# High-Redshift Galaxy Candidates at $z=9-13$ as Revealed by JWST Observations
of WHL0137-08

Larry D. Bradley Space Telescope Science Institute (STScI), 3700 San Martin Drive, Baltimore, MD 21218, USA  Dan Coe Space Telescope Science Institute (STScI), 3700 San Martin Drive, Baltimore, MD 21218, USA  Association of Universities for Research in Astronomy (AURA) for the European Space Agency (ESA), STScI, Baltimore, MD, USA  Center for Astrophysical Sciences, Department of Physics and Astronomy, The Johns Hopkins University, 3400 N Charles St. Baltimore, MD 21218, USA  Gabriel Brammer Cosmic Dawn Center (DAWN), Copenhagen, Denmark  Niels Bohr Institute, University of Copenhagen, Jagtvej 128, Copenhagen, Denmark  Lukas J. Furtak Physics Department, Ben-Gurion University of the Negev, P.O. Box 653, Be’er-Sheva 84105, Israel  Rebecca L. Larson NSF Graduate Fellow  The University of Texas at Austin, Department of Astronomy, Austin, TX, United States  Felipe Andrade-Santos Department of Liberal Arts and Sciences, Berklee College of Music, 7 Haviland Street, Boston, MA 02215, USA  Center for Astrophysics | Harvard & Smithsonian, 60 Garden Street, Cambridge, MA 02138, USA  Rachana Bhatawdekar European Space Agency, ESA/ESTEC, Keplerlaan 1, 2201 AZ Noordwijk, NL  Maruša Bradač University of Ljubljana, Department of Mathematics and Physics, Jadranska ulica 19, SI-1000 Ljubljana, Slovenia  Department of Physics and Astronomy, University of California Davis, 1 Shields Avenue, Davis, CA 95616, USA  Tom Broadhurst Department of Theoretical Physics, University of the Basque Country UPV/EHU, Bilbao, Spain  Donostia International Physics Center (DIPC), 20018 Donostia,Spain  IKERBASQUE, Basque Foundation for Science, Bilbao, Spain  Adam Carnall Institute for Astronomy, University of Edinburgh, Royal Observatory, Edinburgh EH9 3HJ, UK  Christopher J. Conselice Jodrell Bank Centre for Astrophysics, University of Manchester, Oxford Road, Manchester UK  Jose M. Diego Instituto de Física de Cantabria (CSIC-UC). Avda. Los Castros s/n. 39005 Santander, Spain  Brenda Frye Department of Astronomy, Steward Observatory, University of Arizona, 933 North Cherry Avenue, Tucson, AZ 85721, USA  Seiji Fujimoto Hubble Fellow  Department of Astronomy, The University of Texas at Austin, Austin, TX 78712, USA  Cosmic Dawn Center (DAWN), Copenhagen, Denmark  Niels Bohr Institute, University of Copenhagen, Jagtvej 128, Copenhagen, Denmark  Tiger Y.-Y Hsiao Center for Astrophysical Sciences, Department of Physics and Astronomy, The Johns Hopkins University, 3400 N Charles St. 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  Intae Jung Space Telescope Science Institute (STScI), 3700 San Martin Drive, Baltimore, MD 21218, USA  Guillaume Mahler Institute for Computational Cosmology, Durham University, South Road, Durham DH1 3LE, UK  Centre for Extragalactic Astronomy, Durham University, South Road, Durham DH1 3LE, UK  Stephan McCandliss Center for Astrophysical Sciences, Department of Physics and Astronomy, The Johns Hopkins University, 3400 N Charles St. Baltimore, MD 21218, USA  Masamune Oguri Center for Frontier Science, Chiba University, 1-33 Yayoi-cho, Inage-ku, Chiba 263-8522, Japan  Department of Physics, Graduate School of Science, Chiba University, 1-33 Yayoi-Cho, Inage-Ku, Chiba 263-8522, Japan  Marc Postman Space Telescope Science Institute (STScI), 3700 San Martin Drive, Baltimore, MD 21218, USA  Keren Sharon Department of Astronomy, University of Michigan, 1085 S. University Ave, Ann Arbor, MI 48109, USA  M. Trenti School of Physics, University of Melbourne, Parkville 3010, VIC, Australia  ARC Centre of Excellence for All Sky Astrophysics in 3 Dimensions (ASTRO 3D), Australia  Eros Vanzella INAF – OAS, Osservatorio di Astrofisica e Scienza dello Spazio di Bologna, via Gobetti 93/3, I-40129 Bologna, Italy  Brian Welch Department of Astronomy, University of Maryland, College Park, MD 20742, USA  Observational Cosmology Lab, NASA Goddard Space Flight Center, Greenbelt, MD 20771, USA  Center for Research and Exploration in Space Science and Technology, NASA/GSFC, Greenbelt, MD 20771  Rogier A. Windhorst School of Earth and Space Exploration, Arizona State University, Tempe, AZ 85287-1404, USA  Adi Zitrin Physics Department, Ben-Gurion University of the Negev, P.O. Box 653, Be’er-Sheva 84105, Israel

###### Abstract

The James Webb Space Telescope (JWST) was designed to peer into the distant
universe and study galaxies nearer the beginning of time than previously. Here
we report the discovery of 12 galaxy candidates observed 300 – 600 Myr after
the Big Bang with photometric redshifts between $z\sim 8.5-13$ measured using
JWST NIRCam imaging of the galaxy cluster WHL0137$-$08 observed in 8 filters
spanning 0.8–5.0 $\mu$m, plus 9 HST filters spanning 0.4–1.7 $\mu$m. Three of
these candidates are gravitationally lensed by the foreground galaxy cluster
and have magnifications of $\mu\sim 3-8$. The remaining nine candidates are
located in a second JWST NIRCam module, centered $\sim$ 2$\farcm$9 from the
cluster center, with expected magnifications of $\mu\lesssim 1.1$. Our sample
of high-redshift candidates have observed F200W AB magnitudes between 25.9 and
28.1 mag and intrinsic F200W AB magnitudes between 26.4 and 29.7 mag
($M_{UV}=-22.5$ to $-17$). We find the stellar masses of these galaxies are in
the range $\log M_{\star}/M_{\odot}$= $8-9$, and down to 7.5 for the lensed
galaxies. All are young with mass-weighted ages $<100$ Myr, low dust content
$A_{V}<0.15$ mag, and high specific star formation rates sSFR $\sim 10-50$
Gyr-1 for most. One $z\sim 9$ candidate is consistent with an age $<5$ Myr and
a sSFR $\sim 250$ Gyr-1, as inferred from a strong F444W excess, implying [O
iii]+H$\beta$ rest-frame equivalent width $\sim$2000 Å, although an older and
redder $z\sim 10$ object is also allowed. Another $z\sim 9$ candidate
WHL0137–ID9356 is lensed into an arc 2$\farcs$6 long by the effects of strong
gravitational lensing ($\mu\sim 8$), and has at least two bright knots of
unevenly distributed star formation. This arc is the most spatially-resolved
galaxy at $z\sim 9$ known to date, revealing structures $\sim$30 pc across.
Follow-up spectroscopy of WHL0137$-$08 with JWST/NIRSpec is planned for later
this year, which will validate some of these candidates and study their
physical properties in more detail.

Galaxies (573), High-redshift galaxies (734), Strong gravitational lensing
(1643), Galaxy clusters (584)

††facilities: JWST(NIRCam), HST(ACS, WFC3)††software: astropy (The Astropy
Collaboration et al., 2022; Astropy Collaboration et al., 2018), photutils
(Bradley et al., 2022), grizli (Brammer et al., 2022), eazypy (Brammer et al.,
2008), bagpipes (Carnall et al., 2018), beagle (Chevallard & Charlot, 2016),
Jdaviz (JDADF Developers et al., 2022)

##  1 Introduction

The James Webb Space Telescope (JWST), with its 6.5m aperture and infrared
capabilities (Rigby et al., 2022), has opened a new window to study galaxies
in the early universe. In the first weeks of JWST science observation, a
wealth of distant galaxy candidates (Naidu et al., 2022a; Donnan et al., 2022;
Finkelstein et al., 2022; Atek et al., 2022; Castellano et al., 2022; Adams et
al., 2022; Harikane et al., 2022; Yan et al., 2022) have already been reported
from the JWST Early Release Observations (ERO; Pontoppidan et al., 2022) and
the Cosmic Evolution Early Release Science (CEERS) (Finkelstein et al., 2017)
and Through the Looking GLASS (GLASS-JWST) (Treu et al., 2022) Early Release
Science (ERS) programs that surpass the distance record set by the Hubble
Space Telescope (HST) at $z=11.1$ (Oesch et al., 2016). These independent
studies have revealed an unexpectedly large abundance of bright galaxies
($M_{UV}\lesssim-21$; e.g., Finkelstein et al. 2022; Atek et al. 2022; Furtak
et al. 2022; Naidu et al. 2022a) that could pose a challenge to our current
models of galaxy formation (Ferrara et al., 2022; Harikane et al., 2022; Naidu
et al., 2022b). Similarly, some $z\sim 7-11$ candidates were reported to have
surprisingly large stellar masses $M_{*}>10^{10}M_{\odot}$ (Labbe et al.,
2022) in apparent tension with $\Lambda$CDM (Boylan-Kolchin, 2022; Lovell et
al., 2022) unless these galaxies have lower masses (Endsley et al., 2022;
Steinhardt et al., 2022) or incorrect redshifts.

Simulations suggest we should not have expected to find overly massive
galaxies in early JWST observations, but rather that we have likely only
discovered the youngest, most actively star forming galaxies given imaging
depths to date of AB mag $\sim$29 (Mason et al., 2022). Analyses of these
$z\sim 9-16$ candidates observed in JWST imaging further reveal young stellar
ages $\sim~{}10-100$ Myr (Whitler et al., 2022; Furtak et al., 2022), younger
than the median ages $\sim 100$ Myr measured at slightly lower redshifts
$z\sim 7-9$ (Leethochawalit et al., 2022; Endsley et al., 2022). Evidence that
some of these galaxies are extremely young, $<10$ Myr, $z\sim 7-9$ is provided
by very strong emission lines in NIRSpec spectroscopy (Carnall et al., 2022;
Tacchella et al., 2022; Trussler et al., 2022), with flux excesses also
clearly observed in photometry, especially when imaging is available in four
NIRCam long-wavelength filters F277W, F356W, F410M, and F444W.

Gravitational lensing by massive galaxy clusters can address these problems in
some detail as it provides magnified distant galaxies, boosting their
luminosity and revealing small-scale structures that would otherwise be
unobservable. Using these “cosmic telescopes”, surveys such as CLASH (Postman
et al., 2012), the Hubble Frontier Fields (Lotz et al., 2017), and RELICS (Coe
et al., 2019) have revealed hundreds of galaxy candidates in the reionization
epoch. Using this technique, we have discovered highly magnified (Bradley et
al., 2008; Zheng et al., 2012; Hoag et al., 2017; Bouwens et al., 2014;
Bradley et al., 2014; Infante et al., 2015; Salmon et al., 2018, 2020) and
multiply imaged galaxies (Frye & Broadhurst, 1998; Frye et al., 2008; Coe et
al., 2013; Zitrin et al., 2014) at redshifts up to $z\sim 10.8$, many of which
were the most-distant known galaxy at the time of their discovery. Recent JWST
observations of lensing clusters have pushed this frontier even further with
many high-redshift candidates detected in ERO observations of the massive
galaxy cluster SMACS0723 (Adams et al., 2022; Atek et al., 2022; Morishita &
Stiavelli, 2022; Donnan et al., 2022; Harikane et al., 2022) and the GLASS-
JWST cluster Abell 2744 (Naidu et al., 2022a; Castellano et al., 2022;
Leethochawalit et al., 2022; Donnan et al., 2022; Harikane et al., 2022), with
photometric redshifts out to $z\sim 16$ (Atek et al., 2022) or possibly $z\sim
20$ (Yan et al., 2022).

Gravitationally lensed galaxies have allowed us to place strong constraints on
the evolution of the galaxy ultraviolet luminosity function and the star
formation rate density at $z>8$ (Bouwens et al., 2014; Atek et al., 2015;
Ishigaki et al., 2015; Laporte et al., 2015; Livermore et al., 2017; Bouwens
et al., 2017; Atek et al., 2018; Bhatawdekar et al., 2019; Bouwens et al.,
2022). Gravitational lensing has also provided us the ability to study small-
scale structures and star clusters within high-redshift galaxies down to
scales of a few parsec (e.g., Welch et al., 2022a; Vanzella et al., 2022;
Meštrić et al., 2022).

The Reionization Lensing Cluster Survey (RELICS) HST Treasury Program (Coe et
al., 2019) was designed to efficiently discover high-redshift galaxy
candidates bright enough for follow-up observations with current and future
observatories, including the Atacama Large Millimeter/submillimeter Array
(ALMA) and JWST. By observing 41 strong lensing galaxy clusters with Hubble
and Spitzer, RELICS discovered and studied over 300 high-redshift candidates
in the first billion years (Salmon et al., 2020; Strait et al., 2021),
including the brightest robust candidates known at $z\sim 6$, the Sunrise Arc,
a 2$\farcs$5 long arc at $z\sim 6$ (Salmon et al., 2020), and the most distant
spatially-resolved lensed arc, SPT0615-JD1, at $z\sim 10$ (Salmon et al.,
2018). Remarkably, the RELICS survey also discovered the gravitationally
lensed star WHL0137-LS, nicknamed Earendel, with a photometric redshift
$z_{\rm phot}=6.2\pm 0.1$ (Welch et al., 2022b).

Earendel was discovered within the $z\sim 6$ Sunrise Arc Welch et al. (2022a)
lensed by the massive galaxy cluster WHL J013719.8–082841 (hereafter
WHL0137$-$08; RA = 01:37:25.0, Dec = $-$08:27:23, J2000), which is the focus
of this paper. WHL0137$-$08 was discovered by by Wen et al. (2012) based on
photometric redshifts in SDSS-III DR8 (Aihara et al., 2011) and has a
spectroscopic redshift of $z=0.566$ based on two cluster members within
$r_{500}=0.82$ Mpc from its brightest cluster galaxy (Wen & Han, 2015). The
Planck SZ survey also identified this cluster (WHL-J24.3324-8.477) as the 31st
most massive in the Planck PSZ2 catalog with $M_{500}=(8.9\pm 0.7)\times
10^{14}M_{\odot}$ (Planck Collaboration et al., 2016).

In this paper, we present high-redshift candidates at $z\sim 8.5-13$
discovered in JWST NIRCam imaging of WHL0137$-$08, obtained primarily to study
Earendel (Welch et al., 2022c) and the Sunrise Arc in more detail. Our sample
includes both strongly-lensed galaxy candidates discovered behind the cluster
and candidates in the nearby NIRCam module, centered $\sim$ 2$\farcm$9 from
the cluster center, with weak magnifications of $\mu\leq 1.1$. We use the AB
magnitude system, $m_{\rm AB}=31.4-2.5\log(f_{\nu}/{\rm nJy})$ (Oke, 1974; Oke
& Gunn, 1983). Where needed, we adopt a Planck 2018 flat $\Lambda$CDM
cosmology (Planck Collaboration et al., 2020) with $H_{0}=67.7$ km s-1 Mpc-1,
$\Omega_{\rm m}=0.31$, and $\Omega_{\Lambda}=0.69$, for which the universe is
13.8 billion years old and $1\arcsec\sim 4.6$ kpc at $z=9$.

All of the JWST and HST data of WHL0137$-$08 are public. Reduced images,
catalogs, lens models, and analysis code are available via our
website.111https://cosmic-spring.github.io

Figure 1: JWST NIRCam color image (using all eight filters) of the
WHL0137$-$08 cluster field. The locations of the three (of 12 total) strongly
lensed high-redshift candidates in the WHL0137$-$08 cluster field are
indicated with red circles or ellipses. The locations of the other nine high-
redshift candidates are shown in Figure 2.  Figure 2: JWST NIRCam color image
(using all eight filters) of the nearby field (NIRCam A module), centered
$\sim 2\farcm 9$ from the WHL0137$-$08 cluster center. The locations of the
nine (of 12 total) high-redshift candidates in this field are indicated with
red circles. The locations of the other three high-redshift candidates are
shown in Figure 1.

##  2 Observations

Table 1: HST and JWST Observations, Exposure Times, and Depths  |  | Wavelength | Observation Date | Exposure Time |  $m_{\rm lim}$aa5$\sigma$ limiting AB magnitude in a $r=0\farcs 1$ circular aperture
|  $f_{\rm lim}$bb5$\sigma$ limiting flux in a $r=0\farcs 1$ circular aperture
---|---|---|---|---|---|---
Camera | Filter | (µm) |  | (s) | (AB) | (nJy)
HST ACS/WFC | F435W | 0.37–0.47 | 2016 Jun |  2072 | 27.7 |  30.2
HST ACS/WFC | F475W | 0.4–0.55 | 2019 Nov |  3988 | 28.5 |  14.5
HST ACS/WFC | F606W | 0.47–0.7 | 2016 Jul |  2072 | 28.3 |  17.4
HST ACS/WFC | F814W | 0.7–0.95 | 2016 Jun; 2019 Nov–Dec | 13326 | 28.7 |  12.0
HST WFC3/IR | F105W | 0.9–1.2 | 2016 Jun–Jul |  1411 | 27.8 |  27.5
HST WFC3/IR | F110W | 0.9–1.4 | 2019 Nov; 2021 Nov; 2022 Jan | 10047 | 29.1 |  8.3
HST WFC3/IR | F125W | 1.1–1.4 | 2016 Jun–Jul |  711 | 27.3 | 43.7
HST WFC3/IR | F140W | 1.2–1.6 | 2016 Jun–Jul |  711 | 27.4 |  39.8
HST WFC3/IR | F160W | 1.4–1.7 | 2016 Jun–Jul |  1961 | 27.8 |  27.5
JWST NIRCam | F090W | 0.8–1.0 | 2022 Jul |  2104 | 28.3 |  17.4
JWST NIRCam | F115W | 1.0–1.3 | 2022 Jul |  2104 | 28.4 |  15.8
JWST NIRCam | F150W | 1.3–1.7 | 2022 Jul |  2104 | 28.5 |  14.5
JWST NIRCam | F200W | 1.7–2.2 | 2022 Jul |  2104 | 28.7 |  12.0
JWST NIRCam | F277W | 2.4–3.1 | 2022 Jul |  2104 | 29.1 |  8.3
JWST NIRCam | F356W | 3.1–4.0 | 2022 Jul |  2104 | 29.3 |  6.9
JWST NIRCam | F410M | 3.8–4.3 | 2022 Jul |  2104 | 28.6 |  13.2
JWST NIRCam | F444W | 3.8–5.0 | 2022 Jul |  2104 | 29.0 |  9.1

###  2.1 JWST Data

We obtained JWST NIRCam imaging of WHL0137$-$08 (GO 2282, PI Coe) in July 2022
as part of a program to further study Earendel and the Sunrise Arc. The NIRCam
observations cover eight filters (F090W, F115W, F150W, F200W, F277W, F365W,
F410M, and F444W) spanning $0.8-5.0~{}\micron$ with 2104 s of exposure time in
each filter. Each exposure uses the SHALLOW5 readout pattern with ten groups
and one integration. We use the INTRAMODULEBOX dither pattern with four
dithers to fill the 5″ gaps in the short wavelength detectors and to maximize
the area with full exposure time. The dither pattern also mitigates the
effects of bad pixels and image artifacts and also improves the spatial
resolution of the resampled/drizzled images. The NIRCam imaging was obtained
over two $2\farcm 26\times 2\farcm 26$ fields separated by 40.5″, covering
10.2 arcmin2 in total. The WHL0137$-$08 cluster was centered on NIRCam module
B while NIRCam module A obtained observations on a nearby field centered
$\sim$ 2$\farcm$9 from the cluster center. Additional NIRSpec prism
spectroscopy on the cluster field and JWST NIRCam imaging in four filters
(F090W, F115W, F277W, and F356W) are scheduled to be obtained in late
November/December 2022.

###  2.2 HST Data

The RELICS HST Treasury program (GO 14096; Coe et al., 2019) obtained the
first HST imaging of the galaxy cluster WHL0137$-$08 in 2016 with three orbits
of ACS (F435W, F606W, and F814W) and two orbits of WFC3/IR (F105W, F125W,
F140W, and F160W) data spanning $0.4-1.7~{}\micron$. Two follow-up HST imaging
programs (GO 15842 and GO 16668; PI: Coe) have thus far obtained an additional
5 orbits of HST ACS imaging in F814W, 2 orbits in F475W, and 4 orbits with
WFC3/IR in F110W. Two more orbits of WFC3/IR F110W data are yet to be obtained
from the Earendel monitoring program (GO 16668). The HST data cover only the
cluster field.

In total, the JWST and HST observations of WHL0137$-$08 include imaging in 17
filters spanning $0.4-5.0~{}\micron$. We show color images of the JWST data in
Figures 1 and 2. The observations are summarized in Table 1.

##  3 Methods

###  3.1 Data Reduction

We retrieved the HST FLT data and the JWST pipeline-calibrated level-2 imaging
products and processed them using the grizli pipeline (Brammer et al., 2022).
The JWST data were processed with version 1.5.3 of the calibration pipeline
with CRDS context jwst_0942.pmap, which includes photometric calibrations
based on in-flight data. The JWST level-2 data were subsequently scaled with
detector-dependent factors222https://zenodo.org/record/7143382 based on a
NIRCam flux calibration using the flux calibration standard star J1743045.
While calibration of JWST instruments is still ongoing, our updated
photometric zeropoints are similar to those derived by other teams analyzing
the M92 globular cluster data obtained from the JWST Resolved Stellar
Populations ERS program (Boyer et al., 2022; Nardiello et al., 2022). A more
recent calibration based on CAL program data jwst_0989.pmap is consistent
within 3% for all filters analyzed here.

For the JWST data, the grizli reduction pipeline applies a correction to
reduce the effect of $1/f$ noise and masks “snowballs”333https://jwst-
docs.stsci.edu/data-artifacts-and-features/snowballs-artifact that are are
caused by large cosmic ray impacts to the NIRCam detectors. The grizli
pipeline also includes a correction for faint, diffuse stray light features,
called “wisps”444https://jwst-docs.stsci.edu/jwst-near-infrared-camera/nircam-
features-and-caveats/nircam-claws-and-wisps that are present at the same
detector locations in NIRCam images. These stray-light features are most
prominent in the NIRCam A3, B3, and B4 detectors in the F150W and F200W data.
A “wisp” template was subtracted from each of these detectors for both the
F150W and F200W data.

The grizli pipeline aligns the HST and JWST data to a common world coordinate
system registered to the GAIA DR3 catalogs (Gaia Collaboration et al., 2021).
The fully-calibrated images in each filter were combined and drizzled to a
common pixel grid using astrodrizzle (Koekemoer et al., 2003; Hoffmann et al.,
2021). The HST and JWST NIRCam long-wavelength (LW) filters (F277W, F365W,
F410M, and F444W) were drizzled to a grid of 0$\farcs$04 per pixel while the
JWST short-wavelength NIRCam filters (F090W, F115W, F150W, and F200W) were
drizzled to a grid of 0$\farcs$02 per pixel.

These grizli reduced images are available publicly, alongside images and
catalogs from other JWST programs with public
data.555https://s3.amazonaws.com/grizli-v2/JwstMosaics/v4/index.html

###  3.2 Photometric Catalogs

To produce the photometric catalogs, the NIRCam SW images were first rebinned
to a pixel scale of 0$\farcs$04 per pixel, placing the images for all 17
filters on the same pixel grid. Sources were then identified in a detection
image comprised of a weighted sum of all NIRCam LW images (F277W, F356W,
F410M, F444W) using photutils (Bradley et al., 2022) image-segmentation tools.
Visual inspection of the segmentation image revealed a $2\farcs 6$ long lensed
arc that had been segmented into five separate components. Therefore, we
combined the separate arc segments into a single source before performing
photometry.

Source fluxes were measured with photutils in isophotal, circular, and
elliptical Kron apertures (with scale factors of both 1.5 and 2.5). The
photometry was corrected to total fluxes by comparing the total (scale factor
of 2.5) Kron flux measurements to the flux measurements in the detection
image.

###  3.3 Photometric Redshifts

We derive initial photometric redshifts using eazypy (Brammer et al., 2008),
which fits the observed photometry of each galaxy using a set of templates
added in a non-negative linear combination. We use the photometry measured in
elliptical Kron apertures with a scale factor of 1.5. Both JWST and HST
photometry is included in the photometric redshift calculations for the
WHL0137$-$08 cluster field, while only JWST photometry is used for the Module
A field. The photometric redshifts were calculated using a template set
comprised of the 12 “tweak_fsps_QSF_12_v3” templates derived from the Flexible
Stellar Population Synthesis (FSPS) library (Conroy et al., 2009, 2010; Conroy
& Gunn, 2010), which include a range of galaxy types (e.g., star-forming,
quiescent, dusty) and realistic star formation histories (e.g., bursty, slowly
rising, slowly falling). To these FSPS templates, we add six templates from
Larson et al. (2022, in prep) that span bluer colors than the fiducial FSPS
templates. These additional templates were found to provide better
photometric-redshift accuracies for bluer galaxies at $z>9$ (Larson et al.
2022, in prep). We allow the redshifts to span from $0.1<z<20$, in steps of
0.01, and adopt a flat luminosity prior as we are just beginning to explore
galaxies at these epochs.

###  3.4 High-Redshift Candidate Selection

We select our initial sample of high-redshift candidate galaxies using a
combination of criteria using both signal-to-noise and photometric redshift
measurements. Selecting high-redshift galaxy candidates using photometric
redshifts is generally more robust than a Lyman break color-color selection,
especially when using multiband photometry in a large number of filters. The
photometric signal-to-noise (SNR) criteria are used to both ensure non-
detections in filters blueward of the Lyman break and to ensure robust
photometric detections in multiple filters redward of the break, which
minimizes spurious noise detections. We also visually inspect each candidate
galaxy in each filter image and its best-fit SED to remove detector artifacts
and other spurious sources such as diffraction spikes, misidentified parts of
larger galaxies, and spurious noise close to the detector edge.

We used the following criteria to select our initial sample of high-redshift
candidates between $8.5\leq z\leq 13$:

  * •

SNR $<1.5$ in F090W

  * •

SNR $>4.5$ in each of F200W and F277W

  * •

SNR $>4.0$ in F356W

  * •

SNR $>3.5$ in F444W

  * •

Best-fit photometric redshift measured by eazypy of $8.5\leq z_{\rm best}\leq
13$

  * •

Integral of the eazypy posterior redshift probability (${\rm P}(z)$) at $z>8$
of $\int{\rm P}(z>8)~{}{\rm d}z>0.8$

  * •

$\chi^{2}$ of the best-fit eazypy spectral-energy distribution (SED) of
$\chi^{2}<30$

We decrease the SNR criteria in the redder NIRCam filters (F356W and F444W) so
as not to exclude sources with rest-frame UV slopes bluer than $\beta=-2$, as
expected for young star-forming galaxies at these epochs.

We used the following criteria to select high-redshift candidates at $z>13$,
as more of the NIRCam filters fall blueward of the Lyman break at this high
redshift:

  * •

SNR $<1.5$ in each of F090W, F115W, and F150W

  * •

SNR $>4.5$ in F277W

  * •

SNR $>4.0$ in F356W

  * •

SNR $>3.0$ in F444W

  * •

Best-fit photometric redshift measured by eazypy of $z_{\rm best}>13$

  * •

Integral of the eazypy ${\rm P}(z)$ at $z>8$ of $\int{\rm P}(z>8)~{}{\rm
d}z>0.8$

  * •

$\chi^{2}$ of the best-fit eazypy SED of $\chi^{2}<30$

As an additional check, we also calculated photometric redshifts using eazypy
with the recently-added SFHZ templates. These templates have redshift-
dependent star formation histories (SFH) that disfavor star formation starting
earlier than the age of the universe at a given epoch. We excluded candidates
from our high-redshift sample where these templates prefer a low-redshift
($z_{\rm best}<8.2$) solution.

Our results do not appear to be strongly dependent on the current
uncertainties in the NIRCam zeropoints, which appear to be converging based on
in-flight data (Boyer et al., 2022; Nardiello et al., 2022). The most recent
calibration jwst_0989.pmap alters flux measurements by $<$3% for all filters
analyzed here. Uncertainties may remain at the few-percent level, which will
improve in the coming months with ongoing calibration of the JWST detectors.

##  4 Results and Discussion

###  4.1 High-Redshift Sample

After visual inspection of all candidates meeting the above criteria in all
filters, our high-redshift sample consists of 12 candidates at $8.5\lesssim
z\lesssim 13$. Three of these candidates lie in the cluster field, while the
remaining nine are located in the nearby field.

To further refine our selection and to measure the physical properties of our
candidates, we also perform SED fitting to the photometry of these galaxies
using the Bayesian Analysis of Galaxies for Physical Inference and Parameter
EStimation (bagpipes; Carnall et al., 2018) Python package and the BayEsian
Analysis of GaLaxy sEds (beagle; Chevallard & Charlot, 2016) tool (as
described in Section 4.3) with redshift as a free parameter.

Table 2: JWST photometry for the complete sample of high-redshift candidates

Object ID | RA | Dec | F090W | F115W | F150W | F200W | F277W | F356W | F410M | F444W
---|---|---|---|---|---|---|---|---|---|---
|  |  | nJy | nJy | nJy | nJy | nJy | nJy | nJy | nJy
WHL0137-2796 | $24.35728628$ | $-8.44395829$ | $-20.9\pm 8.3$ | $18.6\pm 8.3$ | $42.4\pm 7.2$ | $28.5\pm 5.9$ | $24.7\pm 4.6$ | $30.1\pm 4.2$ | $12.5\pm 7.6$ | $52.6\pm 6.4$
WHL0137-3407 | $24.33681002$ | $-8.43027068$ | $9.3\pm 12.2$ | $-11.5\pm 12.2$ | $42.6\pm 10.5$ | $68.8\pm 8.7$ | $36.0\pm 7.0$ | $51.0\pm 6.3$ | $30.8\pm 11.1$ | $50.2\pm 9.6$
WHL0137-4162 | $24.34989806$ | $-8.41981804$ | $1.2\pm 6.4$ | $21.2\pm 6.5$ | $89.6\pm 6.0$ | $95.3\pm 4.9$ | $93.4\pm 4.0$ | $123.3\pm 3.7$ | $145.9\pm 6.2$ | $257.7\pm 5.4$
WHL0137-5021 | $24.34164298$ | $-8.41088838$ | $6.9\pm 8.5$ | $7.7\pm 8.8$ | $-8.8\pm 7.0$ | $33.1\pm 5.9$ | $23.3\pm 2.5$ | $20.5\pm 2.3$ | $20.9\pm 3.9$ | $24.2\pm 3.3$
WHL0137-5124 | $24.35319048$ | $-8.40969086$ | $-4.8\pm 4.6$ | $-3.2\pm 4.7$ | $2.6\pm 4.1$ | $21.5\pm 4.0$ | $23.2\pm 2.8$ | $22.5\pm 2.6$ | $24.6\pm 4.3$ | $23.2\pm 3.7$
WHL0137-5330 | $24.32695269$ | $-8.40731766$ | $5.3\pm 8.8$ | $-19.8\pm 9.0$ | $35.2\pm 7.6$ | $34.2\pm 6.3$ | $30.6\pm 4.6$ | $38.1\pm 4.2$ | $34.9\pm 7.3$ | $45.0\pm 6.3$
WHL0137-5347 | $24.34722190$ | $-8.40708651$ | $-4.9\pm 15.4$ | $2.4\pm 15.3$ | $72.3\pm 13.2$ | $77.3\pm 11.1$ | $74.0\pm 6.4$ | $83.5\pm 5.7$ | $68.5\pm 9.7$ | $90.6\pm 8.3$
WHL0137-6334 | $24.33004749$ | $-8.39712224$ | $7.8\pm 9.0$ | $58.5\pm 9.4$ | $106.3\pm 8.1$ | $97.2\pm 6.6$ | $81.7\pm 4.7$ | $74.5\pm 4.3$ | $91.4\pm 7.6$ | $79.5\pm 6.4$
WHL0137-7009 | $24.34160793$ | $-8.47343768$ | $-3.3\pm 18.4$ | $93.6\pm 18.7$ | $174.7\pm 15.1$ | $152.8\pm 12.6$ | $107.8\pm 9.2$ | $107.9\pm 8.3$ | $82.3\pm 15.5$ | $107.9\pm 12.6$
WHL0137-8737 | $24.35194851$ | $-8.41252722$ | $-4.5\pm 8.5$ | $13.8\pm 8.7$ | $69.2\pm 7.7$ | $64.1\pm 6.2$ | $34.1\pm 5.2$ | $48.0\pm 4.6$ | $39.8\pm 7.9$ | $39.7\pm 6.8$
WHL0137-8907 | $24.33414448$ | $-8.40719349$ | $8.2\pm 8.8$ | $35.1\pm 9.1$ | $101.7\pm 7.9$ | $84.0\pm 6.5$ | $68.0\pm 5.4$ | $66.4\pm 4.8$ | $83.0\pm 8.3$ | $61.2\pm 7.2$
WHL0137-9356 | $24.35502755$ | $-8.44791872$ | $-12.8\pm 17.5$ | $52.7\pm 19.0$ | $169.8\pm 14.9$ | $135.0\pm 12.2$ | $127.4\pm 9.1$ | $113.5\pm 8.3$ | $101.5\pm 15.2$ | $190.1\pm 12.5$

Note. — Observed fluxes, uncorrected for magnification. $m_{\rm
AB}=31.4-2.5\log(f_{\nu}/{\rm nJy}).$

Table 3: HST Photometry of the three lensed high-redshift candidates

Object ID | F105W | F110W | F125W | F140W | F160W | F435W | F475W | F606W | F814W
---|---|---|---|---|---|---|---|---|---
| nJy | nJy | nJy | nJy | nJy | nJy | nJy | nJy | nJy
WHL0137-2796 | $6.1\pm 28.3$ | $6.2\pm 5.6$ | $-39.6\pm 50.8$ | $5.2\pm 42.1$ | $41.3\pm 29.2$ | $7.1\pm 22.5$ | $-31.4\pm 10.4$ | $-9.9\pm 13.7$ | $2.2\pm 7.7$
WHL0137-7009 | $167.5\pm 85.7$ | $48.3\pm 16.3$ | $84.0\pm 149.1$ | $-9.1\pm 127.2$ | $71.2\pm 85.4$ | $45.6\pm 42.1$ | $-31.5\pm 20.4$ | $27.3\pm 25.6$ | $-36.6\pm 15.5$
WHL0137-9356 | $111.4\pm 55.3$ | $44.6\pm 11.3$ | $41.0\pm 98.0$ | $11.4\pm 82.2$ | $39.6\pm 57.2$ | $-8.4\pm 46.5$ | $16.5\pm 21.0$ | $18.0\pm 26.8$ | $-11.3\pm 15.4$

Note. — Observed fluxes, uncorrected for magnification. $m_{\rm
AB}=31.4-2.5\log(f_{\nu}/{\rm nJy}).$

Figure 3: Cutout images, best-fit spectral energy distributions (SEDs), and
posterior redshift distributions for the high-redshift galaxy candidates
WHL0137–ID2796 and WHL0137–ID3407. Top panels: $3\arcsec\times 3\arcsec$ JWST
cutout images spanning $0.9-4.5~{}\micron$ centered on each candidate. Bottom-
left panels: Source photometry is shown as blue data points or triangle upper
limits. Non-detections are plotted as upper limits at the $1\sigma$ level. The
best-fit bagpipes spectral energy distribution (SED) model at high-redshift
($z\geq 7$) is shown in orange with squares indicating the expected photometry
in a given band. The best-fit bagpipes SED for a low-redshift ($z<7$) solution
is shown in gray. Bottom-right panels: Posterior probability distributions
(${\rm P}(z)$) for the source photometric redshift derived using eazypy (using
both the FSPS+Larson and SFHZ template sets), bagpipes, and beagle.

Figure 4: Same as Figure 3, but for the high-redshift galaxy candidates
WHL0137–ID4162 and WHL0137–ID5021. For WHL0137–ID4162 we also plot the best-
fit beagle SED model (see Section 4.4) in green with squares indicating the
expected photometry in a given band.

Figure 5: Same as Figure 3, but for the high-redshift galaxy candidates
WHL0137–ID5124 and WHL0137–ID5330.

Figure 6: Same as Figure 3, but for the high-redshift galaxy candidates
WHL0137–ID5347 and WHL0137–ID6334.

Figure 7: Same as Figure 3, but for the high-redshift galaxy candidates
WHL0137–ID7009 and WHL0137–ID8737.

Figure 8: Same as Figure 3, but for the high-redshift galaxy candidates
WHL0137–ID8907 and WHL0137–ID9356.

The measured (uncorrected for magnification) JWST photometry of our high-
redshift candidates is presented in Table 2. For the three lensed high-
redshift candidates in the cluster field, we also present their measured
(uncorrected for magnification) HST photometry in Table 3. In Figures 3 – 8 we
present $3\arcsec\times 3\arcsec$ cutout images, the best-fit SEDs, and the
posterior redshift distributions, ${\rm P}(z)$, for each candidate. The
posterior redshift distributions include plots for eazypy (for both the
FSPS+Larson and SFHZ template sets), bagpipes, and beagle. We plot in Figures
3 – 8 the bagpipes best-fit high-redshift ($z\geq 7$) SED along with the best-
fit low-redshift SED constrained with redshift $z<7$.

As observed from the cutout images presented in Figures 3 – 8, about half of
our candidates are located within $1\farcs 5$ of a brighter foreground galaxy.
Our deep JWST images show a clear and distinct separation between the high-
redshift candidates and their neighboring galaxies, with the possible
exception of WHL0137–ID7009, which is directly adjacent to the foreground
galaxy in the segmentation image. The high-redshift galaxy candidates also
have distinct colors from their neighbors suggesting they are not likely
physically associated (e.g., embedded in the outer regions of the foreground
galaxies). Based on integrated number densities in non-lensed fields (see
Windhorst et al., 2022, Figure 10), we would statistically expect a $\sim$22%
probability of finding an unrelated foreground galaxy to $<25$ AB mag. Our
results are slightly above this probability at 33% (3 of 9), which could
possibly suggest that one of our sources is a contaminant. However, this
result may also be due to small number statistics.

###  4.2 Magnifications

To estimate source magnifications, we use the lens models constructed to
analyze Earendel and the Sunrise Arc published in Welch et al. (2022b) and
which were made publicly
available.666https://relics.stsci.edu/lens_models/outgoing/whl0137-08/ These
models were generated using four independent lens modeling software packages:
Light-Traces-Mass (LTM, Zitrin et al., 2009, 2015; Broadhurst et al., 2005),
Glafic (Oguri, 2010), WSLAP+ (Diego et al., 2005, 2007), and Lenstool (Jullo
et al., 2007; Jullo & Kneib, 2009). Due to a lack of multiply-imaged sources
in this cluster, the slope of the lensing potential in these models varies by
a factor of six, which adds considerable uncertainty to our magnification
estimates. For further details about each model, please see Welch et al.
(2022b).

Three of the candidates in our sample are strongly lensed by the WHL0137$-$08
galaxy cluster, while the other nine candidates, located in the nearby NIRCam
module, are expected to have only weak magnifications of $\mu\leq 1.1$. The
three lensed candidates are WHL0137–ID2796, WHL0137–ID7009, and
WHL0137–ID9356. Using the four lens models described above, WHL0137–ID2796 has
a magnification in the range from $\mu=1.3-9.6$, with a mean value of
$\mu=6.1$. WHL0137–ID7009 extends beyond the range of the Glafic lens model,
so its magnification is based on the other three lens models. This source has
a magnification in the range from $\mu=1.5-5.2$, with a mean value of
$\mu=2.9$. WHL0137–ID9356 has the largest magnification with a magnification
in the range from $\mu=2.4-20.2$, with a mean value of $\mu=7.9$. The mean
magnifications and uncertainties are quoted in Tables 4 and 5.

###  4.3 Spectral Energy Distribution (SED) Fitting

####  4.3.1 bagpipes

For each galaxy in our high-redshift sample, we estimate its physical
properties using SED fitting. We first performed SED fitting using the
bagpipes (Carnall et al., 2018) Python package. bagpipes generates model
galaxy spectra over the multidimensional space of physical parameters and fits
these to the photometric data using the multinest nested sampling algorithm
(Feroz & Hobson, 2008; Feroz et al., 2009; Feroz & Skilling, 2013). bagpipes
uses the stellar population synthesis models from the 2016 version of the BC03
(Bruzual & Charlot, 2003) models. These models were generated using a Kroupa
(2002) initial mass function (IMF) and include nebular line and continuum
emission based on Cloudy (Ferland et al., 2013), with the logarithm of
ionization parameter ($\log$ U) allowed to vary between $-4$ to $-2$. We
perform our SED fitting using a delayed exponentially declining SFH where the
star formation rate (SFR) is of the form SFR$(t)\propto t\ \exp{(-t/\tau)}$.
Models assuming a constant star formation rate yield younger ages and higher
sSFRs, as discussed below in §4.4.

For SED fits constrained to be at low redshift ($z<7$, we assume a Calzetti
law (Calzetti et al., 2000) for dust attenuation. For SED fits constrained to
be a high redshift ($z>7$), we assume a Small Magellanic Cloud (SMC) dust law
(Salim et al., 2018). For both cases, we also include a second component to
the dust model that includes birth-cloud dust attenuation that is a factor of
two larger around H ii regions as in the general ISM within the galaxy’s first
10 Myr. We allow dust extinction to range from $A_{V}$ = $0-5$ magnitudes and
we vary metallicity in logarithmic space from $\log Z/Z_{\odot}=0.005-5$.
Formation ages vary from 1 Myr to the age of the universe.

####  4.3.2 beagle

We also perform SED fitting on each candidate galaxy using the beagle tool
(Chevallard & Charlot, 2016) with simplified version of the configuration, fit
parameters, and parameter space used in Atek et al. (2022) and Furtak et al.
(2022). beagle uses SED templates by Gutkin et al. (2016), which also combine
the 2016 version of the BC03 stellar population synthesis models with Cloudy
to account for nebular emission. The templates include ionization parameters
varying from $-4$ to $-1$. These templates all assume a Chabrier (2003) IMF
and model the intergalactic attenuation using the Inoue et al. (2014)
attenuation curves. As with bagpipes, we assume a delayed exponential SFH, but
with the possibility of an ongoing star-burst over the last 10 Myr. This
allows for maximum flexibility of the SFH to be either rising or declining
with a maximum at $t=\tau$. We account for dust attenuation by assuming an
SMC-like dust attenuation law (Pei, 1992), which has been found to fit high-
redshift galaxies best at low metallicities (Capak et al., 2015; Reddy et al.,
2015, 2018; Shivaei et al., 2020). Due to the relatively large number of free
parameters, we fix the metallicity to $Z=0.1\,\mathrm{Z}_{\odot}$ while the
stellar mass, current SFR, maximal stellar age and dust attenuation are
allowed to vary freely in the ranges
$\log(M_{\star}/\mathrm{M}_{\odot})\in[6,11]$,
$\log(\psi/\mathrm{M}_{\odot}\,\mathrm{yr}^{-1})\in[-4,4]$,
$\log(t_{\mathrm{age}}/\mathrm{yr})\in[6,t_{\mathrm{Universe}}]$ and
$A_{V}\in[0,3]$ respectively.

###  4.4 Physical Properties

Table 4: bagpipes photometric redshifts and physical properties of the high-
redshift galaxy candidates

Object ID |  $\mu_{\rm mean}$aaMean magnification and uncertainties based on multiple independent lens models. Candidates in the nearby field are estimated to have magnifications of $\mu\leq 1.1$. |  $z_{\rm phot}$bbPhotometric redshift with 2$\sigma$ uncertainties, using the Calzetti dust law (Calzetti et al., 2000). |  $z_{\rm phot}$ccPhotometric redshift restricted to $z>7$ with 2$\sigma$ uncertainties, using the SMC dust law (Salim et al., 2018). | $\log M_{\star}/M_{\odot}$ | SFRddStar formation rate during the past 1 Myr. |  $\log$ sSFR/Gyr | AgeeeMass-weighted age for the delayed $\tau$ star formation history. | $A_{V}$ |  $t_{\rm form}$ffFormation time in Myr after the Big Bang based on the mass-weighted age.
---|---|---|---|---|---|---|---|---|---
|  |  | $z>7$ |  | $M_{\odot}/yr$ |  | Myr | mag | Myr
WHL0137-2796 | $6^{+4}_{-5}$ | $8.7^{+1.5}_{-8.3}$ | $8.5^{+1.5}_{-0.6}$ | $7.46^{+0.41}_{-0.59}$ | $0.8^{+1.0}_{-0.3}$ | $1.4^{+1.0}_{-0.5}$ | $32^{+95}_{-30}$ | $0.06^{+0.05}_{-0.04}$ | 538
WHL0137-3407 |  $\cdots$ | $10.5^{+1.0}_{-10.5}$ | $10.7^{+0.9}_{-1.6}$ | $8.78^{+0.17}_{-0.33}$ | $7.3^{+2.5}_{-1.2}$ | $1.1^{+0.4}_{-0.2}$ | $70^{+50}_{-44}$ | $0.04^{+0.05}_{-0.03}$ | 371
WHL0137-4162 |  $\cdots$ | $8.8^{+0.1}_{-0.3}$ | $8.8^{+0.1}_{-1.0}$ | $8.42^{+0.05}_{-0.03}$ | $61.4^{+17.3}_{-9.6}$ | $2.4^{+0.1}_{-0.1}$ | $3^{+1}_{-1}$ | $0.13^{+0.02}_{-0.01}$ | 558
WHL0137-5021 |  $\cdots$ | $12.8^{+1.1}_{-12.5}$ | $12.8^{+1.2}_{-1.2}$ | $8.53^{+0.18}_{-0.32}$ | $5.1^{+1.9}_{-1.1}$ | $1.2^{+0.4}_{-0.2}$ | $58^{+37}_{-37}$ | $0.05^{+0.06}_{-0.04}$ | 277
WHL0137-5124 |  $\cdots$ | $12.8^{+1.9}_{-12.4}$ | $12.7^{+1.8}_{-1.5}$ | $8.65^{+0.20}_{-0.30}$ | $6.9^{+3.2}_{-1.9}$ | $1.2^{+0.4}_{-0.2}$ | $59^{+35}_{-37}$ | $0.12^{+0.08}_{-0.06}$ | 276
WHL0137-5330 |  $\cdots$ | $10.0^{+1.1}_{-7.9}$ | $10.0^{+1.1}_{-1.1}$ | $8.77^{+0.16}_{-0.26}$ | $6.4^{+2.6}_{-1.8}$ | $1.0^{+0.3}_{-0.2}$ | $83^{+52}_{-48}$ | $0.11^{+0.07}_{-0.06}$ | 388
WHL0137-5347 |  $\cdots$ | $10.2^{+0.9}_{-9.7}$ | $10.2^{+0.9}_{-1.7}$ | $9.01^{+0.21}_{-0.37}$ | $14.6^{+5.8}_{-3.5}$ | $1.1^{+0.5}_{-0.3}$ | $62^{+54}_{-43}$ | $0.09^{+0.05}_{-0.04}$ | 397
WHL0137-6334 |  $\cdots$ | $8.4^{+0.4}_{-8.2}$ | $8.5^{+0.3}_{-0.4}$ | $8.75^{+0.14}_{-0.19}$ | $9.2^{+2.2}_{-1.3}$ | $1.2^{+0.3}_{-0.2}$ | $50^{+33}_{-25}$ | $0.02^{+0.02}_{-0.01}$ | 547
WHL0137-7009 | $3^{+2}_{-1.5}$ | $8.4^{+0.5}_{-0.3}$ | $8.4^{+0.5}_{-0.4}$ | $8.16^{+0.18}_{-0.23}$ | $5.1^{+1.4}_{-0.8}$ | $1.5^{+0.3}_{-0.3}$ | $22^{+20}_{-12}$ | $0.01^{+0.01}_{-0.01}$ | 575
WHL0137-8737 |  $\cdots$ | $9.3^{+1.0}_{-9.3}$ | $9.2^{+1.0}_{-0.7}$ | $8.46^{+0.24}_{-0.29}$ | $6.0^{+1.6}_{-1.0}$ | $1.3^{+0.4}_{-0.3}$ | $40^{+45}_{-25}$ | $0.01^{+0.02}_{-0.01}$ | 480
WHL0137-8907 |  $\cdots$ | $8.8^{+0.5}_{-0.3}$ | $8.8^{+0.4}_{-0.3}$ | $8.69^{+0.16}_{-0.21}$ | $8.2^{+1.7}_{-1.1}$ | $1.2^{+0.3}_{-0.2}$ | $49^{+36}_{-25}$ | $0.01^{+0.01}_{-0.01}$ | 512
WHL0137-9356 | $8^{+12}_{-6}$ | $8.9^{+0.5}_{-0.4}$ | $8.8^{+0.4}_{-0.5}$ | $7.71^{+0.49}_{-0.34}$ | $2.6^{+3.3}_{-0.9}$ | $1.7^{+0.7}_{-0.7}$ | $14^{+60}_{-12}$ | $0.03^{+0.03}_{-0.02}$ | 538

Note. — Physical parameter results are quoted for high-redshift solutions
restricting $z>7$. We quote the median and the $1\sigma$ range of the joint
posterior distributions for each galaxy. We have modeled star formation
histories as exponential delayed $\tau$ model. If constant star formation
histories are assumed, age estimates decrease and sSFR increases. For the
three lensed sources, stellar masses and SFRs are corrected for the mean
magnification. Multiply these values by $\mu_{\rm mean}/\mu$ to apply a
different magnification. We did not propagate magnification uncertainties to
those parameter uncertainties.

Table 5: beagle photometric redshifts and physical properties of the high-
redshift galaxy candidates

Object ID |  $\mu_{\rm mean}$aaMean magnification and uncertainties based on multiple independent lens models. Candidates in the nearby field are estimated to have magnifications of $\mu\leq 1.1$. | $z_{\rm phot}$ | $\log M_{\star}/M_{\odot}$ | SFRbbStar formation rate during the past 1 Myr. |  $\log$ sSFR/GyrccSpecific star formation rate, capped at 100 Gyr-1 = $1/(10$ Myr$)$. | AgeddMass-weighted age in Myr. | $A_{V}$ |  $\beta$eeRest-frame UV slope. |  $M_{UV}$ffRest-frame absolute UV magnitude in the band that contains 1500 Å at the galaxy’s photometric redshift.
---|---|---|---|---|---|---|---|---|---
|  |  |  |  $M_{\odot}$/yr |  | Myr | mag |  |
WHL0137-2796 | $6^{+4}_{-5}$ | $8.3^{+0.4}_{-0.3}$ | $6.37^{+0.74}_{-0.78}$ | $4.6^{+0.7}_{-0.6}$ | $2.0^{+0.0}_{-0.2}$ | $5^{+12}_{-0}$ | $0.07^{+0.07}_{-0.05}$ | $-2.9\pm 0.4$ | $-17.0$
WHL0137-3407 |  $\cdots$ | $10.0^{+1.0}_{-8.0}$ | $7.58^{+1.20}_{-1.12}$ | $1.4^{+8.8}_{-1.1}$ | $1.8^{+0.2}_{-2.0}$ | $11^{+51}_{-7}$ | $0.11^{+1.04}_{-0.09}$ | $-2.6\pm 0.5$ | $-20.6$
WHL0137-4162 |  $\cdots$ | $10.2^{+0.1}_{-0.1}$ | $10.19^{+0.04}_{-0.04}$ | $0.1^{+0.3}_{-0.1}$ | $-2.3^{+0.7}_{-0.7}$ | $227^{+41}_{-50}$ | $0.02^{+0.02}_{-0.01}$ | $-2.0\pm 0.1$ | $-22.5$
WHL0137-5021 |  $\cdots$ | $13.0^{+0.6}_{-0.7}$ | $8.32^{+0.53}_{-1.54}$ | $4.8^{+2.4}_{-4.7}$ | $1.2^{+0.8}_{-2.1}$ | $16^{+45}_{-11}$ | $0.07^{+0.09}_{-0.04}$ | $-2.7\pm 0.3$ | $-19.5$
WHL0137-5124 |  $\cdots$ | $12.8^{+1.0}_{-1.1}$ | $8.51^{+0.51}_{-1.69}$ | $2.7^{+6.1}_{-2.7}$ | $1.0^{+1.0}_{-2.0}$ | $20^{+56}_{-15}$ | $0.19^{+0.14}_{-0.10}$ | $-1.6\pm 0.7$ | $-20.3$
WHL0137-5330 |  $\cdots$ | $10.0^{+0.7}_{-0.6}$ | $8.18^{+0.75}_{-1.52}$ | $6.6^{+2.6}_{-6.2}$ | $1.7^{+0.3}_{-2.0}$ | $14^{+58}_{-10}$ | $0.13^{+0.10}_{-0.08}$ | $-2.3\pm 0.4$ | $-19.4$
WHL0137-5347 |  $\cdots$ | $9.3^{+1.5}_{-0.2}$ | $7.95^{+1.13}_{-1.41}$ | $13.9^{+4.2}_{-13.2}$ | $2.0^{+0.0}_{-2.2}$ | $5^{+34}_{-0}$ | $0.11^{+0.09}_{-0.06}$ | $-2.0\pm 0.3$ | $-20.4$
WHL0137-6334 |  $\cdots$ | $8.5^{+0.2}_{-0.1}$ | $8.78^{+0.07}_{-0.04}$ | $0.1^{+1.0}_{-0.1}$ | $-0.8^{+1.0}_{-0.8}$ | $15^{+3}_{-2}$ | $0.06^{+0.03}_{-0.04}$ | $-2.4\pm 0.2$ | $-20.1$
WHL0137-7009 | $3^{+2}_{-1.5}$ | $8.3^{+0.2}_{-0.3}$ | $8.39^{+0.04}_{-0.05}$ | $0.2^{+0.9}_{-0.2}$ | $-0.6^{+0.8}_{-0.8}$ | $14^{+1}_{-1}$ | $0.03^{+0.03}_{-0.02}$ | $-2.8\pm 0.2$ | $-19.1$
WHL0137-8737 |  $\cdots$ | $9.1^{+0.3}_{-0.4}$ | $8.47^{+0.10}_{-0.77}$ | $0.9^{+4.0}_{-0.9}$ | $0.4^{+1.5}_{-1.5}$ | $14^{+4}_{-5}$ | $0.03^{+0.04}_{-0.02}$ | $-3.1\pm 0.3$ | $-19.1$
WHL0137-8907 |  $\cdots$ | $8.8^{+0.2}_{-0.2}$ | $8.72^{+0.06}_{-0.07}$ | $0.2^{+0.8}_{-0.1}$ | $-0.6^{+0.9}_{-0.8}$ | $15^{+3}_{-2}$ | $0.04^{+0.03}_{-0.03}$ | $-2.7\pm 0.2$ | $-19.7$
WHL0137-9356 | $8^{+12}_{-6}$ | $8.5^{+0.3}_{-0.2}$ | $6.67^{+0.90}_{-1.08}$ | $18.9^{+1.1}_{-1.6}$ | $2.0^{+0.0}_{-0.2}$ | $5^{+12}_{-0}$ | $0.03^{+0.03}_{-0.02}$ | $-2.4\pm 0.2$ | $-18.1$

Note. — Results are quoted as the median and the $1\sigma$ range of the joint
posterior distributions for each galaxy. For the three lensed sources, stellar
masses and SFRs are corrected for magnification. Multiply these values by
$\mu_{\rm mean}/\mu$ to apply a different magnification. We did not propagate
magnification uncertainties to those parameter uncertainties.

The derived physical properties for our candidate high-redshift galaxies using
bagpipes and beagle are presented in Tables 4 and 5, respectively. The
bagpipes results are quoted for high-redshift solutions restricted to $z>7$.

For each of the three gravitationally-lensed candidates, we divide by its mean
magnification (see Section 4.2) to calculate intrinsic stellar mass and SFR.

We measure intrinsic stellar masses of $\log M_{\star}/M_{\odot}$ $\sim$
$7.5-9$ for all galaxies with bagpipes and for most with beagle. With beagle,
the full range spans almost 4 orders of magnitude between $\log
M_{\star}/M_{\odot}$ = $6.3-10.2$. The typical SFRs range from $\sim 1-9$
$M_{\odot}/{\rm yr}$, with full range between $0-61$ $M_{\odot}/{\rm yr}$. In
all cases, the SED fitting reveals relatively young ages of $<100$ Myr. For
all candidates, we also find low dust content with $A_{V}<0.15$, as expected
due to the relatively blue rest-frame UV slopes in our sample of $\beta=-1.6$
to $-3.1$. Specific star formation rates range from sSFR = 20 – 250 Gyr-1.
Note the beagle run considers the most recent 10 Myr of star formation, so the
sSFR results are capped at 100 Gyr-1 = $1/(10$ Myr$)$.

Median age estimates from bagpipes are typically $\sim$50 Myr, while beagle
median ages are typically younger $\sim$15 Myr. Switching bagpipes to a
constant star formation history (CSFH) also results in younger median ages
typically $\sim$20 Myr and sSFR typically higher by 0.2 dex (up to 1.2 dex).

The beagle SED fits of WHL0137–ID4162 have the largest stellar mass with $\log
M_{\star}/M_{\odot}$= $10.19^{+0.04}_{-0.04}$ coupled with the lowest star
formation rate of $0.08^{+0.32}_{-0.07}$ $M_{\odot}/{\rm yr}$. This is a
result of beagle fitting the red F410M – F444W = 0.6 color as a Balmer break
(see Figure 4; top), with a relatively old mass-weighted age of
$227^{+41}_{-50}$ Myr. On the other hand, bagpipes fits this galaxy as an
extremely young ($3^{+1}_{-1}$ Myr) galaxy with a high sSFR rate of $\sim 250$
Gyr-1 and strong inferred [O iii]+H$\beta$ emission (rest-frame equivalent
width of $\sim 2000$ Å). The bagpipes fit yields a more typical mass of $\log
M_{\star}/M_{\odot}$= $8.42^{+0.05}_{-0.03}$.

WHL0137–ID2796 and WHL0137–ID9356 also have relatively red F410M – F444W
colors of $\gtrsim 0.6$. For these two candidates, both bagpipes and beagle
fit these galaxies with a SED template containing strong [O iii]+H$\beta$
optical emission lines. beagle gives very young ages for both of these
galaxies of $<5$ Myr, while bagpipes yields ages of $\sim$32 and 14 Myr for
WHL0137–ID2796 and WHL0137–ID9356, respectively.

###  4.5 A gravitationally-lensed arc at $z\sim 9$

Figure 9: $8\arcsec\times 6\arcsec$ cutout image from the JWST NIRCam
detection image showing the $z\sim 9$ arc WHL0137–ID9356 (red outline), with a
magnification of $\mu\sim 8$. The arc is 2$\farcs$6 long, has at least two
bright star-forming knots, and is the most-spatially resolved arc at $z\sim 9$
known to date. A potential fainter counterimage of the arc, with a similar
color and photometric redshift, is also shown outlined in blue.

One of our lensed high-redshift candidates, WHL0137–ID9356, is stretched into
an arc 2$\farcs$6 long by the effects of strong gravitational lensing. The arc
has at least two bright knots of unevenly distributed star formation (see
Figure 9). This candidate has a lensed F200W AB magnitude of $26\pm 0.1$.
Assuming a magnification of $\mu=7.9$ ($\mu=2.4-20.2$; see Section 4.2), its
intrinsic AB magnitude is $28.2\pm 0.1$.

After correcting for magnification, the bagpipes results yield a stellar mass
of $\log M_{\star}/M_{\odot}$= $7.71^{+0.49}_{-0.34}$ and a star formation
rate of $2.6^{+3.3}_{-0.9}$ $M_{\odot}/{\rm yr}$. This places WHL0137–ID9356
slightly above the Speagle et al. (2014) time-dependent SFR–$M_{*}$ main
sequence relation extrapolated out to $z\sim 9$. The galaxy is very young with
a mass-weighted age of $14^{+60}_{-12}$ Myr and a formation redshift of
$z_{\rm form}=9.1$ ($t_{\rm form}=538$ Myr).

The beagle results yield a lower stellar mass of $\log M_{\star}/M_{\odot}$=
$6.67^{+0.90}_{-1.08}$ and a significantly higher star formation rate of
$18.9^{+1.1}_{-1.6}$ $M_{\odot}/{\rm yr}$, placing it well above (i.e., higher
SFR for given stellar mass) the extrapolated Speagle et al. (2014) SFR–$M_{*}$
relation. beagle also gives a very young mass-weighted age of $5^{+12}_{-0}$
Myr and a formation redshift of $z_{\rm form}=8.6$ ($t_{\rm form}=583$ Myr).

With a photometric redshift of $z_{\rm phot}=8.9^{+0.5}_{-0.4}$,
WHL0137–ID9356 is the most spatially-resolved galaxy at $z\sim 9$ known to
date. Assuming a primarily linear and tangential magnification of $\mu\sim 8$,
the intrinsic size of the arc is 1.5 kpc at $z=9$. Given the F150W point-
spread function full width at half maximum of $\sim 0.05\arcsec\ (\sim 230$ pc
at $z=9$), we can resolve $\sim$30 pc scales in this $z\sim 9$ galaxy.

Only SPT0615-JD1, the gravitationally lensed 2$\farcs$5 long arc, is more
distant at $z\sim 10$ (Salmon et al., 2018). We show a $6\arcsec\times
6\arcsec$ cutout image of WHL0137–ID9356 from the JWST detection image in
Figure 9.

Unfortunately, WHL0137$-$08 has no multiple image constraints in the northeast
section of the cluster, where we find this $z\sim 9$ arc. This adds
considerable uncertainty to predictions of counter image locations. While some
models (Lenstool) predict two merging images of the arc, and a third image
near the cluster center, other models (LTM) predict no counter images.
Although it is not the case with the current lens models, it is possible that
the two knots in the arc could be multiple images if the critical curve
happens to pass through the arc. Despite the lensing uncertainties, we have
identified a promising counter image $3\farcs 9$ to the west of the arc (RA =
24.35393097∘, Dec = $-$8.44778677∘, J2000) with a similar color. While this
source is $\sim 2$ mag fainter than the $z\sim 9$ arc, eazypy estimates its
$z_{\rm phot}=8.3^{+2.2}_{-7.9}$ ($2\sigma)$, with range that encompasses the
photometric redshift $z_{\rm phot}=8.8$ of the main arc. Additional lens
modeling is ongoing to further investigate this possibility.

###  4.6 Number Counts

Harikane et al. (2022) identified 16 robust $z\sim 9-12$ candidates in GLASS
NIRCam parallel imaging of a “blank” field with similar area $\sim$10 arcmin2
to that studied here, reaching about a magnitude deeper in 7 filters (missing
F410M). This is somewhat more than our 12 candidates, as expected given the
deeper GLASS imaging.

At $z\sim 8$, faint number counts in lensed fields should roughly match those
in blank fields (e.g., Coe et al., 2015), given the UV luminosity function
(LF) faint-end slope $\alpha\sim-2$ (Bradley et al., 2012; Bouwens et al.,
2022). The galaxy cluster can hamper detections somewhat, though advanced
methods can model and/or filter out the brighter cluster light to recover many
faint distant galaxies (e.g., Livermore et al., 2017; Bhatawdekar & Conselice,
2021).

At higher redshifts $z\sim 9-13$, we expect steeper LF faint end slopes,
increasing the advantage for lensing to reveal faint galaxies at these
redshifts. In this dataset, the lensed field yielded 3 candidates, fewer than
the 9 identified in the nearby blank field. There could be several reasons for
this, including small number statistics. Also, only the lensed field had HST
coverage that might have helped rule out lower redshift interlopers. More
detailed analysis injecting artificial sources and measuring completeness will
be required of this and other fields to quantify the lensing advantage at
$z\sim 9$ and higher redshifts. Confirmed suppression of lensed number counts
could indicate LF faint-end slopes hovering around $\alpha\sim-2$ rather than
steepening as expected from both simulations and trends at lower redshifts.

##  5 Conclusions

We present a search for very high-redshift galaxies in the first JWST NIRCam
observations of the lensing cluster WHL0137$-$08 and a nearby parallel field
centered $\sim$ 2$\farcm$9 from the cluster center. Combined with RELICS HST
observations, the JWST and HST observations of WHL0137$-$08 include imaging in
17 filters spanning $0.4-5.0~{}\micron$ in which we use to search for high
redshift galaxies.

We use the eazypy photometric-redshift fitting code with two independent sets
of templates to determine the initial redshift of every galaxy in our fields.
Our high-redshift candidates galaxies were selected using a combination of
both signal-to-noise criteria and photometric redshift measurements to
minimize contamination from low-redshift sources and spurious noise
detections. Additionally, we also visually inspect each candidate galaxy in
each filter image and its best-fit SED to remove detector artifacts and other
spurious sources.

Our final sample of robust candidate high-redshift galaxies consists of 12
candidates at $8.5\lesssim z\lesssim 13$. Three of these candidates lie in the
cluster field, while the remaining nine are located in the nearby parallel
field. Using four independent lens models of the WHL0137$-$08 galaxy cluster
constructed to analyze Earendel and the Sunrise Arc, we estimate the
magnifications of each of our lensed high-redshift candidates. These sources
have magnifications of $\mu\sim 3-8$.

Furthermore, we perform SED fitting to the photometry of these galaxies using
the independent SED-fitting codes bagpipes and beagle to measure the physical
properties of our candidates. We find: stellar masses in the range $\log
M_{\star}/M_{\odot}$ = $7.5-9$, specific star formation rates sSFR $\sim
10-250$ Gyr-1, young mass-weighted ages $<100$ Myr, low dust content with
values $A_{V}<0.15$, and rest-frame UV slopes of $\beta=-1.6$ to $-3.1$.

Other JWST analyses have estimated similarly young ages $<100$ Myr for $z\sim
9-16$ candidates (Whitler et al., 2022; Furtak et al., 2022). Discovering such
young galaxies is consistent with expectations from simulations given our
image depths down to AB mag $\sim$29 (Mason et al., 2022). Deeper JWST imaging
is required to reveal older (and thus fainter) $\sim$100 Myr populations at
$z>9$, perhaps typical for the more numerous fainter galaxies in the early
universe.

One of our high-redshift candidates, WHL0137–ID9356, is magnified to AB mag 26
and stretched into an arc 2$\farcs$6 long by the effects of strong
gravitational lensing. The JWST data reveal at least two bright knots of
unevenly distributed star formation within the arc. This candidate also has
the largest magnification $\mu=8^{+12}_{-6}$. WHL0137–ID9356 is now the most
spatially-resolved galaxy at $z\sim 9$ known to date, similar in length to the
$z\sim 10$ candidate SPT0615-JD1 (Salmon et al., 2018).

JWST GO 2282 will obtain follow-up spectroscopy of WHL0137$-$08 with JWST
NIRSpec observations scheduled later this year. We plan to obtain spectroscopy
of some these candidates, likely those within the cluster field, to validate
these sources and study their physical properties in more detail.

##  6 Acknowledgments

We thank Zolt Levay for making the color images from the JWST WHL0137$-$08
observations. Based on observations with the NASA/ESA/CSA James Webb Space
Telescope 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. Support for Program number JWST-GO-02282 was provided
through a grant from the STScI under NASA contract NAS5-03127. Also based on
observations made with the NASA/ESA Hubble Space Telescope, obtained at STScI,
which is operated by AURA under NASA contract NAS5-26555. The HST observations
are associated with programs HST-GO-14096, HST-GO-15842, and HST-GO-16668.
Cloud-based data processing and file storage for this work is provided by the
AWS Cloud Credits for Research program. AZ and LF acknowledge support by Grant
No. 2020750 from the United States-Israel Binational Science Foundation (BSF)
and Grant No. 2109066 from the United States National Science Foundation
(NSF), and by the Ministry of Science & Technology, Israel.

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