations have shown that these offsets need to be kept small to maximize the overlap of the viable slitlet maps and to avoid the astrometric distortion at the NIRSpec MSA plane that cause some objects to become insufficiently centered. For most tiers of JADES, the main constraint on these offsets is to ensure maximal coverage of the highest priority targets in multiple MSA configurations.  \nBecause of these constraints, one needs a very high target density in order to achieve a high multiplex of assigned targets. JADES typically supplies at least 200 targets per square arcminute, yielding about 150 assigned targets on the prism designs, corresponding to an average assignment rate of only 9%. An obvious consequence of this low average rate is that one does not want to serve the rarer higher-value targets in this limited way. We therefore developed a detailed prioritization of the targets, largely by redshift and flux (see § 5.2). The eMPT allows us to assign slits in a greedy order, assigning higher priorities first. While this slightly decreases the total multiplex, it yields much higher assignment rates on high value targets.  \nNIRSpec prism spectra are relatively short, allowing multiple columns of non-overlapping spectra. For a given prism MSA design, there is a matching grat-  \ning MSA design that is nearly identical. Importantly, we keep nearly all of the same shutters open for the grating configuration so that most of our galaxies will have information at multiple spectral resolutions. The longer traces of the gratings may overlap, as may the zero-order emission, but the emission lines are sparse in these spectra. Emission lines can be associated to their parent object in multiple ways: the location along the three shutter tall 1 . 5 '' slit, the prism spectrum, where the lines appear unoverlapped, and the wavelength ratio of multiple detections. The dispersed continua of the typical faint targets is below the detector noise in the grating spectra and hence the continua of the overlapping spectra do not substantially increase the noise. For the highest priority targets and for the infrequent brighter targets, we do close some shutters to avoid overlap; so a small fraction of objects are observed only with the prism.", '5.2. Target Prioritization': 'Here we summarize the design of the JADES spectroscopic target selection process. The main criteria for placing galaxies into priority classes are their redshifts and fluxes. Redshifts are estimated via photometric redshift algorithms and/or Lyman-break color selection. The highest redshifts are prioritized both because they are rare and because one of the main scientific goals of JADES is to understand the earliest phase of galaxy evolution. Galaxies with higher fluxes (in continuum or predicted emission lines, depending on the category) are prioritized since higher S/N spectra allow a wider range of science investigations.  \nThe details of the priority classes depend on the tier (Deep, Medium/JWST or Medium/HST) and whether the targeting is based only on HST imaging or on the JADES imaging. Deeper spectroscopic observations have lower flux limits for similar classes so that the achieved S/N will be similar for the different tiers.  \nThe highest priority class contains relatively bright galaxies at the highest redshifts; z > 8 . 5 for Deep and Medium/JWST and z > 5 . 7 for Medium/HST program. After these, we prioritize fainter galaxies at the same redshift and then progressively lower redshift bins, favoring the brighter galaxies. Through this, we aim to build up a statistical sample between redshift 1 . 5 < z < 5 . 7 in the lower priority classes over the tiers, with the shallower tiers contributing to the bright end and deeper tiers contributing to the faint end. In addition to these classes we also include a small fraction of galaxies identified as special in other data, e.g. with ALMA, Chandra, Lymanα emitters selected with the ESO VLT/MUSE instrument.  \nTable 5. Summary of the NIRSpec MOS Observations. For each program, we list the number of separate MSA fields, as well as the exposure time per disperser in kiloseconds. Each field consists of 1 to 3 sub-pointings, each with two nearly identical MSA designs: one for the prism and a second for the grating; the latter closes a few shutters to protect certain high-priority spectra from overlap. The quoted times are summed over the sub-pointings, but not all targets can be placed on all sub-pointings. The number of unique targets in each subsurvey is listed; bold values indicate completed observations, whereas other values are estimates at this time. The long-pass filter choices for the gratings are F070LP, F170LP, F290LP, and F290LP, respectively. a Each Medium/HST pointing is split into two distinct MSA locations, separated by the primary dither step across the NIRCam SW chip gaps. As the larger dither causes us to typically observe distinct galaxies, we account each pointing as two fields with one sub-pointing. When the slit registrations are favorable, we do reobserve high-priority targets to double the exposure times on these. b Twelve MSA locations were planned, but only 4 were completed in cycle 1 due to instrument problems. 3 will be redone in cycle 2. c These 5 re-dos were organized to be similar to two Medium/JWST locations, one with 3 sub-positions and one with 2.  \nWe also prioritize a few bright ( H AB < 23 . 5) moderate-redshift ( z > 1 . 5) galaxies, enabling the collection of exquisite infrared spectra from objects around cosmic noon. After these, we prioritize in photometric redshift bins, favoring the rarer brighter examples. Galaxies with photometric redshifts below z < 1 . 5 are used as a low priority filler sample; nevertheless, the large number of these targets yields a substantial observed set. Further details on the target prioritization, including variations per tier, are provided in the JADES Deep/HST data release paper (Bunker et al. 2023a).  \nThe distribution of spectroscopic redshift and F444W magnitudes are shown in Figure 8. One sees that NIRSpec is recovering redshifts to extremely faint flux levels, particularly in the Deep pointing.', '5.3. MSA Target Acquisition': 'Successful use of NIRSpec MOS depends critically on high-quality astrometry. Astrometric distortions in the target coordinates will tend to perturb targets away from the centers of their shutters, lowering performance. More insidiously, NIRSpec MSA Target Acquisition relies on a few bright compact sources to align the MSA to the desired location on the sky, so astrometric errors on those few objects can cause the entire MSA to be misaligned.  \nJADES was fortunate to be able to utilize recent reductions of HST imaging in the GOODS fields that had been aligned to the Gaia DR2 reference frame (G. Bram-  \nmer priv. comm., Gaia Collaboration et al. 2016, 2018). This alleviated concerns of distortions or mismatches between faint targets and bright acquisition sources.  \nHowever, the GOODS-S and GOODS-N fields, being intentionally placed in regions of very low stellar density, do present a severe deficit of stars suitable for target acquisition. Instead, we had to use the HST imaging to identify compact galaxies, using the longest exposure time for the acquisition image to reach down to 24-27 mag. All the JADES target acquisitions so far were successful, although the increased centroiding error for such extended targets may somewhat have reduced the alignment accuracy of the NIRSpec observations. In later spectroscopy, when NIRCam data was available, we used its imaging to select roughly circular compact galaxies and stars, using the multi-band near-IR photometry to more confidently estimate the fluxes in the NIRSpec CLEAR and F140X target acquisition filters and to enforce isolation criteria.', '5.4. NIRSpec Deep Spectroscopy': 'JADES features two long NIRSpec multi-object observations, each of 200 ksec total exposure time and both located in GOODS-S on the UDF and mostly inside the NIRCam Deep Prime footprint. The first pointing was designed to be observed early and be targeted using HST GOODS and CANDELS imaging, supplemented with other pre-JADES data. The second deep pointing will be observed at the end of the program and will use tar-  \nFigure 8. The observed distribution of F444W AB magnitude versus spectroscopic redshift for the Deep/HST pointing (top) and the first Medium/JWST pointing (bottom). The target selection has successfully weighted toward higher redshift galaxies, resulting in a more even redshift distribution.  \n<!-- image -->  \ngets from the full JADES imaging. We refer to these two pointings as Deep/HST and Deep/JWST, respectively.  \nThe NIRSpec Deep/HST observations occurred over three visits between 21 and 25 October 2022 at a V3PA of 321 · . As described above, these observations were intended to be targeted solely on pre-JWST data. Shortly before the scheduled visits, NIRSpec suffered some shorts on the MSA that required us to replan the MSA configurations for these observations. The NIRCam Deep Prime data were taken at the start of October, and an early reduction of the multi-band images and photometry catalogs were available. This enabled us to include some JWST-selected targets, at the expense of lower priority HST-selected targets, in the NIRSpec  \nobservations. We also re-prioritised the catalog using the NIRCam data to improve high-redshift photometric redshift accuracy, and to homogenize the selection in the lower priority classes with respect to the Deep/JWST to be based on the F444W filter. We note that the pointings of the observations were not changed, only the choice of which shutters to open. Two of the additional target galaxies with photometric redshifts from the NIRCam imaging (Robertson et al. 2023a) were spectroscopically confirmed in Deep/HST to lie at the highest redshifts known of 12.6 and 13.2 (Curtis-Lake et al. 2023).  \nThe NIRSpec Deep spectroscopy utilizes five dispersers: the prism and four gratings: G140M/F070LP, G235M/F170LP, G395M/F290LP, and G395H/F290LP. The prism is observed for 100 ksec, and the gratings for 25 ksec each.  \nEach pointing uses slitlets of 3 shutters, with the 3point nod. To provide additional pixel diversity and some dithering in the spectral direction, we design 3 subpointings for each pointing, typically separated by 3-5 shutters in the dispersion direction and 1-2 shutters in the spatial direction such that the optimal common coverage of the highest priority targets in all three dithered pointings is achieved. This results in the target light from a given wavelength for the majority of sources appearing in up to 9 pixel locations. As described earlier, there are actually 2 MSA designs for each sub-pointing (6 in total) because we use a separate configuration for the prism relative to that of the gratings. Each integration uses NRSIRS2 readout with 19 groups, yielding 1400 second apiece. We conduct two integrations per exposure. For the gratings, this means that each nod location is visited only once for 2 consecutive integrations. For the prism, the telescope repeats the nodding 4 times, with 2 integrations per time.  \nAs discussed in § 5.1, it is inevitable that not all targets can be placed on all three sub-pointings, even though this is our preference. We accept this and fill in some targets with only 1 or 2 sub-pointings. Using a smaller dither step increases the ability to repeat targets.  \nThis part of JADES is an investment of 145 hours and results in 111 prime open-shutter hours, a utilization of 76%. The exceptional line-flux sensitivity achieved as a function of wavelength is shown in Figure 9.', '5.5. NIRSpec Medium/JWST Spectroscopy': 'JADES includes 12 medium-depth pointings that are targeted from JWST imaging, but are otherwise scaled down versions of the Deep pointings. Relative to Deep, the prism is scaled down more than the gratings, reflecting the goal of studying the galaxy spectra in more  \ndetail. Exposure times are listed in Table 5. The original plan was 8665 sec in each of the 5 dispersion modes. However, small on-orbit changes in the timing model for parallel observations caused us to make small adjustments in the exposure times to be more efficient with the NIRCam parallels and to fit the program into the allocation.  \nAs with Deep, the observing uses 3-point nods with 3-shutter slits at each of 3 sub-pointing locations, for a total of 9 pixel dither locations. Each of these exposures is a single integration, using NRSIRS2 readout with 12 or 14 groups. As for the Deep pointings, some targets can only be placed on one or two sub-pointings, resulting in proportionally lower exposure time.  \nFour of the twelve Medium/JWST pointings are placed in GOODS-N and eight are in GOODS-S that has wider JADES NIRCam imaging. Three of the GOODSN pointings were observed between April 30 and May 5, 2023 at V3 PA 150.48 · , covering a large fraction of the NIRCam Medium Prime mosaic. The fourth was delayed by an observatory failure to acquire guide stars and was observed at V3 PA 132.93 · on May 27, 2023.  \nUnfortunately, this final JWST/Medium observation in GOODS-N was affected by a short circuit in the NIRSpec MSA for some configurations, which when triggered produced a glow of light that flooded the detectors, ruining the NIRSpec data (Rawle et al. 2022). Half of the configurations were affected by these shorts (two of three prism and one of three grating). The other three configurations did not address the susceptible column of the MSA and therefore did not have the glow. The possible effects on the NIRCam coordinated parallel imaging data are still being investigated at this time.  \nFor GOODS-S, four pointings are in the NIRCam Deep Prime mosaic, with the other four on the Medium Prime mosaic. Most of the GOODS-S Medium/JWST was delayed until Cycle 2, save one pointing observed on January 12 and 13, 2023, at V3 PA 56.17 · . The exact pointing positions and orientations of the remaining seven observations are still to be determined. The pointings will be based on the highest priority targets from the NIRCam Deep Prime, NIRCam Medium Prime and first NIRCam Deep parallel observations.  \nThis part of JADES is an investment of 222 hours, 77 in GOODS-N and 145 in GOODS-S, resulting in 146 prime open-shutter hours, a utilization of 66%. As before, the line detection sensitivity as a function of wavelength is shown in Figure 9.', '5.6. NIRSpec Medium/HST Spectroscopy': "The final tier is the shallowest and results from 'parallel' observations during ten of the NIRCam Medium  \nPrime fields, four in GOODS-N and six in GOODS-S. We remind that our naming convention is following the instrument that is driving our science design; in all coordinated parallels including NIRSpec MOS, NIRSpec is formally the prime instrument. The HST name refers to the fact that in the survey design, the JWST imaging was not yet available and hence the targeting was from HST data. We will describe explicitly the few cases we could use JWST-based targets, due to interruptions in the program.  \nAs the imaging program requires a large 7 '' offset to step over the V2-parallel SW chip gap, we opt to split each parallel opportunity into two largely distinct sets of targets. Offsets of this size when combined with the NIRSpec astrometric distortion at the MSA plane would otherwise cause many targets to become poorly registered within their slits. Each pointing in the mosaic was given a small 1 '' freedom of motion to optimize the slit centration of a few highest priority targets.  \nFor each of these 20 target sets, we use 4 dispersers, omitting the G395H higher resolution grating. Exposure times are listed in Table 5. GOODS-S was observed first, and here we used NRSIRS2 readout with 17 groups for the prism and 14 groups for the gratings, each observed once at each of 3 nod locations. Based on the first tranche of data in GOODS-S, we replanned GOODS-N so that the prism was observed twice with 14 groups at each pointing, to increase the S/N.  \nAs this program results from the parallels of a reasonably tightly packed imaging mosaic, these NIRSpec MOS fields overlap substantially. However, any given object in the footprint of a single MSA pointing will often be poorly centered in its possible shutter, leading to many targets being rejected due to the low expected throughput. Collisions of prism spectral traces block many other targets. Therefore, several returns to a given area can be supported without much duplication. We do allow our targets to be observed twice (and our highest priority targets up to four times), if the slit registration is favorable.  \nOur observations of the GOODS-S portion of this mosaic (observations 25-30 of program 1180) were affected by two short circuits in the NIRSpec MSA, similar to those described in the previous section. Some configurations did not use these columns of the MSA and therefore did not have the glow. The NIRCam coordinated parallel imaging data was unaffected in most cases, but the first half of observations 25 and 30 suffer from a short so bright that the illumination even reached NIRCam, as described in § 4.6.  \nOnly 4 of the 12 target sets were successfully observed without a bright short glow, and even in these cases  \nFigure 9. The unresolved line detection limit as a function of wavelength for two JADES NIRSpec tiers. We assume a well-centered point source and use a 10 σ detection threshold. The blue long lines are the prism, while the orange, green, and cyan lines are the three R = 1000 gratings. The solid lines show the depth in the Deep/HST pointing, while the dashed lines are a representative Medium/JWST pointing. For an unresolved line, the G395H grating has a similar line detection limit to G395M plotted here.  \n<!-- image -->  \nthere is some persistence that affects the prism exposure in a small portion of the image. These are MSA configurations 2, 4, 6, and 10, which are the second half of observations 25, 26, 27, and 29, respectively. For a 5th target set (configuration 5, the first half of observation 26), the grating exposures are unaffected, but the prism exposures were flooded by the short. We plan to complete this 5th set with a return in October 2023.  \nOne of the target sets was not observed due to an unrelated telescope issue (configuration 12, second half of observation 30). As the first half of observation 30 was badly affected by shorts, we will perform a complete repeat of this pointing in October 2023 at the original position angle, albeit with a different set of targets based on NIRCam selection.  \nThe other 5 target sets were re-observed on January 27 & 28, 2023, without new NIRCam parallels. Because the new position angle was already going to require a complete re-plan, we opted to collect the 5 single-nod designs into two pointings with smaller dithers, akin to the Medium/JWST program. Observation 134 has two subpointings; observation 135 has three. For these, we use the same NIRCam-based target selection that was used for the first Medium/JWST observation in GOODS-S.", '5.7. Data Quality Caveats': 'The NIRSpec MOS observations have been processed by using a pipeline developed by the ESA NIRSpec Science Operations Team and the NIRSpec GTO Team. The major steps of the data processing are described in (Bunker et al. 2023a), while a detailed description of the pipeline and its performance will be reported in a forthcoming paper (Carniani, in prep.). Here we discuss the main issues encountered during the data processing and analysis phase.  \nAs mentioned in the previous sections, program 1180 was affected by short circuits in the NIRSpec MSA that produced bright glows of artificial light, ruining most of the exposures. In particular, 76 out of 132 exposures are ruined by such a bright glow. The other exposures did not suffer from this problem, but we found some persistence for the prism exposures that contaminate the spectra of ∼ 10% targets in the MSA design. In some cases, the signal of the persistence is as high as the sky background emission.  \nBy inspecting the count rate maps before background subtraction, we noticed that some shutters dedicated to the targets did not open (Rawle et al. 2022). We excluded these temporarily failed shutters from the data processing workflow. In each pointing, we found, on average, that ∼ 1% of the targets in the MSA masks are affected by this issue. In most cases, only one of the 3-slitlet shutters was unexpectedly closed, but there are the same targets in which two or even all three shutters did not open during the observations. In these cases, the noise of the final products increases as the total exposure time is reduced.  \nAlthough the target selection was optimized to adopt the 3-point nod strategy for the background subtraction process, some background shutters were contaminated by either background or foreground source. We have thus exploited either HST or NIRCam images to identify automatically contaminated shutters and excluded them in the background subtraction steps of the pipeline. This increases the noise of the background subtraction image but avoids a possible over-subtraction of background emission that could alter the final spectra of the targets.', '6.1. MIRI Deep Parallel': "The NIRCam Deep Prime program creates very deep MIRI parallels in GOODS-S, totaling 43.1 hrs of openshutter time in each of the four fields. The fields overlap only slightly, so that the deep area is about 9 arcmin 2 .  \nThe fields were designed to overlap the NIRCam Medium Parallel mosaic, but it turned out that one of the NIRCam Deep Parallel fields substantially overlaps  \nTable 6. Summary of MIRI Observations. The number of pointings, area in arcmin 2 , exposure times per filter, and the final AB magnitude detection threshold per filter for a 10σ point source. For GOODS-N Medium/MIRI and GOODS-S Deep/MIRI, these thresholds are based on or extrapolated from already obtained observations assuming a 0.4 '' aperture and aperturecorrected for both filters. The GOODS-S Medium/MIRI values are projected from GOODS-N Medium/MIRI. Note that the Deep/MIRI pointings partially overlap those of Medium/MIRI, but we do not coadd these exposure times when computing the depth. a One of the GOODS-S pointings is mildly shallower, with 5.6 and 21.5 ks of exposure in F770W and F1280W, respectively. b One of the GOODS-N pointings is mildly shallower, with 6.6 ks of exposure in F1280W. c To date, 61-94 ks have been obtained per pointing of GOODS-S Deep/MIRI.  \nFigure 10. RGB (F770W, F4442W, F335M) image of a trio of z ∼ 6 photometric redshift candidates detected in the GOODS-S JADES Deep/MIRI parallel (24-25.6 AB with SNR ∼ 20 -80 in F770W). All three are likely emission line galaxies, with H α in F444W. The leftmost candidate additionally has significant [OIII]5007 emission in the F335M medium band filter, resulting in a more purple color. The F770W probes the rest-frame 1 µ m emission, a powerful constraint on the properties of older stellar populations.  \n<!-- image -->  \nas well. This allows these MIRI images to provide a very deep look at the high-redshift universe. We note that while the MIRI fields are not on the UDF itself, they do fall near the center of the Chandra Deep Field South.  \nWe decided to focus this time to the study of restframe 1-2 µ m imaging of galaxies at redshifts above 3. For this, we selected the F770W filter as the most promising compromise between the rising background to the red and the lever arm relative to the deeper F410M  \nand F444W data. An example of robust F770W detections of a trio of z ∼ 6 photometric redshift candidates in the GOODS-S Deep/MIRI footprint can be seen in Figure 10. F770W is somewhat less sensitive in AB magnitude than F560W, but it more than doubles the logarithmic wavelength gap relative to 4.4 µ m, allowing it to better detect power-law deviations in the slope of the near-IR SED. The longer band is also less likely to suffer from rest-optical emission line contamination of the continuum light measurement; H α will enter F560W at 6 . 6 < z < 8 . 4, which might be at the frontier of detectability with these long exposures.  \nThe MIRI data must of course follow the NIRCam exposure times and dither pattern. To reduce data volume, we use SLOWR1 readout mode with 57 groups to yield a single integration of 1361 seconds per exposure. Each pointing then has 114 of these exposures, taken at 22 different dither points, for a total of 155.2 ksec. However, on short time scales, the MIRI data is taken cycling through 9 or 4 subpixel dither locations. The resulting 10 σ point source sensitivity is 27.1 AB (Table 6).", '6.2. MIRI Medium Parallel': 'In addition to the deep data, we conduct MIRI parallels with eight of the NIRCam Medium Prime pointings. Five of these are in GOODS-S and three in GOODS-N.  \nAs these data are considerably shallower and yet only mildly more area, we opt to focus on the science of intermediate-redshift galaxies ( z ∼ 3 -5), where we can place strong constraints on the stellar emission SED, such as the regime of the contribution from TP-AGB stars, robustly identify the rising continuum associated with AGN, and look for unusual SEDs. To accomplish these goals, we take moderately deep exposures in F770W and then use most of the time in the F1280W, which gains in sensitivity over the WISE W3 band by a factor of ∼ 1000. We note that some but not all of  \nthe medium area in GOODS-S is also covered by the far deeper F770W imaging from the Deep parallels. In GOODS-N, 2/3 of the MIRI pointings fall off of the planned NIRCam coverage, but are covered by CANDELS.  \nThe exposure times are listed in Table 6. In all pointings, the data set uses 6 dither locations. The dither locations have 3 close pairs with relatively long strides between them, and hence there is a relatively large boundary region that has only 2 or 4 exposures. However, since MIRI is Nyquist sampled, this was considered acceptable. We always use the SLOWR1 readout, so as to reduce the data rate. F770W uses 1 integration per readout; F1280W uses 2 or 3 to avoid saturation on the background. In GOODS-S, where the available exposure times are longer, we observe F770W once per dither location and return to F1280W four times. In GOODS-N, our exposures are shorter and we do not have any coverage from the Deep MIRI parallels; we therefore opt to include two exposures each of F770W and F1280W per dither location.', '6.3. Data Quality Caveats': 'So far, we have not encountered any substantial concerns with the MIRI data acquired. We did find that the subpixel dither pattern used in the first Deep data, based on the F770W PSF size, was smaller than we would have preferred to use for the generation of sky flats. We find this can be mitigated by generating sky flats from roughly contemporaneous exposures over multiple pointings. Nevertheless, we have increased the dither steps in later observations. Moreover, the return to the same Deep field in year 2 will improve the pixel sampling, so we expect this will not be a lasting concern.', '7. PREPARING FOR JADES': "Like many JWST observing programs, the JADES team engaged in substantial preparations for the data set. We were particularly driven by the tight time scale, likely at most 6 weeks, to provide targets for multiobject spectroscopic follow-up from the NIRCam and MIRI imaging. This central goal of the program requires image reduction, mosaicing, source detection, source photometry, photometric redshift generation, target selection, and MSA design to be ready to run in quick order. We also sought to prepare for analysis of the spectroscopy, most obviously for the data reduction, extraction, and spectral analysis, as clearly the spectroscopic results would be desired to feed into the processing of the second field to be observed.  \nPart of this preparation was inherent in the needs of the instrument teams to support a wider range of  \ncommissioning and early science observations. Most obviously, we rely on the effort to develop exposurelevel reduction software such as NCDhas written by K. Misselt and the pre-processing pipeline developed by the ESA NIRSpec Science Operations Team (Birkmann et al. 2022), which subsequently became the basis for the STScI stage 1 and 2 pipelines. To build and validate these tools pre-launch required creation of detailed codes to simulate instrument data: Guitarra 2 for NIRCam and the NIRSpec Instrument Performance Simulator (IPS; Dorner et al. 2016).  \nFor NIRCam, we used Montage 3 to combine the individual exposures into a mosaic. In order to identify outlier pixels (such as cosmic rays that have not been picked up by NCDhas), we first construct a medium-based mosaic, which we then projected this medium-based mosaic back to the individual exposures. We identified and masked outlier pixels that are 3 σ outliers. In a final step, we constructed the mean-based mosaic and fully propagated the errors.  \nAn important additional aspect of JADES preparation included optimizing our instrument configurations, integration times, and area to maximize our key science goals (e.g. bottom panel of Figure 4). To this end, we developed JAGUAR, a novel phenomenological model of galaxy evolution out to z ∼ 15 (JAdes extraGalactic Ultradeep Artificial Realizations; Williams et al. 2018) 4 , incorporating known galaxy abundances, flux, color, and morphology relations across redshift. A key utility of JAGUAR includes both mock SEDs and full-resolution spectra, which we generated using BEAGLE (Chevallard & Charlot 2016) based on selfconsistent models of stellar radiation and its transfer through the interstellar and intergalactic medium. Beyond survey design, JAGUAR also enabled simulation of realistic galaxy fields using mock imaging tools like Guitarra, mock NIRSpec spectra and optimizing our MSA design procedures.  \nWith these tools, JADES then performed data challenges, simulating mock galaxy fields down to individual ramps and then reducing the data to make high-level products. For NIRCam, this included mosaicing, object detection, photometry, and photometric redshifting. For NIRSpec, mock target lists were used to build MSA designs with the eMPT code (Bonaventura et al. 2023), and simulated spectra (Chevallard et al. 2018) were run through reduction and extraction to develop tools for  \nredshift and line flux estimation (Giardino et al. 2019). A key advantage of these data challenges was to define data models for the interfaces between segments of the analysis. They also allowed us to generate test suites to validate each segment.  \nJADES conducted Data Challenge 1 (DC1) to initiate this process. The NIRCam component of DC1 concentrated on a single visit of Proposal 1180 (Observation 7, Visit 2), which is part of the NIRCam Deep Prime pointings. The DC1 simulations used 9 ramps with 7 DEEP8 groups for all filters used in the original JADES deep survey design (F090W, F115W, F150W, F200W, F277W, F356W, F410M and F444W). The source catalog used for DC1 was derived solely from the JAGUAR mock catalog, where we assigned random positions in R.A and declination for the selected galaxies but in such a way to maintain the same surface density of galaxies as the JAGUAR parent sample.  \nThe NIRSpec component of DC1 was based on the NIRSpec Deep/JWST program. 200 point source galaxies with realistic JAGUAR spectra were simulated in the prism and medium resolution grating dispersers in each of the three Deep/JWST pointings. The data were processed with the NIRSpec IPS Pipeline Software (NIPS; Dorner et al. 2016). The resulting output was simulated, flux-calibrated, combined spectra for 370 galaxies, used to validate our choice of integration times for these faint targets (Giardino et al. 2019).  \nFollowing improvements in the code base, we then conducted Data Challenge 2 (DC2) as a set of more comprehensive exercises. DC2 covered about 2/3 of the area of the JADES survey in GOODS-S ( ∼ 80 arcmin 2 ) and included Deep and Medium NIRCam pointings, using the same setup as the planned observations (e.g., exposure time, read out mode, dither positions) as recovered from the APT file. In contrast to DC1, the DC2 simulations included the field-of-view distortions, particularly important to test the ability to make astrometrically correct mosaics in sky coordinates and accounting for pixel sub-sampling when constructing these mosaics. Cosmic-ray hits were also added to the individual ramps. The DC2 sample used a combination of the CANDELS (Grogin et al. 2011; Koekemoer et al. 2011) catalog with S'ersic parameters estimated by van der Wel et al. (2012) and objects from JAGUAR, which also provides S'ersic parameters. The latter enabled including objects beyond the apparent magnitude limit and redshift cutoff of the HST data. In this process, we used the positions and shapes of all observed galaxies and supplemented these with mock galaxies where a fraction of the latter were included until the counts in apparent magnitudes and redshifts were as close as  \npossible to the JAGUAR magnitude-redshift distribution. In addition to the galaxy catalog, we also created a separate set of images with stellar sources, that were used to verify the photometric calibration procedure. In both Data Challenges a few objects with abnormal colors and Population III galaxies (Zackrisson et al. 2011) were added to test the efficacy of algorithms being tailored to detect outliers. For DC2, HST fluxes were also calculated (though no HST images created) which were used to estimate the number of low-redshift contaminants in the photometric redshift calculation. For the JAGUAR galaxies in DC2, noise was added to the mock HST fluxes and uncertainties were estimated according to the depth of the available ancillary HST imaging.  \nFor NIRSpec, these data challenges not only served to verify and practice ingesting NIRCam-generated and -formated target catalogs and images into the NIRSpec target selection and MSA mask design work flow, but also provided a critical opportunity to augment the eMPT with needed features. In particular, we modified eMPT to be able to point the 'prime' NIRSpec instrument such that the 'secondary' NIRCam instrument achieved its intended elaborate mosaicking of the NIRCam Medium Prime fields described in Sections 4.2 and 5.6, while simultaneously exploiting the ≃ 1 arcsec level permissible deviations from the nominal NIRCam pointing pattern to optimize the parallel NIRSpec exposures such that the largest possible number of the highest priority HST targets were captured by the MSA. This task was further complicated by the peculiar manner in which the roll orientation of the NIRSpec MSA assigned to an observation by STScI does not refer to the center of the MSA, but rather to a reference point defined by median location of all targets contained in the NIRSpec input catalog entered into the APT (Bonaventura et al. 2023). Limiting the impact of this complication over the 6 . 4 ' lever arm between the field centers of the two instruments required an iterative approach in which the NIRSpec input catalog was gradually trimmed down to match the outer envelop of the final NIRSpec footprint.  \nThe NIRSpec component of DC2 simulated an approximation of the GOODS-South Medium/HST tier. The NIRCam source scene described above was used to assign spectra and morphologies to the known HST prioritized target catalog. The eMPT was exercised to determine the optimum set of six pairs of pointing locations, within the small tolerance allowed given that in the real Medium/HST a NIRCam mosaic would be made in parallel, that maximized the number of highest priority targets assigned shutters. The eMPT was then run to assign targets to shutters in order of priority class. Spectra were simulated and processed in a similar  \nmanner to DC1. One difference is that contaminants that would fall within the target or background shutter were included in the simulation to assess the effects of contamination.  \nTo manipulate these Data Challenges and to prepare for the real data, JADES also built visualization tools. To browse the sky, we developed FitsMap (Hausen & Robertson 2022), inspired in part by the Legacy Survey viewer led by D. Lang (Dey et al. 2019). FitsMap allows us to zoom and pan the sky, easily changing between image layers, with overlays from various catalogs that provide pop-up access to the database information. To study the SEDs and photometric redshift outputs, we developed JADESview 5 , which shows image thumbnails, photometric SEDs with best-fit template overlays, and photometric redshift likelihoods versus redshift.  \nWe have found these preparations to be invaluable in handling the in-flight data. That said, unsurprisingly the real data have presented additional challenges to which the team (and the community more broadly) must adjust. Our reduction of on-sky data will be described further in Rieke et al. (2023a) and Bunker et al. (2023a), as well as upcoming papers (Alberts et al., in prep.; Carniani et al., in prep.; Robertson et al., in prep; Tacchella et al., in prep.).", '8. CONCLUSIONS': "The JWST Advanced Deep Extragalactic Survey is bringing an ambitious deep imaging and spectroscopic infrared view of the GOODS-S and GOODS-N fields in the first cycle of JWST observing. With JADES, we use 545 hours of open-shutter dual-band NIRCam imaging and 240 open-shutter hours of MIRI imaging to cover about 220 arcmin 2 to very faint flux levels in 12 distinct bands. We then conduct extensive multi-object infrared spectroscopy using 339 open-shutter hours of NIRSpec MOS, observing over 5000 faint targets with both prism and grating dispersers.  \nThe resulting JADES imaging and spectra will provide an exquisite sample for the study of galaxy evolution. Already the data set has yielded many candidates at redshifts above 8 (Hainline et al. 2023) and provided spectroscopic confirmation of 5 galaxies at z > 10 (Robertson et al. 2023a; Curtis-Lake et al. 2023; Tacchella et al. 2023; Bunker et al. 2023b). The amount of detail in both imaging and spectroscopy is very impressive and is revealing high-redshift galaxies to be a diverse set, with clear variations in morphology, emission-line ratios, and star-formation histories (e.g. Dressler et al. 2023; Ends-  \nley et al. 2023; Looser et al. 2023a). The spectra reveal the imprint of reionization through variations in Lyman α emission (Saxena et al. 2023; Witstok et al. 2023a) and signatures of the Gunn-Peterson damping wing (CurtisLake et al. 2023).  \nAt the time of this writing, the GOODS-S data set has been about 40% completed, with half of the imaging and much of the follow-up spectroscopy to happen in the last quarter of 2023. The GOODS-N observing has been successfully completed.  \nJADES also provides a useful design example for deep surveys, which we have documented in this paper. We have found great value in the medium-band F335M and F410M imaging and provide examples to achieve high pixel-diversity in both imaging and spectroscopy. We have demonstrated how the multiplex of grating spectroscopy can be increased by allowing these spectra to overlap and using the shorter prism spectra to disambiguate emission lines. We are also confronting a number of challenges in carrying out the survey, such as recovering from lost data in a survey with substantial geometrical constraints and concerns with NIRCam persistence. We expect these will be useful learning experiences as the JWST mission matures.  \nAs listed in § 3.4, JADES is one of several extragalactic surveys being carried out in Cycle 1 of the JWST mission. These span a range of depth, areas, filter sets, and fields, and there is a productive complementarity in these choices. JADES is important because of its deep and reasonably wide coverage of the GOODS-S/HUDF and GOODS-N/HDF fields, where there is an awesome amount of multi-wavelength imaging and spectroscopy, and because of its close coordination of JWST imaging and spectroscopy.  \nThe first release of JADES data, focusing on year 1 Deep NIRCam imaging and NIRSpec multi-object spectroscopy on the HUDF, is presented in Bunker et al. (2023a) and Rieke et al. (2023a) and available at https://archive.stsci.edu/hlsp/jades and http: //jades.idies.jhu.edu/. Additional releases will follow successively in the coming year, and we post science updates from the survey at the JADES Collaboration website, https://jades-survey.github.io. JADES will provide the foundation for JWST's study of these two premier deep fields, and we look forward to many years of utilization and extension of this data set.  \nThe JADES Collaboration thanks the Instrument Development Teams and the instrument teams at the European Space Agency and the Space Telescope Science Institute for the support that made this program possible. We also thank our program coordinators at STScI for their help in planning complicated parallel observations.  \nProcessing for the JADES NIRCam data release was performed on the lux cluster at the University of California, Santa Cruz, funded by NSF MRI grant AST 1828315. This research makes use of ESA Datalabs (datalabs.esa.int), an initiative by ESA's Data Science and Archives Division in the Science and Operations Department, Directorate of Science. This work was performed using resources provided by the Cambridge Service for Data Driven Discovery (CSD3) operated by the University of Cambridge Research Computing Service (www.csd3.cam.ac.uk), provided by Dell EMC and Intel using Tier-2 funding from the Engineering and Physical Sciences Research Council (capital grant EP/T022159/1), and DiRAC funding from the Science and Technology Facilities Council (www.dirac.ac.uk).  \nMR, AD, EE, DJE, BDJ, BR, GR, FS, and CNAW acknowledge support from the NIRCam Science Team contract to the University of Arizona, NAS5-02015. DJE is further supported as a Simons Investigator. SAr acknowledges support from Grant PID2021-127718NBI00 funded by the Spanish Ministry of Science and Innovation/State Agency of Research (MICIN/AEI/ 10.13039/501100011033). AJB, AJC, JC, IEBW, AS & GCJ acknowledge funding from the 'FirstGalaxies' Advanced Grant from the European Research Council (ERC) under the European Union's Horizon 2020 research and innovation programme (Grant agreement No. 789056). AJC acknowledges funding from the 'FirstGalaxies' Advanced Grant from the European Research Council (ERC) under the European Union's Horizon 2020 research and innovation programme (Grant agreement No. 789056). ECL acknowledges support of an STFC Webb Fellowship (ST/W001438/1).  \nFunding for this research was provided by the Johns Hopkins University, Institute for Data Intensive Engineering and Science (IDIES). The Cosmic Dawn Center (DAWN) is funded by the Danish National Research Foundation under grant no.140. RM, WB, FDE, TJL, JS, LS, and JW acknowledge support by the Science and Technology Facilities Council (STFC) and by the ERC through Advanced Grant 695671 'QUENCH'. RM also acknowledges funding from a research professorship from the Royal Society. JW further acknowledges support from the Fondation MERAC. The research of CCW is supported by NOIRLab, which is managed by the Association of Universities for Research in Astronomy (AURA) under a cooperative agreement with the National Science Foundation. ALD thanks the University of Cambridge Harding Distinguished Postgraduate Scholars Programme and Technology Facilities Council (STFC) Center for Doctoral Training (CDT) in Data intensive science at the University of Cambridge (STFC grant number 2742605) for a PhD studentship. BRP acknowledges support from the research project PID2021-127718NB-I00 of the Spanish Ministry of Science and Innovation/State Agency of Research (MICIN/AEI/ 10.13039/501100011033) RS acknowledges support from a STFC Ernest Rutherford Fellowship (ST/S004831/1). CWo is supported by the National Science Foundation through the Graduate Research Fellowship Program funded by Grant Award No. DGE-1746060. DP acknowledges support by the Huo Family Foundation through a P.C. Ho PhD Studentship. H U gratefully acknowledges support by the Isaac Newton Trust and by the Kavli Foundation through a Newton-Kavli Junior Fellowship. LW acknowledges support from the National Science Foundation Graduate Research Fellowship under Grant No. DGE-2137419. MP acknowledges support from the research project PID2021-127718NB-I00 of the Spanish Ministry of Science and Innovation/State Agency of Research (MICIN/AEI/ 10.13039/501100011033), and the Programa Atracci'on de Talento de la Comunidad de Madrid via grant 2018-T2/TIC-11715 MSS acknowledges support by the Science and Technology Facilities Council (STFC) grant ST/V506709/1. REH acknowledges acknowledges support from the National Science Foundation Graduate Research Fellowship Program under Grant No. DGE-1746060. SC acknowledges support by European Union's HE ERC Starting Grant No. 101040227 - WINGS. The research of KB is supported in part by the Australian Research Council Centre of Excellence for All Sky Astrophysics in 3 Dimensions (ASTRO 3D), through project number CE170100013.", 'REFERENCES': '- -. 2019b, ApJS, 244, 16\n- Whitler, L., Endsley, R., Stark, D. P., et al. 2023a, MNRAS, 519, 157\n- Whitler, L., Stark, D. P., Endsley, R., et al. 2023b, arXiv e-prints, arXiv:2305.16670\n- Williams, C. C., Curtis-Lake, E., Hainline, K. N., et al. 2018, ApJS, 236, 33\n- Williams, C. C., Labbe, I., Spilker, J., et al. 2019, ApJ, 884, 154\n- Williams, C. C., Tacchella, S., Maseda, M. V., et al. 2023, arXiv e-prints, arXiv:2301.09780\n- Williams, R. E., Blacker, B., Dickinson, M., et al. 1996, AJ, 112, 1335\n- Withers, S., Muzzin, A., Ravindranath, S., et al. 2023, arXiv e-prints, arXiv:2304.11181  \nWitstok, J., et al. 2023a, submitted  \n- Witstok, J., Shivaei, I., Smit, R., et al. 2023b, arXiv e-prints, arXiv:2302.05468\n- Wright, G. S., Rieke, G. 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