# The Next Generation Deep Extragalactic Exploratory Public (NGDEEP) Survey

Micaela B. Bagley Department of Astronomy, The University of Texas at Austin,
Austin, TX, USA  Nor Pirzkal ESA/AURA  Space Telescope Science Institute, 3700
San Martin Drive, Baltimore, MD 21218, USA  Steven L. Finkelstein Department
of Astronomy, The University of Texas at Austin, Austin, TX, USA
<EMAIL_ADDRESS>Casey Papovich Department of Physics and
Astronomy, Texas A&M University, College Station, TX, 77843-4242 USA  George
P. and Cynthia Woods Mitchell Institute for Fundamental Physics and Astronomy,
Texas A&M University, College Station, TX, 77843-4242 USA  Danielle A. Berg
Department of Astronomy, The University of Texas at Austin, Austin, TX, USA
Jennifer M. Lotz Gemini Observatory/NSF’s National Optical-Infrared Astronomy
Research Laboratory, 950 N. Cherry Ave., Tucson, AZ 85719, USA  Gene C. K.
Leung Department of Astronomy, The University of Texas at Austin, Austin, TX,
USA  Henry C. Ferguson Space Telescope Science Institute, 3700 San Martin
Drive, Baltimore, MD 21218, USA  Anton M. Koekemoer Space Telescope Science
Institute, 3700 San Martin Drive, Baltimore, MD 21218, USA  Mark Dickinson
NSF’s National Optical-Infrared Astronomy Research Laboratory, 950 N. Cherry
Ave., Tucson, AZ 85719, USA  Jeyhan S. Kartaltepe Laboratory for
Multiwavelength Astrophysics, School of Physics and Astronomy, Rochester
Institute of Technology, 84 Lomb Memorial Drive, Rochester, NY 14623, USA
Dale D. Kocevski Department of Physics and Astronomy, Colby College,
Waterville, ME 04901, USA  Rachel S. Somerville Center for Computational
Astrophysics, Flatiron Institute, 162 5th Avenue, New York, NY, 10010, USA  L.
Y. Aaron Yung NASA Postdoctoral Fellow  Astrophysics Science Division, NASA
Goddard Space Flight Center, 8800 Greenbelt Rd, Greenbelt, MD 20771, USA  Bren
E. Backhaus  Department of Physics, University of Connecticut, Storrs, CT
06269, USA  Caitlin M. Casey Department of Astronomy, The University of Texas
at Austin, Austin, TX, USA  Cosmic Dawn Center (DAWN), Denmark  Marco
Castellano INAF - Osservatorio Astronomico di Roma, via di Frascati 33, 00078
Monte Porzio Catone, Italy  Óscar A. Chávez Ortiz Department of Astronomy, The
University of Texas at Austin, Austin, TX, USA  Katherine Chworowsky
Department of Astronomy, The University of Texas at Austin, Austin, TX, USA
NSF Graduate Fellow  Isabella G. Cox Laboratory for Multiwavelength
Astrophysics, School of Physics and Astronomy, Rochester Institute of
Technology, 84 Lomb Memorial Drive, Rochester, NY 14623, USA  Romeel Davé
Institute for Astronomy, University of Edinburgh, Royal Observatory,
Edinburgh, EH9 3HJ, UK  University of the Western Cape, Bellville, Cape Town
7535, South Africa  Kelcey Davis NSF Graduate Research Fellow  Department of
Physics, 196 Auditorium Road, Unit 3046, University of Connecticut, Storrs, CT
06269, USA  Vicente Estrada-Carpenter Department of Astronomy & Physics, Saint
Mary’s University, 923 Robie Street, Halifax, NS, B3H 3C3, Canada  Adriano
Fontana INAF Osservatorio Astronomico di Roma, Via Frascati 33, 00078
Monteporzio Catone, Rome, Italy  Seiji Fujimoto Hubble Fellow  Department of
Astronomy, The University of Texas at Austin, Austin, TX, USA  Jonathan P.
Gardner Astrophysics Science Division, NASA Goddard Space Flight Center, 8800
Greenbelt Rd, Greenbelt, MD 20771, USA  Mauro Giavalisco Department of
Astronomy, University of Massachusetts, Amherst, MA 01003, USA  Andrea Grazian
INAF–Osservatorio Astronomico di Padova, Vicolo dell’Osservatorio 5, I-35122,
Padova, Italy
Norman A. Grogin Space Telescope Science Institute, 3700 San Martin Drive,
Baltimore, MD 21218, USA  Nimish P. Hathi Space Telescope Science Institute,
3700 San Martin Drive, Baltimore, MD 21218, USA  Taylor A. Hutchison NASA
Postdoctoral Fellow  Astrophysics Science Division, NASA Goddard Space Flight
Center, 8800 Greenbelt Rd, Greenbelt, MD 20771, USA  Anne E. Jaskot Department
of Astronomy, Williams College, Williamstown, MA, USA  Intae Jung Space
Telescope Science Institute, 3700 San Martin Drive, Baltimore, MD 21218, USA
Lisa J. Kewley Center for Astrophysics — Harvard & Smithsonian, 60 Garden
Street, Cambridge, MA 02138, USA  Allison Kirkpatrick Department of Physics
and Astronomy, University of Kansas, Lawrence, KS 66045, USA  Rebecca L.
Larson NSF Graduate Fellow  Department of Astronomy, The University of Texas
at Austin, Austin, TX, USA  Jasleen Matharu Cosmic Dawn Center, Niels Bohr
Institute, University of Copenhagen, Rådmandsgade 62, 2200 Copenhagen, Denmark
Priyamvada Natarajan Department of Astronomy, Yale University, 52 Hillhouse
Avenue, New Haven, CT 06511, USA  Department of Physics, Yale University, P.O.
Box 208121, New Haven, CT 06520, USA  Black Hole Initiative at Harvard
University, 20 Garden Street, Cambridge, MA 02138, USA  Laura Pentericci INAF
- Osservatorio Astronomico di Roma, via di Frascati 33, 00078 Monte Porzio
Catone, Italy  Pablo G. Pérez-González Centro de Astrobiología (CAB), CSIC-
INTA, Ctra. de Ajalvir km 4, Torrejón de Ardoz, E-28850, Madrid, Spain  Swara
Ravindranath Space Telescope Science Institute, 3700 San Martin Drive,
Baltimore, MD 21218, USA  Barry Rothberg Department of Physics and Astronomy,
George Mason University, 4400 University Drive, MSN 3F3, Fairfax, VA 22030,
USA  U.S. Naval Observatory, 3450 Massachusetts Avenue NW, Washington, DC
20392, USA  Russell Ryan Space Telescope Science Institute, 3700 San Martin
Drive, Baltimore, MD 21218, USA  Lu Shen Department of Physics and Astronomy,
Texas A&M University, College Station, TX, 77843-4242 USA  George P. and
Cynthia Woods Mitchell Institute for Fundamental Physics and Astronomy, Texas
A&M University, College Station, TX, 77843-4242 USA  Raymond C. Simons
Department of Physics, 196 Auditorium Road, Unit 3046, University of
Connecticut, Storrs, CT 06269, USA  Gregory F. Snyder Space Telescope Science
Institute, 3700 San Martin Drive, Baltimore, MD 21218, USA  Jonathan R. Trump
Department of Physics, 196 Auditorium Road, Unit 3046, University of
Connecticut, Storrs, CT 06269, USA  Stephen M. Wilkins Astronomy Centre,
University of Sussex, Falmer, Brighton BN1 9QH, UK  Institute of Space
Sciences and Astronomy, University of Malta, Msida MSD 2080, Malta

###### Abstract

We present the Next Generation Deep Extragalactic Exploratory Public (NGDEEP)
Survey, a deep slitless spectroscopic and imaging Cycle 1 JWST treasury survey
designed to constrain feedback mechanisms in low-mass galaxies across cosmic
time. NGDEEP targets the Hubble Ultra Deep Field (HUDF) with NIRISS slitless
spectroscopy (f${}_{\mathrm{lim,line},5\sigma}\approx 1.2\times$10-18
erg/s/cm2) to measure metallicities and star-formation rates (SFRs) for low-
mass galaxies through the peak of the cosmic SFR density ($0.5<z<4$). In
parallel, NGDEEP targets the HUDF-Par2 parallel field with NIRCam
($m_{\mathrm{lim},5\sigma}=30.6-30.9$) to discover galaxies to $z>12$,
constraining the slope of the faint-end of the rest-ultraviolet luminosity
function. NGDEEP overlaps with the deepest HST ACS optical imaging in the sky:
F435W in the HUDF ($m_{\mathrm{lim,F435W}}=29.6$), and F814W in HUDF-Par2
($m_{\mathrm{lim,F814W}}=30$), making this a premier HST+JWST Deep Field. As a
treasury survey, NGDEEP data is public immediately, and we will rapidly
release data products and catalogs in the spirit of previous deep field
initiatives. In this paper we present the NGDEEP survey design, summarize the
science goals, and detail plans for the public release of NGDEEP reduced data
products.

early universe — galaxies: formation — galaxies: evolution

††facilities: JWST (NIRCam, NIRISS), HST (ACS, WFC3)††software: Astropy
(Astropy Collaboration et al., 2013), Drizzle (Fruchter & Hook, 2002), JWST
Exposure Time Calculator (jwst.etc.stsci.edu), MIRAGE (mirage-data-
simulator.readthedocs.io), SciPy (Virtanen et al., 2020), STScI JWST
Calibration Pipeline (jwst-pipeline.readthedocs.io)

##  1 Introduction

Deep field observations push astronomical source detection to the faintest
accessible limits. They are often motivated by the wish to discover, count,
and study the most distant objects. Deep fields also survey the faintest
objects detectable at intermediate distances, constraining luminosity
functions and other statistical properties of the evolving galaxy population.

Although the Hubble Space Telescope (HST) Hubble Deep Field may be the most
iconic early deep field, it was not the first such observation. Astronomers
took deep images of “blank” high-latitude fields using photographic plates
(e.g., Kron, 1978; Koo, 1981) and CCDs (e.g., Tyson & Jarvis, 1979) and at
radio wavelengths (e.g., Windhorst et al., 1985). Measuring and analyzing
faint galaxy number counts was a popular pastime, motivated in part by
cosmological goals, but also providing evidence for the evolution of galaxies
with cosmic time and distance. Observations through two or more filters led to
the recognition of the abundant population of “faint blue galaxies” as further
evidence for an evolving galaxy population (Koo & Kron, 1992; Ellis, 1997),
and measurements with three or more filters were used to estimate galaxy
redshifts (Koo, 1985) and to identify very distant galaxy candidates via
distinctive color signatures caused by the redshifted Lyman break
(Guhathakurta et al., 1990; Steidel & Hamilton, 1992).

The first Hubble Deep Field (HDF, Williams et al., 1996) was conceived as a
public survey with non-proprietary data products available to any researcher.
The HDF data were indeed widely used by the community, and catalyzed extensive
follow-up imaging and spectroscopy from ground- and space-based observatories,
which further enriched the resources of widely-available data to study galaxy
evolution. The HDF was later observed with HST’s near-infrared camera NICMOS
(Thompson et al., 1998, 1999; Dickinson et al., 2000), detecting redshifted
optical rest frame light from galaxies out to $z\approx 3$ and extending the
wavelength baseline for photometric redshift and spectral energy distribution
(SED) analysis. The installation of a more sensitive Advanced Camera for
Surveys (ACS; Clampin et al., 2000) during the second Hubble servicing mission
motivated a Hubble Ultra Deep Field (HUDF, Beckwith et al., 2006a), with
subsequent infrared follow-up with NICMOS (Thompson et al., 2005), the HUDF
parallel program (Oesch et al., 2007), and later with the more sensitive WFC3
(Kimble et al., 2008) infrared channel (Oesch et al., 2010; Ellis et al.,
2013; Koekemoer et al., 2013; Illingworth et al., 2013). The deep infrared
data were used to identify and study galaxies with photometric redshifts as
high as $z\approx 12$.

Space observatories (e.g., Chandra, ISO, Spitzer, and Herschel) conducted
their own deep field programs at X-ray and mid- to far-infrared wavelengths,
typically in fields already surveyed by Hubble and ground-based facilities,
including the HDF and the HUDF. HST itself revisited its deep fields many
times, including deep observations using slitless spectroscopy with ACS and
WFC3 to measure redshifts and other spectral properties for faint objects
without spectroscopic pre-selection, including GRAPES and FIGS (PIDs 9793,
13779, PI S. Malhotra; Pirzkal et al. 2004; Malhotra et al. 2005; Rhoads et
al. 2009; Pirzkal et al. 2017).

The potential of JWST deep fields was evident immediately in Cycle 1 with the
Early Release Observation of the galaxy cluster and gravitational lens SMACS
0723.3-7327 (PID 2736, PI: K. Pontoppidan; Pontoppidan et al., 2022). The
GLASS-JWST Early Release Science Program (PID 1324, PI: T. Treu; Treu et al.,
2022) observed the Abell 2744 lensing galaxy cluster, obtaining spectroscopy
on the cluster with deep parallel imaging that reaches a 5$\sigma$ point
source depth of $\sim$30.2 mag in $\sim$15.7 hours (Paris et al., 2023). The
JADES (PID 1180 PI: D. Eisenstein, Eisenstein et al. 2017; 1210, 1286, 1287,
PI: N. Luetzgendorf, Ferruit 2017; Ferruit et al. 2017; Ferruit & Rieke 2017)
and MIRI Deep Survey (PID 1283, PI: H. U. Nørgaard-Nielsen and G. Östlin;
Norgaard-Nielsen & Perez-Gonzalez, 2017) GTO Programs are continuing the
legacy of deep imaging and spectroscopy in and around the HUDF. Together the
imaging portions of these early programs have easily detected galaxy
candidates out to $z\approx 16$ (e.g., Adams et al., 2022; Castellano et al.,
2022; Donnan et al., 2022; Harikane et al., 2022; Naidu et al., 2022;
Robertson et al., 2022a; Atek et al., 2023; Pérez-González et al., 2023),
while the spectroscopic portions of the programs are confirming galaxies from
$z\sim 7$ to 13 (e.g., Curtis-Lake et al., 2022; Roberts-Borsani et al., 2022;
Schaerer et al., 2022). These and other Cycle 1 surveys represent only the
beginning of the deep field science made possible by JWST’s great leap in
sensitivity and exquisite angular resolution.

Here we present the Next Generation Deep Extragalactic Exploratory Public
(NGDEEP, PID 2079, PIs: S. Finkelstein, C. Papovich, N. Pirzkal)
Survey111Originally named WDEEP in our Cycle 1 proposal, which follows in the
footsteps of previous treasury deep fields, probing a well-studied blank
region of the sky, and providing data to the community with no proprietary
period. NGDEEP leverages JWST’s parallel observation capabilities to obtain
_two_ deep fields for the price of one. NGDEEP primary observations are
comprised of deep NIRISS wide-field slitless spectroscopy (WFSS; Doyon et al.,
2012; Willott et al., 2022) covering the HUDF proper (Beckwith et al., 2006b).
At the same time, NGDEEP will obtain deep NIRCam imaging (Rieke et al., 2003,
2005, 2022) in parallel covering the HUDF05-02 parallel field. We refer to
these two observations as NGDEEP-NIS and NGDEEP-NRC, respectively.

Figure 1: Left: The NGDEEP logo. The hexagonal shapes represent JWST’s mirror,
with depictions of a variety of astrophysical objects, representing the
variety of science possible with our survey. The dispersion of colors
represents both the spectroscopic component of NGDEEP, and also the NGDEEP
team’s commitment to the inclusion of all members. Right: A summary of the
NGDEEP observing modes, key science drivers, and legacy data products.

NGDEEP is designed to illuminate the processes regulating galaxy evolution
across cosmic time. Galaxy evolution is the result of a complex interplay
between gas accretion from the cosmic web, the cooling and conversion of dense
gas into stars, pollution of the interstellar medium (ISM) with heavy
elements, and stellar– and black–hole driven feedback processes which can
disperse heavy elements into the circumgalactic and intergalactic media (CGM,
IGM). Feedback from massive stars and supernovae is a crucial element in
regulating galaxy formation and shaping observable properties of galaxies,
including their stellar mass, star formation history, gas fraction,
metallicity, and morphological structure (Somerville & Davé, 2015, and
references therein). Yet, the physical details of feedback remain highly
uncertain.

Current cosmological simulations cannot calculate the feedback processes
directly, thus they make assumptions which differ significantly from one
simulation to another (e.g., Somerville & Davé, 2015). Gaining insights into
how feedback works requires constraining the observables that are the most
sensitive to these divergent assumptions. This task includes testing the
inflows and outflows of heavy elements through observations of the
mass–metallicity relation, measuring the amplitude and timescales of star-
formation, and constraining star–formation efficiency in galaxies.

Together, both the primary NGDEEP-NIS and parallel NGDEEP-NRC observations
will constrain the mechanisms regulating feedback in low–mass galaxies. At
$z\sim 1-3$, NGDEEP-NIS will obtain spectroscopy of the diagnostic emission
lines in these $m_{\mathrm{UV}}\sim 28$ mag galaxies, leveraging the
multiplexing of NIRISS WFSS to measure S/N $>3$ (5) emission lines of over
2000 (1500) galaxies (see Table 2). These observations will enable (1)
measurements of multi-line metallicities for $>$350 galaxies at $z\sim$ 0.5–4
down to $\log(M_{\ast}/M_{\odot}){\sim}7$, testing predictions for the low-
mass slope of the mass-metallicity relation (MZR) where models currently
diverge (e.g., Ma et al., 2016); (2) measurements of H$\alpha$-based SFRs for
$\sim$1000 low-mass galaxies at $0.7\lesssim z\lesssim 2.3$ to $\sim$ 0.1
M⊙/yr, matching the UV SFR limit from the ultra-deep HUDF F435W imaging. This
will quantify the level of and constrain the effects of the stochasticity of
SFRs in galaxies 100$\times$ lower in mass than the best NIR spectroscopic
surveys (Kriek et al., 2015; Shivaei et al., 2015).

At $z>9$ low–mass galaxies are predicted to be $\sim$30 mag and are only
accessible by deep NIRCam imaging, thus NGDEEP-NRC will probe the population
of faint galaxies ($M_{\mathrm{UV}}=-17.5$, $10\sigma$) out to the highest
redshifts ($z\sim 10-15$), constraining the faint (low-mass) end of the rest-
UV luminosity (stellar mass) function via the discovery of $\sim$ 100 galaxies
at $z>$ 10, and up to 10 galaxies at $z\gtrsim$ 14\. This unique combination
of NIRISS prime spectroscopy and NIRCAM parallel imaging will provide in-depth
insight into galaxy evolution across cosmic time.

In this paper we present the NGDEEP survey, its design, scientific motivation,
and pre-survey predictions. In § 2 we present the survey design, field
orientation and observing timeline, describing the NGDEEP NIRISS (NGDEEP-NIS)
and NIRCam (NGDEEP-NRC) observations in § 2.3 and § 2.4, respectively. We
discuss the leading science cases for NGDEEP-NIS in § 3 and for NGDEEP-NRC in
§ 4. As part of the survey design and verification process, we performed end-
to-end simulations for both observations, which we present in § 5. Finally, we
outline our timeline for the public release of NGDEEP data products in § 6 and
briefly summarize in § 7. We express all magnitudes in the AB system (Oke &
Gunn, 1983) unless otherwise noted.

##  2 Survey Design

In this section, we describe the design of the NGDEEP survey and the
capabilities of each set of observations. We provide a high-level summary of
NGDEEP observations, science drivers, and planned legacy data products in
Figure 1.

Figure 2: The layout of NGDEEP. The background grayscale image is the exposure
time map of HST/ACS F814W imaging, shown with logarithmic scaling as given by
the scale bar. The NGDEEP NIRISS (NGDEEP-NIS) pointing is shown by the magenta
region (in the HUDF), while NGDEEP NIRCam (NGDEEP-NRC) is shown by the red
regions (in the HUDF Par2 parallel field) for one of our two position angles.
Extremely deep HST/ACS F435W imaging exists in the HUDF (Illingworth et al.,
2013), achieving depths of 29.6 AB mag (5$\sigma$, Illingworth et al. 2013),
while the deepest HST/ACS F814W imaging anywhere in the sky is in the HUDF
Par2 field. The inset tables show our expected line-flux sensitivities for
NGDEEP-NIS, and continuum sensitivities for NGDEEP-NRC. The image inset shows
a portion of the ACS F435W imaging, with sources near the detection limit
indicated by white boxes. At $z=2$ the $m_{435}$ magnitudes correspond to
rest-frame UV magnitudes of $M_{\mathrm{UV}}=-16.7$, or an unattenuated SFR of
$0.12$ $M_{\odot}$ yr-1 (Kennicutt & Evans 2012). This SFR would produce
H$\alpha$ fluxes detectable by our NIRISS spectroscopy.

###  2.1 Field Choice and Orientation

We center the NGDEEP-NIS observations on the HUDF to fully exploit the large
investment of HST observations. Imaging with HST/ACS $B$-band (F435W;
Illingworth et al., 2013) reaches a limiting depth of
m${}_{5\sigma\mathrm{,F435W}}=29.6$, sufficient to detect galaxies with UV-
based SFRs to $\sim$0.1 M⊙ yr-1 at $z\sim$ 2, which matches the NIRISS
H$\alpha$ SFR limit of the NGDEEP-NIS observations. Extremely deep WFC3/IR
imaging in the same region provides critical constraints on the stellar masses
of the star-forming galaxies (to log [M∗/M⊙] $\sim$ 7.3 at $z=$ 2). These data
in the HUDF are the deepest available. The separation between NIRISS and
NIRCam on the JWST field-of-view is similar to that of WFC3 and ACS, placing
our coordinated parallels on the HUDF05-02 parallel field (HUDF-Par2). This
field has been observed repeatedly with ACS while NICMOS and WFC3 observed the
HUDF (Stiavelli, 2005; Illingworth, 2009), building the deepest F814W imaging
on the sky ($m_{5\sigma,\mathrm{F814W}}=30.0$). While NIRCam alone can select
$z>$ 9 galaxies, these candidates will be strengthened by non-detections in
this ultra-deep optical image, which covers $\gtrsim$50% of our deepest NIRCam
data, and the deep F814W data also allows dropout-selection to $z\sim$ 7–9.

Centering the NIRISS primary data on the HUDF and placing NIRCam on HUDF-Par2
results in an observatory V3 position angle V3_PA = $\sim$70∘. We obtain the
NIRISS WFSS with both the row (R) and column (C) grisms to provide two-orient
observations. However based on our trade studies, simulated spectroscopy, and
previous work in the literature (Pirzkal et al., 2004; Ryan et al., 2018), an
additional position angle separated by $\sim\\!3^{\circ}$ will significantly
improve the contamination modeling, emission-line identification, and map-
reconstruction without sacrificing the spatial coverage of the HUDF. However,
splitting the observations across two position angles results in less area
covered at total depth for NIRCam. We therefore limit the difference in
position angle to $\Delta$(V3_PA)=3∘, the minimum acceptable for NIRISS
without sacrificing full-depth coverage for NIRCam. Therefore, each source in
the HUDF will be observed in four distinct position angles (V3_PA$=$67,70∘, R
and C grism). The deepest portion of the NIRCam parallel will cover 5 arcmin2
and will reach $\sim$0.5 mag shallower over 10 arcmin2.

In Figure 2, we present a visualization of the NGDEEP-NIS and NGDEEP-NRC field
centroids and orientations. The figure also provides a summary of some of the
existing HST datasets overlapping the NGDEEP observations.

###  2.2 NGDEEP Epochs 1 and 2

The strict position angle requirements for NGDEEP result in a limited window
of $\sim$10–16 days during which the program can be scheduled. Unfortunately,
on January 20, 2023, NIRISS experienced an unexpected software timeout. All
primary and coordinated parallel NIRISS observations were temporarily
suspended while the observatory and instrument teams diagnosed the problem.
When NIRISS observations resumed ten days later, there was not enough time to
observe the entire program before the NGDEEP observing window closed on
February 6. Instead, all observations from a single position angle (V3_PA=70∘)
were obtained in the remaining time. This Epoch 1 of NGDEEP includes all
grisms and filters but half of the total integration time for both
instruments. In Sections 2.3 and 2.4, we present the sensitivity and limiting
magnitude estimates that correspond to the total program time. Epoch 2
(V3_PA=67∘) will be observed in January 2024.

Table 1: NGDEEP Line Sensitivities and Limiting Magnitudes

Filter | SpecificationaaThe observing specification of the deepest observations in each filter/grism, listed as Readout pattern/groups per integration/integrations per exposure. The NGDEEP-NRC F115W, F150W, F200W and F356W filters have additional imaging, observed in parallel to the NIRISS-NIS direct imaging and taken with the SHALLOW4 readout pattern, 3 groups and 1 integration. | Exposure Time (h) | Sensitivity
---|---|---|---
NGDEEP-NIS | (erg s-1 cm-2)
F115W | NIS/20/6 | 52.2 | $1.2\times 10^{-18}$
F150W | NIS/20/8 | 34.8 | $1.3\times 10^{-18}$
F200W | NIS/20/6 | 17.4 | $1.5\times 10^{-18}$
NGDEEP-NRC | (AB mag)
F115W | DEEP8/4/7 | 53.9 | 31.2
F150W | DEEP8/5/7 | 23.0 | 30.9
F200W | DEEP8/4/7 | 18.0 | 30.9
F277W | DEEP8/5/7 | 22.3 | 30.9
F356W | DEEP8/4/7 | 20.8 | 30.8
F444W | DEEP8/4/7 | 51.8 | 30.7

Note. — Estimates for NGDEEP-NIS $5\sigma$ integrated emission line
sensitivities and NGDEEP-NRC $5\sigma$ resolved-source limiting magnitudes are
from v2.0 of the JWST ETC. These estimates are based on the full survey depth,
half of which (Epoch 1) was observed in February 2023.

Figure 3:  Left: The area covered in each NGDEEP-NRC filter as a function of
$5\sigma$ depth measured for resolved sources. The solid lines denote the full
survey (Epochs 1 and 2 covering both position angles), and the dashed line
shows the depth and area coverage achieved in Epoch 1 (V3_PA=70∘) for F277W as
an example. The dotted lines show the depths that will be achieved by the
JADES deep field observations in the HUDF once the survey is completed. While
JADES covers a larger area, NGDEEP-NRC will go $\sim$0.5 mag deeper in F444W
and $\sim$0.3 mag deeper in F115W, allowing for the detection of $z>9.5$
Ly$\alpha$-breaks in galaxies at the detection limit in the F150W, F200W and
F277W. As a treasury program, NGDEEP will also be public immediately,
providing the community the opportunity to explore a JWST deep field right
away in Cycle 1. Right: Exposure time maps in $10^{3}$ seconds for each of the
six NGDEEP-NRC filters. The overlapping position angles, NIRISS filter FWHM-
dependent direct imaging dithers, and short wavelength detector gaps result in
the multiple depth tiers that are present in the left panel.

###  2.3 NGDEEP-NIS Observations

The NGDEEP observations obtained in the HUDF with NIRISS (NGDEEP-NIS) will
provide deep $R\sim 150$ spectroscopy over $1-2.2$µm. The spectra will detect
emission lines from $>$1000 galaxies, many with multiple lines, down to a
limiting emission line flux of $1.2-1.5\times 10^{-18}$ erg s-1 cm-2
(5$\sigma$). This is not only much deeper than previous HST grism surveys
(e.g. Pirzkal et al., 2017; Momcheva et al., 2016), but extends the upper end
of the wavelength range covered from 1.7 $\mu$m to 2.2 $\mu$m (Figure 8).

Multi-line diagnostics for metallicity and dust content requires sampling [O
II], [O III], H$\beta$, and H$\alpha$. NGDEEP-NIS will obtain F115W, F150W,
and F200W spectroscopy in order to examine the redshift evolution of these
metrics (for $1.6<z<2.5$). As mentioned above, we will obtain spectroscopy in
both the R and C grisms as well as at two PAs separated by 3∘
(V3_PA$=$67,70∘). The grism exposures will be obtained with the NIS readout
pattern, 20 groups per integration and 6 integrations per exposures (8
integrations for F150W). We will use a 3 point dither pattern optimized for
NIRISS-NIRCam coordinated parallel observing. The total exposure times in
these three filters will be 190, 86, and 63 ks, respectively. Based on 1D
outputs from the JWST Exposure Time Calculator (ETC, v2.0) and optimal
extractions of our simulated NGDEEP-NIS observations (see §5.1), NGDEEP-NIS
will reach $1.2-1.5\times 10^{-18}$ erg s-1 cm-2 ($5\sigma$). This allows us
to measure metallicities at $\sim$0.2 dex precision down to
log($M_{*}$/M⊙)$=$7 at $z=$ 2 (see §3). We summarize the NGDEEP-NIS observing
specifications, exposure times, and line sensitivities in Table 1. These
observations include direct imaging in the F115W, F150W, and F200W filters
with total exposure times of 10.8, 3.6, and 3.6 ks, reaching m${}_{AB}=$ 29.5,
29.0, and 29.1 (3 $\sigma$), respectively, deep enough to identify the faint
continuum of contaminating sources. Our NGDEEP-NIS simulations (§5)
demonstrate we will detect emission lines ($\geq$ 3$\sigma$) in $>$1000
galaxies (see Table 2).

While the NIRSpec GTO team targets this field with NIRSpec (PI: N
Luetzgendorf, PID 1210), examination of their pre-launch APT file finds that
only $\sim$80 objects in the HUDF will receive slits with $t\\!=$8 ks. Early
results from these GTO observations are already revealing the exquisite
sensitivity of JWST spectroscopy, with spectroscopic confirmations of four
galaxies at $z>10$ (Curtis-Lake et al., 2022; Robertson et al., 2022a). NGDEEP
will expand this legacy, with $>$1000 galaxies receiving 60–190 ks
spectroscopic integrations.

###  2.4 NGDEEP-NRC Observations

The NGDEEP observations obtained in the HUDF-Par2 field with NIRCam (NGDEEP-
NRC) will provide deep imaging from $\sim$1–5 $\micron$. Imaging in
F115W$+$F150W$+$F200W will sample below the Ly$\alpha$ break and the rest-UV
continuum for galaxies at $z>9$. We simultaneously observe with
F277W$+$F356W$+$F444W to fully sample the spectral energy distribution (SED)
and minimize sample contamination. The NIRCam observations will enable the
discovery of $\sim$30–100 galaxies at $z\gtrsim$ 11 and constrain the faint-
end of the rest-UV luminosity function where stellar feedback model
predictions differ the most. NGDEEP-NRC will also constrain black hole
formation and probe the morphological transformation of galaxies. We discuss
the main NGDEEP-NRC science goals in §4.

The NIRCam strategy is set by the primary NIRISS observations, though we
distribute the integration time to achieve approximately uniform sensitivity
(30.7–30.9 mag; 5$\sigma$) in all filters. We increase the time in F115W (and
F444W simultaneously) to detect $\sim$0.3–0.4 mag Ly$\alpha$-breaks at our
limit of $m\\!=$30.7–30.9. These data will allow for a robust selection of
galaxies at $9<z<13$ that are detected in $\geq$4 filters ($>$2 mag deeper
than CEERS and up to 0.1–0.5 mag deeper than the JADES GTO Program). The
individual exposure times are $\sim$5.1 ks (F115W, F200W, F356W, and F444W)
and $\sim$6.7 ks (F150W, F277W) with the DEEP8 readout, 4 groups per
integration (5 for F150W, F277W), and 7 integrations per exposure. Images
taken in parallel to NIRISS direct imaging have t$=$150s using SHALLOW4
readout to allow for 3 groups. The final exposure times will be 60–84 ks
(F150W, F200W, F277W, and F366W) and 170-180 ks (F115W and F444W). We estimate
depths with the ETC, assuming expected resolved sizes (FWHM $\sim$0.07′′ at
$m=30.6$; Kawamata et al. 2018).

The combination of imaging at two position angles separated by 3∘ will result
in tiers of depth in the NGDEEP-NRC mosaic. We present the anticipated area as
a function of depth in the left panel of Figure 3, where these depth tiers are
evident as a set of step functions for the NGDEEP observations. All six bands
are observed in the deepest tier to at least 30.7 mag. The filters F150W,
F200W, and F277W will reach 30.9 mag, and F115W will achieve a depth of 31.2
mag. At an area of 5 arcmin2, NGDEEP-NRC is expected to be comparable in depth
to the deepest tier of JADES in F150W, F200W, F277W, and F356W. However,
NGDEEP-NRC is $\sim$0.3 mag deeper than JADES222NGDEEP vs. GTO Programs: We
derived JADES and MDS exposure times and depths directly from their APT files,
assuming 5$\sigma$ resolved sources for comparison with NGDEEP-NRC depths. Our
estimates of the depths differ in places from the summaries in Williams et al.
(2018, JADES) and Pérez-González et al. (2023, MDS).  in the important F115W
$z\sim$ 10 dropout filter (194 ks over our deepest 5 arcmin2 compared with 143
ks for JADES), allowing robust candidate galaxy selection to the limiting
magnitude in the redder filters. NGDEEP-NRC will also be $\sim$0.5 mag deeper
in F444W (186 ks compared with 94 ks), a crucial filter for limiting
contamination by low-redshift objects. JADES is shown as the dotted lines in
Figure 3.

Figure 4: Understanding the details of the MZR is fundamental for theories of
galaxy evolution. Left: arrows show that (1) metal abundance increases with
the nucleosynthetic yields of star formation, (2) accretion of metal-poor gas
both dilutes metals and can trigger star formation, (3) outflows remove
enriched gas with an efficiency that is inversely proportional to the galaxy
gravitational well. The purple line and swath show the MZR and its scatter
measured from synthetic NIRISS spectra, derived from our simulations: NGDEEP
will significantly extend the MZR mass coverage by $\sim$2 dex. Right: The
diversity in the evolution of the MZR slope predicted by simulations with
different assumptions about feedback (with color scheme as in the left panel):
NGDEEP will measure this slope and scatter, and thereby constrain the physics
of feedback.

The MIRI Deep Survey (MDS) operated by the MIRI European Consortium Team is
also obtaining deep observations with MIRI on the HUDF. Their parallel NIRCam
imaging includes 55 ks of integration for F115W, F150W, F277W, and F356W. We
note that three of the four planned visits were observed in December 2022,
with the final visit scheduled for December 2023. Additionally, one of the
three visits was observed at a slightly different position angle. As a result,
the current set of MDS NIRCam observations include 55 ks in F115W+F277W and 28
ks in F150W+F356W, reaching depths of m$\sim$30.0-30.2 in all filters and
m$\sim$30.7 in F277W. There is an area of $\sim$8 arcmin2 in common between
the two filter sets, $\sim$3.7 arcmin2 of which overlaps with the NGDEEP-NRC
footprint. Early results from Pérez-González et al. (2023) have identified 45
new, faint $z>8$ candidates, highlighting the potential offered by the
increased depth and filter coverage that NGDEEP-NRC brings to this region.

Based on the predictions of a range of models, NGDEEP-NRC will discover
$\sim$50–100$+$ galaxies at $z\sim 10$, and up to 60, 25, 12 and 10 galaxies
at $z\sim$ 11, 12, 13 and 14–15, respectively (see §4), sufficient to
distinguish between competing models for high-$z$ galaxy evolution. In §5.2,
we also demonstrate that NGDEEP-NRC’s $\sim$2 mag increase in depth compared
to CEERS is essential to detect galaxies at $z=10-13$.

##  3 NGDEEP-NIS Science Cases: Star-Formation, Enrichment, and Feedback at
$z=$ 0.5–4

###  3.1 Constraining Feedback via the Low–Mass end of the Mass–Metallicity
Relation

A fundamental probe of galaxy evolution is the stellar-mass versus gas-phase
metallicity relation (MZR; e.g., Tremonti et al., 2004; Maiolino et al.,
2008). The MZR is thought to result from the general growth of galaxies over
time, where they increase their both their stellar mass and abundance of
metals produced, but are also sensitive to competing feedback processes.
Figure 4 shows the expected tight, positive MZR for NGDEEP-NIS. The MZR slope,
normalization, and intrinsic scatter is shaped by galaxy feedback processes,
where metals are created by star formation, ejected by outflows, and diluted
by gas infall (Tremonti et al., 2004; Zahid et al., 2014). Further, the MZR is
observed to exist out to at least $z{\sim}3$–4 (e.g., Maiolino & Mannucci,
2019; Sanders et al., 2020), where it has been observed to have a lower
normalization than at $z\sim 0$. This redshift evolution is thought to result
from a number of effects including stellar and AGN feedback-driven outflows,
changing stellar yields, and star formation histories. Simulations predict the
MZR in detail (e.g., Davé et al., 2011; Torrey et al., 2014), but show
significant tension. As depicted in the right hand panel of Figure 4,
different state-of-the-art models predict staggeringly different redshift
evolution of the MZR slope at low-masses: predictions vary by more than 0.3
dex in $d\log Z/d\log M_{\ast}$. Progress requires robust metallicity
measurements in low-mass galaxies across a range of redshifts.

Figure 5: NGDEEP-NIS will enable the measurement of the SFR-Stellar Mass
(SFMS) relation and its scatter at $z=1-2$, for galaxies 10$-$100$\times$
fainter than previous surveys (e.g., MOSDEF). Left: The predicted SFR-Stellar
Mass (SFMS) relation for NGDEEP-NIS (small red circles). NIRISS will derive
SFRs from H$\alpha$ for galaxies to SFR$=0.22$ (0.040) M⊙ yr-1 at $z=2$
($z=1$). The H$\alpha$-derived SFR limits are well matched to the UV-derived
SFRs from the HUDF ACS F435W imaging. The black-solid line shows the SFMS at
$z=2$ (Tomczak et al., 2014), the black-dashed line is the extrapolation to
log$M_{*}/M_{\odot}<9$. Right: The NGDEEP-NIS H$\alpha$-/UV-SFRs will measure
the scatter in the SFMS. The data points show the scatter from the SFMS for
galaxies above a given stellar mass. For NIRISS, we show the true scatter (red
open triangles) compared to the measured scatter (large red-filled triangles),
which include measurement errors. The difference in the scatter between UV and
H$\alpha$ SFRs provides a strong constraint on feedback in simulations: this
is predicted to be strongest at the lower stellar masses
(log$M_{*}/M_{\odot}<9$, see Sparre et al. 2017) probed by NGDEEP-NIS.  Table
2: Expected Emission Line Counts in NGDEEP-NIS

Line or Index | Number | Number | Redshift Range
---|---|---|---
| ($3\sigma$) | ($5\sigma$) |
Any line | 2266 | 1601 |
Ly$\alpha$ $\lambda$1216 | 6 | 1 | 7.22–17.09
Mg II $\lambda$$\lambda$2796,2804 | 40 | 19 | 2.57–6.87
[O II] $\lambda$$\lambda$3727,3730 | 464 | 307 | 1.68–4.90
[Ne III] $\lambda$3870 | 40 | 8 | 1.58–4.68
H$\beta$ $\lambda$4863 | 289 | 162 | 1.06–3.52
[O III] $\lambda$5008 | 837 | 618 | 1.00–3.39
H$\alpha$ $\lambda$6565 | 965 | 676 | 0.52–2.35
[S II] $\lambda$$\lambda$6718,6732 | 156 | 96 | 0.49–2.27
Number of Galaxies with $\Delta z<0.2$ dex |
$z>1$ | 361 |
$z>2$ | 275 |
$z>3$ | 98 |

Note. — Number of emission lines (or robust multi-line metallicities) in our
end-to-end NGDEEP-NIS simulations at 3 and 5$\sigma$ significance, using the
JADES galaxy mock catalog as input (see §5.1). We note that the Ly$\alpha$
predictions debend on the assumed IGM attenuation and may be underestimates,
as several Ly$\alpha$ detections at $z>7$ have already been confirmed (e.g.,
Vanzella et al., 2011; Castellano et al., 2018; Tilvi et al., 2020; Jung et
al., 2020, 2022; Larson et al., 2022). Note that wavelengths are in rest-frame
vacuum. Doublets will be blended.

NGDEEP-NIS will obtain NIRISS slitless spectroscopy covering an observed range
of 1.0–2.2 µm with the sensitivity to detect emission lines as faint as $\sim
10^{-18}$ erg s-1 cm-2. This will enable the measurement of galaxy gas-phase
metallicities using well-calibrated rest-frame optical emission-line
diagnostics from $R_{23}\equiv$ ([O II]$\lambda$3727 + [O
III]$\lambda$5008)/H$\beta$ at $1.7<z<3.4$ and Ne3O2 $\equiv$ [Ne
III]$\lambda$3868$/$[O II]$\lambda$3727 to $z\lesssim 5$ (e.g., Maiolino &
Mannucci, 2019). While most MZR studies only probe the most massive galaxies
in targeted surveys, NGDEEP-NIS will measure metallicities for an unbiased
galaxy sample (i.e., no preselection) with stellar masses of $\log
M_{\ast}/M_{\odot}{\gtrsim}7$ at these redshifts. Recently, Li et al. (2022)
used stacks of JWST observations of 55 $z\sim 2-3$ galaxies to reveal our
first glimpse of the evolution of the MZR out to cosmic noon. This work hints
at a shallower slope for low-mass galaxies ($M_{\star}<10^{9}M_{\odot}$),
possibly due to the dominance of different feedback processes in the low-mass
regime. NGDEEP-NIS will significantly increase the sample size of low-mass
galaxies on the MZR at cosmic noon, allowing us to discern any turnover
resulting from varying feedback sources.

Figure 4 shows the MZR (slope, normalization, and scatter) from our NGDEEP-NIS
simulations using $R_{23}$, showing constraints to $\lesssim$0.2 dex across
our mass range. Comparing to simulation predictions, the NGDEEP-NIS MZR will
place stringent empirical constraints on the appropriate feedback
prescriptions that should be incorporated into models. Joint constraints on
the low-mass end of the stellar mass function and the MZR can constrain the
mass-loading factors of stellar- and AGN-driven winds, and test if feedback is
ejective or preventative, thereby constraining the energy content of winds.
NGDEEP-NIS measurements of the MZR will thus provide critical benchmarks for
the next generation of galaxy formation simulations in and after the JWST era.

###  3.2 Constraints on Bursty Star Formation from rest-UV and H$\alpha$
measurements

A powerful capability of NGDEEP-NIS is that it combines NIRISS measurements of
the H$\alpha$ recombination line for galaxies at $0.7<z<2.3$ with rest-UV
measurements from HUDF ACS F435W (the deepest $B$-band imaging anywhere on the
sky, $m_{5\sigma}=29.6$; Illingworth et al. 2013). Figure 5 shows that the
NIRISS H$\alpha$ line flux limit is well matched to the ACS rest-UV limit:
both will detect SFRs from galaxies down to 0.22 (0.04) $M_{\odot}$ yr-1 at
$z=2$ ($z=1$). With NGDEEP-NIS we will make a first measurement of the
stellar-mass–SFR relation down to $\log M_{\ast}/M_{\odot}=7$ at $z=1$–2.

Figure 6:  Redshift versus H$\alpha$ flux for galaxies in simulated NGDEEP-NIS
data. The small grey points represent all sources in the simulation. The red
squares are simulated objects with NIRISS-detected H$\alpha$ emission (SNR
$>3\sigma$). NGDEEP will measure faint H$\alpha$ emission from $>$900 sources
from $0.7<z<2.3$ (see Table 2). The open circles are sources that would have
been targeted by MOSDEF, a dedicated survey using the 10m Keck telescope.
Surveys like MOSDEF must preselect objects and are subject to slit crowding:
MOSDEF only targeted galaxies with $H_{160}<25$ AB mag and had a flux limit of
$F\simeq 10^{-17}$ erg s-1 cm-2 ($3\sigma$). MOSDEF would be sensitive to
fewer than 70 of the NGDEEP-NIS sources (at higher stellar masses).

These NGDEEP SFR observations will provide diagnostics on the stochasticity of
star formation, another strong probe of feedback. The amplitude and
characteristic timescale of star formation variability is a test of state-of-
the-art cosmological hydro simulations which implement star formation and
feedback differently (Iyer et al., 2020), where increased star formation
efficiency and stronger feedback produce more stochastic star formation
(Hopkins et al., 2018). The H$\alpha$ and UV emission are sensitive to
different star-formation timescales: the UV continuum is emitted by massive
(OB) stars, and probes SF variations on $\sim$100 Myr timescales; H$\alpha$
emission requires ionization from the most massive (O) stars, and probes 5-10
Myr timescales (Kennicutt & Evans, 2012). Observations of H$\alpha$ and UV
SFRs are therefore sensitive to stochasticity and bursts, the effects of which
are strongest in lower mass galaxies (Weisz et al., 2012; Broussard et al.,
2019).

With NGDEEP-NIS we will combine the H$\alpha$ emission from NIRISS and rest-UV
from ACS to study star-formation variability in low-mass galaxies ($\log
M_{\ast}/M_{\odot}{\simeq}7$) at $0.7{<}z{<}2.3$. NGDEEP-NIS enables the
measurement of the scatter in these SFRs for galaxies above a fixed SFR and
stellar mass, achieving results for galaxies $10\times$ fainter than previous
work (MOSDEF, see Figure 6, Shivaei et al. 2015), where theory predicts the
SFR scatter is more pronounced (Sparre et al., 2017; Iyer et al., 2020). The
right panel of Figure 5 shows we are able to recover the intrinsic SFR scatter
$\sigma$=0.45 for H$\alpha$ and 0.3–0.35 for the UV for our simulated dataset.
If the real difference between the H$\alpha$ and UV SFR scatter is larger than
predicted by models, then it would imply stronger ejective feedback is needed
to regulate star formation in low-mass systems. NGDEEP-NIS is the only survey
sensitive enough to measure SFRs to these limits in both H-recombination lines
and UV continua for galaxies at $z{\sim}1$–2.

###  3.3 Physical conditions of galaxies in the HUDF

The unbiased nature of the NIRISS slitless spectroscopy means the data probe
every galaxy in the HUDF. This will enable additional science for galaxies
beyond that articulated here. This includes galaxies with additional
diagnostic lines (see Table 2), such as rest-UV spectra of faint galaxies at
$z{>}4$. Therefore the dataset here has a legacy value with which to study
galaxies in this JWST$+$HST deep field.

Figure 7: Left: Predicted cumulative number of high-redshift galaxies detected
across the NGDEEP NIRCam imaging mosaic. Simulations (solid lines; Behroozi &
Silk, 2015; Mason et al., 2015b; Wilkins et al., 2022; Dayal et al., 2017,
Yung et al., in prep) span a wide range, reflecting the lack of observational
constraints prior to JWST. Across the full NGDEEP NIRCam mosaic (to the F277W
5$\sigma$ limit) NGDEEP should cover $\sim$50–1100 galaxies at $z\sim 10$,
3–25 galaxies a $z\sim$ 13, and up to 10 galaxies at $z=$ 13.5-15,
distinguishing between these models. We note that early results from CEERS
(Finkelstein et al., 2022a) are consistent with the most optimistic of these
models (Behroozi & Silk, 2015). Right: Model uncertainties highlight our state
of knowledge of important physical processes. Purple shading shows the
plausible range of the dependence of SFR on gas surface density, which
primarily affects the bright-end which is constrained by wider-area programs
like CEERS and COSMOS-Web (Casey et al., 2022). Red shading denotes the
plausible range in stellar feedback mass loading factors, which primarily
affect the faint end (Yung et al., 2019a). The symbols show the precision
achievable by CEERS and NGDEEP+JADES (assuming the fiducial Yung et al. 2019a
luminosity function; dotted line). At $M_{\mathrm{UV}}=-17.5$ (NGDEEP-NRC
$10\sigma$ limit), NGDEEP-NRC alone will significantly constrain these models
($\sim$4.5$\sigma$, including cosmic variance, improving to $\sim$5.5$\sigma$
with the eventual combination with JADES), placing the first definitive
constraints on feedback processes in early galaxies.

##  4 NGDEEP-NRC Science Cases: A Public and Parallel Deep Survey Towards
First Light

NGDEEP parallel NIRCam imaging will achieve m${}_{\mathrm{AB,5\sigma}}=30.7$
(30.4) from 1–5$\mu$m over 5 (11) arcmin2, on the deepest F814W imaging in the
sky (m${}_{AB,5\sigma}=30.0$). These data will allow some of the first robust
constraints on galaxy formation at $z>10$. Public NGDEEP data will enable
immediate community-led deep-field legacy science up to magnitudes comparable
or deeper than proprietary GTO NIRCam surveys, all coming in parallel at
essentially no added observational cost.

###  4.1 Physical Processes Regulating the Emergence of the First Galaxies

Over the first 500 Myr of cosmic time ($z\\!\\!>$10) galaxies began to
coalesce, enriching and ionizing their environments, altering subsequent gas
accretion and star formation. HST has only scratched the surface with just a
handful of $z\sim$9–11 (mostly) tenuous candidates (McLeod et al., 2015; Oesch
et al., 2018; Bouwens et al., 2019; Bagley et al., 2022a; Finkelstein et al.,
2022b). Prior to JWST, the number of faint galaxies ($M_{UV}{<}-$17) found by
different surveys was in tension, and there is evidence for both smooth or
accelerated decline in the observable cosmic SFR density (Finkelstein et al.,
2015; Bouwens et al., 2015; Oesch et al., 2018; McLeod et al., 2015;
Finkelstein, 2016; Bouwens et al., 2019). This leaves theoretical models
highly unconstrained, where differences in star-formation and feedback
prescriptions result in a wide range of predictions (Figure 7; Behroozi &
Silk, 2015; Mason et al., 2015b; Wilkins et al., 2022; Dayal et al., 2017;
Behroozi et al., 2020; Yung et al., 2019a; Mason et al., 2015a; Wilkins et
al., 2017; Gnedin, 2016; Davé et al., 2019). This leads to uncertainties on
the details of the history of reionization of the IGM (Robertson et al., 2015;
Finkelstein et al., 2019; Yung et al., 2020b, a).

NGDEEP will provide robust observations of the number density of galaxies at
$z>10$. This measures the shape of the rest-UV luminosity function (UVLF),
which constrains the relative strength of processes governing gas conversion
into stars (and these depend on gas density, metallicity, magnetic field
strength, turbulence, and feedback mechanism). Different theoretical
predictions for the UVLF at $z>10$ vary by orders of magnitude in galaxy
number density (e.g., Behroozi & Silk, 2015; Mason et al., 2015b; Wilkins et
al., 2022; Dayal et al., 2017), because of differences in adopted sub-grid
physics. Two physical processes are most important for the shape and
normalization of the UVLF at high redshift: the star-formation law (i.e., the
star formation efficiency as a function of cold gas surface density), and the
prescription for stellar feedback.

Using a semi-analytic model (SAM), Yung et al. (2019a) explored how
modifications to these relationships alter the UVLF, shown in the right-hand
panel of Figure 7. Altering the star-formation efficiency primarily changes
the bright end of the UVLF, which will be constrained by medium-depth, wider-
field JWST programs (such as CEERS, Finkelstein et al. 2022c, and COSMOS-Web,
Casey et al. 2022). However, stellar feedback dominates the UVLF of faint
galaxies (as feedback regulates star-formation in lower-mass halos). In
particular, this feedback depends on the mass-loading factor of ejected gas,
and changing this within the currently allowable parameter space changes the
number density of the lowest-luminosity galaxies ($M_{UV}{\lesssim}{-18}$) by
up to 1 dex. NGDEEP provides the missing constraint: Figure 7 shows that
adding NGDEEP observations achieves an uncertainty on the number density of
faint galaxies $\sim$4–5$\times$ less than the range currently spanned by
models (this includes both counting and a 30% fractional cosmic variance
uncertainty; Bhowmick et al. 2020).

To make this measurement as accurate as possible requires deep surveys of
blank fields. This is complementary to surveys of regions that are strongly
lensed by clusters of galaxies. Those observations can reach fainter intrinsic
luminosities over small volumes, albeit with uncertainties associated with the
magnification. By directly identifying galaxies to $m{>}$30.5 mag, NGDEEP will
measure the evolution of the UVLF and SFR density to $z{>}10$–15, and provide
unique constraints on stellar feedback physics at $z{>}10$. In Figure 7 we
also list predicted numbers of high-redshift galaxies to be discovered by
NGDEEP based on a range of recent models. As early JWST results are finding
observed yields at the high end of predictions, these numbers may be lower
limits (e.g., Castellano et al., 2022; Naidu et al., 2022; Finkelstein et al.,
2022c, a; Donnan et al., 2022; Harikane et al., 2022; Adams et al., 2022; Atek
et al., 2023; Pérez-González et al., 2023).

###  4.2 The Onset of Chemical Enrichment

As we explore higher redshifts, we will eventually witness the periods during
which galaxies have formed no more than a few generations of stars,
characterized by extremely low metallicities. Exactly how low is critical — if
all dense gas in the universe is rapidly enriched beyond the critical
metallicity ($\sim$10-4 Z⊙), both the stellar initial mass function and
stellar photospheric temperatures will likely not be dramatically different
than those seen in low-metallicity environments. If the opposite is true, and
fairly massive metal-free stars can form down to even $z\sim$ 10, we expect
markedly harder stellar spectra, with consequences on the ability of stellar
light to reionize the IGM.

Work using HST data found that the colors of the most distant galaxies are
consistent with low (but non-zero) metallicities, without much dust
obscuration in the lowest mass galaxies (Finkelstein et al., 2012; Dunlop et
al., 2013; Bouwens et al., 2014; Wilkins et al., 2016). NGDEEP NIRCam imaging
will push this analysis to $z>10$, allowing us to measure the UV spectral
slope $\beta$; where f${}_{\lambda}\propto\lambda^{\beta}$ (Calzetti et al.,
1994) with four (three) rest-UV colors for galaxies at $z\sim 10$ (12).
Simulations at our proposed depths show that we can recover $\beta$ with
minimal bias and $\sigma_{\beta}=0.2$ to $z>13$. NGDEEP will also improve
measures of $\beta$ in galaxies at $z=6-8$ (currently restricted to just one
or two colors), measuring $\beta$ with five colors.

###  4.3 The Sites of Early Black Hole Formation

Massive black hole seeds forming at $z>12$ via direct collapse, with masses
$\sim 10^{4}-10^{5}\,M_{\odot}$, are expected to form in the satellite halos
of early star-forming galaxies, that will eventually merge and acquire a
stellar component (Agarwal et al., 2016). In these galaxies with overly-
massive black holes (referred to as OBGs), the accretion luminosity outshines
the stellar component (Natarajan et al., 2017), offering a unique way to
discriminate between light and massive initial black hole seeds. Computing the
multi-wavelength energy output of OBGs, they should stand out from typical
galaxies via their steep 1–3$\mu$m SED, identified via NGDEEP colors, with
candidates cross-correlated with the very deep Chandra X-ray data in this
field. The boosted infra-red luminosity of OBGs (predicted $m_{AB}<25$) makes
them easily and unambiguously detectable in the proposed NGDEEP survey. Recent
models predict $\sim$2–5 OBG candidates between $z\sim 9-12$ in the proposed
NGDEEP fields, revealing the sites of early BH formation and enabling
discrimination between early BH seeding models (Ricarte & Natarajan, 2018).

###  4.4 Galaxy Morphologies

Ultra-deep sub-kpc imaging across the near-IR is needed to understand how
galaxies assembled. The suppression of runaway star formation by feedback is
encoded in galaxies’ structural and mass-assembly histories. Additionally,
models predict various pathways for emergence of galaxy structure at early
times (e.g., Wellons et al., 2016) and the role of galaxy mergers in the mass
assembly of galaxies over the age of the universe remains uncertain. This is
especially true for galaxies at $z\gg 2$, at $M_{*}<10^{10}M_{\odot}$, and for
minor mergers (Kaviraj, 2014; Martin et al., 2017; Mantha et al., 2018; Duncan
et al., 2019). By characterizing structures in and around low-mass galaxies,
we can constrain the link between feedback physics and galaxy structure over
cosmic time (e.g., Moody et al., 2014; Oklopčić et al., 2017; Zhang et al.,
2019). Early morphological studies with JWST have demonstrated its power to
probe the detailed morphologies of galaxies out to very high redshift, to
reveal low-surface brightness features in galaxies that were previously
undetected with HST, and to identify complex structures even at $z>7$ (e.g.,
Robertson et al., 2022b; Ferreira et al., 2022; Kartaltepe et al., 2022;
Nelson et al., 2022; Bowler et al., 2022; Finkelstein et al., 2022a; Treu et
al., 2023; Chen et al., 2023).

NGDEEP will push morphological analyses into new frontiers through the
measurement of rest-frame optical morphologies and sizes of galaxies at very
high redshift and those with low-mass, including the structure of spheroids,
disks, and clumps and will characterize the detailed morphological
substructure of faint disks, streams, and other low surface brightness
features. The deep imaging will enable the detection of galaxies in the
process of merging as well as post-mergers through the identification of
shells, tidal tails, double nuclei, and other surrounding debris (e.g., Mantha
et al., 2019; Hsiao et al., 2022; Kokorev et al., 2023). NGDEEP imaging will
also push spatially-resolved SED fitting to $z>4$, probing inside-out
quenching and the formation of early bulges, by allowing reconstruction of the
radial profiles of SFR, stellar mass surface density, and specific SFR of
galaxies (e.g., Abdurro’uf et al., 2023).

Figure 8: NGDEEP-NIS WFSS Simulations. Bottom Left: The NIRISS grism covers a
wide range of emission lines over a wide range of redshifts. Bottom Right:
Zoomed-in simulated WFSS observations using the F115W cross filter where
emission lines are clearly visible. The insets show full images and the region
in F115W that is zoomed-in. All known instrumental and WFSS related effects
are included in the simulated data. Top: The GRISMR (orange) and GRISMC
(green) extracted NIRISS spectra of a galaxy at $z=2.21$ with
$F(H\alpha)=10^{-17}$ erg/s/cm2 (SNR=22), $10^{7.7}$ $m_{\odot}$. We will
measure $\sigma>5$ emission lines in over 1500 galaxies in the HUDF.

###  4.5 Closing the Gap between the
Near Field and Deep Fields

Resolved stellar population studies of Local Group galaxies can be used to
reconstruct the high-redshift luminosity function out to $z\sim 4$–5 down to
very faint magnitudes (e.g., Weisz et al., 2014). The unprecedented depth of
NGDEEP’s multi-band imaging, combined with deep HST imaging, will allow us to
probe very faint galaxies at $z\sim 4$–5 _directly_ , and test for consistency
with the fossil record. NGDEEP will probe to $M_{\rm UV}\sim-15.5$ ($-15.7$)
at $z=4$ ($z=5$), overlapping the brightest bins from the Weisz et al. (2014)
Local Group analysis. Future resolved stellar population studies with JWST and
ground-based ELTs will be able to probe more distant galaxies beyond the Local
Group, improving the fossil constraints and the overlap with the NGDEEP
constraints.

##  5 NGDEEP Simulated Observations

We performed a careful evaluation of the feasibility of NGDEEP using a
complete set of end to end simulations for both the primary and parallel
observations. We used the Multi-Instrument Ramp Generator333mirage-data-
simulator.readthedocs.io (MIRAGE) to generate mock NGDEEP observations for
both JWST instruments. The simulations are based on the NGDEEP APT file, and
so reproduce the filters, grisms, exposure specifications, dither patterns and
position angles of the planned observations. These simulations include
realistic noise, sky background structure, and all known instrument-dependent
(e.g., bad pixels, cross talk, etc.) and scene-dependent (e.g., variation in
dispersed background, object morphology, crowding) effects for the NIRISS WFSS
and NIRCam imaging. We reduced and analyzed these data in exactly the same way
we plan to do with using real data. We describe each set of simulations in the
following sections.

Figure 9: Full simulated NGDEEP-NRC F277W 22.3 hour mosaic, displaying the
footprint of the proposed observations, including all instrumental effects and
sensitivities. The main input for this simulation is the ultra-deep Santa Cruz
SAM lightcone (Yung et al., 2022). The central inset zooms in on a 10.7″
region, demonstrating the increase in depth compared with CEERS. On the right,
we show composite NGDEEP-NRC images of $z=1.5$ and $z=3$ galaxies from the
VELA simulation (Simons et al., 2019) with faint tidal features (indicated by
white dashed lines) clearly detected in the planned exposure times. By
resolving low-mass galaxies at early times, NGDEEP will probe a new frontier
in galaxy assembly. On the upper left we show 2″ postage stamps of two massive
galaxies at $z=4$ generated from the SIMBA simulation (Davé et al., 2019),
with the NGDEEP-NRC images on top and stamps of the same sources imaged at the
CEERS depth on the bottom. Extended emission and complicated morphologies are
evident in all filters at the NGDEEP-NRC depth. We also show 1″ postage stamps
of six $z>9.5$ galaxies, again compared with CEERS imaging, highlighting the
power of NGDEEP-NRC imaging to detect $m>30$ galaxies to $z=13$.

###  5.1 NGDEEP-NIS Simulations

As input to the NIRISS WFSS simulations we used the JADES catalog (Williams et
al., 2018), which provides morphological and spectroscopic data. The resulting
input catalogs and spectra were used in conjunction with an APT observing plan
and the simulation software MIRAGE to produce individual uncalibrated NIRISS
imaging and WFSS exposures. We therefore produced a set of rate files with
dithers and readout mode that were the same as our proposed observations.
Spectra from the WFSS rate files were then extracted using the SBE method,
following closely the methodology described in Pirzkal et al. (2018). Combined
GRISMR and GIRSMC 1D spectra, wavelength and flux calibrated were produced and
served to check our expected S/N and we stress that our simulations include as
detailed as possible treatment of all the known instrumental effect and of the
observing strategy. We show an example of our simulated WFSS observations in
Figure 8. This figure also shows the extracted spectra for a source as seen by
the GRISMR and GRISMC grisms.

###  5.2 NGDEEP-NRC Simulations

For the mock NIRCam observation inputs, we used a modified version of the
ultra-deep simulated lightcone presented by Yung et al. (2022). The galaxies
therein are simulated using the Santa Cruz semi-analytic model (SAM Somerville
et al., 2015, 2021; Yung et al., 2019a, b), with dark matter halos extracted
from the IllustrisTNG-100 dark matter-only simulation (Nelson et al., 2019)
and Monte Carlo merger trees constructed based on the extended Press-Schechter
formalism (e.g., Somerville & Kolatt, 1999; Somerville et al., 2008). The SAM
incorporates the evolution of a variety of physical processes, such as
cosmological accretion, cooling, star formation, chemical enrichment, and
stellar and AGN feedback. See Yung et al. (2022) for a concise summary of the
internal workflow of the SAM and lightcone construction. The free parameters
in the SAM are calibrated to a subset of observed constraints at $z\sim 0$ and
the model performance at high redshift has been tested extensively and shown
to well-reproduce a wide variety of observed constraints (Yung et al., 2019a,
2020a, 2021).

The predicted star formation and chemical enrichment histories of each mock
galaxy are coupled with synthetic stellar SEDs from Bruzual & Charlot (2003),
and are forward modelled into rest-frame and observed-frame photometry in the
NIRCam filters, accounting for ISM dust (Calzetti et al., 2000) and IGM
extinction (Madau et al., 1996). Each synthetic SED also includes nebular
emission lines simulated based on the predicted contributions of young stars,
AGN, and post-ABG stellar populations (Hirschmann et al., 2017, 2019, 2022,
Yung, Hirschmann, Somerville et al., in prep.). The mock catalog contains
galaxies out to $z\sim 12$ and is complete to $m_{\text{F200W}}\sim 34$. The
SAM mock galaxies also provide simulated Sérsic profiles (Sérsic, 1963, 1968)
with Sérsic indices and effective radii determined as described in Brennan et
al. (2015).

We supplemented this galaxy mock catalog with three additions. First, we
injected $\sim$20 galaxies at redshifts $11-15$, with NIRCam filter magnitudes
pulled from the SAM extended Press-Schechter catalogs, providing us with
realistic photometry for these high-redshift galaxies. We placed these
additional sources randomly in the NGDEEP-NRC footprint with the goal of
evaluating the expected recovery rate of galaxies with $m\gtrsim 30$ and
$z>12$, should they exist in the real field. Next, we included postage stamps
of extended sources with fully realistic morphologies from both the
VELA444https://archive.stsci.edu/prepds/vela/ (Simons et al., 2019) and SIMBA
(Davé et al., 2019) simulations. The VELA simulated sources were included to
test the recovery of faint, extended structures such as streams and tidal
features, and the SIMBA simulated sources provided tests of morphological
measurements of substructures such as spheroids, disks and clumps.

The full NGDEEP-NRC simulation includes 1400 simulated images (140 exposures
each with ten NIRCam detectors). We created raw images with MIRAGE and reduced
them using the JWST Calibration Pipeline555jwst-pipeline.readthedocs.io. We
show an example of our simulated NIRCam observations in Figure 9, which
highlight the ability of these data to identify very high-redshift galaxies
fainter than 30th magnitude.

##  6 Data Release Plans

The NGDEEP survey builds on HST’s legacy surveys – the HDF, UDF, GOODS
(Giavalisco, 2002), CANDELS (Grogin et al., 2011; Koekemoer et al., 2011),
etc. – whose success resulted in part from the immediate release of the data.
NGDEEP also achieves a primary goal of JWST: “First Light and Reionization …to
see the first stars and galaxies …”, which requires deeper surveys than the
ERS programs. NGDEEP leverages HST’s legacy by combining JWST data with the
deepest HST imaging in the $B$\- and $I$-bands, and will enable the study of
galaxies from $z{\sim}$1–2 to $z{>}10$. Progressing from having a few secure
$z{>}$10 candidates to having a robust sample of galaxies will require a
concerted effort over the first several years of JWST operations. NGDEEP will
form a crucial cornerstone of Cycle 1 extragalactic surveys, informing the
design of future JWST programs (e.g., deep field proposal strategies in Cycle
3 and beyond). With NGDEEP and GTO programs (such as JADES) as building
blocks, we envision programs executed by multiple teams to ultimately push
several fields to ambitious depths early in the mission and get data to the
community rapidly. NGDEEP offers a very efficient first step toward this goal.

To that end, we will rapidly deliver high–quality data products to enable
broad community science from NGDEEP. We will reduce the NGDEEP-NRC
observations using the STScI JWST Calibration Pipeline with custom additions
and modifications we have identified through our work with CEERS imaging
(Bagley et al., 2022b). These modifications include the removal of low-level
features such as wisps and $1/f$ correlated noise, a careful astrometric
alignment, and a global background subtraction, steps that are necessary to
achieve the expected NGDEEP-NRC imaging depths. The NGDEEP-NIS observations
will be processed through Stage 1 of the JWST Calibration Pipeline with any
necessary modifications, and the spectra will be extracted using the SBE
method (Pirzkal et al., 2017). The NIRISS release will include 2D and 1D
calibrated spectra of each source detected in the field with an accurate
correction for spectral contamination as demonstrated by Pirzkal et al.
(2017). Our data-management plan is built on successful Hubble Treasury
programs, where speed is valued over perfection for the first v0.5 releases,
with limitations noted in the accompanying documentation. Our first reductions
will therefore represent a best effort based on the current state of the
instrument calibrations, especially that of the NIRISS WFSS mode. Later v1
releases will include more extensive testing and refinement, and be
accompanied by well-tested catalogs. Our released catalogs will be accompanied
by Python Jupyter notebooks to train users to interact with data products. All
products will be shared with STScI, and hosted on our own team website. Table
3 shows the NGDEEP data release schedule.

Table 3: NGDEEP Data Release Plan

Data Product | v0.5 | v1 |  Notes
---|---|---|---
Reprocessed NIRISS images | 3 | 6 |  Anticipated improvements: registration, cosmic ray rejection, background estimation
Extracted NIRISS spectra | 3 | 9 |  1 dimensional spectra and contamination maps
NIRISS emission line catalog and redshifts | 6 | 12 |  Emission–line analysis
NIRISS+HST Catalog |  $\cdots$ | 12 |  Continuum + emission–line analysis
Reprocessed NIRCam images | 3 | 6 |  Anticipated improvements: registration, cosmic ray rejection, background estimation
NIRCam+HST photometric catalog | 3 | 9 |  PSF–matched photometry across all bands (v1=NIRCam, v2 includes _HST_)
NIRCam+HST morphology |  $\cdots$ | 12 |  Sersic fits + non-parametric morphologies

The version columns refer to the months following acquisition when each data
product will be released.
---
These are estimates, with the exact releases depending on data reduction and
analysis timescales.

##  7 Summary

We present the Next Generation Deep Extragalactic Exploratory Public Survey,
which is obtaining deep NIRISS WFSS of the HUDF and deep NIRCam imaging in the
HUDF-Par2 parallel field. The NGDEEP observations are split across two
position angles, with V3_PA=70∘ observed in February 2023 (Epoch 1) and
V3_PA=67∘ scheduled for January 2024 (Epoch 2). The position angles are chosen
to improve the NIRISS emission line identification and contamination modeling
while maximizing the overlap between the two NIRCam imaging sets.

The NGDEEP NIRISS observations (NGDEEP-NIS) are obtaining spectroscopy from
$1-2.2$µm with the GRISMR and GRISMC grisms dispersed through the F115W, F150W
and F200W filters. The integration times are distributed to achieve
approximately uniform emission line sensitivities at all wavelengths, with
expected 5$\sigma$ integrated line sensitivities of 1.2, 1.3 and $1.5\times
10^{-18}$ ergs s-1 cm-2 for F115W, F150W, and F200W, respectively. The NGDEEP-
NIS observations will detect emission lines from $>$1000 galaxies, many of
which have multiple lines. The unbiased nature of the NGDEEP-NIS slitless
spectroscopy will result in near infrared spectroscopic measurements for every
source in the HUDF, complemented by the deep ACS F435W imaging in the field.

The NGDEEP NIRCam observations (NGDEEP-NRC) are obtaining imaging from $1-5$µm
with the F115W, F150W, F200W, F277W, F356W, and F444W filters. The NIRCam
imaging will reach comparable depths in all filters ($m=30.7-30.9$, $5\sigma$
resolved source) and $m=31.2$ in F115W. The NGDEEP-NRC observations are
defined by the NIRISS observing strategy, including the exposure times, dither
patterns, and NIRISS direct imaging. There are therefore multiple tiers of
depth in the NIRCam imaging, with $\sim$5 arcmin2 of the deepest imaging where
the two position angles overlap. This imaging will enable the discovery of
$\sim$30–100 galaxies at $z\gtrsim 11$, probing the faint end of the rest-UV
luminosity function 2 magnitudes fainter than that possible with CEERS.
NGDEEP-NRC is supplemented by deep ACS F814W imaging covering the NIRCam
footprint, with 50% of the footprint covered by the deepest F814W imaging on
the sky (m${}_{5\sigma}\approx$ 30).

Together, these coordinated parallel observations are designed to explore the
dominant feedback mechanisms in low-mass galaxies across cosmic time. NGDEEP
will constrain:

  * •

the redshift evolution and scatter in the MZR slope from $z\sim$ 1–5;

  * •

the stochasticity, burstiness and variability of star formation at
$z=0.7-2.3$;

  * •

the physical processes (stellar feedback and star formation efficiencies)
regulating the emergence of the first galaxies;

  * •

the evolution of chemical enrichment starting as early as $z\gtrsim 12$;

  * •

the sites and mechanisms of early black hole formation;

  * •

the link between feedback and morphological structures in and around low-mass
galaxies.

As a program continuing the legacy of HST ultra deep field astronomy, NGDEEP
will enable many additional community-led explorations into the study of
galaxies from cosmic noon ($z\sim 1-2$) to the early epochs of galaxy
formation ($z>10$).

NGDEEP provides the deepest publicly available spectroscopy and imaging
obtained in Cycle 1, making it one of the first JWST deep fields. When
combined with NGDEEP Epoch 2 as well as the JADES and MIRI GTO programs, these
legacy observations will transform deep field science and dramatically enhance
our understanding of the universe.

MBB, SLF, DAB, GCKL, CMC, OACO, KC, SF, and RLL acknowledge that the location
where part of this work took place, the University of Texas at Austin, that
sits on indigenous land. The Tonkawa lived in central Texas and the Comanche
and Apache moved through this area. We pay our respects to all the American
Indian and Indigenous Peoples and communities who have been or have become a
part of these lands and territories in Texas, on this piece of Turtle Island.
We thank the entire JWST team, including the engineers for making possible
this wonderful over-performing telescope, the instrument and commissioning
teams for establishing and characterizing observatory performance, the
scheduling team for squeezing in Epoch 1 of NGDEEP as the observing window was
closing, and the pipeline teams for their work over the years building and
supporting the pipeline. The authors acknowledge the Texas Advanced Computing
Center (TACC) at The University of Texas at Austin for providing HPC and
visualization resources that have contributed to the research results reported
within this paper. This work is based on observations with the NASA/ESA/CSA
JWST obtained from the Mikulski Archive for Space Telescopes at the Space
Telescope Science Institute (STScI), which is operated by the Association of
Universities for Research in Astronomy (AURA), Incorporated, under NASA
contract NAS5-03127. We acknowledge funding support from STScI through JWST-
GO-2079. PGP-G acknowledges support from Spanish Ministerio de Ciencia e
Innovación MCIN/AEI/10.13039/501100011033 through grant PGC2018-093499-B-I00.

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