# The Rise of Faint, Red AGN at $z>4$:
A Sample of Little Red Dots in the JWST Extragalactic Legacy Fields

Dale D. Kocevski Department of Physics and Astronomy, Colby College,
Waterville, ME 04901, USA  Steven L. Finkelstein Department of Astronomy, The
University of Texas at Austin, 2515 Speedway, Stop C1400, Austin, TX 78712,
USA  Guillermo Barro Department of Physics, University of the Pacific,
Stockton, CA 90340 USA  Anthony J. Taylor Department of Astronomy, The
University of Texas at Austin, Austin, TX, USA  Antonello Calabrò Osservatorio
Astronomico di Roma, via Frascati 33, Monte Porzio Catone, Italy  Brivael
Laloux Centre for Extragalactic Astronomy, Department of Physics, Durham
University, UK  Institute for Astronomy & Astrophysics, National Observatory
of Athens, V. Paulou & I. Metaxa, 11532, Greece  Johannes Buchner Max Planck
Institute for Extraterrestrial Physics, Giessenbachstrasse, 85741 Garching,
Germany  Jonathan R. Trump Department of Physics, 196 Auditorium Road, Unit
3046, University of Connecticut, Storrs, CT 06269, USA  Gene C. K. Leung
Department of Astronomy, The University of Texas at Austin, Austin, TX, USA
Guang Yang Kapteyn Astronomical Institute, University of Groningen, P.O. Box
800, 9700 AV Groningen, The Netherlands  SRON Netherlands Institute for Space
Research, Postbus 800, 9700 AV Groningen, The Netherlands  Mark Dickinson
NSF’s National Optical-Infrared Astronomy Research Laboratory, 950 N. Cherry
Ave., Tucson, AZ 85719, USA  Pablo G. Pérez-González Centro de Astrobiología
(CAB), CSIC-INTA, Ctra. de Ajalvir km 4, Torrejón de Ardoz, E-28850, Madrid,
Spain  Fabio Pacucci Center for Astrophysics $|$ Harvard & Smithsonian,
Cambridge, MA 02138, USA  Black Hole Initiative, Harvard University,
Cambridge, MA 02138, USA  Kohei Inayoshi Kavli Institute for Astronomy and
Astrophysics, Peking University, Beijing 100871, China  Rachel S. Somerville
Center for Computational Astrophysics, Flatiron Institute, 162 5th Avenue, New
York, NY 10010, USA  Elizabeth J. McGrath Department of Physics and Astronomy,
Colby College, Waterville, ME 04901, USA  Hollis B. Akins Department of
Astronomy, The University of Texas at Austin, 2515 Speedway Blvd Stop C1400,
Austin, TX 78712, USA  Micaela B. Bagley Department of Astronomy, The
University of Texas at Austin, Austin, TX, USA  Rebecca A.A. Bowler Jodrell
Bank Centre for Astrophysics, Department of Physics and Astronomy, School of
Natural Sciences, The University of Manchester, Manchester, M13 9PL, UK  Laura
Bisigello Dipartimento di Fisica e Astronomia ”G.Galilei”, Universitá di
Padova, Via Marzolo 8, I-35131 Padova, Italy  INAF–Osservatorio Astronomico di
Padova, Vicolo dell’Osservatorio 5, I-35122, Padova, Italy  Adam Carnall
Institute for Astronomy, University of Edinburgh, Royal Observatory,
Edinburgh, EH9 3HJ, UK  Caitlin M. Casey Department of Astronomy, The
University of Texas at Austin, Austin, TX, USA  Yingjie Cheng University of
Massachusetts Amherst, 710 North Pleasant Street, Amherst, MA 01003-9305, USA
Nikko J. Cleri 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  Luca Costantin Centro de Astrobiología (CAB),
CSIC-INTA, Ctra. de Ajalvir km 4, Torrejón de Ardoz, E-28850, Madrid, Spain
Fergus Cullen Institute for Astronomy, University of Edinburgh, Royal
Observatory, Edinburgh, EH9 3HJ, UK  Kelcey Davis NSF Graduate Research Fellow
Department of Physics, 196A Auditorium Road, Unit 3046, University of
Connecticut, Storrs, CT 06269, USA  Callum T. Donnan Institute for Astronomy,
University of Edinburgh, Royal Observatory, Edinburgh, EH9 3HJ, UK  James S.
Dunlop  Institute for Astronomy, University of Edinburgh, Royal Observatory,
Edinburgh, EH9 3HJ, UK  Richard S. Ellis Jodrell Bank Centre for Astrophysics,
Department of Physics and Astronomy, School of Natural Sciences, The
University of Manchester, Manchester, M13 9PL, UK  Henry C. Ferguson Space
Telescope Science Institute, 3700 San Martin Drive, Baltimore, MD 21218, USA
Seiji Fujimoto Hubble Fellow  Department of Astronomy, The University of Texas
at Austin, Austin, TX 78712, USA  Adriano Fontana INAF - Osservatorio
Astronomico di Roma, via di Frascati 33, 00078 Monte Porzio Catone, Italy
Mauro Giavalisco University of Massachusetts Amherst, 710 North Pleasant
Street, Amherst, MA 01003-9305, USA  Andrea Grazian INAF–Osservatorio
Astronomico di Padova, Vicolo dell’Osservatorio 5, I-35122, Padova, Italy
Norman A. Grogin Space Telescope Science Institute, Baltimore, MD, USA  Nimish
P. Hathi Space Telescope Science Institute, 3700 San Martin Drive, Baltimore,
MD 21218, USA  Michaela Hirschmann Institute of Physics, Laboratory of Galaxy
Evolution, Ecole Polytechnique Fédérale de Lausanne (EPFL), Observatoire de
Sauverny, 1290 Versoix, Switzerland  Marc Huertas-Company Instituto de
Astrofísica de Canarias (IAC), La Laguna, E-38205, Spain  Observatoire de
Paris, LERMA, PSL University, 61 avenue de l’Observatoire, F-75014 Paris,
France  Université Paris-Cité, 5 Rue Thomas Mann, 75014 Paris, France
Universidad de La Laguna. Avda. Astrofísico Fco. Sanchez, La Laguna, Tenerife,
Spain  Center for Computational Astrophysics, Flatiron Institute, New York, NY
10010, USA  Benne W. Holwerda University of Louisville, Department of Physics
and Astronomy, 102 Natural Science Building, Louisville, KY 40292, USA  Garth
Illingworth Department of Astronomy and Astrophysics, UCO/Lick Observatory,
University of California, Santa Cruz, CA 95064, USA  Stéphanie Juneau NSF’s
NOIRLab, 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  Anton M. Koekemoer Space Telescope Science Institute, 3700 San
Martin Dr., Baltimore, MD 21218, USA  Wenxiu Li Kavli Institute for Astronomy
and Astrophysics, Peking University, Beijing 100871, China  Ray A. Lucas Space
Telescope Science Institute, 3700 San Martin Drive, Baltimore, MD 21218, USA
Dan Magee Department of Astronomy and Astrophysics, UCO/Lick Observatory,
University of California, Santa Cruz, CA 95064, USA  Charlotte Mason  Cosmic
Dawn Center (DAWN), Jagtvej 128, DK-2200, Copenhagen N, Denmark  Niels Bohr
Institute, University of Copenhagen, Jagtvej 128, DK-2200, Copenhagen N,
Denmark  Derek J. McLeod Institute for Astronomy, University of Edinburgh,
Royal Observatory, Edinburgh, EH9 3HJ, UK  Ross J. McLure  Institute for
Astronomy, University of Edinburgh, Royal Observatory, Edinburgh, EH9 3HJ, UK
Lorenzo Napolitano INAF – Osservatorio Astronomico di Roma, via Frascati 33,
00078, Monteporzio Catone, Italy  Dipartimento di Fisica, Università di Roma
Sapienza, Città Universitaria di Roma - Sapienza, Piazzale Aldo Moro, 2,
00185, Roma, Italy  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  Nor Pirzkal ESA/AURA Space
Telescope Science Institute  Giulia Rodighiero Department of Physics and
Astronomy, Università degli Studi di Padova, Vicolo dell’Osservatorio 3,
I-35122, Padova, Italy  INAF - Osservatorio Astronomico di Padova, Vicolo
dell’Osservatorio 5, I-35122, Padova, Italy  Paola Santini INAF - Osservatorio
Astronomico di Roma, via di Frascati 33, 00078 Monte Porzio Catone, Italy
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  L. Y. Aaron Yung Space Telescope Science Institute,
3700 San Martin Drive, Baltimore, MD 21218, USA

###### Abstract

We present a sample of 341 ”little red dots” (LRDs) spanning the redshift
range $z\sim 2-11$ using data from the CEERS, PRIMER, JADES, UNCOVER and
NGDEEP surveys. These sources are likely heavily-reddened AGN that trace a
previously-hidden phase of dust-obscured black hole growth in the early
Universe. Unlike past use of color indices to identify LRDs, we employ
continuum slope fitting using shifting bandpasses to sample the same rest-
frame emission blueward and redward of the Balmer break. This approach allows
us to identify LRDs over a wider redshift range and is less susceptible to
contamination from galaxies with strong breaks that otherwise lack a rising
red continuum. The redshift distribution of our sample increases sharply at
$z<8$ and then undergoes a rapid decline at $z\sim 4.5$, which may tie the
emergence, and obscuration, of these sources to the inside-out growth that
galaxies experience during this epoch. We find that LRDs are 2-3 dex more
numerous than bright quasars at $z\sim 5-7$, but their number density is only
0.6-1 dex higher than X-ray and UV selected AGN at these redshifts. Within our
sample, we have identified the first X-ray detected LRDs at $z=3.1$ and
$z=4.66$. An X-ray spectral analysis confirms that these AGN are moderately
obscured with $\log\,(N_{\rm H}/{\rm cm}^{2}$) of $23.3^{+0.4}_{-1.3}$ and
$22.72^{+0.13}_{-0.16}$. Our analysis of these X-ray sources reveals that
reddened AGN emission dominates their rest-optical light, while the rest-UV
originates from their host galaxies. We also present NIRSpec observations from
the RUBIES survey of 17 LRDs that show broad emission lines consistent with
AGN activity. The confirmed AGN fraction of our sample is $71\%$ for sources
with F444W$<26.5$. In addition, we find three LRDs with narrow blue-shifted
Balmer absorption features in their spectra, suggesting an outflow of high-
density, low ionization gas from near the central engine of these faint, red
AGN.

High-redshift galaxies (734); Quasars (1319); Supermassive black holes (1663)

##  1 Introduction

One of the more surprising results to come from the first year of JWST
observations is the detection of numerous faint, broad-line AGN at $z>5$
(Onoue et al., 2023; Kocevski et al., 2023; Harikane et al., 2023; Matthee et
al., 2023; Maiolino et al., 2023; Larson et al., 2023; Greene et al., 2023).
These sources have luminosities that are 2-3 dex below that of bright quasars
identified by ground-based surveys at similar redshifts (e.g., Willott et al.
2010; Jiang et al. 2016; Mazzucchelli et al. 2017; Matsuoka et al. 2022; Yang
et al. 2023b) and are powered by BHs with masses of $\approx 10^{6-7}~{}{\rm
M_{\odot}}$, making them among the least-massive BHs known in the early
Universe. These faint quasars are more representative of the underlying BH
population at high redshifts and potentially the key to constraining models of
BH seeding (Pacucci & Loeb, 2022; Li et al., 2023), the contribution of AGN to
hydrogen reionization (Dayal et al., 2020; Yung et al., 2021; Giallongo et
al., 2019; Finkelstein et al., 2019), and the early coevolution of galaxies
and BHs (Habouzit et al., 2022; Inayoshi et al., 2022; Pacucci et al., 2023).

About 20% of the broad-line AGN identified with JWST appear to be heavily
obscured, featuring a steep red continuum in the rest-frame optical, while
also exhibiting relatively blue colors in the rest-frame UV (Kocevski et al.,
2023; Harikane et al., 2023; Matthee et al., 2023; Greene et al., 2023; Killi
et al., 2023). Sources with this “v-shaped”, red plus blue spectral energy
distribution (SED) have come to be known as “little red dots” (LRDs) in the
literature (Matthee et al., 2023)111While the definition of a ”little red dot”
has varied in the literature,
in this study, the term is used to refer to compact sources with
red-optical and blue-UV colors.. Due to their unique colors and compact
morphologies, LRDs have been identified photometrically and found to be quite
ubiquitous, having number densities of $\sim 10^{-5}$ Mpc-3 mag-1, which
amounts to a few percent of the galaxy population at redshift $z\sim 5-6$
(Barro et al., 2023; Labbe et al., 2023; Kokorev et al., 2024). Using follow-
up spectroscopy, Greene et al. (2023) demonstrated that over 80% of
photometrically-selected LRDs show broad-line emission when care is taken to
exclude brown dwarf contaminants (e.g., Langeroodi & Hjorth 2023).

The origin of the red and blue emission in these sources has been heavily
debated. Their steep rest-frame optical slopes are consistent with either a
reddened AGN continuum or emission from dusty star-formation (Kocevski et al.,
2023; Barro et al., 2023; Labbe et al., 2023; Akins et al., 2023), with lines
of evidence supporting both scenarios. For example, if the continuum is
dominated by stellar emission, then the implied H$\alpha$ equivalent widths
(EWs) would far exceed that of typical star-forming galaxies at lower redshift
(i.e., Greene et al. 2023; Fumagalli et al. 2012; Whitaker et al. 2014). On
the other hand, photometric constraints in the mid-infrared favor SED models
consistent with a dusty, compact starburst and only mild contribution from an
obscured AGN (Williams et al., 2023; Pérez-González et al., 2024a).

Several emission mechanisms have also been proposed to explain the UV excess
observed in LRDs, including scattered light from the central AGN and stellar
emission emerging from a relatively dust-free host or escaping unattenuated
due to patchy dust (Kocevski et al., 2023; Barro et al., 2023; Labbe et al.,
2023; Akins et al., 2023; Killi et al., 2023). While red sources with a UV
excess have been found at lower redshifts ($z<3$), they are rarer, making up
only 1% of IR-bright, dust-obscured galaxies (Noboriguchi et al., 2019).

A substantial portion of black hole (BH) growth in the Universe is thought to
be heavily obscured (Gilli et al., 2007; Ueda et al., 2014) and there are
signs that the fraction of obscured AGN increases with redshift and decreasing
luminosity (Hasinger, 2008; Merloni et al., 2014; Aird et al., 2015; Vito et
al., 2018; Ni et al., 2020; Peca et al., 2023, although see Scholtz et al.
2023). If most LRDs are indeed powered by buried accretion, they would be an
important population of previously-hidden AGN at high redshifts and provide a
unique window into the early, obscured growth phase of today’s supermassive
black holes.

Table 1: NIRCam Survey Areas and $5\sigma$ Point-Source Sensitivities Survey | Field | Area | F444W
---|---|---|---
|  | (armin2) | (AB mag)
NGDEEP | GDS | 11.4 | 30.65
UNCOVER | Abell 2744 | 43.8 | 29.33
JADES | GDS | 62.1 | 29.62
CEERS | EGS | 88.6 | 28.97
PRIMER | COS | 138.9 | 28.78
PRIMER | UDS | 243.0 | 28.54

In this study, we construct the largest sample of photometrically-selected
LRDs to date using publicly available JWST imaging in several extragalactic
legacy fields. Our selection technique centers around measuring rest-frame UV
and optical continuum slopes using shifting bandpasses in order to sample the
same rest-frame emission blueward and redward of the Balmer break. This
enables us to self-consistently search for compact sources with red optical
and blue UV colors over a wide range of redshifts ($z\sim 2-11$). It also
allows us to identify lower-redshift analogs to the LRDs found at $z\sim 6$,
where the host galaxy may be more readily visible, helping us to understand
the origin of their unusual SEDs.

Our analysis is presented as follows. In Section 2 we describe the JWST
imaging used for this study, while Section 3 describes our target selection
and the details of our SED modeling. We present our results in Section 4 and
the implications of our findings are discussed in Section 5. When necessary
the following cosmological parameters are used: $H_{0}=70~{}{\rm
km~{}s^{-1}~{}Mpc^{-1};\Omega_{tot},\Omega_{\Lambda},\Omega_{m}=1,0.7,0.3}$.

##  2 Data Description & Reduction

###  2.1 NIRCam Imaging

In this study, we make use of JWST NIRCam imaging from the Cosmic Evolution
Early Release Science Survey (CEERS; Finkelstein et al. (2022)), the Next
Generation Deep Extragalactic Exploratory Public (NGDEEP) survey (Bagley et
al., 2023), the JWST Advanced Deep Extragalactic Survey (JADES; Eisenstein et
al. 2023), the Public Release IMaging for Extragalactic Research (PRIMER)
survey (Dunlop et al., 2021), and the Ultradeep NIRSpec and NIRCam
Observations Before the Epoch of Reionization (UNCOVER) survey (Bezanson et
al., 2022). The fields and area covered with NIRCam by each survey are listed
in Table 1.

For the JADES survey, we make use of the public NIRCam mosaics made available
as part of the JADES second data
release222https://archive.stsci.edu/hlsp/jades. For UNCOVER, we use the
reductions made available by the GLASS-JWST data
release333https://archive.stsci.edu/hlsp/glass-jwst. The CEERS, PRIMER, and
NGDEEP NIRCam data were processed using the JWST Calibration
Pipeline444http://jwst-pipeline.readthedocs.io/en/latest/ (versions 1.8.5,
1.10.2, and 1.9.2, respectively) with custom modifications described in
Finkelstein et al. (2022) and Bagley et al. (2022). The resulting images were
registered to the same World Coordinate System reference frame (based on Gaia
DR1.2; Gaia Collaboration et al. (2016)) and combined into a single mosaic for
each field using the drizzle algorithm with an inverse variance map weighting
(Fruchter & Hook, 2002; Casertano et al., 2000) via the Resample step in the
pipeline. The final mosaics in all fields have pixel scales of
0$\farcs$03/pixel.

Source detection and photometry on the NIRCam mosaics were computed on PSF-
matched images using SExtractor (Bertin & Arnouts, 1996) version 2.25.0 in
two-image mode, with an inverse-variance weighted combination of the PSF-
matched F277W and F356W images as the detection image. Photometry was measured
in all of the available NIRCam bands in each field, as well as the F606W and
F814W HST bands using public data from the CANDELS and 3D-HST surveys (Grogin
et al., 2011; Koekemoer et al., 2011; Brammer et al., 2012; Momcheva et al.,
2016). This process is similar to that described in Finkelstein et al. (2023),
so we refer the reader there for additional details.

Table 2: Bands Used to Derive Continuum Slope versus Redshift Redshift | $\beta_{\rm UV}$ | $\beta_{\rm opt}$
---|---|---
$2<z<3.25$ | F606W, F814W, F115W | F150W, F200W, F277W
$3.25<z<4.75$ | F814W, F115W, F150W | F200W, F277W, F356W
$4.75<z<8$ | F115W, F150W, F200W | F277W, F356W, F444W
$z>8$ | F150W, F200W, F277W | F356W, F444W

We compute photometric redshifts using the eazy (Brammer et al., 2008)
software package for all sources in our photometric catalogs. eazy fits non-
negative linear combinations of user-supplied templates to derive probability
distribution functions (PDFs) for the redshift, based on the quality of fit of
the various template combinations to the observed photometry for a given
source. We use the default template set “tweak_fsps_QSF_12_v3”, which consists
of 12 templates derived from the stellar population synthesis code FSPS
(Conroy et al., 2010), as well as the six bluer templates created by Larson et
al. (2022), as described in Finkelstein et al. (2023). A flat redshift prior
with respect to luminosity was assumed and redshifts from $z=0$ to 20 were
considered. We also perform a “low-redshift” run with the maximum redshift set
to $z=7$ to allow for visualization of the best-fitting low-redshift model for
sources found to be at $z>9$.

###  2.2 NIRSpec Spectroscopy

The NIRSpec observations used in this study consist of three pointings in the
UDS field taken on 16, 18, and 19 January 2024 and six pointings in the EGS
field taken on 13 and 20 March 2024 as part of the RUBIES program (GO-4233;
PI: A. de Graaff). The observations were taken with the G395M/F290LP $R\simeq
1000$ grating/filter pair using a three-nod pattern. The coadded spectra have
a total exposure time of 5689.7 s. The data were reduced using version 1.13.4
of the JWST Science Calibration Pipeline with the Calibration Reference Data
System (CRDS) mapping 1215, starting from the Level 0 uncalibrated data
products (“_uncal.fits” files) available on MAST. Custom parameters were used
for the jump step at the detector-level calibration for a better treatment of
the “snowballs”555https://jwst-docs.stsci.edu/data-artifacts-and-
features/snowballs-and-shower-artifacts produced by high-energy cosmic ray
events, and a nodded background subtraction was adopted.

Figure 1: Best-fit SED of the obscured, broad-line AGN CEERS 746 from Kocevski
et al. (2023). The blue and red bars denote the filters blueward and redward
of the Balmer break at 3645Å (the dashed vertical line) used to determine the
rest-frame UV and optical continuum slopes, respectively, of each source given
its redshift. Figure 2: Examples of our continuum slope fits for sources at a
range of redshifts. The bands used to measure the rest-frame UV and optical
slopes are shown as blue and red squares, respectively. The F444W image
cutouts of each source are $1^{\prime\prime}\times 1^{\prime\prime}$ in size.
The best-fit SEDs shown in light grey are galaxy plus QSO hybrid models (see
§3 for details). $2\sigma$ upper limits are shown for bands with non-
detections. Figure 3: Distribution of best-fit optical and UV spectral slopes,
$\beta_{\rm opt}$ and $\beta_{\rm UV}$, measured in the CEERS, PRIMER-COSMOS,
PRIMER-UDS, UNCOVER, JADES, and NGDEEP datasets for galaxies at $z>2$ detected
in the F444W filter with a ${\rm SNR}>12$. The horizontal and vertical dashed
lines denote our selection criteria of $\beta_{\rm opt}>0$ and $\beta_{\rm
UV}<-0.37$ meant to select sources with red and blue colors in the rest-frame
optical and UV, respectively. The horizontal dotted line denotes the
$\beta_{\rm opt}$ limit that corresponds to the color cut used in Barro et al.
(2023) (i.e., ${\rm F277W-F444W}>1.5$). The vertical dot-dashed line denotes
the $\beta_{\rm UV}$ limit that corresponds to the blue color cut used by
Greene et al. (2023) to exclude brown dwarfs (i.e., ${\rm F115W-F200W}<-0.5$).
The red circles are sources that satisfy both our spectral slope and size cuts
(see §3 for details). Also shown are sources excluded from our primary sample
due to either failing our size cut (blue squares) or being flagged as
potential strong line emitters (orange circles). The smaller light blue, dark
blue, and pink circles are the sample of LRDs identified in Pérez-González et
al. (2024a), Barro et al. (2023), and Labbe et al. (2023), respectively. The
light blue diamonds indicate sources in our sample with broad emission line
detections.

The reduced two-dimensional (2D) spectra (“s2d”) have a rectified trace with a
flat slope. To best optimize the extraction of one-dimensional (1D) spectra
from the 2D spectra, we perform a weighted extraction based on the methodology
of Horne (1986). Briefly, for a given spectrum, we take the median of the 2D
spectrum along the spectral direction to produce a spatial profile for the
source. We then identity the central peak of this profile, which corresponds
to the source’s spectral trace. We then set all pixels in the spatial profile
that are not a part of this central feature to zero and normalize the area
under this masked spatial profile to one. We then use the normalized profile
as the variable P in Table 1 of Horne (1986) and follow the prescription given
therein to extract an optimized 1D spectrum.

##  3 Methodology

###  3.1 Sample Selection

Following the approach of Barro et al. (2023) and Labbe et al. (2023), we
identify LRDs as sources with a compact morphology that are red at rest-frame
optical wavelengths and blue in the rest-frame UV. While these previous
studies used color indices measured in a single combination of bands (i.e.,
F277-F444W), in this study we perform our search using cuts on the UV and
optical continuum slope measured by fitting photometry in multiple bands
blueward and redward of the Balmer break at 3645Å.

To determine the continuum slope, $\beta$ (where $\beta$ is defined such that
$f_{\lambda}\propto\lambda^{\beta})$, for a source, we perform a $\chi^{2}$
minimization fit to the observed magnitudes using the linear relationship:

$m_{i}=-2.5~{}(\beta+2)~{}\log{(\lambda_{i})}+c$ (1)

where $m_{i}$ is the AB magnitude measured in the $i$th filter with an
effective wavelength of $\lambda_{i}$. We perform this fit to determine both
the rest-frame UV and optical spectral slopes, $\beta_{\rm UV}$ and
$\beta_{\rm opt}$, using fluxes measured in bands blueward and redward of
3645Å based on the redshift of each source. The filter combinations used for
these fits as a function of source redshift are listed in Table 2 and shown in
Figure 1. Three bands are used to measure the slope in all cases except for
sources at $z>8$, where only the F356W and F444W bands are used to determine
the rest-frame optical slope. Examples of our slope fits for sources at a
range of redshifts are shown in Figure 2.

Figure 4: F444W magnitude versus half-light radius for galaxies in the CEERS,
PRIMER-COSMOS, PRIMER-UDS, UNCOVER, JADES, and NGDEEP datasets at $z>2$
detected in the F444W filter with a ${\rm SNR}>12$. Green circles are stars
and the dashed line denotes our best-fit to the stellar locus. Our magnitude-
dependant size cut is shown by the dotted line, which is 1.5 times our best-
fit to the magnitude-size relationship for stars in each field. Symbols are
the same as in Figure 3

Uncertainties on our measured $\beta$ slopes are calculated using a Monte
Carlo approach. For each band, we perform 1000 random draws from a Gaussian
whose mean is set to the measured flux in that band and whose standard
deviation is set to the photometric error. Our continuum slope measurements
are then repeated on all 1000 mock SEDs and standard deviations are calculated
from the resulting distributions.

We can translate the color cuts used by previous studies to identify extremely
red objects into continuum slopes using the relationship

$\beta=\frac{0.4(m_{1}-m_{2})_{\rm AB}}{\log\,(\lambda_{2}/\lambda_{1})}-2$
(2)

For this study, we select red sources with a UV-excess using an optical
continuum slope cut of $\beta_{\rm opt}>0$ and a UV slope cut of $\beta_{\rm
UV}<-0.37$ (which correspond to the color cuts F277W-F444W ¿ 1.0 mag and
F150W-F200W ¡ 0.5 for sources at $z\sim 5$). The bands used to measure the two
slopes shift as a function of redshift as illustrated in Figure 1, ensuring
that we fit the same portion of the spectral energy distribution of all
sources from $z=2$ out to $z\sim 10$.

Figure 3 shows the resulting $\beta_{\rm UV}$ versus $\beta_{\rm opt}$
distribution for all galaxies at $z>2$ that are detected with a signal-to-
noise ratio (SNR) greater than 12 in the F444W band. We find 791 sources with
$\beta_{\rm opt}>0$, $\beta_{\rm UV}<-0.37$, and SNR${}_{\rm F444W}>12$ in the
six fields we examined.

Figure 5: Examples of our continuum slope fits for sources removed from our
sample. The bands used to measure the rest-frame UV and optical slopes are
shown as blue and red squares, respectively. Panels A, B and C show examples
of candidate brown dwarfs cut from the sample due to their low rest-frame UV
continuum slopes. The dashed green line shows the best-fit LOWZ brown dwarf
atmosphere model from Meisner et al. (2021). Panels D, E, and F show examples
of sources whose rest-frame optical continuum slope may be boosted due to
strong line emission in one or more bands. The F444W image cutouts of each
source are $1^{\prime\prime}\times 1^{\prime\prime}$ in size. The best-fit
SEDs shown in light grey are galaxy plus QSO hybrid models (see §3 for
details).  Figure 6: Color image cutouts of a subset of our LRDs. The RGB
images are composed of images in the F115W, F200W, and F444W filters. All
images are $1\farcs 5\times~{}1\farcs 5$ in size.

From this sample, we select sources with compact morphologies by applying an
additional cut on half-light radius, $r_{h}$, as measured by SExtractor in the
F444W band. This cut is magnitude dependent and is designed to follow the tilt
of the stellar locus apparent in the $m_{\rm F444W}$ versus $r_{h}$ parameter
space, which can be seen in Figure 4. To account for the increased scatter in
size measurements at faint magnitudes, we select compact sources as those with
$r_{h}$ within 1.5 times of the stellar locus (the dotted line in Figure 4).
This size cut excludes 189 sources.

This amounts to 24% of the sample, which indicates that most objects selected
to have red optical and blue UV colors also have compact morphologies. This
agrees with the findings of Barro et al. (2023), whose sample of EROs is
largely unresolved. Our size cut reduces our sample size from 791 to 602
sources.

We apply two further selection criteria to remove potential contaminants. The
first is an additional cut on $\beta_{\rm UV}$ to remove brown dwarfs, which
have similar near-infrared colors as reddened AGN, but appear significantly
bluer at shorter wavelengths (Langeroodi & Hjorth, 2023). To account for this,
we exclude from our sample all sources with $\beta_{\rm UV}<-2.8$, which
corresponds to the color cut ${\rm F115W-F200W}<-0.5$ employed by Greene et
al. (2023). Examples of potential brown dwarfs removed from our sample based
on its $\beta_{\rm UV}$ slope are shown in panels A, B, and C of Figure 5.
Each panel shows both our best-fit galaxy plus AGN hybrid model and the best-
fit LOWZ brown dwarf atmosphere model from Meisner et al. (2021). This color
cut removes 63 objects and reduces the sample size to 539 sources.

The second refinement to our selection is meant to identify sources whose
$\beta_{\rm opt}$ may be boosted due to strong line emission affecting one or
more bands. The SEDs of three such sources are shown in Figure 5. Panel D and
E show sources with a flat spectral slope between F277W and F356W, followed by
an increase in flux at F444W that can be explained by contamination from
strong [O iii]+H$\beta$ lines given the redshift of the two sources. The SED
of the source in Panel F shows an elevated flux in F356W and F444W relative to
F410M, which can be explained by [O iii]+H$\beta$ and H$\alpha$+[N ii]
emission boosting the flux in each band. To remove such sources, we impose an
additional requirement that $\beta_{\rm F277W-F356W}>-1$ and $\beta_{\rm
F277W-F410M}>-1$ (when F410M photometry is available, which is true for all
fields except NGDEEP). For sources at $z>8$, only the second condition is
imposed. This requirement ensures that sources have a rising continuum over
the entire wavelength range in which the optical continuum slope is measured.
The equivalent color cuts are ${\rm F277W-F356W}>0.53$ and ${\rm
F277W-F410M}>0.84$. This additional cut removes 198 sources, including all
three sources shown in Figure 5, resulting in a final sample size of 341
sources.

In summary, our primary selection criteria are:

  1. (i)

${\rm SNR_{F444W}}>12\,$

  2. (ii)

$\beta_{\rm opt}>0\,$

  3. (iii)

$-2.8<\beta_{\rm UV}<-0.37\,$

  4. (iv)

$r_{h}<1.5~{}r_{h,~{}{\rm stars}}.$

To this, we add the following conditions aimed at removing sources whose
optical continuum slope is likely boosted by strong line emission:

  1. (v)

$\beta_{\rm F277W-F356W}>-1~{}~{}({\rm only~{}at}~{}z<8),$

  2. (vi)

$\beta_{\rm F277W-F410M}>-1~{}~{}({\rm when~{}F410M~{}available}).$

Table 3: Properties of our primary sample of Little Red Dots

ID | RA | Dec | $z_{\rm best}$ | $z_{\rm flag}$ | $\beta_{\rm UV}$ | $\beta_{\rm opt}$ | $m_{\rm F444W}$ | $M_{\rm UV}$ |
---|---|---|---|---|---|---|---|---|---
|  | (J2000) | (J2000) |  |  |  | (AB mag) | (AB mag) |
CEERS 260 | 214.805768 | 52.878048 | 7.93 | 1 | $-2.23\pm 0.18$ | $1.20\pm 0.09$ | 26.13 | -19.57 |
CEERS 941 | 214.757973 | 52.839706 | 7.42 | 1 | $-1.68\pm 0.18$ | $0.33\pm 0.09$ | 25.69 | -19.70 |
CEERS 965 | 214.912514 | 52.949437 | 5.95 | 1 | $-1.87\pm 0.47$ | $0.30\pm 0.20$ | 26.86 | -18.11 |
CEERS 1669 | 214.817697 | 52.877855 | 5.47 | 1 | $-2.48\pm 0.10$ | $0.04\pm 0.06$ | 25.54 | -20.21 |
CEERS 1914 | 214.998408 | 53.004619 | 6.49 | 1 | $-2.05\pm 0.24$ | $2.31\pm 0.05$ | 24.83 | -19.02 |
CEERS 1954 | 215.002842 | 53.007588 | 7.48 | 1 | $-1.48\pm 0.26$ | $0.86\pm 0.11$ | 26.36 | -18.86 |
CEERS 2285 | 214.956832 | 52.973153 | 5.86 | 1 | $-1.61\pm 0.26$ | $0.97\pm 0.10$ | 25.80 | -18.64 |
CEERS 2520 | 214.844768 | 52.892101 | 8.74 | 1 | $-1.75\pm 0.12$ | $2.18\pm 0.19$ | 25.34 | -20.40 |
CEERS 3153 | 214.925762 | 52.945661 | 5.23 | 1 | $-1.63\pm 0.59$ | $1.20\pm 0.09$ | 25.99 | -17.24 |
CEERS 4363 | 214.780370 | 52.834802 | 4.75 | 1 | $-1.93\pm 1.39$ | $0.24\pm 0.17$ | 26.73 | -17.01 |

Note. — Field acronyms: EGS = Extended Groth Strip; GDS = Great Observatories
Origins Deep Survey - South (GOODS-S); UDS = UKIDSS Ultra Deep Survey; COS:
Cosmic Evolution Survey (COSMOS)

Note. — $z_{\rm flag}$: 1 = phot redshift, 2 = spect redshift. This table is
available in its entirety at https://github.com/dalekocevski/Kocevski24

Figure 7: The redshift distribution of sources with (_top_) red rest-frame
optical colors ($\beta_{\rm opt}>0$), (_middle-top_) red rest-frame optical
and blue rest-frame UV colors ($-2.8<\beta_{\rm UV}<-0.37$), (_middle-bottom_)
red rest-frame optical color and a compact morphology, and (_bottom_) red
rest-frame optical and blue rest-frame UV colors and a compact morphology (see
§3). The bottom panel is the redshift distribution of our final sample of
LRDs.

###  3.2 Vetting of $z>9$ Candidates

We apply additional scrutiny to sources in our sample with photometric
redshifts of $z>9$ that is meant to remove potential lower-redshift
interlopers (e.g., Zavala et al., 2023). Our selection criteria for such
sources are similar to those of Finkelstein et al. (2023) and are based on a
combination of flux detection significances and the probability density
function of the photometric redshift, $P(z)$. First, we require a SNR $<3$ in
all bands blueward of the Lyman break. This includes F814W for $z>9$ and F115W
for $z>11$. Here the SNRs are measured in $0\farcs 2$ diameter apertures in
our non-PSF-matched images. Second, the integrated probability that the source
lies at $z>7$ must exceed 95%, i.e. $\int P(z>7)>0.95$. Third, the difference
between the $\chi^{2}$ of the best-fit low-redshift ($z<7$) and high-redshift
models must exceed 4 ($\Delta\chi^{2}>4$), corresponding to a $2\sigma$
significance (Bowler et al., 2020). Lastly, the (nonreduced) $\chi^{2}$ of the
best-fit model must be $\chi^{2}<60$ to ensure a good fit to the photometry.

###  3.3 SED Fitting

We model the SEDs of our sources using a custom $\chi^{2}$-minimization fit
that employs multiple galaxy and AGN components in a manner similar to that
described in Kocevski et al. (2023). We emphasize that these SED fits are not
used for our sample selection and are instead only meant to visualize a
possible SED consistent with all of our observed photometry in various figures
throughout this paper. For the AGN component, we use the composite quasar
spectrum of Vanden Berk et al. (2001) that is reddened by up to 4.5 magnitudes
of visual extinction using a Calzetti et al. (2000) attenuation law. To this,
we add dust-free, scattered AGN emission that ranges from 0 to 10% of pre-
reddened AGN light. For the stellar population, we assume a Chabrier (2003)
initial mass function, Bruzual & Charlot (2003) stellar population models,
fixed solar metallicity, Calzetti et al. (2000) dust attenuation, and a
“delayed-$\tau$” star formation history with $\tau$ in the range of 0.1 Gyr to
the age of the Universe at the source redshift (e.g., Maraston et al. 2010).

In §4.4, we examine the SED of an X-ray detected LRD in greater detail using
CIGALE v2022.1 (Boquien et al., 2019; Yang et al., 2020, 2022). For this
modeling, we adopt parameters similar to those used in Yang et al. (2023a). We
use the standard delayed-$\tau$ module sfhdelayed for the star formation
history, a Chabrier (2003) initial mass function with a solar metallicity
($Z=0.02$), and Bruzual & Charlot (2003) for the simple stellar population
(SSP) module. We add nebular emission using the nebular model (Villa-Vélez et
al., 2021) and use the dustatt_modified_starburst module for the dust
attenuation. For the AGN component, we adopt the skirtor2016 module based on a
clumpy torus model from Stalevski et al. (2012, 2016). The relative strength
between the AGN and galaxy components, set by the fracAGN parameter, is
allowed to vary from 0 to 0.99.

##  4 Results

Using the continuum slope and size criteria outlined in §3.1, we have
identified 341 candidate obscured quasars with compact morphologies and red
optical and blue UV colors. These sources are split among the fields and
datasets we examined as follows: 117 from PRIMER-UDS, 81 from PRIMER-COSMOS,
64 from CEERS, 46 from JADES, 23 from UNCOVER, and 10 from NGDEEP. The
coordinates, redshifts, and best-fit continuum slopes are reported in Table 3.
Color images of a subset of these sources, drawn from each dataset, are shown
in Figure 6. In the following sections, we compare our sample to previous LRD
compilations, examine the redshift distribution and number density of our
sample in greater detail, present a case study of the first X-ray detected
LRD, and discuss broad emission line detections among our sample.

###  4.1 Comparison to Previous Samples

In Figures 3 and 4, we highlight the sample of LRDs presented in three
previous studies: Barro et al. (2023, hereafter B23) in the EGS field selected
using CEERS data, Pérez-González et al. (2024b, hereafter PG24) in the GOODS-S
field selected using JADES data, and Labbe et al. (2023, hereafter L23) in the
Abell 2744 field using data from the UNCOVER survey. The B23 sample consists
of 37 EROs selected to have NIRCam colors of ${\rm F277W}-{\rm F444W}>1.5$ and
${\rm F444W}<28$. We recover all 37 of these sources, however two (B23 ID
48777 and 72897) are excluded from our primary sample as potential brown
dwarfs since they have UV spectral slopes of $\beta_{\rm UV}<-2.8$. Of the
remaining 35 sources, all but four have $\beta_{\rm opt}>1$, making them among
the reddest in our CEERS sample.

The PG24 sample consists of 31 sources selected to have NIRCam colors of ${\rm
F277W}-{\rm F444W}>1.0$, ${\rm F150W}-{\rm F200W}<0.5$ and ${\rm F444W}<28$.
Our primary sample includes 21 of these sources. Two were excluded for failing
our SNR cut (i.e., ${\rm SNR_{F444W}}>12$), three were excluded for having
$\beta_{\rm opt}<0$, and one source was excluded due to having a photometric
redshift of $z<2$. Of the remaining 25 sources, four were removed as their
optical continuum slopes are potentially contaminated by strong line emission.

The L23 sample consists of 33 sources selected to have one of two possible red
optical and blue UV color combinations (referred to as _red1_ and _red2_), as
well as a compact morphology. The _red1_ criteria include ${\rm F115W}-{\rm
F150W}<0.8$ & ${\rm F200W}-{\rm F277W}>0.7$ & ${\rm F200W}-{\rm F356W}>1.0$,
while the _red2_ criteria are ${\rm F150W}-{\rm F200W}<0.8$ & ${\rm
F277W}-{\rm F356W}>0.7$ & ${\rm F277W}-{\rm F444W}>1.0$. These color criteria
are the same as those used in Kokorev et al. (2024).

Of these sources, two were excluded from our sample as they were
spectroscopically confirmed to be brown dwarfs by Greene et al. (2023, L23 IDs
23778 and 29466) and another two were flagged as potential strong emission
line galaxies (L23 IDs 8602 and 15798). Six sources were excluded for failing
our optical slope cut (L23 IDs 2476, 6151, 37108, 46991, 49555 and 49567).

These six sources highlight a notable difference between our selection
criteria and that of L23 and Kokorev et al. (2024). The SEDs of these sources
exhibit a jump between F200W and F277W, consistent with the Balmer break
falling between the two bands, but otherwise have flat SEDs blueward and
redward of the break. Such SEDs will be selected by the two red color criteria
in _red1_ , namely ${\rm F200W}-{\rm F277W}>0.7$ & ${\rm F200W}-{\rm
F356W}>1.0$. However, when the continuum is fit using three bands (i.e.,
F200W, F277W, and F356W), the flat SED after the break reduces the inferred
spectral slope and ultimately drops it below our selection threshold. Overall,
18% (6/33) of the L23 sample failed to make our selection for this reason. Our
continuum slope fitting technique appears less susceptible to contamination
from galaxies with strong breaks, especially at $z\sim 5-6$, where the Balmer
break falls between the F200W and F277W bands. The SEDs of such sources are
likely galaxy-dominated and not the AGN candidates with rising red continua
that our LRD selection is intended to identify.

Figure 8: The UV luminosity function of our sample measured at rest-frame
1450Å in two redshift bins: $4.5<z<6.5$ (_left_) and $6.5<z<8.5$ (_right_). We
find good agreement with previous photometric and spectroscopic compilations
of LRDs (Matthee et al., 2023; Greene et al., 2023; Kokorev et al., 2024). We
find LRDs are $\sim 4$ and $\sim 10$ times more numerous at $M_{\rm UV}=-19$
than X-ray AGN at $z\sim 5$ (Parsa et al., 2018) and UV-selected AGN at $z\sim
7$ (Kulkarni et al., 2019), respectively. We also note fair agreement with the
model predictions of Li et al. (2023).

###  4.2 Redshift Distribution

Our spectral slope fitting technique, which uses shifting bandpasses to sample
the same rest-frame emission blueward and redward of 3645Å, allows us to self-
consistently search for AGN candidates with red optical and blue UV colors
over a wide range of redshifts. The bottom panel of Figure 7 shows the
redshift distribution of our resulting sample. We find sources with this
unique spectral shape and compact morphology emerge at $z\sim 8$ and have a
median redshift of $z\sim 6.4$. Their number density then undergoes a rapid
decline at $z\sim 4$.

Our methodology of using shifting bandpasses was meant to help identify lower-
redshift analogues of the LRDs previously identified in the literature.
However, we identify very few unresolved sources with red optical and blue UV
colors at $z<4$: only 17 are found in our sample. This is not due to sources
becoming more extended at lower redshifts. Even without our size cut, we find
few sources with red optical and blue UV colors at the lowest redshifts we
examined. This fact can be seen in the top and middle-top panels of Figure 7,
which show the redshift distribution of all red sources ($\beta_{\rm opt}>0$)
and red plus blue sources ($-2.8<\beta_{\rm UV}<-0.37$) regardless of their
effective radii. While we find a growing number of optically red sources at
$z<4$, most ($82\%$) are removed from our sample based on our UV color cut.
Only $14\%$ of the optically red and UV blue sources are cut based on their
size. Our findings suggest the population of LRDs with a UV-excess emerge in
large numbers for the first time at about $z\sim 4$. This may explain why such
sources were not previously identified using imaging from HST and
Spitzer/IRAC.

At the high-redshift end, our selection becomes increasingly incomplete as
long-wavelength filters start to shift blueward of the Balmer break. For
example, the F356W band probes fully blueward of 4000Å at $z\sim 9$. This will
flatten the inferred spectral slope (i.e., lower $\beta_{\rm opt}$) for
sources that are blue in the rest-frame UV and increase the likelihood that
sources will fall below our continuum slope cut. This may help explain the
rapid decline in the redshift distribution above $z\sim 8$.

###  4.3 Number Density

Table 4: Rest-frame UV luminosity function of our sample of LRDs in the redshift range $4.5<z<6.5$ and $6.5<z<8.5$.  $M_{\rm UV}$ | $N$ | $\Phi$
---|---|---
(AB Mag) |  | (Mpc-3 mag-1)
$4.5<z<6.5$
-17.0 | 22 | $-4.59\pm 0.10$
-18.0 | 62 | $-4.53\pm 0.06$
-19.0 | 56 | $-4.69\pm 0.06$
-20.0 | 22 | $-5.10\pm 0.10$
-21.0 | 3 | $-5.96^{+0.29}_{-0.34}$
$6.5<z<8.5$
-17.0 | 14 | $-4.53\pm 0.13$
-18.0 | 33 | $-4.61\pm 0.08$
-19.0 | 28 | $-4.87^{+0.09}_{-0.08}$
-20.0 | 13 | $-5.23^{+0.13}_{-0.14}$
-21.0 | 3 | $-5.87^{+0.29}_{-0.34}$
-22.0 | 1 | $-6.35^{+0.52}_{-0.76}$

In this section, we present the rest-frame UV luminosity function (LF) of the
LRDs in our sample. To determine the rest-UV magnitude of our sources, we
extrapolate our best-fit to the blue continuum to rest-frame 1450Å. The
resulting absolute magnitudes at this wavelength are listed in Table 3. To
compute the number density of our sample, we employ the $1/V_{\rm max}$ method
(Schmidt, 1968):

$\Phi(m)~{}{\rm d}m=\sum\limits_{i}\frac{1}{V_{i}(M_{i})}$ (3)

where $V_{i}(M_{i})$ is the maximum comoving volume in which source $i$ with
absolute magnitude $M_{i}$ is detectable. For a given survey area
$\Delta\Omega$ and a redshift range $z_{\rm min}<z<z_{\rm max}$, the comoving
volume is computed as:

$V_{i}=\frac{c~{}\Delta\Omega_{i}}{H_{0}}\int_{z_{\rm min}}^{z_{{\rm
max},i}}\frac{D_{L}(z)^{2}}{(1+z)^{2}}[\Omega_{m}(1+z)^{3}+\Omega_{\Lambda}]^{-1/2}.$
(4)

For this calculation, we exclude sources selected from the UNCOVER dataset due
to the variable magnification in the Abell 2744 field. We account for
magnitude incompleteness effects by computing the total survey area
($\Delta\Omega_{i}$) and maximum redshift ($z_{{\rm max},i}$) over which each
source could have been detected. Given that our sources are substantially
fainter in the rest-UV versus the rest-optical, the latter is largely driven
by the requirement that sources have rest-UV flux measurements with which to
measure a continuum slope.

We calculate the LF using a bin size of 1.0 magnitude and over two redshift
ranges: $4.5<z<6.5$ and $6.5<z<8.5$. The uncertainty on the resulting number
densities is estimated with Poisson statistics corrected for low number counts
following Gehrels (1986). Our calculated number densities are listed in Table
4 and shown in Figure 8.

We find good agreement with the number densities reported by Kokorev et al.
(2024) for their color-selected samples of LRDs, as well as those inferred by
Matthee et al. (2023) and Greene et al. (2023) for their spectroscopically-
confirmed samples of dust-reddened, broad-line AGN at both $z\sim 5$ and
$z\sim 7$. Comparing to the results Harikane et al. (2023) and Maiolino et al.
(2023), we find that if LRDs are indeed powered by reddened AGN, they would
make up 10-15% of the overall faint, broad-line AGN population detected by
JWST.

Figure 9: (_top_) Multi-wavelength image cutouts of the source PRIMER-COS 3866
(CXOC100024.2+022510). The source is one of only two little red dots in our
sample which are X-ray detected. All images are $2\farcs 5\times 2\farcs 5$ in
size. (_bottom_) Images of the underlying host galaxy after subtracting our
best-fit point-source model. Figure 10: Best-fit galaxy plus AGN SED model
from CIGALE of the X-ray detected, obscured AGN PRIMER-COS 3866. The red and
purple points indicate the observed and model flux densities, respectively.
The black curves represent the total model SEDs. The orange and blue curves
indicate the AGN and attenuated stellar components, respectively. Figure 11:
Results of the X-ray spectral analysis of PRIMER-COS 3866 by Laloux et al.
(2023) using BXA with the UXCLUMPY model. The blue crosses are the extracted
X-ray spectrum grouped to yield an SNR above 1 per bin. The red line
corresponds to the UXCLUMPY model, the yellow line represents the soft
scattering, and the green line is the background model. The sum of all three
components above is shown with the black line. The shaded regions correspond
to the $1\sigma$ confidence interval of the corresponding component. The lower
panel plots the logarithmic ratio between the X-ray spectrum and the best-
fitting model as a function of the energy.

In agreement with previous results (Kocevski et al., 2023; Matthee et al.,
2023; Greene et al., 2023), we find that our candidate faint, red AGN are 2-3
dex more numerous than would be expected based on simple extrapolations of the
quasar luminosity function measured from the ground at $z\sim 5-7$ (Niida et
al., 2020; Matsuoka et al., 2023). However, we find better agreement with the
number densities measured for lower-luminosity AGN at these redshifts. The
number density of LRDs at $z\sim 5$ is $4\times$ higher than that of X-ray AGN
reported in Parsa et al. (2018). This offset becomes more pronounced at $z\sim
7$, where we infer LRDs to be $10\times$ more common than color-selected AGN
at this redshift (Kulkarni et al., 2019). We note that we do find fair
agreement with the predicted quasar luminosity function at the faint regime by
Li et al. (2023), which is the result of a semianalytical model for BH
formation and growth that considers multiple accretion bursts with variable
Eddington ratios and is primarily calibrated with the quasar abundance at the
bright end of $M_{\rm UV}<-24$. Finally, At $z\sim 7$, we find that our
sources constitute $\sim 3\%$ of the overall galaxy population at $M_{\rm
UV}=-20$. This fraction rises to $\sim 10\%$ at $M_{\rm UV}=-22$, although
this is based on a single bright source.

###  4.4 X-ray Detected Little Red Dots

We cross-matched our sample of 341 candidate red AGN with the publicly
available X-ray source catalogs from the AEGIS-XD survey (Nandra et al.,
2015), the X-UDS survey (Kocevski et al., 2018), the C-COSMOS survey (Elvis et
al., 2009), and 7 Ms observations in GOODS-South (Luo et al., 2017). We find
only two objects that are directly detected: PRIMER-COS 3866 and JADES 21925.
These sources have redshifts of $z=4.66$ and $z=3.1$, respectively and appear
to be bright, lower-redshift analogs of the LRDs identified at $z=5-7$. As
such, they may provide unique insight into the nature of these objects. In
this section, we examine the properties of both sources in greater detail.

####  4.4.1 PRIMER-COS 3866 at $z=4.66$

PRIMER-COS 3866 was first identified as an X-ray emitter by Elvis et al.
(2009) as CXOC100024.2+022510 and later spectroscopically confirmed to be at
$z=4.66$ by Civano et al. (2011). The source has a F444W magnitude of 19.75,
making it the brightest object in our sample. Images of PRIMER-COS 3866 in
multiple NIRCam bands are shown in Figure 9. In addition to its strong NIRCam
detection, the source is also detected in the rest-frame UV with _Hubble_ ACS
imaging and in the near- and mid-infrared with _Spitzer_ IRAC and MIPS
imaging.

Figure 12: Multi-wavelength image cutouts of the source JADES 21925. The
source is one of only two little red dots in our sample which are X-ray
detected. All images are $1\farcs 5\times 1\farcs 5$ in size. Figure 13: Best-
fit galaxy plus AGN SED model from CIGALE of the X-ray detected, obscured AGN
JADES 21925. The red and purple points indicate the observed and model flux
densities, respectively. The black curves represent the total model SEDs. The
orange and blue curves indicate the AGN and attenuated stellar components,
respectively.

In Figure 10, we show the best-fit galaxy plus AGN SED model produced by
fitting the available photometry with CIGALE v2022.1 using the parameters
listed in §2.2. For this fit, we use _Spitzer_ IRAC and MIPS fluxes from the
‘super-deblended’ infrared photometric catalogue of Jin et al. (2018). We find
the $3-30\mu m$ emission of the source is well-fit, and dominated by, AGN
emission that is moderately reddened by polar dust with an $E(B-V)=0.40\pm
0.01$. The skirtor2016 model used for the AGN component is based on a clumpy
torus model, which would suggest the observed extinction is due to torus-level
obscuration as opposed to galaxy-wide obscuration. The CIGALE results suggest
the relatively blue color of the source in the rest-frame UV is due to
emission from the host galaxy at $<1\mu m$. CIGALE places the stellar mass of
the underlying galaxy at ${\rm log}(M_{*}/{\rm
M}_{\odot})=10.60^{+0.2}_{-0.4}$.

Because there has been considerable debate as to the origin of the blue rest-
frame UV emission from LRDs (e.g. Kocevski et al. 2023), we used the GALFIT
software (Peng et al., 2002) to subtract off emission from the central point
source in several NIRCam bands to search for signs of the underlying galaxy.
For this modeling, we provide GALFIT with empirical PSFs constructed from the
PRIMER-COS mosaic and noise images that account for both the intrinsic image
noise (e.g., background and readout noise) and added Poisson noise due to the
objects themselves. The results of the point source subtraction can be seen in
the lower panels of Figure 9. We see clear signs of an elongated, potentially
clumpy host galaxy emerging in the short-wavelength NIRCam images, in general
agreement with our best-fit SED model.

Lastly, the X-ray emission from PRIMER-COS 3866 affords us an independent way
to assess the obscured nature of the source. The shape of an AGN’s X-ray
spectrum can both reveal the presence of gas obscuring the central engine and
provide a measure of its column density, $N_{\rm H}$. An X-ray spectral
analysis of PRIMER-COS 3866 was recently carried out by Laloux et al. (2023),
where the UXCLUMPY clumpy torus model of Buchner et al. (2019) was fit to the
observed X-ray spectrum using the Bayesian X-ray Analysis (BXA) package
(Buchner et al., 2014). The results of this analysis are shown in Figure 14.
The best-fit column density is found to be $\log\,(N_{\rm H}/{\rm
cm}^{-2})=23.3^{+0.4}_{-1.3}$ , resulting in an obscuration-corrected X-ray
luminosity of $\log\,(L_{2-10~{}{\rm keV}}/{\rm erg~{}s}^{-1})=44.7\pm 0.2$.
The ratio of our measured extinction to our best-fit gas column density,
$E(B-V)/N_{\rm H}$, is a factor of $\sim 80$ below the Galactic standard value
of $1.7\times 10^{-22}$ mag cm-2 (Savage & Mathis, 1979), but in good
agreement with the reduced $E(B-V)/N_{\rm H}$ ratios reported by Maiolino et
al. (2001) for various classes of luminous ($L_{\rm 2-10~{}keV}>10^{43}$ erg
s-1) AGN.

These results confirm that PRIMER-COS 3866 harbors a luminous, moderately
obscured AGN, in agreement with our SED modeling of the source. The best-fit
$2-10$ keV luminosity, combined with a bolometric correction $L_{\rm
bol}/L_{\rm 2-10kev}\sim 20$ (Duras et al., 2020) appropriate for this
luminosity class, leads to an estimate of the black hole mass of $\sim 8\times
10^{7}\,{\rm M}_{\odot}$, assuming it is accreting at the Eddington limit.
Given the estimated stellar mass of the host, this black hole mass places the
source above the standard local relation between the stellar mass and black
hole mass, as seen in dozens of other $z>4$ galaxies discovered by JWST (see,
e.g., Pacucci et al. 2023).

####  4.4.2 JADES 21925 at $z=3.1$

JADES 21925 was first identified as an X-ray emitter by Giacconi et al. (2002)
as CXOCDFSJ033220.9-275223 in the 1 Msec Chandra Deep Field South observations
and more recently detected in the 7 Ms observations of the field presented in
Luo et al. (2017). Images of JADES 21925 in multiple NIRCam bands are shown in
Figure 12. The source shows clear signs of an extended, blue structure
surrounding a reddened point source that only becomes prominent at wavelengths
longer than 2$\mu$m. The photometric redshift of the source was reported as
$z=1.5$ in the Luo et al. (2017) catalog, which we revise upward to $z=3.1$
with the inclusion of JWST photometry from JADES. Based on its X-ray
detection, JADES 21925 is the lowest redshift LRD confirmed to host an AGN (a
record it holds with RUBIES-BLAGN-1 (Wang et al., 2024), which is found to
have the same redshift; see §4.5 below).

In Figure 13, we show the best-fit galaxy plus AGN SED model for JADES 21925
produced with CIGALE v2022.1 using the parameters listed in §2.2. For this
fit, we use _Spitzer_ IRAC and MIPS fluxes from the photometric catalogue of
Guo et al. (2013). Like PRIMER-COS 3866, we find the $3-30\mu m$ emission of
JADES 21925 is dominated by AGN emission, while the rest-frame UV emission is
attributed to the host galaxy. We find the extinction of the AGN emission by
polar dust to be $E(B-V)=1.39\pm 0.5$ and CIGALE’s estimate for the stellar
mass of the underlying galaxy is ${\rm log}(M_{*}/{\rm
M}_{\odot})=8.84^{+0.15}_{-0.38}$.

Figure 14: Results of our X-ray spectral analysis of JADES 21925 using BXA
with the UXCLUMPY model. The blue crosses are the extracted X-ray spectrum
grouped to yield an SNR above 1 per bin. The red line corresponds to the
UXCLUMPY model, the yellow line represents the soft scattering, and the green
line is the background model. The sum of all three components above is shown
with the black line. The shaded regions correspond to the $1\sigma$ confidence
interval of the corresponding component. The lower panel plots the logarithmic
ratio between the X-ray spectrum and the best-fitting model as a function of
the energy.

We also performed an X-ray spectral analysis of JADES 21925 using the BXA
package and the UXCLUMPY torus model of Buchner et al. (2019). The model
assumes a powerlaw with a photon index prior of $1.95\pm 0.15$ reprocessed
with a torus (including absorption, Compton scattering, and Fe fluorescence)
and an additionally absorbed reflection component. The results of this
analysis indicate JADES 21925 is moderately attenuated, with a best-fit column
density of $\log\,(N_{\rm H}/{\rm\,cm}^{-2})=22.72^{+0.13}_{-16}$, resulting
in an obscuration-corrected X-ray luminosity of $\log\,(L_{2-10~{}{\rm
keV}}/{\rm\,erg\,s}^{-1})=43.73\pm 0.06$. The ratio of our measured extinction
and column density again favors a $E(B-V)/N_{\rm H}$ ratio below that of the
Galactic standard value. Using the median of the ratios reported in Maiolino
et al. (2001) and our measured $E(B-V)$ extinction would predict a column
density of $\log\,(N_{\rm H}/{\rm cm}^{-2})=22.5$, which agrees with our
measured value, within the errors, better than the 21.6 cm-2 obtained using
the Galactic standard ratio.

Our measured X-ray luminosity, coupled with the relatively low stellar mass
that we infer for the host from our SED fit, indicates that JADES 21925, like
PRIMER-COS 3866, may harbor an overmassive black hole. Using a bolometric
correction of $L_{\rm bol}/L_{\rm 2-10kev}\sim 20$ and assuming the system is
accreting at its Eddington limit, results in a black hole mass of $\sim
8.5\times 10^{6}\,M_{\odot}$. This would imply this source lies significantly
above the local black hole versus galaxy stellar mass relationship.

Figure 15: NIRSpec spectra with uncertainties (grey shaded region) taken in
the G395M grating of 15 LRDs in the EGS and UDS fields that feature broad line
emission detected at a ${\rm SNR}>3$. Green lines show the best-fit Gaussian
for the narrow emission line component, blue lines show the best-fit broad
component, and red lines show the best overall (narrow plus broad) fit the
emission line. The H$\beta$ emission line is shown for source CEERS 7902 and
the P$\delta$ line for PRIMER-UDS 33823. The H$\alpha$ emission line is shown
for all other sources. The FWHM of the broad component (corrected for
instrument broadening) is shown in the upper left of each panel.

###  4.5 Broad-Line Detections

A high fraction of LRDs have been shown to exhibit broad line emission (e.g.,
Matthee et al., 2023; Greene et al., 2023), confirming the presence of an AGN
in these sources. Among our sample, 11 sources were previously reported to
have broad H$\alpha$ emission. These are CEERS 82815 from Kocevski et al.
(2023, their ID 746), CEERS 69459 from Harikane et al. (2023, their ID 672),
JADES 12068 from Maiolino et al. (2023, their ID 10013704), UNCOVER 3989,
4535, 9358, 9497, 9904, 25119, and 29255 from Greene et al. (2023, L23 IDs
30782, 28343, 8798, 8296, 6430, 20080, and 13556), and PRIMER-UDS 33823 from
Wang et al. (2024, their ID RUBIES-BLAGN-1). These sources are highlighted as
cyan diamonds in Figures 3 and 4.

Figure 16: NIRSpec spectra with uncertainties (grey shaded region) taken in the G395M grating of 2 LRDs that feature broad line emission detected at a ${\rm SNR}<3$. Model lines are the same as described in Figure 15. Table 5: Properties of LRDs in our sample with new broad line detections ID | RUBIES ID | RA | Dec | $z_{\rm spec}$ | Line |  FWHMbroad | $\log\,(M_{\rm BH}/{\rm M_{\odot}})$ | $\log\,(M_{\rm BH}/{\rm M_{\odot}})$ | $A_{\rm V}$
---|---|---|---|---|---|---|---|---|---
|  | (J2000) | (J2000) |  |  |  (km s-1) |  ($A_{\rm V}=0$) | (Dust Corr.) |
CEERS 5760 | RUBIES-CEERS 61496 | 214.972445 | 52.962196 | 5.079 | H$\alpha$ | $1800\pm 300$ | $6.72\pm 0.17$ | $7.04\pm 0.17$ | 1.8
CEERS 6126 | RUBIES-CEERS 60935 | 214.923377 | 52.925588 | 5.288 | H$\alpha$ | $1670\pm 60$ | $7.18\pm 0.03$ | $7.63\pm 0.03$ | 2.5
CEERS 7902 | RUBIES-CEERS 55604 | 214.886801 | 52.855376 | 6.986 | H$\beta$ | $4180\pm 220$ | $8.24\pm 0.06$ | $9.19\pm 0.06$ | 3.4
CEERS 10444 | RUBIES-CEERS 49140 | 214.795367 | 52.788848 | 6.687 | H$\alpha$ | $5420\pm 370$ | $8.57\pm 0.07$ | $9.11\pm 0.07$ | 3.0
CEERS 13135 | RUBIES-CEERS 42232 | 214.990983 | 52.916523 | 4.955 | H$\alpha$ | $1850\pm 50$ | $7.39\pm 0.03$ | $7.83\pm 0.03$ | 2.4
CEERS 13318 | RUBIES-CEERS 42046 | 214.983037 | 52.956006 | 5.280 | H$\alpha$ | $3300\pm 60$ | $8.34\pm 0.03$ | $8.88\pm 0.03$ | 3.0
CEERS 14949 | RUBIES-CEERS 37124 | 215.137064 | 52.988557 | 5.684 | H$\alpha$ | $1520\pm 115$ | $6.95\pm 0.08$ | $7.46\pm 0.08$ | 2.8
CEERS 20496 | RUBIES-CEERS 927271 | 215.078257 | 52.948504 | 6.786 | H$\alpha$ | $1410\pm 200$ | $6.45\pm 0.18$ | $6.97\pm 0.18$ | 2.9
CEERS 20777 | RUBIES-CEERS 926125 | 214.892248 | 52.877406 | 5.286 | H$\alpha$ | $1690\pm 70$ | $6.84\pm 0.04$ | $7.32\pm 0.04$ | 2.7
PRIMER-UDS 29881 | RUBIES-UDS 50716 | 34.313132 | -5.226765 | 6.17 | H$\alpha$ | $2280\pm 220$ | $6.98\pm 0.11$ | $7.52\pm 0.11$ | 3.0
PRIMER-UDS 31092 | RUBIES-UDS 47509 | 34.264581 | -5.232544 | 5.675 | H$\alpha$ | $2160\pm 130$ | $7.10\pm 0.06$ | $7.45\pm 0.06$ | 1.9
PRIMER-UDS 32438 | RUBIES-UDS 44043 | 34.241809 | -5.239401 | 3.500 | H$\alpha$ | $2420\pm 120$ | $6.98\pm 0.05$ | $7.36\pm 0.05$ | 2.1
PRIMER-UDS 33823 | RUBIES-UDS 40579 | 34.244190 | -5.245834 | 3.103 |  Pa$\delta$ | $2700\pm 130$ | $8.16\pm 0.04$ | $8.29\pm 0.04$ | 4.0
PRIMER-UDS 116251 | RUBIES-UDS 59971 | 34.260537 | -5.209120 | 5.365 | H$\alpha$ | $1540\pm 280$ | $6.44\pm 0.20$ | $6.83\pm 0.20$ | 2.2
PRIMER-UDS 119639 | RUBIES-UDS 63166 | 34.312143 | -5.202546 | 6.518 | H$\alpha$ | $2200\pm 400$ | $7.09\pm 0.17$ | $7.82\pm 0.17$ | 4.0

We cross-matched our primary sample with the publicly available NIRSpec data
in our target fields and have identified 18 sources in the EGS field and six
sources in the UDS field that were recently observed by the RUBIES program
(GO-4233; PI: A. de Graaff). We find evidence for broad emission lines
detected with a ${\rm SNR}>3$ in nine CEERS sources (5760, 6126, 7902, 10444,
13135, 13318, 14949, 20496, 20777) and six PRIMER-UDS sources (31092, 32438,
33823, 116251, and 119639). We also detect tentative broad emission with ${\rm
SNR}<3$ in two additional CEERS sources (13748 and 114801). In addition, one
source from the sample of B23 (ID 48777) that was removed from our primary
sample for having a UV slope of $\beta_{\rm UV}<-2.8$ was also observed and
confirmed to be a brown dwarf.

The G395M/F290LP spectra of the sources that show a broad emission feature, in
regions near the broad component, is shown in Figures 15 and 16, along with
our best-fit two component (narrow plus broad) emission line model for each
line. For these fits, we employ a Levenberg-Marquardt least-squares method
described in Kocevski et al. (2023), where each line is fit with two
Gaussians: one narrow with width $\sigma<350$ km s-1 and one broad with width
$\sigma>350$ km s-1. The line centers, widths, and fluxes are all free
parameters. The broad-line widths we measure are listed in Table 5 and range
from $\sim 1400$ to 5400 km s-1. The continuum slopes and magnitude
distribution of these sources can be seen in Figures 3 and 4.

Of the remaining seven sources observed, we find the emission lines of four
are best-fit using a narrow component only (CEERS 2520, 7872, 9083, and
12833), while three sources (CEERS 18850, 99879, and 111399) show only weak
H$\alpha$ or H$\beta$ emission in their G395M/F290LP spectra and it remains
inconclusive whether they require a broad component. These three sources are
the faintest of the 24 observed, all with F444W$>26.5$. The full G395M/F290LP
spectra of the 24 LRDs observed by the RUBIES survey are shown in Appendix A.

In summary, 15 LRDs out of a sample of 24 observed show evidence of a broad
emission component, or 63%. This fraction increases to 71% (17/24) if we
include the two sources with broad lines detected at a lower SNR. If we only
consider sources with F444W$<26.5$, where we could effectively measure line
widths, the broad-line detection fraction is 71% (15/21) excluding the low SNR
sources and 81% (17/21) with them included.

Interestingly, three sources in our sample show evidence of blue-shifted
absorption in their Balmer lines (CEERS 7902, 10444, and 13318). Adding an
absorption component to our fits, we find that these lines have a FWHM in the
range 250-500 km s-1 and are blue-shifted by 200-300 km s-1 relative to the
line center of our best-fit narrow component. Blue-shifted He i $\lambda
1.083\mu$m absorption was also noted in PRIMER-UDS 33823 by Wang et al.
(2024), meaning that 27% (4/15) of our sample of broad-line LRDs show such
features. Matthee et al. (2023) previously reported the presence of H$\alpha$
absorption lines in two LRDs with broad-line detections, raising the
possibility that such features may be common in the spectra of these faint,
red AGN.

While broad absorption line quasars (BAL QSOs) often show absorption in their
rest-frame UV lines, only a handful of quasars are known to exhibit Balmer
absorption; see Schulze et al. (2018) and references therein. The creation of
these lines requires neutral hydrogen gas at such high column densities ($\sim
10^{19}$ cm-2) that Ly$\alpha$ trapping becomes important in replenishing
electrons in the $n=2$ shell (Hall, 2007). This suggests the absorber is
located close to the central engine and is exposed to the quasar’s ionizing
continuum. Previous studies place the location beyond the broad-line region
but within the dust sublimation radius (Hall, 2007; Zhang et al., 2015;
Schulze et al., 2018). Therefore the detection of blueshifted Balmer
absorption in these LRDs suggests the presence of high density, low ionization
gas that is outflowing from near the central engine.

Finally, we conclude this section by estimating BH masses for the 15 LRDs with
secure broad-line detections. For this calculation, we follow Kocevski et al.
(2023) and make use of the scaling relationships presented in Greene & Ho
(2005). For sources with H$\alpha$ detections, we use the relationship:

$M_{\rm BH}=2.0\times 10^{6}\left(\frac{L_{\rm H\beta}}{10^{42}\ {\rm erg\
s^{-1}}}\right)^{0.55}\left(\frac{{\rm FWHM_{\rm H\beta}}}{10^{3}\ {\rm km\
s^{-1}}}\right)^{2.06}M_{\odot}.$ (5)

For sources with only H$\beta$ detections (CEERS 7902), we use the
corresponding relationship that employs the H$\beta$ line width and
luminosity:

$M_{\rm BH}=3.6\times 10^{6}\left(\frac{L_{\rm H\alpha}}{10^{42}\ {\rm erg\
s^{-1}}}\right)^{0.56}\left(\frac{{\rm FWHM_{\rm H\alpha}}}{10^{3}\ {\rm km\
s^{-1}}}\right)^{2}M_{\odot}.$ (6)

In Table 5, we list our measured BH masses, both with and without dust
corrections to the observed line luminosities. For this correction we use the
$A_{V}$ values derived from our best-fit galaxy plus AGN SED modeling
described in §3.3. For PRIMER-UDS 33823, we make use of the P$\delta$ line
width and luminosity, assuming a P$\delta$-H$\alpha$ line ratio of 46.7,
consistent with Case B recombination. We find that our derived BH mass for
this source ($\log M_{\rm BH}/{\rm M}_{\odot}=8.26\pm 0.04$) is in good
agreement with the range of BH masses ($\log M_{\rm BH}/{\rm
M}_{\odot}=7.9-8.6$ ) presented in Wang et al. (2024) based on their analysis
of multiple broad lines.

Figure 17: Spectral energy distributions for LRDs in our sample that have
photometric redshifts of $z>9$. The probability density function for the
measured photometric redshift of each source is shown in the inset. $2\sigma$
upper limits are shown for bands with non-detections.

###  4.6 The $z>9$ LRD Sample

In this section, we highlight the highest redshift ($z>9$) LRDs in our sample.
Despite the rapid decline in the redshift distribution above $z\sim 8$, we
detect 22 LRD at $z>9$. The SEDs of these sources and their photometric
redshift $P(z)$ distributions are shown in Figures 17.

Four of our LRDs at $z>9$ (CEERS 23931, 36308, 53047, and 80072) were
previously identified as high-redshift sources in Finkelstein et al. (2023,
their IDs 98518, 92463, 88331, and 1398). Four sources at $z>8.5$ (CEERS 2520,
7872, 80438, and 81443) were previously identified as potential high-redshift,
massive galaxies in Labbé et al. (2023, their IDs 16624, 14924, 21834, and
35300).

The highest redshift source in our sample is PRIMER-COS 70533, which has a
photometric redshift of 11.92. However, this source also has a secondary
photometric redshift solution at $z=9.2$. The other three sources with $z>11$
are JADES 67592 and PRIMER-UDS 106389 and 151408, the latter two of which have
relatively broad $P(z)$ distributions. If the redshifts and AGN nature of
these sources is confirmed, they would be among the most distant AGN ever
discovered, with redshift much higher than the highest-redshift AGN identified
in the pre-JWST, which was found at $z=7.6$ (Wang et al., 2021). However, we
note that because of the reduced number of filters available for our continuum
fitting in the rest-optical at these extreme redshifts, these sources may
suffer a greater likelihood of contamination from strong emission lines, which
further motivates the need for future deep spectroscopic follow-up of these
targets.

Figure 17 (Cont.): Spectral energy distributions for LRDs in our sample that
have photometric redshifts of $z>9$. The probability density function for the
measured photometric redshift of each source is shown in the inset. $2\sigma$
upper limits are shown for bands with non-detections.

##  5 Discussion

One of our primary findings is that the red compact objects that have come to
be known as little red dots appear in large numbers at $z>4$. Our selection
method is designed to pick up lower redshift LRDs that might be missed using a
fixed color selection; however, we find few analogs of these sources at $z<4$.
This likely explains why this population was not previously identified using
imaging from HST.

The redshift distribution that we observe for our sample of LRDs may provide
insight into the nature of their obscuration and the mechanisms fueling their
nuclear activity. The fact that they are largely limited to $z>4$ could be a
natural consequence of inside-out growth (e.g., Carrasco et al., 2010; van
Dokkum et al., 2014), where early galaxies experience more compact, centrally
concentrated star formation. The dissipative gas collapse that fuels such
activity (e.g., Dekel & Burkert, 2014; Tacchella et al., 2018) may also be
responsible for triggering concurrent growth of the central SMBH (Kocevski et
al., 2017; Aird et al., 2022). The rapid accumulation of metals in the proto-
bulge then provides the reddening we observe. At later epochs, infalling gas
will have higher angular momentum, which results in star formation moving to
larger scales. As less dust is deposited near the AGN, we observe fewer
heavily-reddened LRDs at lower redshifts.

In this scenario, the nuclear emission from the central AGN would be reddened
by host obscuration as opposed to nuclear obscuration. Previous work on red
quasars at lower redshifts ($z<0.7$) have found that they are indeed
predominantly obscured by dust in their host galaxies, as opposed to, for
example, a moderate viewing angle that passes through a dust torus (Kim & Im,
2018). In addition, Gilli et al. (2022) have used deep ALMA observations to
show that the ISM column density toward the nucleus of galaxies at $z>6$ can
reach Compton-thick levels of obscuration (Gilli et al., 2022). They conclude
that 80-90% of SMBH growth at these early epochs is likely hidden from view
due to the ISM of their host galaxies.

Obscuration from a compact host galaxy would be consistent with the reported
high fraction of LRDs that are not detected using MIRI imaging out to $21\mu
m$ (Williams et al., 2023; Pérez-González et al., 2024a) since galactic-scale
dust would produce reprocessed emission that falls beyond the MIRI wavelength
coverage. That said, the mid-infrared emission from the X-ray detected LRDs we
have identified at $z\sim 3-4$ is well explained using a clumpy torus model,
which suggests a fraction of these sources may indeed be obscured by a dusty
torus. It is likely that different scales of obscuration exist in these
systems, as has been previously inferred from samples of infrared-selected red
quasars (e.g., Yan et al., 2019). Better constraints on the fraction of LRDs
that exhibit hot dust emission may help elucidate the scale of the obscuration
in these systems and the prevalence of nuclear-scale dust. We plan to examine
the mid-infrared properties of our sample in a forthcoming paper (Leung et
al., in prep).

Another source of obscuration in these systems can be inferred from the
presence of Balmer absorption lines in the spectra of several LRDs. These
absorption features may help explain one of the more perplexing properties of
LRDs: their lack of X-ray emission. While we have presented two X-ray bright
LRDs, the vast majority of them (including all with broad-line detections)
remain undetected even in the deepest _Chandra_ observations. The fraction of
LRDs that show Balmer absorption features provides information on the fraction
of sight-lines to the central engine that are obscured by high-density,
neutral hydrogen clouds, i.e. the covering factor. The higher fraction that we
find relative to that observed in BAL QSOs, for example, suggests an increase
in the covering factor among these fainter AGN. At the gas densities required
to produce these Balmer absorption lines, soft x-ray photons will ionize
neutral hydrogen and create Ly$\alpha$ photons via recombination, which
subsequently get trapped. Since most BAL QSOs are X-ray weak (Brandt et al.,
2000; Gallagher et al., 2001), we may surmise that the presence of this high-
density, absorbing material may also help attenuate the X-ray emission from
LRDs. Coupled with potentially high column densities in the ISM of their host
galaxies (e.g., Gilli et al., 2022), this may help explain the low fraction of
LRDs that are X-ray detected.

While it remains to be determined what fraction of our full sample are
reddened AGN, we find that 17 of 21 newly-observed LRDs where we could
effectively measure emission line widths in the G395M/F290LP spectra show
evidence for broad-line emission, which is consistent with the high fraction
(80%) reported in Greene et al. (2023) when brown dwarf contaminants are
excluded. Such a high AGN fraction would have important ramifications for the
bright galaxy samples being reported at high redshift. For example, 11/13 of
the massive galaxy candidates originally presented in Labbé et al. (2023) are
identified as LRDs using our selection. If the rest-optical emission of these
sources is dominated by AGN emission, as seen in other LRDs, then this may
help explain the anomalously high stellar masses reported for these sources.

The discovery of a new population of AGNs at high redshift naturally begs the
question of whether this population could significantly contribute to the
reionization photon budget. While the declining abundance of UV-bright quasars
implies that such objects are not contributors at z ¿ 6 (e.g., Hopkins et al.,
2007), the uncertain abundance of UV-faint AGN leaves open the door for a
modest contribution by such sources (e.g. Giallongo et al., 2015; Finkelstein
et al., 2019). While the high bolometric luminosity inferred for LRDs ($L_{\rm
bol}\sim 10^{43}-10^{46}$ erg/s; e.g., Labbe et al., 2023; Kokorev et al.,
2024) implies the AGNs may be producing large quantities of ionizing photons,
the high dust reddening measured in these sources ($A_{\rm V}\geq 3$; Barro et
al., 2023; Labbe et al., 2023) strongly limits the escape of ionizing photons.
This is evidenced by the weak UV emission from these galaxies. While it
remains unclear whether the UV emission is dominated by unobscured stellar
light or scatted AGN light, the abundance of LRDs is $\sim 100\times$ lower
than continuum-selected star-forming galaxies (see Figure 8). Thus even if the
escaping UV light is AGN-dominated, it is insignificant compared to the known
star-forming galaxy population at these redshifts.

##  6 Conclusions

We present the largest sample of little red dots compiled to date using JWST
data from the CEERS, PRIMER, JADES, UNCOVER, and NGDEEP surveys. Our sample
contains 341 sources spanning the redshift range $2<z<11$ in a total area
covering 587.8 arcmin2. These sources are selected to have red colors in the
rest-frame optical and blue colors in the rest-frame UV, coupled with a
compact morphology. While previous studies used color indices measured in a
single combination of bands (i.e., F277-F444W) to identify LRDs, we perform
our search by fitting the UV and optical continuum slope of sources using
multiple bands blueward and redward of the Balmer break. The bands used for
these fits shift as a function of redshift to ensure the same rest-frame
emission is sampled for each source. This allows us to identify LRDs over a
wider redshift range than a fixed color selection and is less susceptible to
contamination from galaxies with strong breaks that otherwise lack a rising
red continuum.

Using our sample, we find:

  * •

LRDs emerge in large numbers at $z\sim 8$ and then experience a rapid decline
in their number density at $z\sim 4.5$. This redshift distribution may reflect
that the fueling and obscuration of these sources is tied to the dissipative
gas collapse that drives the inside-out growth of galaxies during this epoch.
In this scenario, the decline in the number of LRDs at later times would be
due to star formation moving to larger scales, resulting in less dust being
deposited near the AGN and a possible drop in their duty cycle.

  * •

LRDs are 2-3 dex more numerous at $z\sim 5-7$ than would be expected based on
extrapolations of the quasar luminosity function measured from the ground.
However, the number density of LRDs at $z\sim 5$ is only 0.6 dex higher than
that of lower-luminosity X-ray AGN identified at the same redshift. This
offset increases to a full dex at $z\sim 7$ relative to color-selected AGN. At
this redshift, LRDs constitute $\sim 3\%$ of the overall galaxy population at
$M_{\rm UV}=-20$.

  * •

We identify the first LRDs detected at X-ray wavelengths. An X-ray spectral
analysis of these two sources confirms that they are moderately obscured, with
equivalent neutral Hydrogen column densities of $\log\,(N_{\rm H}/{\rm
cm}^{-2})=$ $23.3^{+0.4}_{-1.3}$ and $22.72^{+0.13}_{-0.16}$. An analysis of
their SEDs and morphologies suggests the rest-frame optical emission from both
sources is dominated by light from the reddened AGN, while their rest-frame UV
emission originates from their host galaxies.

  * •

We present follow-up spectroscopy of 17 LRDs in our sample that show broad
emission features with line widths of $\sim 1400$ to 5400 km s-1, consistent
with AGN activity. We measure their black hole masses to be in the range
$M_{\rm BH}=10^{6-8}$ M⊙, which is 1-2 dex below that of bright quasars at
similar redshifts.

  * •

The confirmed AGN fraction of our sample is 71% among sources with
F444W$<26.5$, where we could effectively measure emission line widths in the
G395M/F290LP spectra. This fraction increases to 81% if we include sources
whose broad emission lines are detected with a $SNR<3$.

  * •

A relatively high fraction (24%) of LRDs in our sample with broad emission
lines also show narrow, blue-shifted Balmer or He i absorption features in
their spectra, suggesting a prevalence of outflows in these sources. We
propose that a high covering factor of high-density, neutral hydrogen gas,
coupled with potentially high column densities in the ISM of their host
galaxies, may help explain the relatively weak X-ray emission from LRDs.

While much remains to be determined about the nature of LRDs, the prevalence
of broad emission lines in their spectra suggests this population is shedding
light on a phase of obscured black hole growth in the early universe that was
largely undetected prior to the JWST era. Forthcoming mid-infrared imaging and
spectroscopic follow-up of these sources will soon better constrain the number
density of these faint AGN and shed light on the nature of the obscuring
medium in these systems.

##  Appendix A NIRSpec Spectra of Newly Observed LRDs

In this appendix, we present the full G395M/F290LP spectra of the 24 LRDs from
our sample in the EGS and UDS fields that were recently observed by the RUBIES
program. These spectra are shown in Figures 18, 19, 20, 21, 22, and 23.

Figure 18: NIRSpec spectra from the RUBIES survey of sources CEERS 2520, 5760,
6126, and 7872 taken in the G395M grating. The locations of several prominent
emission lines are noted. Figure 19: NIRSpec spectra from the RUBIES survey of
sources CEERS 7902, 9083, 10444, and 12833 taken in the G395M grating. The
locations of several prominent emission lines are noted. Figure 20: NIRSpec
spectra from the RUBIES survey of sources CEERS 13135, 13318, 13748, and 14949
taken in the G395M grating. The locations of several prominent emission lines
are noted. Figure 21: NIRSpec spectra from the RUBIES survey of sources CEERS
18850, 20496, 20777, and 99879 taken in the G395M grating. The locations of
several prominent emission lines are noted. Figure 22: NIRSpec spectra from
the RUBIES survey of sources CEERS 111399 and 114801, as well as PRIMER-UDS
29881 and 31092 taken in the G395M grating. The locations of several prominent
emission lines are noted. Figure 23: NIRSpec spectra from the RUBIES survey of
sources PRIMER-UDS 32438, 33823, 116251, and 119639 taken in the G395M
grating. The locations of several prominent emission lines are noted. PRIMER-
UDS 33823 is the same source as RUBIES-BLAGN-1 presented in Wang et al.
(2024).

##  Appendix B Acknowledgments

We thank the RUBIES team for their work in designing and preparing the NIRSpec
observations used in this study. This work is supported by NASA grants JWST-
ERS-01345 and JWST-AR-02446 and based on observations made with the
NASA/ESA/CSA James Webb Space Telescope. The data were obtained from the
Mikulski Archive for Space Telescopes at the Space Telescope Science
Institute, which is operated by the Association of Universities for Research
in Astronomy, Inc., under NASA contract NAS 5-03127 for JWST.

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