Why a Multi-Cycle Treasury Program is Essential to Maximize JWST's Scientific Contributions to Galaxy Formation

Introduction

Two of the James Webb Space Telescope’s (JWST) primary science goals are “discovering and characterizing the first stars and galaxies”, and “understanding how these objects evolved into the galaxies we see in the nearby Universe” [39]. These questions – when the first galaxies emerged from the cosmic dark ages, how the first massive black holes formed, and how the heavy elements necessary for life were forged in the first stars —- together mark the genesis of our own Milky Way, and of the conditions that made life possible.

The fundamental importance of these questions has been called out by the past three Astronomy and Astrophysics decadal surveys, and formed the primary motivation for investing decades of effort and billions of dollars to making the JWST mission a reality. Most recently, the Astro2020 decadal identified “Cosmic Ecosystems: Unveiling the Hidden Drivers of Galaxy Growth” as a priority science area, stating: “An essential milestone on the pathway to revealing these drivers is a complete understanding of the formation and buildup of galaxies and their structures, stellar populations, metals, and central black holes over cosmic time. JWST is poised to revolutionize this subject by imaging and identifying galaxies out to some of the first generations during the epoch of reionization, and by obtaining deep redshifted ultraviolet–visible spectra for thousands of galaxies spanning the period from reionization to the present.” [77]. Other key questions identified by the Astro2020 science panels that JWST can address include: 1) What are the seeds of supermassive black holes and how do they grow? 2) How did the intergalactic medium and the first sources of radiation evolve from cosmic dawn through the epoch of reionization? 3) How do gas, metals, and dust flow into, through, and out of galaxies? 4) How do supermassive black holes form, and how is their growth coupled to the evolution of their host galaxies? [78]

JWST’s performance has been even better than expected, and the Universe has also cooperated by disclosing a bounty of unexpected discoveries. Despite the associated excitement, these discoveries have posed as many new questions as they have answered, and major goals of the JWST mission arguably remain un-achieved. A uniform, statistically controlled legacy dataset is now required to transform these discoveries into a quantitative physical understanding of early galaxy formation. Here we argue that this requires a coordinated and ambitious community-led strategy, demanding a significantly larger time allocation than has been approved through the standard TAC process to date. Over the past five years, the JWST user community has gained substantial expertise in designing observing strategies and in interpreting the resulting data. Now is the time for JWST to embark on the next phase of scientific discovery, by enabling these kinds of larger efforts.

Lessons from the Hubble Space Telescope

Large, ambitious extragalactic surveys with space telescopes have a long and successful legacy, beginning in 1995 when HST devoted ten consecutive days of telescope time to an apparently blank patch of sky, creating the iconic Hubble Deep Field [102]. While this program was considered a significant risk, and arguably never would have survived the standard peer-review TAC process, these observations revealed a universe teeming with galaxies at every stage of evolution, fundamentally changing our understanding of galaxy formation. The HDF pioneered an entirely new mode of “blank-field” astronomy, which is now the dominant observational paradigm for early universe discovery. Major advances in our empirical understanding of galaxy formation over the past three decades trace back to this lineage: from the HDF [102] (done in HST Cycle 5!) to the Hubble Ultra Deep Field [3] and Great Observatories Origins Deep Survey (GOODS, a GO program; [43]), to the Hubble Frontier Fields [66], and many in between. These programs were made possible through Director’s Discretionary Time (DDT). Their success led to the first HST Multi-Cycle Treasury (MCT) program call to enable programs far beyond what the standard TAC process could accommodate. This call resulted in three transformative programs: CANDELS [47, 60], the largest HST survey ever at the time, which mapped galaxy evolution across five legacy fields over 902 orbits; CLASH (524 orbits), which used cluster lensing to probe the high-redshift universe [86], paving the way for the HFFs; and PHAT (828 orbits), which resolved stellar populations across a third of the Andromeda galaxy [23]. DDT contributed roughly a third of the $\sim2250$ allocated orbits, with the remainder drawn from the GO pool. A second MCT call in 2023 yielded two programs now underway [58, 67].

Figure 1 shows the distribution of HST GO program sizes, which are predominantly $\le200$ orbits. Only Treasury/MCT and DDT programs exceed this threshold, accounting for all programs which exceed 400 orbits. Among these are the most transformative studies in galaxy evolution history which have continuously pushed back our redshift horizon to $z \sim4$ (HDF), $z \sim6$ (e.g., GOODS and COSMOS [90]), and $z \sim10$ (e.g., CANDELS and CLASH). These programs are highly impactful even 1–2 decades after survey completion, providing legacy data in the key fields which continue to be observed with JWST and other facilities today. GOODS and CANDELS are generating $\sim10$ and 5 citations/orbit/year even today. The gold histogram indicates the JWST GO program distribution – similar to HST, the TAC-gated GO programs rarely exceed 300 hr.

The Galaxy Formation Landscape and Key Unanswered Questions

The observable properties of galaxies are forged by a complex suite of multi-scale and multi-physics processes. Scaling relations (correlations between observable properties such as mass, internal velocity, size, star formation rate [SFR], and metallicity) encode these processes and are essential for constraining theories of galaxy formation. Over the past several decades, HST, Spitzer, and ground-based observations pushed our view of galaxy evolution ever farther back in cosmic time, revealing the evolution of these fundamental scaling relations and the emergence of the Hubble sequence.

Just prior to JWST’s launch, the redshift frontier had been pushed back to $z \sim10$ [e.g., [80, 31]]. Empirical extrapolations from these observations as well as the general consensus of theoretical models predicted that the cosmic SFR density and the number density of UV-bright galaxies would continue to decline towards even higher redshifts [with the exact rate of decline debated; e.g., [6, 79, 72]], forecasting that JWST should see few if any UV luminous galaxies at $z > 10$ in the initial rather small surveys. Instead, JWST has transformed our understanding of the very early universe by revealing that galaxies grow surprisingly fast and furiously at cosmic dawn, reaching unexpectedly high luminosities and masses, at earlier times than most pre-launch theoretical and empirical models predicted [e.g., 32, 49, 65, 1, 26]. Moreover, the exquisite capability of the NIRSpec instrument onboard JWST has not only confirmed the redshifts of many of these high-$z$ objects [e.g., 20, 2], but has begun to reveal their internal physical properties. These studies suggest that early galaxies have experienced significant chemical enrichment [7, 9]. Some have elemental abundance ratios and ISM properties that are significantly different from those of their lower redshift counterparts, and perhaps reflective of early star-cluster formation [e.g., 10, 96].

The highest-redshift spectroscopically confirmed galaxies identified with JWST to date are at redshifts of $z \simeq14$ [13, 74], and there are photometric candidates with redshifts as high as $z \gtrsim20$ [e.g., 84, 38, 16]. The inferred star formation histories and metallicities of the $z \simeq14$ objects strongly imply that they should have detectable progenitors at $z \gtrsim15$ [29]. Although these objects are apparently not composed of Pop III stars, JWST has found tantalizing, though hotly debated, hints of possible pockets of Pop III star formation at lower redshifts [e.g., 73, 69, 99]. Lyman-$\alpha$ emission has been discovered out to $z \sim13$ [103], indicating that regions of the Universe were already re-ionized at these surprisingly early epochs, and painting a picture of highly patchy reionization.

Another major discovery area is the study of early black hole growth at $z > 6$, via the measurement of Balmer emission lines tracing the AGN broad-line region [e.g., 50, 95]. In addition, JWST has discovered a mysterious population of objects termed “Little Red Dots” [LRDs; [71]], which have ultra-compact morphologies and unusual “V-shaped” spectral energy distributions, and are more common at $z > 4$ [59, 61]. The majority of LRDs exhibit very broad emission lines [45], leading to the interpretation that they are powered by supermassive black holes which may be overmassive relative to their host galaxies [e.g., 81, 48], but they are generally undetected in the X-ray and radio [37, 91], unlike traditional AGN. Their red nature is (typically) not linked to the presence of large amounts of dust [82, 14], complicating the interpretation in terms of the canonical AGN engine structure. Their physical nature remains highly debated, with interpretations ranging from accreting black holes with unusual accretion and obscuration properties [55] to alternative stellar-powered scenarios, including supermassive stars [76, 85, 63], star clusters [18], and quasi-stars [75, 4].

The ability to perform continuum and absorption-line spectroscopy of massive galaxies at $z \gtrsim4$ has revealed the existence of a surprisingly large population that apparently assembled and quenched their star formation very early and rapidly [12, 44]. Some of the tension with current simulations may be relieved by appealing to stellar population models with more realistic chemical abundance patterns [24], spatially resolved spectroscopy [22], and more sophisticated modeling of early star formation and AGN feedback [93, 28], but just how much remains to be seen. Furthermore, JWST imaging has revealed the emergence of well-developed structural and morphological features like bars, spheroids, and disks, earlier in cosmic history than previously thought [e.g. 54].

These discoveries lead to several open questions that JWST can uniquely address:

• When and how do the earliest galaxies first emerge from the cosmic dark ages, and which processes govern their star formation?

• Can we identify and characterize primordial Population III stars during their lives or their explosive deaths?

• What do the unusual elemental abundance patterns reveal about the formation modes of the first galaxies?

• When and how do the first massive black holes form, what are their masses, and what is their connection to the mysterious population of LRDs?

• How do massive galaxies form and quench so early and rapidly?

• When do the scaling relations that encode the physics regulating galaxy evolution first emerge, and how do they evolve across the first few billion years?

• When and how did reionization occur, and what were the powering sources?

The Limits of Existing Programs to Answer These Questions

The Limits of Existing Programs to Answer These Questions

Over the course of the first five cycles of JWST observations, inclusive of Early Release Science (ERS [33, 15]), Guaranteed Time Observation (GTO [27, 83, 89, 98]), and GO programs, the galaxy formation community has employed many of the telescope’s key observational modes. These include large multi-band NIRCam imaging surveys, utilizing both broad and medium-band filters, undertaken in well-studied legacy fields (e.g., JADES, CEERS, PRIMER, COSMOS-Web, MINERVA) and in lensing cluster fields (e.g., GLASS-ERS, CANUCS, UNCOVER, GLIMPSE, VENUS), while multi-epoch imaging campaigns have enabled high-redshift time-domain astrophysics (e.g., NEXUS, VENUS, PEARLS-NEP). Spectroscopic survey programs have utilized the NIRSpec MSA (e.g., JADES, CEERS, CAPERS, JWS3, RUBIES) and NIRCam grism (e.g., FRESCO, COSMOS-3D, CONGRESS) to assemble large samples. Smaller samples have been observed with NIRSpec and NIRISS to greater depths (e.g., SPURS, DIVER, DAJE, NGDEEP), and with the NIRSpec IFU to spatially map high-redshift galaxies (e.g., GA-NIFS, ALPINE-CRISTAL, REBELS-IFU, Black-THUNDER). MIRI imaging has been obtained in parallel for several NIRCam programs (e.g., CEERS, PRIMER, COSMOS-Web, MINERVA) and prime in the HUDF (e.g., MIDIS, SMILES, MIRAGE, MEOW), whereas MIRI spectroscopy has yet to be widely deployed over large samples.

Large quantities of data from ERS, Large, and GTO programs suitable for high-redshift analyses are now publicly available, and have been reduced into a science-ready state in archives such as the DAWN JWST Archive [53]. Public imaging data from multiple surveys have been combined to produce powerful statistical samples tracing the evolving galaxy UV luminosity function at $M_{\mathrm{UV}} \le-18$ to $z \sim15$ (and even, tentatively, to $z \sim18$; [34], and references therein), and the galaxy stellar mass function at $M_* \ge10^8 M_\odot$ to $z \sim9$ (and even, tentatively, to $z \sim13$; e.g., [101, 52]). Lensing enables the extension of the UV luminosity function $\sim2$ magnitudes fainter at $z \sim15$ [17, 62]. Spectroscopic emission-line measurements (e.g., H$\alpha$, H$\beta$, [OIII], [OII], [NeIII]) out to $z \sim10$ allow us to constrain the evolving fundamental baryonic scaling relations among galaxy SFR, stellar mass, metallicity, and chemical abundance patterns; measure the ionizing efficiency and burstiness of galaxy stellar populations; and reveal strikingly different relations between the masses of supermassive black holes and their host galaxies, compared to observations in the local universe.

Despite significant progress in uncovering the first billion years of galaxies with JWST enabled by this wealth of data, we identify several fundamental limitations of the currently available data:

• The surveyed imaging area is too small at the depth required to uncover a robust $z > 15$ photometric sample for spectroscopic follow-up (the deepest imaging [NGDEEP+MIDIS [65, 84] reaches $m_{\mathrm{lim}} \sim31$ over $\mathcal{O}(1\ \mathrm{arcmin}^2)$). Furthermore, the sample of galaxies at $z > 10$ with robust stellar masses based on MIRI rest-optical data is insufficient for determining the dominant physics behind the observed UV luminosity function evolution (bursty star-formation histories, enhanced star-formation efficiency; [25]).

• Despite efforts at photometric pre-selection [36, 97] and spectroscopic observations of low-mass systems at $z > 6$ [73, 69], we still lack any confirmed Pop III systems, as the current upper limits on metal-line fluxes do not reach the Pop III regime.

• There is no consensus regarding the underlying physical model for LRDs. Ongoing debate pertains to the mass scale of their SMBHs (e.g., [46]), or if LRDs even contain BHs (e.g., [18, 85]). Key problems include the heterogeneity of LRD selection criteria, and the small, biased and incomplete samples with high-quality spectra.

• Simulations [e.g. 100, 64] predict that disentangling BH seeding and accretion models will require pushing to either higher redshifts ($z \gtrsim9$) or lower-mass galaxies than probed by current samples [42]. Uncertainties in single-epoch SMBH estimates must also be surmounted [81, 92, 68, 88].

• Although large photometric samples of apparently quiescent galaxies have been assembled within the first 2 billion years of cosmic time ($z > 3$), the number with deep spectroscopic measurements [44, 11, 24] remains too incomplete to systematically constrain quenching models.

• Spectroscopic samples at $z \ge4$ have several critical limitations: (1) they are incomplete and biased towards higher than average sSFR values at low masses ($M_\ast< 10^{8.5}M_\odot$); (2) the subset of galaxies with sufficient depth for detecting multiple emission lines is still too small to perform robust evolutionary studies of galaxy scaling relations across multiple redshift bins at $z > 4$ [e.g. 19, 56]; (3) there is no comprehensive $R \gtrsim1000$ spectroscopic sample with sufficient statistics, which was also selected uniformly from NIRCam imaging [cf. JADES 8, 21]. Such uniform selection is essential for comparison with galaxy formation simulations.

• Ultradeep spectroscopy has proven particularly powerful for elucidating the origin of multiple chemical elements (C, N, O, Fe) in the earliest galaxies, the nature of massive stars, and the central regions of LRDs [e.g., 96, 5, 70, 94], yet the sample of distant galaxies with such coverage ($N < 100$) is too small for robust population studies.

The Time is Now for a JWST MCT-Scale Investment

While JWST is fully capable of acquiring the ambitious datasets needed to answer these questions, the distribution of approved JWST GO programs across Cycles 1-5 tells a clear story: the largest extragalactic GO programs (NEXUS [368 hr], VENUS [303 hr], and COSMOS-Web [255 hr]) represent the practical ceiling of what TACs are willing to approve, and several of these required multi-cycle strategies (both for scheduling and science reasons). The science described above demands larger time allocations: $\sim$ 1000-2000 hr. As discussed in many companion white papers, reaching $z > 15$ requires NIRCam imaging depths $\gtrsim1$ mag deeper than existing data ($\sim$100–150 hr/filter in a deep blank or lensed field to reach $m_{\lim} \sim32$, or $m_{\lim} \sim30$ over a substantially wide field). A spectroscopic survey capable of robustly constraining galaxy scaling relations dictates thousands of uniformly selected targets, across a wide dynamic range in source luminosity, requiring long integration times. The earliest black holes, (relatively) evolved stellar populations, and dust-obscured systems require MIRI imaging depths and areas significantly exceeding what has been achieved (tens of hours per filter over many pointings). Time domain science requires cadenced observations that are structurally impossible within a single-cycle program. One or more unified MCT programs will optimize survey design to most effectively use critical observing resources (such as the MSA) with uniform and well characterized selection functions, which are crucial for statistical studies and for addressing multiple science goals, as demonstrated by previous legacy surveys such as the SDSS.

While existing programs provide invaluable constraints, their heterogeneous selection criteria, depths, and observing strategies limit the construction of statistically complete and uniform samples. A comprehensive JWST MCT program would provide the scale, homogeneity, and multi-cycle continuity needed to address these interconnected science goals [e.g. 30, 57, 35, 51]. Such a program would naturally yield high-level data products, catalogs, and tools for comparison with theory.

A suite of extragalactic MCT programs is time-critical: as JWST completes its five-year prime mission, most instruments are still at peak performance, but there are modes that are at risk or already in reduced efficiency (e.g., longer wavelength MIRI, NIRSpec MSA growing stuck shutters). MCT programs over the next few cycles will maximize synergy with contemporary and upcoming facilities such as ALMA, Euclid, Roman, Rubin, SKA, PRIMA, and LISA; identify high-value science targets for the ELTs and ngVLA; and guide the scientific goals of the next-generation missions from X-ray to radio. Now is the time for bold, ambitious surveys to fully complete the picture of how galaxies evolve from first light in the universe to our Milky Way today, accomplishing the first two primary science goals for the JWST mission.

Authors – 420 Co-Signers From the Extragalactic Community

Alice Shapley¹, Steven L. Finkelstein^2,3, Rachel S. Somerville⁴, James Dunlop⁵, Adriano Fontana⁶, Pascal A. Oesch^7,8, Danielle A. Berg², Rachel Bezanson⁹, Maruša Bradač¹⁰, Gabriel Brammer⁸, Caitlin M Casey¹¹, John Chisholm², Emma Curtis-Lake¹², Mark Dickinson¹³, Xiaohui Fan¹⁴, Yuichi Harikane¹⁵, Harley Katz¹⁶, Pablo G. Pérez-González¹⁷, Brant E. Robertson¹⁸, Raffaella Schneider¹⁹, Abdurro’uf²⁰, Angela Adamo²¹, K. Aditya²², Jose M. Afonso^23,24, Belen Alcalde Pampliega²⁵, Hiddo Algera²⁶, Omar Almaini²⁷, Almudena Alonso-Herrero¹⁷, Javier Álvarez-Márquez¹⁷, Ricardo Amorín²⁸, Makoto Ando²⁹, Jacqueline Antwi-Danso³⁰, Lorena Aragüete Riesco³¹, Archana Aravindan², Karla Z. Arellano-Cordova³², Flor Denisse Arevalo Gonzalez³³, Junya Arita³⁴, Hakim Atek³⁵, Mic Bagley³⁶, William M. Baker³⁷, Guillermo Barro³⁸, Arghyadeep Basu³⁹, Andrew J. Battisti⁴⁰, Ryan Begley⁴¹, Peter Behroozi¹⁴, Sirio Belli⁴², Samantha Berek⁴³, Pietro Bergamini⁴⁴, Davide Bevacqua⁶, Souradeep Bhattacharya¹², Fuyan Bian⁴⁵, Longji Bing⁴⁶, Laura Bisigello⁴⁷, Torsten Böker⁴⁸, Leindert A. Boogaard⁴⁹, Sownak Bose⁵⁰, Sarah E. I. Bosman⁵¹, Martin A. Bourne¹², Gibson B. Bowling⁵², Michael Boylan-Kolchin², Larry D. Bradley⁵³, Volker Bromm², Greg L. Bryan⁵⁴, Andrew J Bunker⁵⁵, Denis Burgarella⁵⁶, Emilie Burnham⁵⁷, Cristina Cabello⁵⁸, Corentin Cadiou³⁵, Christopher Cain^59,60,52, Antonello Calabro’̀⁶, Riccardo Caleno^61,6, Alex J. Cameron^62,8, Pedro R. Capelo⁶³, Karina Caputi⁶⁴, Timothy Carleton⁵², Adam Carnall⁵, Stefano Carniani⁶⁵, Courtney Carreira¹⁸, Marco Castellano⁶, Michele Catone^66,47, Karin Cescon⁶⁷, Anirban Chakraborty⁶⁸, Jaclyn Champagne⁵³, Tsang Keung Chan⁶⁹, Chandana Chandrashekhar⁶², Stéphane Charlot³⁵, Owen Chase², Yingjie Cheng⁷⁰, Chloe M. Cheng³⁰, Hyunseop Choi⁷¹, Sunmyon Chon⁷², Nicholas Choustikov^60,59, Katherine Chworowsky², Leonardo Clarke¹, Nikko J. Cleri⁵⁷, R. K. Cochrane⁷³, Luis Colina¹⁷, Benjamin P. Collins⁷⁴, Thomas Connor⁷⁵, Christopher J. Conselice⁷⁶, M. C. Cooper⁷⁷, Ryan A. Cooper⁷⁸, Suchetha Cooray⁷⁹, Carla Cornil-Baïotto^80,81, Luca Costantin¹⁷, Nuno Miguel Andrez de Oliveira Covas⁸², Isa Cox⁸³, Weiguang Cui⁸⁴, Fergus Cullen⁵, Mirko Curti⁴⁴, Poulomi Dam⁸⁵, Romeel Davé⁵, Rebecca L. Davies⁸⁶, Kelcey Davis⁸⁷, Maya Debski^2,3, Alice Deconto-Machado⁸⁸, Guillaume Desprez⁸⁹, Miroslava Dessauges-Zavadsky⁷, Claudia Di Cesare⁹⁰, Jose M. Diego⁹¹, Floor van Donkelaar^59,60, Callum T. Donnan⁹², Nicole E. Drakos⁹³, Qiao Duan⁶⁰, Eiichi Egami¹⁴, Anna-Christina Eilers⁹⁴, Daniel J. Eisenstein⁹⁵, David Elbaz⁹⁶, Richard Ellis⁹⁷, Gaia Edes Esposito⁴⁷, Andreas L. Faisst⁹⁸, Marion Fardcy⁹⁹, Emanuele Paolo Farina^100,44, Qinyue Fei³⁰, Henry Ferguson⁵³, Juan Antonio Fernández Ontiveros³², Andrea Ferrara⁶⁵, Anna Ferré-Mateu¹⁰¹, Sophia R. Flury⁵, Maximilien Franco³⁵, Seiji Fujimoto³⁰, Lukas Furtak², Francesco Gabrielli¹⁰², Samuel Gagnon-Hartman⁶⁵, Prakash Gaikwad¹⁰³, Giovanni Gandolfi⁶, Enrico Garaldi¹⁰⁴, Ismael García-Bernete¹⁷, Eric Gawiser¹⁰⁵, Mauro Giavalisco⁴³, Steven Gillman⁶², Giovanni¹⁰⁶, Giorgia Girardi⁴⁷, Karl Glazebrook¹⁰⁷, Anniek Gloudemans¹³, Simon C. O. Glover¹⁰⁸, Nickolay Y. Gnedin¹⁰⁹, Sebastian Gomez², Mauro González-Otero¹¹⁰, Andrea Grazian⁴⁷, Luca Graziani¹⁹, Jenny E Greene¹¹¹, Thomas R. Greve⁶², Norman A. Grogin⁵³, Yicheng Guo¹¹², Ansh R. Gupta^2,3, Thales A. Gutcke¹¹³, Martin G. Haehnelt⁶⁰, Aryana Haghjoo¹¹⁴, ChangHoon Hahn², Santosh Harish⁵³, Pablo Arrabal Haro^115,116, Anishya Harshan¹¹⁷, Nimish P. Hathi¹¹⁸, Evanthia Hatziminaoglou^101,45, Calum Hawcroft⁵³, Matthew J. Hayes²¹, Kasper E. Heintz⁶², Jakob M. Helton⁵⁷, Aurélien Henry¹¹⁹, Michaela Hirschmann¹²⁰, Benne W. Holwerda¹²¹, Tiger Hsiao², Marc Huertas-Company^101,122, Taylor A. Hutchison², Anne Hutter¹²³, Patricia Iglesias-Navarro¹⁰¹, Felix Martinez III¹²⁴, Ryota Ikeda⁶⁷, Kohei Inayoshi¹²⁵, Akio Inoue¹²⁶, Kei Ito⁶², Lucy R. Ivey⁶⁰, Kartheik Iyer¹²⁷, Takuma Izumi¹²⁸, Mathilde Jauzac¹²⁹, Junehyoung Jeon², Tae Bong Jeong², Christian Kragh Jespersen³⁰, Shuowen Jin$^{130}$, Gareth C Jones$^{60,131}$, Tucker Jones$^{132}$, Brenda L. Jones$^{133}$, Stephanie Juneau$^{13}$, Intae Jung$^{134}$, Ignas Juodžbalis$^{135}$, Darshan Kakkad$^{12}$, Jeyhan S. Kartaltepe$^{83}$, Shreya Karthikeyan$^{1}$, Gourav Khullar$^{136}$, Taysun Kimm$^{137}$, Tomokazu Kiyota$^{128}$, Dale Kocevski$^{138}$, Anton M. Koekemoer$^{53}$, Vasily Kokorev$^{2}$, Mitsuru Kokubo$^{139}$, Hyunsu Kong$^{140}$, Sophie Koudmani$^{12}$, Mariska Kriek$^{141}$, Nimisha Kumari$^{53}$, Haruka Kusakabe$^{142}$, Alvaro Labiano$^{143}$, Erini Lambrides$^{144}$, Ivanna Langan$^{17}$, Danial Langeroodi$^{60}$, Andrea Lapi$^{145}$, Muhammad Latif$^{146}$, Khee-Gan Lee$^{147}$, Joohyun Lee$^{2,3}$, Joel Leja$^{57}$, Gene C. K. Leung$^{148}$, Ho-Hin Leung$^{5}$, Zi-Jian Li$^{149}$, Mingyu Li$^{150}$, Yongming Liang$^{128}$, Yongming Liang$^{128}$, Xiaojing Lin$^{150}$, Weizhe Liu$^{14}$, Yuankang Liu$^{50}$, Mario Llerena$^{6}$, Federica Loiacono$^{44}$, Arianna S. Long$^{70}$, Christopher C. Lovell$^{60}$, Ting-Yi Lu$^{11}$, Alessandro Lupi$^{151}$, Georgios Magdis$^{62}$, Umberto Maio$^{152}$, Matthew Malkan$^{1}$, Filippo Mannucci$^{153}$, Rui Marques-Chaves$^{7}$, Sergio Martin-Alvarez$^{154}$, Zorayda Martinez$^{2,3}$, Nicholas S. Martis$^{10}$, Sara Mascia$^{90}$, Richard Massey$^{50}$, Jorryt Matthee$^{90}$, Lucio Mayer$^{155}$, Elizabeth J. McGrath$^{138}$, Derek J. McLeod$^{5}$, Shyam H Menon$^{4}$, Emiliano Merlin$^{47}$, Andrei Mesinger$^{156}$, Romain A. Meyer$^{7}$, Mar Mezcua$^{88}$, Iker Millan-Irigoyen$^{135}$, Takahiro Morishita$^{157}$, Takashi Moriya$^{128}$, Lauro Moscardini$^{158}$, Julian B. Munoz$^{2}$, Kentaro Nagamine$^{159}$, Yurina Nakazato$^{4}$, Themiya Nanayakkara$^{160}$, Lorenzo Napolitano$^{6}$, Desika Narayanan$^{161}$, Olof Nebrin$^{21}$, Dylan Nelson$^{162}$, Ivan Nikolić$^{62}$, Gaël Noirot$^{53}$, Pierre Ocvirk$^{163}$, Kazuyuki Omukai$^{164}$, Yoshiaki Ono$^{165}$, Masafusa Onoue$^{126}$, Katherine Ormerod$^{166}$, Göran Östlin$^{21}$, Masami Ouchi$^{128,142}$, Fabio Pacucci$^{75}$, Anthony Pahl$^{167}$, Zhiwei Pan$^{168}$, Richard Pan$^{169}$, Casey Papovich$^{170}$, Robert Pascalau$^{60}$, Yingjie Peng$^{171}$, Laura Pentericci$^{6}$, Borja Pérez-Díaz$^{6}$, Elia Pizzati$^{75}$, Ava Polzin$^{172}$, Francesca Pozzi$^{173}$, Sedona H. Price$^{53}$, Maria Pudoka$^{14}$, Louis Quilley$^{76}$, Marc Rafelski$^{53}$, Raunaq Singh Rai$^{97}$, John Regan$^{174}$, Eniko Regos$^{175}$, Marta Reina-Campos$^{176}$, Martin P. Rey$^{177}$, Massimo Ricotti$^{178}$, Pierluigi Rinaldi$^{2,3}$, Daniel Roberts$^{179}$, Guido Roberts-Borsani$^{97}$, Giulia Rodighiero$^{180}$, Francisco Rodríguez Montero$^{181}$, William Roper$^{182}$, Lucie E. Rowland$^{45}$, Tirthankar Roy Choudhury$^{183}$, Elka Rusta$^{62}$, R. E. Ryan Jr$^{53}$, Kanak Saha$^{184}$, Bahareh S. Salmasi$^{185}$, Stefania Salvadori$^{186}$, Rasha M. Samir$^{187}$, Jenna Samuel$^{2,3}$, Ryan L. Sanders$^{188}$, Paola Santini$^{6}$, Daniel Schaerer$^{7}$, Jan-Torge Schindler$^{189}$, Dominik R.G. Schleicher$^{19}$, Francesco Shankar$^{190}$, Paul Shapiro$^{2}$, Xuejian Shen$^{75}$, Yue Shen$^{191}$, Irene Shivaei$^{17}$, Maddie Silcock$^{12}$, Robert Simcoe$^{192}$, Charlotte Simmonds$^{193}$, Raymond C. Simons$^{194}$, Renske Smit$^{195}$, Thomas M. Stanton$^{5}$, Elizabeth R. Stanway$^{196}$, Mauro Stefanon$^{197}$, Massimo Stiavelli$^{53}$, Maria C. Straight$^{2}$, Amber Straughn$^{198}$, Yuma Sugahara$^{199}$, Yang Sun$^{14}$, Guochao Sun$^{200}$, Sandro Tacchella$^{131}$, Margherita Talia$^{173}$, Yoichi Tamura$^{201}$, Takumi Tanaka$^{202}$, Masayuki Tanaka$^{128}$, Maxime Tarrasse$^{203}$, Anthony J. Taylor$^{2,3}$, Elizabeth Taylor$^{5}$, Wei Leong Tee$^{57}$, Chamilla Terp$^{62}$, Dewachter Tim$^{204}$, Yoshiki Toba$^{205}$, Daisuke Toyouchi$^{159}$, Alberto Traina$^{206}$, Benny Trakhtenbrot$^{207}$, Michele Trenti$^{208}$, Tommaso Treu$^{1}$, Nikolaos Triantafyllou$^{65}$, Alessandro Trinca$^{6}$, Roberta Tripodi$^{6}$, Jonathan R. Trump$^{209}$, Takafumi Tsukui$^{210}$, Jack C. Turner$^{46}$, Hannah Übler$^{211}$, Hideki Umehara$^{201}$, Anavi Uppal$^{18}$, Eros Vanzella$^{44}$, Alessandra Venditti$^{2,3}$, Giacomo Venturi$^{153}$, Enrico Veraldi$^{145}$, Aswin P Vijayan$^{46}$, Natalia C. Villanueva$^{2,3}$, Fabio Vito$^{44}$, Mark Vogelsberger$^{212}$, Marta Volonteri$^{35}$, Benedetta Vulcani$^{47}$, Fabian Walter$^{213}$, Feige Wang$^{214}$, Tao Wang$^{203}$, Bingjie Wang$^{111}$, John R. Weaver$^{215}$, Arjen van der Wel$^{216}$, Andrew Weldon$^{170}$, Katherine E. Whitaker$^{43,62}$, Stephen Wilkins$^{52}$, Hayley Williams$^{12}$, Christopher N. A. Willmer$^{14}$, Rogier Windhorst$^{52}$, John H. Wise$^{217}$, Eden Wise$^{2}$, Joris Witstok$^{62,8}$, Ian E. Wolter$^{218}$, Zihao Wu$^{75}$, Yunjing Wu$^{219}$, Po-Feng Wu$^{220}$, Mengyuan Xiao$^{7}$, Haojing Yan$^{221}$, Hiroto Yanagisawa$^{165,222}$, Jinyi Yang$^{214}$, Guang Yang$^{223}$, L. Y. Aaron Yung$^{224}$, Erik Zackrisson$^{225}$, Tommaso Zana$^{226}$, Anita Zanella$^{44}$, Zijian Zhang$^{125}$, Huanian Zhang$^{227}$, Saiyang Zhang$^{3}$, Hao Zhang$^{228}$, Haowen Zhang$^{229}$, Roy J. Zhao$^{230}$, Dazhi Zhou$^{231}$, Yongda Zhu¹⁴, Ming-Yang Zhuang²³², Adi Zitrin²³³

¹ University of California, Los Angeles, CA 90095, USA ² Department of Astronomy, The University of Texas at Austin, Austin, TX, USA ³ Cosmic Frontier Center, The University of Texas at Austin, Austin, TX, USA ⁴ Center for Computational Astrophysics, Flatiron Institute, New York, NY 10010, USA ⁵ Institute for Astronomy, University of Edinburgh, Royal Observatory, Blackford Hill, Edinburgh EH9 3HJ, UK ⁶ INAF – Osservatorio Astronomico di Roma, Via Frascati 33, I-00078 Monte Porzio Catone, Italy ⁷ Department of Astronomy, University of Geneva, Chemin Pegasi 51, 1290 Versoix, Switzerland ⁸ Cosmic Dawn Center (DAWN), Niels Bohr Institute, University of Copenhagen, Jagtvej 128, DK-2200 Copenhagen, Denmark ⁹ University of Pittsburgh ¹⁰ University of Ljubljana, Faculty of Mathematics and Physics, Jadranska ulica 19, SI-1000 Ljubljana, Slovenia ¹¹ University of California, Santa Barbara, CA 93106, USA ¹² Centre for Astrophysics Research, University of Hertfordshire, Hatfield AL10 9AB, UK ¹³ NSF NOIRLab ¹⁴ Steward Observatory, University of Arizona, 933 North Cherry Avenue, Tucson, AZ 85721, USA ¹⁵ Department of Astronomy, Graduate School of Science, Kyoto University, Kitashirakawa-Oiwakecho, Sakyo-ku, Kyoto 606-8502, Japan ¹⁶ Department of Astronomy & Astrophysics, University of Chicago, 5640 S Ellis Avenue, Chicago, IL 60637, USA ¹⁷ Centro de Astrobiología (CAB), CSIC-INTA, Ctra. de Ajalvir km 4, E-28850 Torrejón de Ardoz, Madrid, Spain ¹⁸ Department of Astronomy and Astrophysics, University of California, Santa Cruz, CA 95064, USA ¹⁹ Sapienza University of Rome ²⁰ Department of Astronomy, Indiana University, 727 East Third Street, Bloomington, IN 47405, USA ²¹ Department of Astronomy, Stockholm University, AlbaNova University Centre, SE-10691 Stockholm, Sweden ²² Instituto de Estudios Astrofísicos, Facultad de Ingeniería y Ciencias, Universidad Diego Portales, Av. Ejército 441, Santiago, Chile ²³ Instituto de Astrofísica e Ciências do Espaço, Portugal ²⁴ Faculdade de Ciências da Universidade de Lisboa, Portugal ²⁵ SKA Observatory, Jodrell Bank, SK11 9FT, UK ²⁶ Institute of Astronomy and Astrophysics, Academia Sinica (ASIAA), Taipei 106319, Taiwan ²⁷ University of Nottingham ²⁸ Instituto de Astrofísica de Andalucía (IAA-CSIC) ²⁹ Institute for Cosmic Ray Research, University of Tokyo ³⁰ David A. Dunlap Department of Astronomy and Astrophysics, University of Toronto, Toronto, ON M5S 3H4, Canada ³¹ Universidad de Granada, Departamento de Física Teórica y del Cosmos. Avenida de Fuentenueva S/N, 18071, Granada, Spain ³² Centro de Estudios de Física del Cosmos de Aragón (CEFCA), Plaza San Juan 1, 44001 Teruel, Spain ³³ INAF – Department of Astronomy, School of Science, The University of Tokyo, 7-3-1. Hongo, Bunkyo, Tokyo 113-0033, Japan ³⁴ Institut d’Astrophysique de Paris, Sorbonne Université, CNRS, UMR 7095, 98 bis bd Arago, 75014 Paris, France ³⁵ SURA/NASA Goddard ³⁶ DARK, Niels Bohr Institute, University of Copenhagen, Jagtvej 155A, DK-2200 Copenhagen, Denmark ³⁷ DARK, Niels Bohr Institute, University of Copenhagen, Jagtvej 155A, DK-2200 Copenhagen, Denmark ³⁸ University of the Pacific ³⁹ Centre de Recherche Astrophysique de Lyon (CRAL) ⁴⁰ (1) International Centre for Radio Astronomy Research, University of Western Australia, 7 Fairway, Crawley, WA 6009, Australia (2) Research School of Astronomy and Astrophysics, Australian National University, Weston Creek, ACT 2611, Australia ⁴¹ Armagh Observatory and Planetarium, College Hill, Armagh, BT61 9DG, N. Ireland, UK ⁴² Università di Bologna, Italy ⁴³ University of Massachusetts Amherst, 710 North Pleasant Street, Amherst, MA 01003, USA ⁴⁴ INAF – Osservatorio di Astrofisica e Scienza dello Spazio di Bologna, via Gobetti 93/3, I-40129 Bologna, Italy ⁴⁵ European Southern Observatory (ESO), Karl-Schwarzschild-Str. 2, 85748 Garching, Germany ⁴⁶ Astronomy Centre, University of Sussex, Falmer, Brighton BN1 9QH, UK ⁴⁷ INAF – Osservatorio Astronomico di Padova, Vicolo dell’Osservatorio 5, 35122 Padova, Italy ⁴⁸ European Space Agency ⁴⁹ Leiden Observatory, Leiden University, PO Box 9513, NL-2300 RA Leiden, The Netherlands ⁵⁰ Institute for Computational Cosmology, Durham University, South Road, Durham DH1 3LE, UK ⁵¹ Institute for Theoretical Physics, University of Heidelberg ⁵² School of Earth and Space Exploration, Arizona State University, Tempe, AZ 85287, USA ⁵³ Space Telescope Science Institute, 3700 San Martin Drive, Baltimore, MD 21218, USA ⁵⁴ Columbia University ⁵⁵ Department of Physics, University of Oxford, Denys Wilkinson Building, Keble Road, Oxford, OX1 3RH, UK ⁵⁶ Aix Marseille Université, CNRS, CNES, LAM, Marseille, France ⁵⁷ Department of Astronomy and Astrophysics, The Pennsylvania State University, University Park, PA 16802, USA ⁵⁸Departamento de Fisica y Matematicas, Universidad de Alcala, Campus Universitario, E-28871 Alcala de Henares, Madrid, Spain ⁵⁹Institute of Astronomy, University of Cambridge, Madingley Road, Cambridge CB3 0HA, UK ⁶⁰Kavli Institute for Cosmology, University of Cambridge, Madingley Road, Cambridge CB3 0HA, UK ⁶¹Dipartimento di Fisica, Sapienza Università di Roma, Piazzale Aldo Moro 2, 00185 Roma, Italy ⁶²Cosmic Dawn Center (DAWN), DTU Space, Technical University of Denmark, 2800 Kgs. 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