# COSMOS-Web: The Overabundance and Physical Nature of “Little Red Dots”-Implications for Early Galaxy and SMBH Assembly

Hollis Akins, Caitlin Casey, Erini Lambrides, Natalie Allen, Irham Andika, Malte Brinch, Jaclyn Champagne, Olivia Cooper, Xuheng Ding, Nicole Drakos, et al.

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To cite this version:

Hollis Akins, Caitlin Casey, Erini Lambrides, Natalie Allen, Irham Andika, et al. COSMOS-Web: The Overabundance and Physical Nature of “Little Red Dots”-Implications for Early Galaxy and SMBH Assembly. The Astrophysical Journal, 2025, 991 (1), pp.37. 10.3847/1538-4357/ade984 . hal-05474554

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# COSMOS-Web: The Overabundance and Physical Nature of “Little Red Dots”— Implications for Early Galaxy and SMBH Assembly

Hollis B. Akins¹,²,<fnref n="35" />, Caitlin M. Casey⁴,³,¹, Erini Lambrides⁵,<fnref n="37" />, Natalie Allen³,⁶, Irham T. Andika⁷,⁸, Malte Brinch³,⁹, Jaclyn B. Champagne¹⁰, Olivia Cooper¹,<fnref n="35" />, Xuheng Ding¹¹, Nicole E. Drakos¹², Andreas Faisst¹³, Steven L. Finkelstein¹, Maximilien Franco¹, Seiji Fujimoto¹,<fnref n="36" />, Fabrizio Gentile¹⁴,¹⁵, Steven Gillman³,⁹, Ghassem Gozaliasl¹⁶, Santosh Harish¹⁷, Christopher C. Hayward¹⁸, Michaela Hirschmann¹⁹,²⁰, Olivier Ilbert²¹, Jeyhan S. Kartaltepe¹⁷, Dale D. Kocevski²², Anton M. Koekemoer²³, Vasily Kokorev¹, Daizhong Liu²⁴, Arianna S. Long¹,<fnref n="36" />, Henry Joy McCracken²⁵, Jed McKinney¹,<fnref n="36" />, Masafusa Onoue¹¹,²⁶,²⁷, Louise Paquereau²⁵, Alvio Renzini²⁸, Jason Rhodes²⁹, Brant E. Robertson¹², Marko Shuntov³,⁶, John D. Silverman¹¹,²⁶,³⁰,³¹, Takumi S. Tanaka¹¹,²⁶,³⁰, Sune Toft³,⁶, Benny Trakhtenbrot³², Francesco Valentino³³, and Jorge Zavala³⁴

¹ Department of Astronomy, The University of Texas at Austin, 2515 Speedway Boulevard Stop C1400, Austin, TX 78712, USA; hollis.akins@gmail.com

² Cosmic Frontier Center, The University of Texas at Austin, Austin, TX 78712, USA

³ Cosmic Dawn Center (DAWN), Denmark

⁴ Department of Physics, University of California, Santa Barbara, CA 93106, USA

⁵ NASA Goddard Space Flight Center, 8800 Greenbelt Road, Greenbelt, MD 20771, USA

⁶ Niels Bohr Institute, University of Copenhagen, Jagtvej 128, DK-2200, Copenhagen N, Denmark

⁷ Technical University of Munich, TUM School of Natural Sciences, Department of Physics, James-Franck-Str. 1, 85748 Garching, Germany

⁸ Max-Planck-Institut für Astrophysik, Karl-Schwarzschild-Str. 1, 85748 Garching, Germany

⁹ DTU-Space, Technical University of Denmark, Elektrovej 327, DK-2800 Kgs. Lyngby, Denmark

¹⁰ Steward Observatory, University of Arizona, 933 N Cherry Avenue, Tucson, AZ 85721, USA

¹¹ Kavli Institute for the Physics and Mathematics of the Universe (WPI), The University of Tokyo Institutes for Advanced Study, The University of Tokyo, Kashiwa, Chiba 277-8583, Japan

¹² Department of Astronomy and Astrophysics, University of California, Santa Cruz, 1156 High Street, Santa Cruz, CA 95064, USA

¹³ Caltech/IPAC, 1200 E. California Boulevard, Pasadena, CA 91125, USA

¹⁴ University of Bologna, Department of Physics and Astronomy (DIFA), via Gobetti 93/2, I-40129, Bologna, Italy

¹⁵ INAF—Osservatorio di Astrofisica e Scienza dello Spazio, via Gobetti 93/3, I-40129, Bologna, Italy

¹⁶ Department of Physics, University of Helsinki, P.O. Box 64, FI-00014 Helsinki, Finland

¹⁷ Laboratory for Multiwavelength Astrophysics, School of Physics and Astronomy, Rochester Institute of Technology, 84 Lomb Memorial Drive, Rochester, NY 14623, USA

¹⁸ Center for Computational Astrophysics, Flatiron Institute, 162 Fifth Avenue, New York, NY 10010, USA

¹⁹ Institute for Physics, Laboratory for Galaxy Evolution and Spectral modelling, Ecole Polytechnique Federale de Lausanne, Observatoire de Sauverny, Chemin Pegasi 51, 1290 Versoix, Switzerland

²⁰ INAF, Osservatorio Astronomico di Trieste, Via Tiepolo 11, 34131 Trieste, Italy

²¹ Aix Marseille Université, CNRS, CNES, LAM, Marseille, France

²² Department of Physics and Astronomy, Colby College, Waterville, ME 04901, USA

²³ Space Telescope Science Institute, 3700 San Martin Drive, Baltimore, MD 21218, USA

²⁴ Max-Planck-Institut für Extraterrestrische Physik (MPE), Giessenbachstr. 1, D-85748 Garching, Germany

²⁵ Institut d'Astrophysique de Paris, UMR 7095, CNRS, and Sorbonne Université, 98 bis boulevard Arago, F-75014 Paris, France

²⁶ Center for Data-Driven Discovery, Kavli IPMU (WPI), UTIAS, The University of Tokyo, Kashiwa, Chiba 277-8583, Japan

²⁷ Kavli Institute for Astronomy and Astrophysics, Peking University, Beijing 100871, People's Republic of China

²⁸ INAF—Osservatorio Astronomico di Padova, Vicolo dell'Osservatorio 5, I-35122 Padova, Italy

²⁹ Jet Propulsion Laboratory, California Institute of Technology, 4800 Oak Grove Drive, Pasadena, CA 91001, USA

³⁰ Department of Astronomy, Graduate School of Science, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo, 113-0033, Japan

³¹ Center for Astrophysical Sciences, Department of Physics & Astronomy, Johns Hopkins University, Baltimore, MD 21218, USA

³² School of Physics and Astronomy, Tel Aviv University, Tel Aviv 69978, Israel

³³ European Southern Observatory, Karl-Schwarzschild-Strasse 2, D-85748, Garching bei München, Germany

³⁴ National Astronomical Observatory of Japan, 2-21-1 Osawa, Mitaka, Tokyo 181-8588, Japan

Received 2024 June 14; revised 2025 June 9; accepted 2025 June 11; published 2025 September 12

## Abstract

JWST has revealed a population of compact and extremely red galaxies at $z \gtrsim 4$, which likely host active galactic nuclei (AGNs). We present a sample of 434 “little red dots” (LRDs), selected from the 0.54 deg² COSMOS-Web survey. We fit galaxy and AGN spectral energy distribution models to derive redshifts and physical properties; the sample spans $z \sim 5-9$ after removing brown dwarf contaminants. As a thought experiment, we consider two extreme physical scenarios: either LRDs are all AGNs, and their continuum emission is dominated by the accretion disk, or they are all compact star-forming galaxies, and their continuum is dominated by stars. If LRDs

<figure><img src="image_3.png" /></figure>

<footnote n="35">³⁵ NSF Graduate Research Fellow.</footnote>

<footnote n="36">³⁶ Hubble Fellow.</footnote>

<footnote n="37">³⁷ NPP Fellow.</footnote>
are AGN-dominated, our sample exhibits bolometric luminosities ~$10^{45-47}$ erg s⁻¹, spanning the gap between JWST AGNs in the literature and bright, rare quasars. We derive a bolometric luminosity function (LF) ~100 times the (UV-selected) quasar LF, implying a nonevolving black hole accretion density of ~$10^{-4} M_{\odot}$ yr⁻¹ Mpc⁻³ from z ~2–9. By contrast, if LRDs are dominated by star formation, we derive stellar masses ~$10^{8.5-10} M_{\odot}$. MIR/F770W is key to deriving accurate stellar masses; without it, we derive a mass function inconsistent with Λ cold dark matter. The median stellar mass profile is broadly consistent with the maximal surface densities seen in the nearby Universe, though the most massive objects exceed this limit, requiring substantial AGN contribution to the continuum. Nevertheless, stacking all available X-ray, mid-IR, far-IR/submillimeter, and radio data yields nondetections. Whether dominated by dusty AGNs or compact star-formation, the high masses/luminosities and remarkable abundance of LRDs implies a dominant mode of early galaxy/SMBH growth.

*Unified Astronomy Thesaurus concepts: Active galactic nuclei (16); Quasars (1319); High-redshift galaxies (734); Galaxies (573)*

*Materials only available in the online version of record: figure set, machine-readable table*

# 1. Introduction

The launch of JWST has revealed new classes of objects unseen before: in particular, an abundant population of compact and extremely red objects, so-called “little red dots” (LRDs; J. Matthee et al. 2024). These objects are characterized by pointlike morphology, red colors from observed-frame ~2–5 µm, and often exhibit flat or even blue colors from 1–2 µm. The population appears to be ubiquitous from z ≳ 3 (G. Barro et al. 2024) to z ~ 9 (G. C. K. Leung et al. 2023), spanning several orders of magnitude in luminosity. At these redshifts, the distinctive colors imply a blue UV slope with a steep/red optical continuum. Initial studies interpreted these objects as high-mass (≥$10^{10} M_{\odot}$), z ≳ 6 galaxy candidates (e.g., H. B. Akins et al. 2023; I. Labbé et al. 2023), with either high equivalent width (EW) emission lines or strong Balmer breaks and likely with significant dust attenuation driving the red optical color. Reconciling these high masses with the pointlike morphology requires rapid starbursts in compact cores (see, e.g., J. F. W. Baggen et al. 2023), and implies a high stellar mass density in the early Universe, which, for some time, appeared to be in tension with expectations for the halo mass function in Λ cold dark matter (CDM; M. Boylan-Kolchin 2023). While more recent analysis has, in some cases, brought down the exceedingly large stellar masses, relieving the possible tension with ΛCDM (e.g., R. Endsley et al. 2023b; K. Chworowsky et al. 2024; D. D. Kocevski et al. 2023), in others, the high redshifts and high stellar masses have been reaffirmed by spectroscopic observations (e.g., B. Wang et al. 2024a). Nevertheless, the sheer abundance of these objects seems to be at odds with a massive galaxy interpretation.

An alternative interpretation of these “little red dots” is that they are dominated by emission from an active galactic nucleus (AGN). Indeed, spectroscopy has been obtained for ≥50 LRDs, in ~80% of cases confirming the high redshifts (z > 5) and identifying broad Balmer lines (≥2000 km s⁻¹; e.g., M. Killi et al. 2024; D. D. Kocevski et al. 2023; V. Kokorev et al. 2023; L. J. Furtak et al. 2024; J. E. Greene et al. 2024; B. Wang et al. 2024; D. D. Kocevski et al. 2025; J. Matthee et al. 2025). The pointlike morphology and broad Balmer emission lines are signatures of unobscured (Type I) AGNs; i.e., we have a direct view to the broad-line region (BLR) and the accretion disk, but with foreground dust attenuation either from a dusty interstellar medium (ISM) or polar dust, nuclear to the AGN (see, e.g., H. Netzer 2015; R. C. Hickox & D. M. Alexander 2018). This configuration is

similar to the “red quasars” at 1 < z < 3 (e.g., T. Urrutia et al. 2008; M. Banerji et al. 2012; E. Glikman et al. 2012; E. Glikman et al. 2022), for which the dust attenuation is thought to originate from the galaxy-scale ISM (M. Banerji et al. 2018; M. J. Temple et al. 2019), and which have also been found out to high-z (e.g., N. Kato et al. 2020; S. Fujimoto et al. 2022). Although at face value, the LRDs appear to populate the faint end of the AGN UV luminosity function, when accounting for dust obscuration, their intrinsic luminosities can be quite large ($L_{bol} \gtrsim 10^{45}$ erg s⁻¹; e.g., V. Kokorev et al. 2024). Consistent with these high luminosities, many authors have derived large black hole masses relative to the host galaxy mass (e.g., Á. Bogdán et al. 2024; J. E. Greene et al. 2024; I. Juodžbalis et al. 2024; O. E. Kovács et al. 2024; R. Maiolino et al. 2024a). This may imply exotic black hole seed/growth mechanisms, but also could be consistent with selection bias (J. Li et al. 2025). However, the origin of the red continuum emission—whether it is dominated by an AGN or host galaxy—remains unclear, but has major implications for our interpretation of these objects as massive galaxies, luminous quasars, or some combination thereof.

There exists some evidence that the continuum emission from the LRDs is actually dominated by stars. For one, multiband JWST/MIRI observations from 5–25 µm have shown a remarkably flat spectral energy distribution (SED) in the rest-frame mid-IR for a number of LRDs, placing strong upper limits on the contribution from hot dust in the AGN torus, in tension with the implied luminosities of the quasars (C. C. Williams et al. 2023; G. C. K. Leung et al. 2024; P. G. Pérez-González et al. 2024). Moreover, several broad-line objects exhibit clear Balmer breaks in their spectra, implying a dominant contribution from evolved stars in the rest-frame optical, though the precise contribution is degenerate, with stellar mass estimates ranging over 2 orders of magnitude (B. Wang et al. 2024a). Even still, not all LRDs with spectroscopic coverage exhibit clear broad lines (e.g., G. Barro et al. 2024; J. E. Greene et al. 2024), perhaps indicating that the population may not be homogeneous. It remains unclear whether the LRDs can be explained entirely by AGNs, with unique geometry/dust properties, or also represent a significant population of compact/massive galaxies in the early Universe.

In this work, we present a large sample of 434 z ≳ 5 LRDs selected from the COSMOS-Web JWST survey. With the large sample size, nearly doubling the number of known LRDs (D. D. Kocevski et al. 2025; V. Kokorev et al. 2024), and large
on-sky area, minimizing the impact of cosmic variance, we provide strong constraints on the volume density of this population. In Section 2 we describe the COSMOS-Web survey, our data reduction methodology, and ancillary multi-wavelength data. In Section 3 we describe our sample selection and SED fitting methodology. We adopt a “thought experiment” approach, wherein we fit each object to both pure galaxy and pure AGN models to characterize the two extreme scenarios. In Section 4.1 we consider the interpretation of the LRDs as AGNs; in particular, we derive their contribution to the bolometric luminosity function and black hole accretion density. In Section 4.2, we consider the interpretation of the LRDs as instead compact star-forming galaxies; in particular, we present the derived stellar mass function and examine the feasibility of such dense stellar systems. In Section 5 we stack the available multiwavelength data over the entire sample, providing constraints on the panchromatic SED of the typical LRD. In Section 6 we discuss this sample in context with other JWST results, with particular focus on the physical processes that may be responsible for the unique characteristics of the LRD population. Throughout this paper, we adopt a P. Kroupa (2002) initial mass function and a cosmology consistent with the Planck Collaboration (2020) results ($H_0 = 67.66 \text{ km s}^{-1} \text{ Mpc}^{-1}$, $\Omega_{m,0} = 0.31$). All magnitudes are quoted in the AB system (J. B. Oke 1974).

## 2. Data

### 2.1. COSMOS-Web

COSMOS-Web is a large JWST Cycle 1 treasury program imaging a contiguous 0.54 deg² with NIRCam and 0.19 deg² with MIRI (C. M. Casey et al. 2023) in the COSMOS field (N. Scoville et al. 2007). The COSMOS-Web imaging includes four NIRCam filters (F115W, F150W, F277W, and F444W) at approximate 5σ depths of 27.4–28.2 AB mag, and one MIRI filter (F770W) at a 5σ depth of 26 AB mag. The full details on the NIRCam and MIRI reduction process will be presented in upcoming papers (M. Franco et al. 2025, in preparation; S. Harish et al. 2025, in preparation, respectively) but are briefly described here. The raw NIRCam imaging was reduced by the JWST Calibration Pipeline version 1.12.1, with the addition of several custom modifications (as has also been done for other JWST studies; e.g., M. B. Bagley et al. 2023) including the subtraction of 1/f noise and sky background. We use the Calibration Reference Data System (CRDS)<fnref n="38" /> pmap 1170, which corresponds to NIRCam instrument mapping imap 0273. The final mosaics are created in Stage 3 of the pipeline with a pixel size of 0.03 pixel⁻¹. Astrometric calibration is conducted via the JWST/Hubble Space Telescope (HST) alignment tool (JHAT; A. Rest et al. 2023), with a reference catalog based on an HST/F814W 0.03 pixel⁻¹ mosaic in the COSMOS field (A. M. Koekemoer et al. 2007) with astrometry tied to Gaia-EDR3 (Gaia Collaboration 2018). The median offset in R.A. and decl. between our reference catalog and the NIRCam mosaic is <5 mas. The MIRI/F770W observations were reduced using version 1.8.4 of the JWST Calibration pipeline, along with additional steps for background subtraction that were necessary to mitigate instrumental effects. The resulting mosaic was resampled onto a

common output grid with a pixel scale of 0.03 pixel⁻¹ and aligned with ancillary HST/F814W imaging of the region.

### 2.2. PRIMER-COSMOS

The Public Release Imaging for Extragalactic Research (PRIMER) survey (P.I. J. Dunlop, GO#1837) is a large Cycle 1 Treasury Program to image the COSMOS and UDS fields in CANDELS (N. A. Grogin et al. 2011; A. M. Koekemoer et al. 2011) with NIRCam+MIRI (C. T. Donnan et al. 2024). The PRIMER-COSMOS field comprises ~130 sq. arcmin and is contained entirely within the COSMOS-Web footprint (see C. M. Casey et al. 2023 for details on the field layout), providing additional depth and filter coverage over ~8% of the field. PRIMER imaging includes eight NIRCam bands (adding F090W, F200W, F356W, and F410M to the COSMOS-Web filter set), plus two MIRI bands (adding F1800W). We have reduced the PRIMER data following the same procedure as with the COSMOS-Web data.

### 2.3. Ancillary Multiwavelength Data

While the COSMOS field is covered with substantial ground-based (Subaru and UltraVISTA) and Spitzer/IRAC imaging, we do not use these additional photometric data in our SED fitting. The lower resolution of these maps, relative to the HST+JWST imaging, mandates careful deblending, which can suffer from significant uncertainties. However, the deep ground-based imaging of the COSMOS field can be useful to constrain photometric redshifts and rule out degenerate low-redshift solutions, which we discuss briefly in Section 3.1.

Even beyond the optical/near-infrared, the COSMOS field is rich with ancillary multiwavelength data in the X-ray, MIR, far-IR (FIR)/submillimeter, and radio. We make use of Chandra X-ray imaging from the COSMOS Legacy Survey (F. Civano et al. 2016), Spitzer/MIPS 24+70 µm imaging from S-COSMOS (D. B. Sanders et al. 2007), Herschel/PACS +SPIRE imaging from PEP and HerMES (D. Lutz et al. 2011; S. J. Oliver et al. 2012), SCUBA-2 850 µm imaging from S2COSMOS (C. M. Casey et al. 2013; J. E. Geach et al. 2017; J. M. Simpson et al. 2019), Atacama Large Millimeter/ submillimeter Array (ALMA) 1.2 mm imaging from CHAMPS (over 0.18 deg²; Faisst et al. 2025, in preparation), ALMA 2 mm imaging from MORA (over ~0.2 deg²; C. M. Casey et al. 2021; A. S. Long et al. 2025), and radio imaging from MeerKAT at 1.4 GHz (I. Heywood et al. 2022) and the Very Large Array (VLA) at 3 GHz (V. Smolčić et al. 2017).

### 2.4. Catalog Construction

Details on the photometric catalogs for COSMOS-Web will be presented in a future paper (M. Shuntov et al. 2025, in preparation); here, we provide a brief summary of the photometric catalog used in this work. We conduct source detection and aperture photometry using SEP (K. Barbary 2016), the python implementation of SExtractor (E. Bertin & S. Arnouts 1996). We perform source detection on a $\chi^2$ detection image constructed from all four NIRCam bands (e.g., A. S. Szalay et al. 1999). First, F115W, F150W, and F277W are point-spread function (PSF)-homogenized to F444W, using PSFs derived from PSFEx (E. Bertin 2011). Each image is converted to a noise-equalized image by multiplying by the square root of the weight map. We then fit the negative tail of the pixel distribution to a Gaussian function to measure the

<footnote n="38">³⁸ https://jwst-crds.stsci.edu/</footnote>
per-pixel rms of the noise-equalized map. The maps are normalized by this rms and truncated at negative values to avoid false positives arising from multiple colocated negative noise peaks. The detection image is then computed by adding these PSF-homogenized, truncated signal-to-noise maps in quadrature. The resulting $\sqrt{\chi^2}$ image can be directly related to the probability of an individual pixel value being drawn from the sky noise distribution (see A. S. Szalay et al. 1999).

We adopt a detection threshold of $\sqrt{\chi^2} = 3.698$ (with no background subtraction), equivalent to a $2.33\sigma$ detection, or a 1% probability of drawing a given pixel value from the noise distribution. We then perform aperture photometry on the available HST/Advanced Camera for Surveys (ACS), JWST/NIRCam, and JWST/MIRI imaging. Similar to S. L. Finkelstein et al. (2023), we utilize small elliptical apertures (with a Kron factor $k = 1.1$) and correct to the total flux based on the default Kron aperture flux in F444W ($k = 2.5$). ACS and NIRCam images are PSF-matched to F444W (as with the detection stage), and photometry is corrected for the F444W PSF flux falling outside of the large Kron aperture. For the MIRI bands, we adopt the same aperture sizes and apply a correction for the fractional flux loss due to the larger PSF. In particular, we compare the aperture flux in the native resolution F444W image to the flux after PSF-matching F444W to the MIRI F770W PSF, and apply this correction to the measured MIRI flux.

Photometric uncertainties are adjusted using a random aperture method to account for correlated noise in the mosaics. For each band, and for a range of aperture sizes, we place 200,000 random circular apertures across the field, avoiding areas with detected sources, and measure the standard deviation of the measured fluxes by fitting the negative tail of the Gaussian distribution. Similar to S. L. Finkelstein et al. (2023) and M. J. Rieke et al. (2023), we fit a power law of the form $\sigma_N = \alpha N^{\beta/2}$, where N is the number of pixels in the aperture. All photometric uncertainties are then added in quadrature with this random aperture noise measurement $\sigma_N$ for the corresponding aperture size.

### 3. Sample Selection and Characterization

From the COSMOS-Web data, we construct our sample of LRDs, fit them each to a series of SED models, and characterize the typical properties and volume density of the population. Before describing our sample selection and SED fitting methodology, we present a brief note of clarification on the motivation behind the strategy we adopt. While, ideally, we would be able to fit each object with a composite galaxy/AGN SED model, decomposing the two components, the limited information available (largely due to the lack of spectroscopic redshifts) makes this kind of analysis prone to overfitting. Instead, we would like to limit the number of free parameters; rather than attempting to decompose the SEDs into galaxy/AGN components, we explore two extreme scenarios:

(a) QSO models: the LRD population is primarily composed of dust-reddened AGNs, with the optical continuum dominated by the direct thermal emission from the accretion disk (\ll 1 pc scales, temperatures $\gtrsim 10^5$ K; e.g., I. Labbé et al. 2025; J. E. Greene et al. 2024; V. Kokorev et al. 2024; J. Matthee et al. 2024). Note that in this scenario, the host galaxy may dominate in the rest-frame UV, but is negligible in the rest-frame optical.

(b) Galaxy models: the LRD population is primarily composed of compact/dusty starbursts, with the optical continuum dominated by the emission from young stellar populations (e.g., C. C. Williams et al. 2023; P. G. Pérez-González et al. 2024). Note that this scenario does not preclude the presence of AGNs in the population, but just requires that the red continuum emission in the optical is dominated by the stellar component.

These two scenarios may be thought of as “edge cases”; while neither likely represents the true nature of the entire population, exploring the implications of either scenario yields valuable physical insight. In both cases, we assume that the characteristic blue UV slope of the LRDs is simply leakage or scattering through a clumpy obscuring medium, similar to what is seen in some lower-redshift DSFGs (e.g., C. M. Casey et al. 2014b) and red quasars (e.g., E. Glikman et al. 2023), and we note that we do not select directly for this blue component.

#### 3.1. Sample Selection

Figure 1 outlines our color-compactness sample selection procedure. From our master photometric catalog described in Section 2.4, we first select all sources with signal-to-noise ratio (S/N) of $S/N_{277} > 3$ and $S/N_{444} > 12$; the higher detection threshold in F444W is motivated by the need to detect sources redder than $m_{277} - m_{444} > 1.5$. We then downselect further to objects that appear compact in F444W, defined via the compactness metric

$$C_{444} = f_{444}(d = 0.2') / f_{444}(d = 0.5'). \quad (1)$$

We use F444W, despite the larger PSF relative to shorter-wavelength bands, since the LRDs are brightest in this band (and it is sometimes the only band with sufficient S/N to yield a reliable measure of compactness). Through a series of source injection simulations, we found that point sources reliably have $0.5 < C_{444} < 0.7$ provided the signal-to-noise is $\gtrsim 20$. We select objects with $C_{444} > 0.5$, meaning that $\gtrsim 50\%$ of the F444W broadband emission within a $0.2'$ diameter aperture is contained within a $0.2'$ diameter aperture. We exclude objects with $C_{444} > 0.7$, which tend to be imaging artifacts (hot pixels), which do not follow the curve-of-growth associated with the PSF. In Section 3.3, we fit these objects to 2D profiles to verify their compact/pointlike nature.

We then select objects with red F277W - F444W colors,

$$m_{277} - m_{444} > 1.5. \quad (2)$$

This is the same threshold that was adopted by G. Barro et al. (2024), who found that almost all objects satisfying this color threshold appear pointlike and blue from 1–2 µm. Similarly, while J. Matthee et al. (2024) selected for broad-line AGNs based on the H$\alpha$ emission, the majority of their objects show similarly red colors from 2µm to $\sim 3–5$ µm. We note that this color threshold is more stringent than several recent works that select LRDs via F277W - F444W > 0.7 or F200W - F356W > 1.0 (e.g., I. Labbé et al. 2025; V. Kokorev et al. 2024). We focus on the reddest subset of the LRD population, which may bias our sample toward more dust-obscured and/or higher-redshift objects. Figure 2 shows our sample compared to other literature samples in color-redshift space; here, we adopt the redshifts from QSO SED models as described in section 3.4.1. We also show in Figure 2 the
<figure><img src="image_4.png" /></figure>

**Figure 1.** Color–magnitude and color–color diagrams illustrating the selection of LRDs in this paper. Left panel: the *m*<sub>277</sub> – *m*<sub>444</sub> vs. *m*<sub>444</sub> color–magnitude diagram. We select all sources with signal-to-noise ratio (S/N) of S/N<sub>444</sub> > 12 (roughly *m*<sub>444</sub> brighter than 27.2) and *m*<sub>277</sub> – *m*<sub>444</sub> > 1.5. Dark-red points indicate the subsample that is covered by MIRI imaging, while light-red points indicate those with only NIRCam coverage. COS-756434, which is spectroscopically confirmed at *z* = 6.99, is marked with a star. Blue points indicate objects for which a brown dwarf solution is preferred via SED fitting. Center panel: the *m*<sub>277</sub> – *m*<sub>444</sub> color vs. compactness *C*<sub>444</sub>, defined as the ratio of the F444W fluxes in 0′′2 and 0′′5 diameter apertures. Objects with *C*<sub>444</sub> < 0.5 are generally extended, while those with *C*<sub>444</sub> > 0.7 are generally imaging artifacts, i.e., hot pixels. Right panel: the *m*<sub>277</sub> – *m*<sub>444</sub> vs. *m*<sub>150</sub> – *m*<sub>277</sub> color–color diagram. While we do not select for blue SW colors (either *m*<sub>115</sub> – *m*<sub>150</sub> or *m*<sub>150</sub> – *m*<sub>277</sub>), as the imaging is too shallow to constrain SW colors at high S/N, we demonstrate here that the NIRCam colors can serve to filter out brown dwarfs, which tend to have bluer SW colors than galaxies at temperatures *T*<sub>BD</sub> < 1200 K.

<figure><img src="image_5.png" /></figure>

**Figure 2.** Comparison of our sample to literature LRD samples in F277W–F444W color vs. (photometric) redshift space. Our sample is shown in red, as in Figure 1, and literature photometric/spectroscopic samples are shown in gray open/filled points, respectively (I. Labbé et al. 2025; J. E. Greene et al. 2024; D. D. Kocevski et al. 2025; J. Matthee et al. 2024). The blue and green points/lines highlight two lower-redshift LRDs with high-S/N PRISM spectra (J0647_1045 at *z* = 4.5 from M. Killi et al. 2024 and RUBIES-BLAGN-1 at *z* = 3.1 from B. Wang et al. 2024a) and their F277W–F444W color when redshifted. The dark-orange line shows a redshifted Sloan Digital Sky Survey extreme emission-line galaxy (EELG) template (the ASK15 template from J. Sánchez Almeida et al. 2010). We see that selecting for the reddest objects, (*m*<sub>277</sub> – *m*<sub>444</sub> > 1.5, as indicated by the gray line) biases our sample to *z* > 5 due to the shifting rest-frame wavelengths probed by F277W and F444W. The bimodal redshift distribution of our sample is a result of either Hα (from *z* ~ 5–7) or [O III] λ5007 (*z* ~ 7–9) falling into F444W and contributing to the extremely red color, though the selection for *m*<sub>277</sub> – *m*<sub>444</sub> > 1.5 mitigates contamination from intrinsically blue, strong emission-line objects.

F277W – F444W color versus redshift derived by redshifting the high-S/N NIRSpec/PRISM spectra of two lower-redshift LRDs (J0647_1045 at *z* = 4.532 from M. Killi et al. 2024 and RUBIES-BLAGN-1 at *z* = 3.104 from B. Wang et al. 2024a). Indeed, by selecting for the reddest objects, we bias our sample to *z* > 5, where F277W – F444W covers the rest-frame optical range. Moreover, the somewhat bimodal redshift distribution is a result

of either Hα (from *z* ~ 5–7) or [O III] λ5007 (*z* ~ 7–9) falling into F444W and contributing to the extremely red color. We note that we have further verified the high-redshift nature of these sources by visually inspecting cutouts from deep Subaru/HSC g- and r-band images, as sources with g + r detections are likely *z* < 5 contaminants; we remove two from our sample.

We note that our selection is perhaps better described as a selection for extremely red objects (as in G. Barro et al. 2024), as LRDs are often selected based on the composite blue+red spectral shape (e.g., I. Labbé et al. 2025; D. D. Kocevski et al. 2025; V. Kokorev et al. 2024). However, as the physical origin of the blue UV component is unclear, requiring it in selection may bias the sample toward objects with unobscured host galaxies or unique dust geometries. Because of this, and due to the shallow depth of the F115W + F150W imaging in COSMOS-Web (5σ ~ 27.1–27.6 AB mag), we opt to use only the red F277W–F444W criterion. We also note that other LRD studies (e.g., I. Labbé et al. 2025; V. Kokorev et al. 2024) often require red colors in multiple filter pairs to rule out contamination from extreme emission-line galaxies (EELGs), which may exhibit a very red F277W–F444W color despite a blue continuum. While our selection has the potential to yield such contaminants, we note that by focusing on the reddest objects (~0.5 mag redder than other selections), we largely mitigate this effect; in fact, ~90% of our sample that is covered by the PRIMER survey (N = 37) satisfies the multiband color selection described in I. Labbé et al. (2025). If we instead adopted a less stringent single color criteria, F277W – F444W > 0.7, this fraction drops to 65%.

The simple selection criteria described above yields a sample of 533 sources across the 0.54 sq. degree COSMOS-Web field. Of these, 163 sources are covered with MIRI F770W imaging (32 of which also have F1800W imaging from PRIMER), and 37 are covered with PRIMER NIRCam imaging. The objects covered by PRIMER NIRCam imaging are outlined in blue in Figure 2; while only ~5% of the sample, they span the bulk of the parameter space, though notably do not reach the reddest colors of the most extreme objects.
## 3.2. Removal of Likely Brown Dwarfs

In order to remove contaminating brown dwarf stars in the Milky Way (e.g., D. Langeroodi & J. Hjorth 2023; A. J. Burgasser et al. 2024; K. N. Hainline et al. 2024), we fit each candidate with a grid of low-temperature stellar atmospheric models. We construct a grid of models that spans a large parameter space, including cloudy, chemical equilibrium models (Sonora-Diamondback, *T* ~ 900–2400 K; C. V. Morley et al. 2024), cloud-free models in both chemical equilibrium (Sonora-Bobcat, *T* ~ 200–1300 K; M. S. Marley et al. 2021) and disequilibrium (ElfOwl, *T* ~ 300–1000 K; S. Mukherjee et al. 2024), and low-metallicity models (LOWZ, [M/H] = −1; A. M. Meisner et al. 2021). We explore a range of temperatures *T* ~ 200–2400 K, surface gravities *g* = 100 and 3160, and metallicities [M/H] = −1, −0.5, and 0. We convolve the model SEDs with the HST+JWST filter curves and perform a simple grid-fitting routine, scaling the fluxes of each model to minimize the χ². We adopt the model with the lowest χ² as the best-fitting stellar model, and compare with the best-fit galaxy/quasar SEDs described later in Section 3.4. Note that 104 objects in our sample have a brown dwarf model χ² less than the minimum galaxy/quasar model χ² and are removed. The fraction of sources estimated to be brown dwarfs is ~9% for the MIRI subsample, and ~24% for the NIRCam-only sample. This difference is due to the presence of strong absorption bands in cold brown dwarfs at ~8 µm, allowing MIRI/F770W imaging to break degeneracies between galaxy/QSO and brown dwarf models, particularly given that our NIRCam data have only four bands.

After the brown dwarf removal procedure, our final LRD sample contains 434 sources, 148 of which are covered with MIRI F770W imaging, and 29 of which are covered with PRIMER NIRCam imaging.

## 3.3. Morphological Fitting

We perform 2D image fitting to the JWST/NIRCam imaging to validate the simplified “compactness” selection and determine whether any sources are marginally resolved. We do this using GALSIM, a galaxy image forward-modeling code designed to produce realistic simulated images based on analytical profiles (B. T. P. Rowe et al. 2015). We opt for this approach, rather than the commonly used image fitting tools (such as GALFIT; C. Y. Peng et al. 2002, 2010), in order to conduct Bayesian inference; specifically, we utilize the nested sampling algorithm MULTINEST (F. Feroz & M. P. Hobson 2008; F. Feroz et al. 2009, 2019) to fully explore the parameter space and obtain robust uncertainties on the derived sizes for each object. We fit the F444W imaging for each object to a PSF-convolved 2D Sérsic profile with the effective radius allowed to vary from 0''001 to 0''3, the Sérsic index *n* from 0.5 to 4, and the axis ratio *q* from 0.7–1. Figure 3 shows the measured F444W effective radius versus the F444W magnitude for our sample. The half-width at half-maximum (HWHM) for the F444W PSF is shown in the black dotted line, as an approximate resolution limit for the observations. We can constrain the sizes even below the PSF size, for high-S/N sources, as even slightly extended objects would show some residuals after PSF subtraction. To quantify this effect, we performed our Sérsic profile fitting to PSF stars identified via their position in the half-light radius versus magnitude plane. To avoid including marginally resolved sources in this selection, at *m*<sub>444</sub> > 24, we adopt

<figure><img src="image_6.png" /><figcaption>**Figure 3.** Effective radius vs. F444W magnitude for our sample. The dotted line indicates the half-width at half-maximum (HWHM) for the F444W PSF. The dashed line indicates the effective resolution limit based on the measured sizes of PSF stars. While the majority of our sample is unresolved, a few sources appear marginally resolved, perhaps indicating host galaxy contribution.</figcaption></figure>

the brown dwarf sample (identified as contaminants in Section 3.1) to estimate the limiting size. We then fit a curve to the 90th percentile of the sizes measured in bins of F444W magnitude, deriving effective resolution limit shown in the dashed line in Figure 3.

Nearly all of our candidates are unresolved, which is to be expected, as we are selecting for compact sources based on the F444W aperture photometry. The unresolved nature of the LRDs places an upper limit on their physical sizes, which ranges from $R_{\text{eff}} \lesssim 0''01$ at $m_{444} \approx 22$ to $\lesssim 0''04$ at $m_{444} \approx 27$. At $z=6$, this corresponds to effective radii $\lesssim 100–300$ pc. A few sources are marginally resolved, particularly the brightest subset ($m_{444} \lesssim 24$), perhaps indicating some host galaxy contribution. We keep these marginally resolved sources in the sample, as they satisfy the original compactness criteria and have effective radii $\lesssim 200$ pc.

## 3.4. Spectral Energy Distribution Fitting

We fit both galaxy and QSO models to all objects in our sample. However, we do not intend to use these results to classify objects as either galaxy- or AGN-dominated based on goodness-of-fit—there are, in general, more free parameters in the model than we have data points. Instead, as we are testing the validity of either extreme scenario (the “edge cases”), we intend to examine the results from the model fitting under the assumption of either scenario.

### 3.4.1. QSO Models

We first fit each LRD in the sample to Type I AGN models. In particular, we adopt broad-line AGN templates, consistent with the high fraction of broad-line AGNs confirmed in LRDs observed with JWST spectroscopy (e.g., J. E. Greene et al. 2024; J. Matthee et al. 2024). While existing SED fitting codes such as CIGALE (D. Burgarella et al. 2005; S. Noll et al. 2009; M. Boquien et al. 2019) or PROSPECTOR (J. Leja et al. 2017; B. D. Johnson et al. 2021) do include AGN models, these are primarily designed to decompose host galaxy/AGN components, particularly in the rest-frame mid-IR, and thus are not
ideal for this study. Moreover, these codes do not typically
include strong/broad emission lines from the AGNs, which
may contribute significantly to the observed photometry. We
therefore employ a custom SED fitting code, assuming that the
emission is dominated by AGNs, and employing flexible dust
attenuation and emission-line models.

We model the intrinsic accretion disk emission as a single
power law with a slope $\beta$ ($f_{\lambda} \propto \lambda^{\beta}$). The normalization is set
by the intrinsic UV magnitude $M_{\text{UV,int}}$, prior to any dust
attenuation. We allow $M_{\text{UV,int}}$ to vary from -18 to -27 and $\beta$
to vary from -1.5 to -2.8, both with flat priors.

We employ the M. J. Temple et al. (2021) QSO emission-line
template with emline_type=0, corresponding to the
average emission-line template at z = 2, though we employ a
few adjustments. In particular, we allow the overall emission-
line scaling to vary from 1–2 times the nominal value, which is
calibrated to a reference QSO continuum. This is motivated by
the higher broad-line EWs observed for JWST-selected AGNs
compared to local samples (see, e.g., R. Maiolino et al. 2025).
We also disable Ly$\alpha$ emission due to the opacity of the IGM at
the redshifts relevant to our study (though we note that several
LRDs exhibit Ly$\alpha$ emission, even at z > 7; e.g., V. Kokorev
et al. 2023; L. J. Furtak et al. 2024). Even at z < 7, this choice
should not impact the results significantly, given the relatively
low EWs typical of Ly$\alpha$ emission (\lesssim100 \AA; M. A. R. Kobayashi
et al. 2010) compared to the filter bandwidths (\sim3000 \AA).

We additionally use a flexible dust attenuation prescription to
account for the blue UV slope characteristic of this population.
We adopt the QSO attenuation law from M. J. Temple et al.
(2021), which is similar to the SMC extinction curve (except at
$\lambda \lesssim 1700$ \AA, where it is significantly shallower). We add an
additional parameter, a “scattering” fraction, or a fraction of the
intrinsic spectrum that escapes unattenuated. We allow this
scattering fraction to vary from $10^{-5}$–$10^{-1}$ with a log-uniform
prior. The effect of this is similar to employing an even grayer
attenuation law, but adds a bit more flexibility and aids in the
interpretation of the blue slope as coming from scattering
around the AGN torus (e.g., I. Labbé et al. 2025) or leakage
through holes in the obscuring medium, perhaps created by
outflows (e.g., A. Noboriguchi et al. 2023). We additionally
include a parameter, $\eta_{\text{NLR}}$, representing the scaling of the dust
attenuation in the narrow-line region (NLR). While the BLR
and accretion disk are subject to the nominal $A_{\text{V}}$, the more
spatially extended NLR is attenuated by $\eta_{\text{NLR}}A_{\text{V}}$. We adopt a
fixed $\eta_{\text{NLR}} = 0.3$, consistent with the LRD Balmer decrement
measurements from M. Killi et al. (2024).

We fit these QSO models using the MULTINEST nested
sampling algorithm (F. Feroz & M. P. Hobson 2008; F. Feroz
et al. 2009, 2019). As a test, we apply our SED fitting code to
the reported JWST/NIRCam photometry for the two confirmed
$z > 7$ broad-line AGNs reported in L. J. Furtak et al. (2024) and
V. Kokorev et al. (2023). We recover the spectroscopic redshifts
within $1\sigma$, and our estimate of the bolometric luminosity (from
the continuum) is consistent with the estimate derived from the
H$\beta$ line for the source in V. Kokorev et al. (2023). We note that
we overestimate the bolometric luminosity for the source in
L. J. Furtak et al. (2023) by a factor of $\sim 5$, though this is
consistent with the continuum-based $L_{\text{bol}}$ estimate from I. Labbé
et al. (2025).

3.4.2. Galaxy Models

To test the other “edge case,” that the population is
dominated by compact star-forming galaxies, we fit each
object to a galaxy SED model. Here we assume that all of the
light originates from the galaxy, including the blue/UV and
red/optical components. We use BAGPIPES, a Bayesian SED
fitting code (A. C. Carnall et al. 2018) designed to fit galaxy
photometry and spectra. We use the BPASS library of stellar
SED models (J. J. Eldridge et al. 2017) and a nonparametric
star formation history (SFH) model. The SFH is parameterized
by the $\Delta \log(\text{SFR})$ in adjacent time bins; we adopt the
continuity prior (described in J. Leja et al. 2019), i.e., the prior
on $\Delta \log(\text{SFR})$ is a t-distribution with $\sigma = 0.3$ and $\nu = 2$
degrees of freedom. We adopt five age bins for the SFH, with
the first three at fixed ages from 0–10 Myr, 10–50 Myr, and
50–200 Myr and two more logarithmically spaced from
200 Myr to $z = 20$.

We adopt log-uniform priors on the stellar mass (from $10^6$
to $10^{13} M_{\odot}$) and metallicity (from $10^{-3}$ to 1.5 $Z_{\odot}$). Nebular
emission is implemented via CLOUDY, specifically the updated
grids presented in N. Byler et al. (2017), with log $U_{\text{ion}}$ allowed
to vary from -4 to -1. We adopt an SMC dust law with $A_{\text{V}}$
allowed to vary from 0-6; to be consistent with our QSO
modeling, we modify the dust attenuation prescription to
include a similar “scattering fraction” parameter, which we
allow to vary with a log-uniform prior from $10^{-5}$ to $10^{-1}$. We
note, however, that in the galaxy case, this is better interpreted
as representing “leakage” through holes in the ISM dust
screen, as is found in some lower-redshift DSFGs (e.g.,
C. M. Casey et al. 2014b).

3.5. Individual Objects

We highlight a few individual objects that stand out from our
sample. Figure 4 shows the cutouts and SEDs for six
particularly bright LRDs ($m_{444} \sim 22-24$). In each panel, the
best-fit QSO model is shown in black, and the best-fit BAGPIPES
model is shown in blue. For sources that fall in the PRIMER
coverage, we plot the PRIMER photometry as well. For the
brightest LRDs in our sample, we derive bolometric luminos-
ities $10^{46-47.5} \text{ erg s}^{-1}$ from the QSO modeling, or stellar masses
$10^{10-12}$ from the BAGPIPES modeling. This is due to their steep,
red optical continuum slopes, anchored by bright F444W/
F770W magnitudes, implying significant dust obscuration.

Several bright LRDs in our sample also fall into the
PRIMER MIRI coverage, which includes F1800W. We
highlight four of these objects in Figure 5. The only object
in our sample detected in F1800W is COS-105829, which is
also the brightest LRD in the F1800W coverage ($m_{770} \sim 22.7$)
but is not in the PRIMER NIRCam coverage. No other source
is detected, despite several (pictured in Figure 5) being
similarly bright in F444W and F770W. The MIRI limits imply
flat SED (in $f_{\lambda}$) between observed-frame 7.7–18 $\mu$m, or rest-
frame $\sim 1-3 \mu$m at the redshifts of these objects. This may
indicate marginal contribution from a hot dust torus, which we
return to in Section 6.2.

We provide the SED-derived properties of our sample in
Table 1.

3.6. Spectroscopic Confirmation of COS-756434

We identify one source in our sample, COS-756434, with
public JWST/NIRSpec observations. COS-756434 was
<figure><img src="image_7.png" /><figcaption>**Figure 4.** Cutouts and SEDs for six particularly bright ($m_{444} \lesssim 24$) LRDs. We show 1.5 square cutouts in HST/ACS F814W, JWST/NIRCam F115W, F150W, F277W, and F444W, and JWST/MIRI F770W (where available). Measured photometry is shown in red, or $2\sigma$ upper limits for nondetections; the best-fitting QSO model is shown in black, *bagpipes* in blue, and brown dwarf in light gray. The inset panels show the redshift probability distribution with the maximum likelihood value marked with a dashed line. The complete figure set (434 images) is available. Copies are also available at https://github.com/hollisakins/akins24_cw.
(The complete figure set (434 images) is available in the online article.)</figcaption></figure>

observed with ~6 hr PRISM spectroscopy as part of a DDT program (#6585, P.I. D. Coulter) targeting high-redshift supernovae. We reduce the NIRSpec data using the standard JWST pipeline (version 1.14.0); the automatically extracted 1D spectrum is shown in Figure 6. The spectrum exhibits strong [O III] $\lambda\lambda4959, 5007 + H\beta$ and $H\alpha$ emission,

confirming the redshift at $z_{\text{spec}} = 6.9993$. This is quite consistent with the photometric redshift of $z_{\text{phot}} \sim 7.05_{-0.05}^{+0.09}$, which is similar for both the galaxy and QSO models. We fit the spectrum with a simple model including narrow+broad $H\beta$ and $H\alpha$ emission, narrow emission for other detected lines, and a piecewise power-law continuum. We detect the $H\gamma$ and
<table><caption>**Table 1**

Photometric Measurements and Derived Physical Properties for the COSMOS-Web LRDs</caption><thead><tr><th rowspan="2">ID</th><th rowspan="2">R.A.<br>(J2000)</th><th rowspan="2">Decl.<br>(J2000)</th><th rowspan="2">F277W<br>(AB mag)</th><th rowspan="2">F444W<br>(AB mag)</th><th rowspan="2">F770W<br>(AB mag)</th><th colspan="3">QSO Fitting</th><th colspan="3">BAGPIPES</th><th rowspan="2">R<sub>eff,444</sub><br>(mas)</th></tr><tr><th>z<sub>qso</sub></th><th>log L<sub>bol</sub></th><th>A<sub>V</sub></th><th>z<sub>gal</sub></th><th>log M<sub>x</sub></th><th>A<sub>V</sub></th></tr></thead><tbody><tr><td>1491</td><td>09h59m22s58</td><td>+02d07m43s17</td><td>26.45</td><td>24.77</td><td>...</td><td>6.2<sup>+1.2</sup><sub>-0.5</sub></td><td>46.2<sup>+0.4</sup><sub>-0.3</sub></td><td>3.4<sup>+0.7</sup><sub>-0.5</sub></td><td>6.1<sup>+1.2</sup><sub>-0.7</sub></td><td>10.7<sup>+0.3</sup><sub>-0.3</sub></td><td>3.3<sup>+0.8</sup><sub>-0.7</sub></td><td>19.3<sup>+2.8</sup><sub>-3.6</sub></td></tr><tr><td>3962</td><td>09h59m08s80</td><td>+02d10m48s23</td><td>26.24</td><td>24.66</td><td>...</td><td>7.3<sup>+1.9</sup><sub>-1.8</sub></td><td>46.2<sup>+0.3</sup><sub>-0.4</sub></td><td>2.2<sup>+0.6</sup><sub>-0.3</sub></td><td>7.0<sup>+3.1</sup><sub>-2.3</sub></td><td>10.4<sup>+0.3</sup><sub>-0.2</sub></td><td>2.0<sup>+1.0</sup><sub>-0.5</sub></td><td>37.1<sup>+1.5</sup><sub>-2.1</sub></td></tr><tr><td>4056</td><td>09h59m27s39</td><td>+02d09m10s80</td><td>27.15</td><td>25.37</td><td>24.98</td><td>6.0<sup>+1.0</sup><sub>-0.5</sub></td><td>45.8<sup>+0.2</sup><sub>-0.2</sub></td><td>2.9<sup>+0.5</sup><sub>-0.5</sub></td><td>6.2<sup>+2.2</sup><sub>-0.7</sub></td><td>9.4<sup>+0.3</sup><sub>-0.3</sub></td><td>2.2<sup>+0.5</sup><sub>-0.5</sub></td><td>4.0<sup>+3.6</sup><sub>-2.0</sub></td></tr><tr><td>8203</td><td>09h59m18s51</td><td>+02d13m25s82</td><td>26.96</td><td>25.20</td><td>26.07</td><td>8.3<sup>+0.4</sup><sub>-0.4</sub></td><td>46.2<sup>+0.2</sup><sub>-0.3</sub></td><td>5.1<sup>+0.6</sup><sub>-1.9</sub></td><td>5.3<sup>+0.2</sup><sub>-0.2</sub></td><td>8.7<sup>+0.1</sup><sub>-0.1</sub></td><td>1.7<sup>+0.3</sup><sub>-0.2</sub></td><td>28.4<sup>+1.8</sup><sub>-2.4</sub></td></tr><tr><td>9430</td><td>09h59m13s39</td><td>+02d14m38s54</td><td>27.44</td><td>25.84</td><td>25.24</td><td>7.3<sup>+1.0</sup><sub>-1.2</sub></td><td>45.9<sup>+0.3</sup><sub>-0.3</sub></td><td>3.1<sup>+0.8</sup><sub>-0.5</sub></td><td>7.8<sup>+0.6</sup><sub>-0.6</sub></td><td>9.8<sup>+0.3</sup><sub>-0.3</sub></td><td>1.9<sup>+0.5</sup><sub>-0.4</sub></td><td>15.7<sup>+3.2</sup><sub>-5.0</sub></td></tr><tr><td>9680</td><td>09h59m18s44</td><td>+02d14m20s41</td><td>27.51</td><td>25.27</td><td>24.88</td><td>7.5<sup>+0.7</sup><sub>-1.4</sub></td><td>46.3<sup>+0.3</sup><sub>-0.3</sub></td><td>3.8<sup>+1.4</sup><sub>-0.6</sub></td><td>5.8<sup>+1.6</sup><sub>-0.4</sub></td><td>9.3<sup>+0.2</sup><sub>-0.2</sub></td><td>3.0<sup>+0.4</sup><sub>-0.6</sub></td><td>11.9<sup>+4.2</sup><sub>-3.8</sub></td></tr><tr><td>10023</td><td>09h59m11s55</td><td>+02d15m09s29</td><td>27.69</td><td>26.04</td><td>26.01</td><td>6.0<sup>+1.0</sup><sub>-0.4</sub></td><td>45.3<sup>+0.2</sup><sub>-0.2</sub></td><td>2.4<sup>+0.5</sup><sub>-0.4</sub></td><td>6.0<sup>+2.3</sup><sub>-0.6</sub></td><td>8.9<sup>+0.3</sup><sub>-0.2</sub></td><td>1.9<sup>+0.5</sup><sub>-0.5</sub></td><td>34.4<sup>+4.5</sup><sub>-4.9</sub></td></tr><tr><td>10511</td><td>09h59m17s57</td><td>+02d14m53s62</td><td>26.53</td><td>25.03</td><td>25.30</td><td>5.9<sup>+0.4</sup><sub>-0.3</sub></td><td>45.6<sup>+0.1</sup><sub>-0.1</sub></td><td>1.9<sup>+0.3</sup><sub>-0.3</sub></td><td>5.5<sup>+0.6</sup><sub>-0.3</sub></td><td>8.9<sup>+0.1</sup><sub>-0.1</sub></td><td>1.7<sup>+0.2</sup><sub>-0.3</sub></td><td>18.2<sup>+1.7</sup><sub>-1.4</sub></td></tr><tr><td>11737</td><td>09h59m26s60</td><td>+02d14m49s10</td><td>27.38</td><td>25.23</td><td>...</td><td>7.8<sup>+1.5</sup><sub>-1.8</sub></td><td>46.5<sup>+0.5</sup><sub>-0.4</sub></td><td>3.6<sup>+1.1</sup><sub>-0.8</sub></td><td>7.5<sup>+1.7</sup><sub>-2.3</sub></td><td>10.7<sup>+0.7</sup><sub>-0.4</sub></td><td>3.3<sup>+1.1</sup><sub>-0.8</sub></td><td>29.1<sup>+1.7</sup><sub>-1.8</sub></td></tr><tr><td>13618</td><td>09h59m18s95</td><td>+02d16m51s10</td><td>28.10</td><td>26.34</td><td>25.91</td><td>6.0<sup>+0.6</sup><sub>-0.5</sub></td><td>45.4<sup>+0.2</sup><sub>-0.2</sub></td><td>2.8<sup>+0.6</sup><sub>-0.5</sub></td><td>6.2<sup>+2.1</sup><sub>-0.8</sub></td><td>9.1<sup>+0.5</sup><sub>-0.3</sub></td><td>2.1<sup>+0.4</sup><sub>-0.6</sub></td><td>28.2<sup>+5.7</sup><sub>-6.9</sub></td></tr><tr><td>14599</td><td>09h59m23s86</td><td>+02d16m57s03</td><td>27.16</td><td>25.55</td><td>25.59</td><td>5.9<sup>+0.4</sup><sub>-0.4</sub></td><td>45.5<sup>+0.2</sup><sub>-0.2</sub></td><td>2.3<sup>+0.4</sup><sub>-0.4</sub></td><td>5.6<sup>+2.1</sup><sub>-0.4</sub></td><td>8.9<sup>+0.3</sup><sub>-0.2</sub></td><td>1.9<sup>+0.3</sup><sub>-0.3</sub></td><td>19.9<sup>+3.0</sup><sub>-3.7</sub></td></tr><tr><td>15495</td><td>09h59m39s19</td><td>+02d16m04s16</td><td>27.39</td><td>25.18</td><td>25.20</td><td>8.1<sup>+0.5</sup><sub>-0.7</sub></td><td>45.9<sup>+0.2</sup><sub>-0.2</sub></td><td>2.4<sup>+0.7</sup><sub>-0.3</sub></td><td>5.5<sup>+0.5</sup><sub>-0.3</sub></td><td>9.1<sup>+0.2</sup><sub>-0.1</sub></td><td>2.6<sup>+0.2</sup><sub>-0.2</sub></td><td>16.5<sup>+4.2</sup><sub>-4.7</sub></td></tr><tr><td>15654</td><td>09h59m39s29</td><td>+02d16m08s81</td><td>26.48</td><td>24.72</td><td>24.11</td><td>5.7<sup>+0.4</sup><sub>-0.3</sub></td><td>46.2<sup>+0.2</sup><sub>-0.2</sub></td><td>3.6<sup>+0.5</sup><sub>-0.5</sub></td><td>5.6<sup>+0.6</sup><sub>-0.3</sub></td><td>9.8<sup>+0.2</sup><sub>-0.2</sub></td><td>2.8<sup>+0.3</sup><sub>-0.3</sub></td><td>24.4<sup>+1.9</sup><sub>-1.8</sub></td></tr><tr><td>15961</td><td>09h59m15s84</td><td>+02d18m26s22</td><td>26.71</td><td>25.08</td><td>...</td><td>6.2<sup>+0.9</sup><sub>-0.5</sub></td><td>46.3<sup>+0.4</sup><sub>-0.3</sub></td><td>4.2<sup>+1.1</sup><sub>-0.9</sub></td><td>6.4<sup>+1.2</sup><sub>-0.6</sub></td><td>10.9<sup>+0.4</sup><sub>-0.4</sub></td><td>4.2<sup>+1.1</sup><sub>-1.0</sub></td><td>17.2<sup>+3.4</sup><sub>-4.2</sub></td></tr><tr><td>16108</td><td>09h59m17s01</td><td>+02d18m26s10</td><td>27.99</td><td>25.77</td><td>25.25</td><td>6.0<sup>+1.3</sup><sub>-0.4</sub></td><td>45.8<sup>+0.2</sup><sub>-0.2</sub></td><td>3.6<sup>+0.6</sup><sub>-0.6</sub></td><td>5.6<sup>+0.5</sup><sub>-0.4</sub></td><td>9.2<sup>+0.2</sup><sub>-0.2</sub></td><td>3.2<sup>+0.4</sup><sub>-0.5</sub></td><td>7.6<sup>+5.5</sup><sub>-4.4</sub></td></tr><tr><td>16692</td><td>09h59m04s68</td><td>+02d08m20s30</td><td>28.43</td><td>26.75</td><td>...</td><td>6.6<sup>+2.0</sup><sub>-1.3</sub></td><td>45.5<sup>+0.4</sup><sub>-0.4</sub></td><td>3.1<sup>+1.7</sup><sub>-0.9</sub></td><td>6.5<sup>+2.1</sup><sub>-1.5</sub></td><td>9.7<sup>+0.5</sup><sub>-0.4</sub></td><td>2.8<sup>+1.6</sup><sub>-1.0</sub></td><td>28.5<sup>+18.5</sup><sub>-9.7</sub></td></tr><tr><td>17632</td><td>09h59m04s72</td><td>+02d08m56s02</td><td>29.97</td><td>26.73</td><td>...</td><td>7.7<sup>+1.1</sup><sub>-1.5</sub></td><td>46.0<sup>+0.4</sup><sub>-0.4</sub></td><td>4.3<sup>+0.9</sup><sub>-1.0</sub></td><td>6.9<sup>+1.8</sup><sub>-1.5</sub></td><td>10.3<sup>+0.6</sup><sub>-0.5</sub></td><td>4.2<sup>+1.1</sup><sub>-1.2</sub></td><td>25.1<sup>+6.6</sup><sub>-8.6</sub></td></tr><tr><td>18065</td><td>09h59m05s10</td><td>+02d09m07s29</td><td>27.54</td><td>25.95</td><td>...</td><td>5.9<sup>+1.9</sup><sub>-0.5</sub></td><td>45.8<sup>+0.3</sup><sub>-0.4</sub></td><td>3.9<sup>+1.3</sup><sub>-1.4</sub></td><td>5.2<sup>+1.9</sup><sub>-0.7</sub></td><td>10.0<sup>+0.4</sup><sub>-0.4</sub></td><td>4.1<sup>+1.2</sup><sub>-1.5</sub></td><td>26.9<sup>+4.4</sup><sub>-4.0</sub></td></tr><tr><td>19068</td><td>09h59m07s68</td><td>+02d09m24s36</td><td>28.69</td><td>27.18</td><td>...</td><td>6.5<sup>+2.1</sup><sub>-1.4</sub></td><td>45.2<sup>+0.3</sup><sub>-0.4</sub></td><td>2.8<sup>+1.9</sup><sub>-0.8</sub></td><td>6.7<sup>+2.0</sup><sub>-1.6</sub></td><td>9.4<sup>+0.4</sup><sub>-0.3</sub></td><td>2.2<sup>+1.2</sup><sub>-0.7</sub></td><td>9.5<sup>+8.2</sup><sub>-5.7</sub></td></tr><tr><td>26156</td><td>09h59m32s88</td><td>+02d11m00s35</td><td>28.39</td><td>26.28</td><td>...</td><td>7.3<sup>+1.8</sup><sub>-1.5</sub></td><td>46.0<sup>+0.6</sup><sub>-0.5</sub></td><td>3.8<sup>+1.3</sup><sub>-1.0</sub></td><td>7.0<sup>+1.9</sup><sub>-1.8</sub></td><td>10.3<sup>+0.7</sup><sub>-0.5</sub></td><td>3.7<sup>+1.2</sup><sub>-1.1</sub></td><td>27.0<sup>+5.7</sup><sub>-6.5</sub></td></tr><tr><td>27062</td><td>09h59m17s69</td><td>+02d12m52s84</td><td>28.82</td><td>27.28</td><td>...</td><td>6.1<sup>+1.8</sup><sub>-0.9</sub></td><td>45.3<sup>+0.4</sup><sub>-0.4</sub></td><td>3.7<sup>+1.6</sup><sub>-1.3</sub></td><td>5.7<sup>+2.2</sup><sub>-1.1</sub></td><td>9.4<sup>+0.4</sup><sub>-0.4</sub></td><td>3.3<sup>+1.7</sup><sub>-1.4</sub></td><td>5.8<sup>+5.9</sup><sub>-3.1</sub></td></tr><tr><td>27100</td><td>09h59m14s24</td><td>+02d13m13s22</td><td>28.59</td><td>26.42</td><td>...</td><td>6.9<sup>+1.2</sup><sub>-1.0</sub></td><td>45.8<sup>+0.4</sup><sub>-0.4</sub></td><td>3.7<sup>+1.3</sup><sub>-1.0</sub></td><td>6.7<sup>+1.7</sup><sub>-1.6</sub></td><td>10.2<sup>+0.6</sup><sub>-0.5</sub></td><td>3.5<sup>+1.2</sup><sub>-1.0</sub></td><td>23.3<sup>+6.6</sup><sub>-6.5</sub></td></tr><tr><td>29753</td><td>09h59m19s49</td><td>+02d14m10s35</td><td>28.35</td><td>26.48</td><td>25.68</td><td>6.0<sup>+1.6</sup><sub>-0.6</sub></td><td>45.6<sup>+0.2</sup><sub>-0.3</sub></td><td>3.6<sup>+0.9</sup><sub>-1.0</sub></td><td>6.8<sup>+1.5</sup><sub>-1.3</sub></td><td>9.6<sup>+0.3</sup><sub>-0.3</sub></td><td>2.1<sup>+0.7</sup><sub>-0.5</sub></td><td>2.8<sup>+1.8</sup><sub>-1.4</sub></td></tr><tr><td>36933</td><td>09h59m19s29</td><td>+02d17m12s99</td><td>28.59</td><td>26.97</td><td>26.32</td><td>6.4<sup>+1.6</sup><sub>-0.9</sub></td><td>45.3<sup>+0.3</sup><sub>-0.3</sub></td><td>3.1<sup>+1.2</sup><sub>-0.9</sub></td><td>7.2<sup>+1.3</sup><sub>-1.5</sub></td><td>9.3<sup>+0.2</sup><sub>-0.3</sub></td><td>1.8<sup>+0.6</sup><sub>-0.4</sub></td><td>28.7<sup>+7.2</sup><sub>-8.3</sub></td></tr><tr><td>37490</td><td>09h59m30s92</td><td>+02d16m24s49</td><td>28.52</td><td>26.86</td><td>25.83</td><td>6.5<sup>+1.8</sup><sub>-1.2</sub></td><td>45.6<sup>+0.3</sup><sub>-0.3</sub></td><td>3.6<sup>+1.6</sup><sub>-1.2</sub></td><td>6.4<sup>+1.9</sup><sub>-1.4</sub></td><td>9.5<sup>+0.3</sup><sub>-0.3</sub></td><td>2.2<sup>+0.8</sup><sub>-0.6</sub></td><td>29.9<sup>+6.6</sup><sub>-8.2</sub></td></tr><tr><td>39192</td><td>09h59m13s42</td><td>+02d18m47s20</td><td>28.52</td><td>26.65</td><td>...</td><td>6.7<sup>+2.0</sup><sub>-1.1</sub></td><td>45.7<sup>+0.4</sup><sub>-0.4</sub></td><td>3.3<sup>+1.5</sup><sub>-0.8</sub></td><td>6.4<sup>+2.0</sup><sub>-1.5</sub></td><td>9.9<sup>+0.6</sup><sub>-0.4</sub></td><td>3.3<sup>+1.4</sup><sub>-1.1</sub></td><td>74.2<sup>+25.6</sup><sub>-22.0</sub></td></tr><tr><td>42832</td><td>09h59m50s78</td><td>+02d05m43s96</td><td>28.41</td><td>26.41</td><td>...</td><td>7.6<sup>+1.7</sup><sub>-1.5</sub></td><td>46.0<sup>+0.5</sup><sub>-0.4</sub></td><td>3.7<sup>+1.2</sup><sub>-0.9</sub></td><td>7.9<sup>+1.4</sup><sub>-2.2</sub></td><td>10.4<sup>+1.0</sup><sub>-0.6</sub></td><td>3.6<sup>+1.2</sup><sub>-1.1</sub></td><td>3.3<sup>+3.3</sup><sub>-1.6</sub></td></tr><tr><td>42963</td><td>10h00m01s24</td><td>+02d04m50s94</td><td>28.16</td><td>26.27</td><td>...</td><td>8.1<sup>+1.3</sup><sub>-1.9</sub></td><td>46.1<sup>+0.6</sup><sub>-0.5</sub></td><td>3.7<sup>+1.3</sup><sub>-0.9</sub></td><td>8.1<sup>+1.0</sup><sub>-2.3</sub></td><td>10.5<sup>+0.9</sup><sub>-0.6</sub></td><td>3.3<sup>+1.4</sup><sub>-1.0</sub></td><td>3.4<sup>+3.4</sup><sub>-1.6</sub></td></tr><tr><td>44171</td><td>09h59m37s77</td><td>+02d07m38s65</td><td>27.47</td><td>25.75</td><td>...</td><td>7.2<sup>+2.0</sup><sub>-1.6</sub></td><td>45.9<sup>+0.4</sup><sub>-0.4</sub></td><td>2.6<sup>+0.9</sup><sub>-0.5</sub></td><td>6.9<sup>+1.9</sup><sub>-2.0</sub></td><td>10.1<sup>+0.4</sup><sub>-0.3</sub></td><td>2.4<sup>+1.0</sup><sub>-0.6</sub></td><td>8.3<sup>+6.3</sup><sub>-4.5</sub></td></tr><tr><td>46758</td><td>09h59m54s88</td><td>+02d07m34s62</td><td>25.16</td><td>23.51</td><td>23.62</td><td>5.7<sup>+0.2</sup><sub>-0.2</sub></td><td>46.3<sup>+0.1</sup><sub>-0.1</sub></td><td>2.5<sup>+0.2</sup><sub>-0.2</sub></td><td>5.2<sup>+0.2</sup><sub>-0.2</sub></td><td>9.6<sup>+0.1</sup><sub>-0.1</sub></td><td>2.0<sup>+0.1</sup><sub>-0.1</sub></td><td>4.8<sup>+0.4</sup><sub>-0.0</sub></td></tr><tr><td>47467</td><td>09h59m41s90</td><td>+02d09m07s89</td><td>26.53</td><td>24.92</td><td>24.12</td><td>5.4<sup>+0.3</sup><sub>-0.2</sub></td><td>46.2<sup>+0.2</sup><sub>-0.2</sub></td><td>4.3<sup>+0.6</sup><sub>-0.6</sub></td><td>5.4<sup>+0.4</sup><sub>-0.3</sub></td><td>9.9<sup>+0.2</sup><sub>-0.2</sub></td><td>3.0<sup>+0.4</sup><sub>-0.4</sub></td><td>23.9<sup>+3.6</sup><sub>-3.8</sub></td></tr><tr><td>47745</td><td>09h59m58s60</td><td>+02d07m46s94</td><td>27.27</td><td>25.70</td><td>25.48</td><td>5.9<sup>+0.5</sup><sub>-0.4</sub></td><td>45.5<sup>+0.2</sup><sub>-0.2</sub></td><td>2.7<sup>+0.5</sup><sub>-0.5</sub></td><td>5.8<sup>+2.3</sup><sub>-0.5</sub></td><td>9.1<sup>+0.4</sup><sub>-0.3</sub></td><td>2.2<sup>+0.5</sup><sub>-0.7</sub></td><td>38.9<sup>+3.4</sup><sub>-5.1</sub></td></tr><tr><td>48256</td><td>10h00m03s90</td><td>+02d07m34s23</td><td>27.14</td><td>24.71</td><td>24.17</td><td>6.3<sup>+1.8</sup><sub>-0.4</sub></td><td>46.3<sup>+0.1</sup><sub>-0.2</sub></td><td>3.5<sup>+0.5</sup><sub>-0.7</sub></td><td>5.7<sup>+0.7</sup><sub>-0.4</sub></td><td>9.6<sup>+0.2</sup><sub>-0.2</sub></td><td>3.2<sup>+0.3</sup><sub>-0.4</sub></td><td>14.5<sup>+5.1</sup><sub>-3.1</sub></td></tr></tbody></table>

Note. Table 1 is available in its entirety in machine-readable format. A copy is also available at https://github.com/hollisakins/akins24_cw. A portion is shown here for guidance regarding its form and content.

(This table is available in its entirety in machine-readable form in the online article.)

[O III] λ4363 lines, [Ne III] λλ3869, 3967 and even the high-ionization line [Ne IV] λ2423, consistent with the AGN interpretation. We measure a broad $H\alpha/H\beta$ ratio of $\gtrsim 10$, which implies a dust attenuation to the BLR of $A_{V,BLR} \sim 2.9$, assuming an intrinsic ratio of 3.06 (X. Dong et al. 2008). We measure a broad-line FWHM = $2920_{-50}^{+40}$ km s$^{-1}$, corresponding to a black hole mass $\log M_{BH} \sim 7.8 \pm 0.5$ using the calibration from J. E. Greene & L. C. Ho (2005). Adopting a bolometric correction from $H\alpha$ of 130 (G. T. Richards et al. 2006), we get a bolometric luminosity of $\log L_{bol,H\alpha}/\text{erg s}^{-1} = 45.2 \pm 0.4$ and an Eddington ratio of $\sim 0.2$. We note that the bolometric luminosity inferred from $H\alpha$ is significantly lower than that inferred from the continuum ($\sim 46.5$). This is due to the different bolometric corrections assumed and the different dust correction employed; for the continuum, we derive $A_V \sim 5$. Though we do not discuss the spectrum of this object in detail, we report the properties measured from the spectrum in Table 2 and adopt its spectroscopic redshift in the remainder of the paper.

## 4. Two Interpretations of LRDs

We now consider the two alternative interpretations of LRDs as either reddened quasars/dusty AGNs or compact star-forming galaxies. As a reminder, we approach this as a “thought experiment”; while the LRDs will realistically have some contribution from both AGN and stars, examining these two extremes allows us to bracket the range of possibilities and examine the physical implications of either scenario, in particular the resulting mass/luminosity functions.

### 4.1. Dusty AGNs/Reddened Quasars

First, we discuss the interpretation of the LRDs as a population of reddened AGNs, as has been posited (e.g., I. Labbé et al. 2025; J. Matthee et al. 2024). We characterize the LRDs in terms of their bolometric luminosity, i.e., the total AGN luminosity after correcting for dust attenuation; we consider the bolometric luminosity rather than the UV luminosity as these sources are quite obscured. We compute
<figure><img src="image_8.png" /><figcaption>**Figure 5.** Same as Figure 4, but for four bright LRDs with MIRI F1800W coverage from PRIMER. Two sources (above) are only in COSMOS-Web NIRCam coverage, but fall within the PRIMER MIRI coverage; two sources (below) have both PRIMER NIRCam and MIRI coverage. In all cases, the MIRI F1800W imaging yields marginal or nondetections, consistent with a flat SED in $f_{\nu}$ from rest-frame ~1–3 µm.</figcaption></figure>

the bolometric luminosity from the intrinsic model SED (i.e., before any dust attenuation), using the monochromatic luminosity at 3000 Å and a bolometric correction of 5.15 (G. T. Richards et al. 2006).

Figure 7 shows the COSMOS-Web LRDs in the AGN bolometric luminosity versus redshift plane. Literature AGNs with JWST spectroscopy are shown in purple (reddened AGNs) and blue (broad-line AGNs). We also show a compilation of bright quasars from the literature (X. Fan et al. 2023). The COSMOS-Web LRDs span the range between the literature JWST samples and the bright quasars, with a handful reaching similar bolometric luminosities ~$10^{47}$ erg s$^{-1}$. These luminosities are generally much higher than other LRD samples, due to the wide/shallow nature of COSMOS-Web, but we note that similarly luminous LRDs have been observed at $z \sim 3–5$ (e.g., UNCOVER-45924 at $z = 4.66$; J. E. Greene et al. 2024; RUBIES-BLAGN-1 at $z = 3.1$; B. Wang et al. 2024a). However, the high luminosities and abundance of these objects are surprising given the relative scarcity of luminous quasars.

To quantify the excess of luminous AGNs in our sample, we compute the bolometric luminosity function. We note that here, and in our estimates of the stellar mass function in Section 4.2, we compute the volume of the survey as the differential comoving volume scaled to the survey area of

$0.54 \text{ deg}^2$ and integrated over the redshift bin. In order to capture the large uncertainties on the redshifts and luminosities of our objects, we marginalize over the joint posterior distribution of $L_{\text{bol}}$ and redshift for each source; that is, individual objects can fractionally span multiple redshift and luminosity bins. We additionally marginalize over the bin size, computing the luminosity function in bins centered at $\log L_{\text{bol}} \sim 43, 43.2, \dots, 48$ with bin widths randomly drawn from 0.3–1.0 dex. This avoids biases imparted by the choice of bin size.

We additionally employ a simple completeness correction based on our photometric catalog and source selection procedure. In short, we inject 10,000 mock point sources into the NIRCam data, with realistic colors uniformly spanning the range of colors observed for the full sample. We then repeat our cataloging and selection procedures, as we have on the real data, including the color and size criteria. We estimate the completeness as a function of $m_{444}$, sampling the mock sources according to their $m_{277} - m_{444}$ colors to ensure a color distribution representative of our full sample. The completeness is estimated as ~80% at $m_{444} = 26$ and falls to ~20% for the faintest objects in the sample, at $m_{444} = 27$. We translate this to be a function of $L_{\text{bol}}$ using the correlation between $m_{444}$ and the median $L_{\text{bol}}$ derived from our SED fitting for each source. This relationship has some scatter, so we account for
<figure><img src="image_9.png" /><figcaption>**Figure 6.** JWST/NIRSpec PRISM spectrum of COS-756434. The source is clearly detected in continuum and exhibits strong [O III] + Hβ and Hα emission, confirming the redshift at z = 6.9993 ± 0.0001, consistent with the photometric redshift zphot ~ 7.05±0.09. Broad components are visible in both the Hβ and Hα lines, with an FWHM of 2750 ± 40 km s⁻¹, a clear signature of AGN activity. The top panels highlight the broad+narrow-line decomposition for Hβ and Hα, as well as the deblending of [O III]λ4363 and Hγ. The source also exhibits several high-ionization emission lines, including [Ne IV]λ2423 and [Ne III]λ3869, consistent with the AGN interpretation.</figcaption></figure>

<table><caption>**Table 2**
Spectroscopic Measurements For COS-756434</caption><thead><tr><th>Property</th><th>Units</th><th>Value</th></tr></thead><tbody><tr><td>z<sub>spec</sub></td><td>...</td><td>6.9993 ± 0.0001</td></tr><tr><td>R.A.</td><td>hms</td><td>10:00:25.6561</td></tr><tr><td>Decl.</td><td>dms</td><td>+02:21:36.165</td></tr><tr><td>f<sub>λ,5100</sub></td><td>10<sup>-21</sup> erg s<sup>-1</sup> cm<sup>-2</sup> Å<sup>-1</sup></td><td>3.20<sup>+0.04</sup><sub>-0.03</sub></td></tr><tr><td>A<sub>V,BLR</sub></td><td>AB mag</td><td>2.9<sup>+0.2</sup><sub>-0.2</sub></td></tr><tr><td>log M<sub>BH</sub></td><td>M<sub>☉</sub></td><td>7.8 ± 0.5</td></tr><tr><td>log L<sub>bol,Hα</sub></td><td>erg s<sup>-1</sup></td><td>45.2 ± 0.4</td></tr><tr><td>λ<sub>Edd</sub></td><td>...</td><td>0.19<sup>+0.30</sup><sub>-0.11</sub></td></tr><tr><td>FWHM<sub>narrow</sub></td><td>km s<sup>-1</sup></td><td>494<sup>+5</sup><sub>-11</sub></td></tr><tr><td>FWHM<sub>broad</sub></td><td>km s<sup>-1</sup></td><td>2920<sup>+40</sup><sub>-50</sub></td></tr><tr><td>F<sub>[O III]λ4363</sub></td><td>10<sup>-20</sup> erg s<sup>-1</sup> cm<sup>-2</sup></td><td>7.07<sup>+0.63</sup><sub>-0.67</sub></td></tr><tr><td>F<sub>Hβ,narrow</sub></td><td>10<sup>-19</sup> erg s<sup>-1</sup> cm<sup>-2</sup></td><td>1.18<sup>+0.13</sup><sub>-0.13</sub></td></tr><tr><td>F<sub>Hβ,broad</sub></td><td>10<sup>-19</sup> erg s<sup>-1</sup> cm<sup>-2</sup></td><td>0.23<sup>+0.02</sup><sub>-0.02</sub></td></tr><tr><td>F<sub>[O III]λ4959</sub></td><td>10<sup>-19</sup> erg s<sup>-1</sup> cm<sup>-2</sup></td><td>2.77<sup>+0.07</sup><sub>-0.07</sub></td></tr><tr><td>F<sub>[O III]λ5007</sub></td><td>10<sup>-19</sup> erg s<sup>-1</sup> cm<sup>-2</sup></td><td>7.98<sup>+0.08</sup><sub>-0.08</sub></td></tr><tr><td>F<sub>Hα,narrow</sub></td><td>10<sup>-18</sup> erg s<sup>-1</sup> cm<sup>-2</sup></td><td>1.11<sup>+0.02</sup><sub>-0.03</sub></td></tr><tr><td>F<sub>Hα,broad</sub></td><td>10<sup>-18</sup> erg s<sup>-1</sup> cm<sup>-2</sup></td><td>2.44<sup>+0.03</sup><sub>-0.03</sub></td></tr></tbody></table>

the uncertainty on the completeness from the same correlation using the 16th and 84th percentile L<sub>bol</sub>; this is added in quadrature with the Poisson uncertainty from the luminosity function.

Figure 8 shows the AGN bolometric luminosity function inferred from our photometric candidate sample at z ~ 5–7 (top) and z ~ 7–9 (bottom). Our sample is shown in red, with the solid line corresponding to the MIRI subsample. We also show lower limits on the bolometric LF from LRDs selected in spectroscopic surveys (UNCOVER; J. E. Greene et al. 2024; and FRESCO; J. Matthee et al. 2024) and estimates from other photometric surveys (V. Kokorev et al. 2024). Our results are consistent with spectroscopic samples, and suggest an overall

excess of red AGNs relative to the quasar bolometric luminosity function measured from rest-UV-selected quasars (shown in gray; X. Shen et al. 2020). While the faint-end slope of the quasar bolometric luminosity function remains uncertain, our results suggest that the knee of the LF could be dominated by these dust-reddened AGNs, even up to L<sub>bol</sub> ~ 10<sup>47</sup> erg s<sup>-1</sup>. In particular, we find a factor of ~100 overabundance of the LRDs relative to UV-bright quasars, at fixed L<sub>bol</sub>. This could also be explained if we were overestimating the bolometric luminosities of the LRDs, though we note that this would also require a factor of ~100 in luminosity to be consistent with the quasar luminosity function (QLF). Our estimated bolometric luminosity function is tabulated in 0.5 dex bins of luminosity in Table 3.

How does the abundance of AGNs at z ~ 5 compare to the population at lower redshift? Figure 9 shows the evolution of the black hole accretion rate density (BHAD) with redshift. Results from X-ray AGN surveys (J. Aird et al. 2015) are shown in black, extrapolated above z ~ 5. We also show the SFRD (scaled down by 1500; P. Madau & M. Dickinson 2014) as black hole galaxy coevolution scenarios would suggest that the BHAD should follow a similar evolution to the SFRD. Results from JWST/MIRI observations of z ~ 1–5 obscured AGNs in CEERS are shown in blue (G. Yang et al. 2023). We compute the BHAD by integrating the bolometric luminosity function and assuming a radiative efficiency factor ϵ = 0.1. As Figure 9 shows, if the LRDs are universally AGNs, our results imply a nonevolving black hole accretion density of ~10<sup>-4</sup> M<sub>☉</sub> yr<sup>-1</sup> Mpc<sup>-3</sup> from z ~ 1 to z ~ 9. This is an order of magnitude above the scaled SFRD, and several orders of magnitude above the X-ray extrapolations.

## 4.2. Compact SFGs

Next we consider the interpretation of the LRDs as compact dust-obscured star-forming galaxies, as has been suggested in
<figure><img src="image_10.png" /><figcaption>**Figure 7.** Bolometric luminosity vs. redshift. AGNs from the literature with JWST spectroscopy are shown in purple (reddened AGNs; L. J. Furtak et al. 2024; J. E. Greene et al. 2024; V. Kokorev et al. 2023; J. Matthee et al. 2024) and blue (typical broad-line AGNs; Y. Harikane et al. 2023; R. L. Larson et al. 2023; Á. Bogdán et al. 2024; R. Maiolino et al. 2023, 2024a). Our sample from COSMOS-Web spans the range of luminosities between the literature JWST AGNs and the UV-bright quasars discovered in wide-field ground-based surveys (X. Fan et al. 2023).</figcaption></figure>

the literature (e.g., H. B. Akins et al. 2023; I. Labbé et al. 2023; C. C. Williams et al. 2023; P. G. Pérez-González et al. 2024). Under this interpretation, the continuum emission would originate primarily from starlight, with the red color either coming from an old stellar population with a strong Balmer break or high EW emission lines combined with strong dust attenuation. The lack of mid-IR detections for these sources may further support their star-forming nature (C. C. Williams et al. 2023; P. G. Pérez-González et al. 2024), and the relative abundance is more consistent with galaxies than quasars.

Figure 10 shows the derived stellar mass versus redshift for our LRD sample. We indicate the region of parameter space that would be disfavored or disallowed in a ΛCDM framework in dark gray, corresponding to the stellar mass of the most massive halo in a given area assuming the cosmic baryon fraction of $f_b = 0.158$ and stellar baryon fraction $\epsilon = 1$. Here we compute the halo mass function using the `hmf` python package (S. G. Murray et al. 2013) assuming an SMT fitting function (R. K. Sheth et al. 2001). We plot the relevant threshold for the full sky, the COSMOS-Web area ($0.5 \text{ deg}^2$), and the MIRI area ($0.17 \text{ deg}^2$) in successively lighter shades of gray. We note that a more reasonable upper limit on the observed stellar mass would use $\epsilon \approx 0.2$, the maximum inferred from the peak of the stellar mass to halo mass relation across a range of redshifts (R. Mandelbaum et al. 2006; F. Shankar et al. 2006; C. Conroy & R. H. Wechsler 2009; P. S. Behroozi et al. 2010; P. Behroozi et al. 2019; M. Shuntov et al. 2022).

A few of our LRDs exceed the maximum thresholds expected/allowed in ΛCDM, particularly at $z \gtrsim 7$. This may be seen as reason to favor the AGN interpretation: if they are dominated by stellar light, they are simply too massive. However, we note that the subsample with MIRI coverage does not violate these thresholds; the stellar masses derived for the MIRI subsample are generally lower than those for the NIRCam-only sample. To test this further, we perform a series of *bagpipes* runs on the MIRI sample, both including and omitting the F770W data point. We find systematic offsets of

<figure><img src="image_11.png" /><figcaption>**Figure 8.** AGN bolometric luminosity function at $z \sim 5-7$ (top panel) and $z \sim 7-9$ (bottom panel). Our results are shown in red, for the MIRI subsample (solid) and the full sample (dashed). The bolometric luminosity function from J. E. Greene et al. (2024) is shown in turquoise, for which we adopt upper limits given the incomplete nature of NIRSpec follow-up spectroscopy. LF measurements from J. Matthee et al. (2024), from wide-field slitless spectroscopy, are shown in purple. Since J. Matthee et al. (2024) did not apply a dust correction, we also indicate in dashed lines the impact of correcting their $H\alpha$ luminosities with $A_V = 3$ mag (the median value inferred for our sample). Photometric estimates from V. Kokorev et al. (2024), derived from other JWST imaging surveys, are shown in dark blue. The $z \sim 6$ quasar luminosity function from X. Shen et al. (2020) is shown in gray. If the LRDs are all AGNs, our results imply a factor of $\sim 100$ overabundance of luminous AGNs relative to pre-JWST estimates from UV-bright quasars.</figcaption></figure>

$\sim 1-2$ dex, toward larger masses, when not including the MIRI data. Similar results have been found in other surveys with MIRI imaging (e.g., CEERS; C. Papovich et al. 2023; SMILES; C. C. Williams et al. 2023). In our case, this effect is largely due to the impact of strong emission lines boosting the photometry in the F444W bands. With the additional data point on the red end, the modeling tends to favor younger stellar populations with stronger emission lines and lower masses—i.e., a compact starburst. We explored using the MIRI subsample to construct more appropriate SFH priors for fitting the NIRCam-only sample, but found that the resulting posteriors were almost unchanged from the input priors. With relatively limited broadband coverage, the MIRI imaging is necessary to achieve a robust constraint for the stellar mass by anchoring the red end of the SED and reducing the degeneracy with the SFH. We therefore conclude that the LRDs do not
<figure><img src="image_12.png" /><figcaption>**Figure 9.** The black hole accretion rate density as a function of redshift. Our results are shown in red, for our full sample (light red, smaller points) and our MIRI subsample (dark red, larger points). Results from X-ray AGN surveys (J. Aird et al. 2015) are shown in black, including extrapolation at $z > 5$. Results from JWST/MIRI are shown in green (G. Yang et al. 2023). If the red dots are universally AGNs, our results imply a nonevolving black hole accretion density of ~0.5–1 × 10⁻⁴ M☉ yr⁻¹ Mpc⁻³ from $z \sim 1$ to $z \sim 9$.</figcaption></figure>

<table><caption>**Table 3**
Binned AGN Bolometric Luminosity Function</caption><thead><tr><th rowspan="2">Redshift</th><th rowspan="2">log L<sub>bol</sub><br>(erg s<sup>-1</sup>)</th><th colspan="2">log φ [# dex<sup>-1</sup> Mpc<sup>-3</sup>]</th></tr><tr><th>Full Sample</th><th>MIRI Subsample</th></tr></thead><tbody><tr><td>5–7</td><td>45</td><td>-3.99<sup>+1.31</sup><sub>-0.81</sub></td><td>-3.89<sup>+1.33</sup><sub>-0.84</sub></td></tr><tr><td>5–7</td><td>45.5</td><td>-4.39<sup>+0.65</sup><sub>-0.34</sub></td><td>-4.24<sup>+0.64</sup><sub>-0.35</sub></td></tr><tr><td>5–7</td><td>46</td><td>-4.54<sup>+0.31</sup><sub>-0.18</sub></td><td>-4.50<sup>+0.32</sup><sub>-0.18</sub></td></tr><tr><td>5–7</td><td>46.5</td><td>-4.80<sup>+0.22</sup><sub>-0.14</sub></td><td>-4.84<sup>+0.23</sup><sub>-0.16</sub></td></tr><tr><td>5–7</td><td>47</td><td>-5.32<sup>+0.19</sup><sub>-0.16</sub></td><td>-5.39<sup>+0.25</sup><sub>-0.28</sub></td></tr><tr><td>7–9</td><td>45.5</td><td>-4.19<sup>+1.30</sup><sub>-0.59</sub></td><td>-4.17<sup>+1.33</sup><sub>-0.65</sub></td></tr><tr><td>7–9</td><td>46</td><td>-4.42<sup>+0.58</sup><sub>-0.28</sub></td><td>-4.42<sup>+0.58</sup><sub>-0.28</sub></td></tr><tr><td>7–9</td><td>46.5</td><td>-4.67<sup>+0.26</sup><sub>-0.17</sub></td><td>-4.73<sup>+0.27</sup><sub>-0.20</sub></td></tr><tr><td>7–9</td><td>47</td><td>-5.32<sup>+0.29</sup><sub>-0.35</sub></td><td>-5.32<sup>+0.29</sup><sub>-0.35</sub></td></tr></tbody></table>

individually violate ΛCDM limits, but care must be taken to derive accurate stellar masses, particularly accounting for the contribution of strong emission lines (whether from recent SF or AGN activity) to the photometry.

However, even without individual objects violating ΛCDM, the ubiquity of these sources suggests a high number density of massive galaxies. Figure 11 shows the stellar mass function (SMF) derived from our LRD sample. We show the pre-JWST estimates of the SMF from CANDELS (M. Stefanon et al. 2021) and COSMOS (J. R. Weaver et al. 2023) in blue and green, respectively. As discussed previously, our full sample shows a strong excess relative to pre-JWST estimates, and with several candidates in the region prohibited by ΛCDM. However, the subsample with MIRI coverage does not show as strong of an excess, and in fact shows a bright-end slope more consistent with the steep slope derived in previous studies. This suggests that these objects could be dominated by star formation. Importantly, though, this implies that the massive galaxy population at $z \gtrsim 5$ is dominated by these compact starbursts, which has important implications for our understanding of early stellar mass growth.

<figure><img src="image_13.png" /><figcaption>**Figure 10.** Stellar mass vs. redshift from galaxy SED fitting with bagpipes. The dashed lines indicate the maximum stellar mass we would expect to find in a given volume based on the halo mass function (assuming a global star formation efficiency $\epsilon = 1$, or $\epsilon = 0.2$ for a more realistic assumption). We plot the stellar masses inferred for LRDs in JADES from C. C. Williams et al. (2023), as well as the three ultramassive objects identified in M. Xiao et al. (2023).</figcaption></figure>

A stronger constraint can be placed on the stellar content of these objects based on their pointlike morphology. There exists a maximum stellar mass surface density observed in dense stellar systems (P. F. Hopkins et al. 2010), which remains consistent across $z \sim 0–3$ and over ~9 dex in stellar mass. In other words, local and $z \lesssim 3$ stellar systems show similar maximum stellar densities ~10¹¹ M☉ kpc⁻² in their cores. Figure 12 shows the stellar mass profiles derived for our sample, in comparison to the average profiles for various local and high-redshift populations from P. F. Hopkins et al. (2010). Here we include only the MIRI subsample, for which we can derive reliable stellar masses. We find a median central stellar density of log $\Sigma_{\star} \sim 11.6$, higher than—but broadly consistent with—that observed in the lower-redshift Universe. Approximately half of the sample, however, has stellar mass profiles significantly in excess of this limit. On the one hand, these central densities may be reduced over time due to N-body relaxation, the timescale for which can be $\lesssim 1$ Gyr for particularly compact stellar systems (P. F. Hopkins et al. 2010). On the other hand, this may imply that the stellar masses are simply overestimated, requiring significant AGN contribution to the continuum to reconcile the derived central densities.

## 5. Multiwavelength Stacking

The COSMOS field is rich in multiwavelength coverage from the X-ray, MIR, FIR/submillimeter, and radio. As described in Section 2, we inspect cutouts around each source in Chandra X-ray imaging, Spitzer/MIPS 24 µm, SCUBA-2 and ALMA millimeter/submillimeter imaging, and VLA/MeerKAT radio data. No source in our sample is individually detected in any of these data; this is somewhat surprising, given the large sample size and inclusion of several remarkably luminous objects in the sample. In particular, under the AGN interpretation, objects with $L_{bol} \gtrsim 10^{46}$ erg s at $z \gtrsim 4$ are regularly detected in the X-ray (J. Aird et al. 2015),
<figure><img src="image_14.png" /><figcaption>**Figure 11.** Stellar mass functions at $z \sim 5-7$ (top panel) and $z \sim 7-9$ (bottom panel). As in Figure 8, our sample is shown in red, for the MIRI subsample (solid) and the full sample (dashed). The blue and green lines show the pre-JWST estimates of the SMF from M. Stefanon et al. (2021) and J. R. Weaver et al. (2023). The gray shaded region shows the parameter space prohibited by ΛCDM, scaling the halo mass function by the cosmic baryon fraction $f_b$ and a maximal “efficiency” $\epsilon = 1$. The gray dashed line shows a more realistic efficiency $\epsilon = 0.2$. While the SMF for the full sample violates the limits imposed by ΛCDM, particularly at $z > 7$, the impact of MIRI on the stellar masses brings the SMF into agreement with literature estimates.</figcaption></figure>

mid-infrared (from the dusty torus), and radio (e.g., R. Endsley et al. 2023a; E. Lambrides et al. 2023).

To push the multiwavelength constraints deeper, we stack the data for the entire sample. Even without individual detections, if these objects exhibit ubiquitous, faint flux, it would show up in stacking. We perform a simple median stack of the cutouts in each map. We note that we explored different methods of stacking, including rescaling each source to a consistent F444W flux before stacking, but found that the resulting stacked photometry is quite consistent with the simple median. We note that for Chandra we compute the *sum*, rather than the median, as the median is always 0 given the low X-ray counts. We additionally perform stacking on Spitzer/MIPS 70 µm and Herschel imaging from PACS (100 and 160 µm; D. Lutz et al. 2011) and SPIRE (250, 350, and 500 µm; S. J. Oliver et al. 2012); while SPIRE imaging is severely confusion-limited, stacking on maps with a mode equal to 0 removes flux boosting from adjacent sources (see also K. E. K. Coppin et al. 2015). Due to the widely varying PSF size of the various data sets, we stack relatively large cutouts (ranging from 5" for HST/JWST to 10' for Herschel/SCUBA data).

The stacked cutouts are shown in the top panels of Figure 13. No flux is detected in our stacks in any band aside from HST/JWST. To quantify the flux limits implied by the

<figure><img src="image_15.png" /><figcaption>**Figure 12.** Median stellar mass surface density profile for the COSMOS-Web LRDs, compared to the compilation of dense stellar systems in P. F. Hopkins et al. (2010). Individual profiles are shown in the thin, light-red lines. The different colors/symbols correspond to the different classes of objects compiled by P. F. Hopkins et al. (2010), ranging from local globular clusters/nuclear disks to massive ellipticals at $z \gtrsim 2$; all exhibit similar central densities, roughly consistent with the median LRD in our sample.</figcaption></figure>

nondetections in the various multiwavelength data sets, we show in the lower panel of Figure 13 the median (observed-frame) panchromatic SED for the COSMOS-Web LRDs. For HST/JWST data, we measure photometry directly from the stacked cutouts; note that we find marginal flux in F1800W (2.9σ), but formally take this as an upper limit. For the other data sets, we derive the upper limits for each band in the following manner. For the ALMA data, which comes from the CHAMPS (A. L. Faisst et al. 2025, in preparation) and MORA surveys (C. M. Casey et al. 2021; A. S. Long et al. 2025), and SCUBA-2, we add in quadrature the rms at the position of each source, and divide by N. For all other maps, which have relatively uniform depth, we adopt the reported depths, scaled down by $\sqrt{N}$. For Chandra, we use the limiting depths reported in F. Civano et al. (2016) for the 0.5–2 and 2–7 keV bands. For Spitzer/MIPS, Herschel/PACS, and SPIRE, we use the depths reported in D. B. Sanders et al. (2007), D. Lutz et al. (2011), and H. T. Nguyen et al. (2010; confusion limits), respectively. Stacked photometry and upper limits are provided in Table 4.

Do the stacked limits provide useful constraints on the physical properties of the LRDs? To answer this, we show with the dark-red line in Figure 13 the maximal SED allowed by the limits. This SED model is tuned to fall just below the upper limits at each wavelength, allowing us to quantitatively assess how surprising the nondetections are. The UV/optical/NIR SED is constructed from our QSO model (see Section 3.4.1) to match the photometry, with $A_V = 3$ and $f_{scat} = 1\%$ at $z = 6$. The intrinsic (unattenuated) SED is shown in light blue, with a UV magnitude of $M_{UV} = -21.8$ and a 3000 Å continuum luminosity of $L_{3000} = 5.5 \times 10^{44}$ erg s. Note that these properties are very similar to the average SED-derived properties for the sample as a whole. While we do not show the equivalent galaxy model, we note that it is similar to the QSO model in the UV-optical, but with somewhat different emission-line EWs.

For the X-ray SED, we adopt a photon index of $\Gamma = 1.8$ and an upper energy cut at 300 keV (following X-CIGALE;
<figure><img src="image_16.png" /><figcaption>**Figure 13.** Median-stacked panchromatic SED for the COSMOS-Web LRDs. Top panel: stacked images in all HST/JWST bands available, as well as Chandra X-ray, Spitzer/MIPS 24 µm, JCMT/SCUBA-2 850 µm, ALMA 1.2 and 2.0 mm imaging, and MeerKAT/VLA 1.3 and 3GHz imaging. Each stack is annotated with the number of objects contributing to the stack. For HST/JWST, we show in light red the apertures used to extract photometry directly from the stacks. For the remaining bands, we show a 5" square to guide the eye given the varying resolution of the images. Bottom panel: full panchromatic SED for the median COSMOS-Web LRD. Photometry measured from stacks (or $5\sigma$ upper limits from the nondetections) is shown in black. We plot the maximal allowed SED model in red. The faint blue lines in the X-ray and UV/optical show the intrinsic (i.e., unattenuated) SEDs for the corona and the accretion disk. We plot two alternative X-ray SEDs consistent with the data, a Compton-thin model with an anomalously low $\alpha_{OX}$ (solid) and a Compton-thick model with a normal $\alpha_{OX}$ given the optical luminosity (dashed). In the far-IR (FIR), we show several single-temperature blackbodies at different normalizations, ranging from cold ISM dust to the hottest possible dust, at the sublimation temperature. The maximal SED model includes a total dust luminosity of $2 \times 10^{12} L_{\odot}$ with a Gaussian temperature distribution $\sim 200 \pm 75$ K. Finally, in the radio, we adopt a slope $\alpha = -1.5$ consistent with radio-loud AGNs (R. Endsley et al. 2022; E. Lambrides et al. 2023). For reference, we also plot the best-fit model SEDs for a $z = 5.85$ DSFG (MAMBO-9; H. B. Akins et al. 2025b) and a $z = 6.85$ obscured AGN (COS-87259; R. Endsley et al. 2022, 2023a).</figcaption></figure>

G. Yang et al. 2020). The normalization is set by the (unattenuated) optical SED, using the conversion parameter $\alpha_{OX} \equiv -0.3838 \log(L_{\nu,2500}/L_{2\,\text{keV}})$. We then attenuate the SED assuming a column density $N_{\text{H}}$, using the photoelectric absorption cross sections provided in R. Morrison & D. McCammon (1983). We show with the darker, solid line the X-ray SED assuming Compton-thin absorption $\log N_{\text{H}}/\text{cm}^{-2} = 23$. This column density is consistent with

the moderate dust attenuation ($A_V \approx 3$) based on empirical relations between dust attenuation and gas absorption in red quasars (E. Glikman et al. 2024). With this column density, the X-ray limits require $\alpha_{OX} < -2$; by contrast, we expect $\alpha_{OX} \approx -1.45$ ($\pm 0.1$) from the $\alpha_{OX}-L_{2500}$ relation (D. W. Just et al. 2007). An alternative model adopts $\alpha_{OX} = -1.45$ but a much higher column density $\log N_{\text{H}}/\text{cm}^{-2} > 24.5$. In this Compton-thick model, the X-ray SED falls just below the
<table><caption>**Table 4**
Observed-frame Stacking Results</caption><thead><tr><th>Band</th><th>Wavelength</th><th>N</th><th>Units</th><th>F<sub>ν</sub></th></tr></thead><tbody><tr><td>Chandra 2–10 keV<sup>a</sup></td><td>0.28 nm</td><td>434</td><td>erg s<sup>-1</sup> cm<sup>-2</sup></td><td>&lt;7.2 &times; 10<sup>-17</sup></td></tr><tr><td>Chandra 0.5–2 keV<sup>a</sup></td><td>1.24 nm</td><td>434</td><td>erg s<sup>-1</sup> cm<sup>-2</sup></td><td>&lt;1.1 &times; 10<sup>-17</sup></td></tr><tr><td>HST/ACS F606W</td><td>0.60 &mu;m</td><td>29</td><td>nJy</td><td>&lt; 3.85</td></tr><tr><td>HST/ACS F814W</td><td>0.81 &mu;m</td><td>434</td><td>nJy</td><td>4.11 &plusmn; 0.52</td></tr><tr><td>JWST/NIRCam F090W</td><td>0.90 &mu;m</td><td>29</td><td>nJy</td><td>7.37 &plusmn; 1.22</td></tr><tr><td>JWST/NIRCam F115W</td><td>1.16 &mu;m</td><td>434</td><td>nJy</td><td>15.76 &plusmn; 0.62</td></tr><tr><td>JWST/NIRCam F150W</td><td>1.50 &mu;m</td><td>434</td><td>nJy</td><td>16.46 &plusmn; 0.51</td></tr><tr><td>JWST/NIRCam F200W</td><td>2.00 &mu;m</td><td>29</td><td>nJy</td><td>17.66 &plusmn; 0.77</td></tr><tr><td>JWST/NIRCam F277W</td><td>2.77 &mu;m</td><td>434</td><td>nJy</td><td>30.51 &plusmn; 0.23</td></tr><tr><td>JWST/NIRCam F356W</td><td>3.58 &mu;m</td><td>29</td><td>nJy</td><td>83.30 &plusmn; 0.56</td></tr><tr><td>JWST/NIRCam F410M</td><td>4.08 &mu;m</td><td>29</td><td>nJy</td><td>113.56 &plusmn; 1.03</td></tr><tr><td>JWST/NIRCam F444W</td><td>4.42 &mu;m</td><td>434</td><td>nJy</td><td>173.00 &plusmn; 0.33</td></tr><tr><td>JWST/MIRI F770W</td><td>7.66 &mu;m</td><td>148</td><td>nJy</td><td>277.99 &plusmn; 2.94</td></tr><tr><td>JWST/MIRI F1800W</td><td>18.00 &mu;m</td><td>24</td><td>nJy</td><td>(435.2 &plusmn; 150.9)</td></tr><tr><td>Spitzer/MIPS</td><td>24 &mu;m</td><td>434</td><td>&mu;Jy</td><td>&lt;3.43</td></tr><tr><td>Spitzer/MIPS</td><td>70 &mu;m</td><td>434</td><td>mJy</td><td>&lt;0.36</td></tr><tr><td>Herschel/PACS</td><td>100 &mu;m</td><td>434</td><td>mJy</td><td>&lt;0.40</td></tr><tr><td>Herschel/PACS</td><td>160 &mu;m</td><td>434</td><td>mJy</td><td>&lt;0.82</td></tr><tr><td>Herschel/SPIRE</td><td>250 &mu;m</td><td>434</td><td>mJy</td><td>&lt;0.65</td></tr><tr><td>Herschel/SPIRE</td><td>350 &mu;m</td><td>434</td><td>mJy</td><td>&lt;0.86</td></tr><tr><td>Herschel/SPIRE</td><td>500 &mu;m</td><td>434</td><td>mJy</td><td>&lt;1.24</td></tr><tr><td>SCUBA-2</td><td>850 &mu;m</td><td>434</td><td>&mu;Jy</td><td>&lt;239</td></tr><tr><td>ALMA</td><td>1.2 mm</td><td>30</td><td>&mu;Jy</td><td>&lt;157</td></tr><tr><td>ALMA</td><td>2.0 mm</td><td>128</td><td>&mu;Jy</td><td>&lt;35.4</td></tr><tr><td>VLA 3 GHz</td><td>10 cm</td><td>434</td><td>uJy</td><td>&lt;0.56</td></tr><tr><td>MeerKAT 1.28 GHz</td><td>23 cm</td><td>434</td><td>uJy</td><td>&lt;1.80</td></tr></tbody></table>

**Note.**

<sup>a</sup> For Chandra, we quote the absolute flux limit (rather than flux density) to be consistent with X-ray surveys. Uncertainties are quoted as 1σ; for nondetections, we quote the 5σ upper limits.

limits for the shallower hard-band, and is entirely attenuated in the soft band. Several other authors have reported X-ray measurements for LRDs that imply lower masses/luminosities than the broad lines in the optical (e.g., T. T. Ananna et al. 2024; R. Maiolino et al. 2025; M. Yue et al. 2024), which may indicate a fundamental difference in the nuclear structure in these objects.

Turning to the FIR, the stacked limits provide a constraint on the dust SED of the LRDs. We plot four single-temperature modified blackbody models, from cold ISM dust ($T = 30$ K) to the hottest dust in the AGN torus, at the sublimation temperature ($T = 1500$ K). The ALMA/SCUBA constraints limit the cold dust component to $\lesssim 10^{11} L_{\odot}$, and the MIRI/MIPS constraints limit the hottest dust components to $\lesssim 10^{10} L_{\odot}$. We note that while the MIRI/F1800W limit is only based on ~5% of the sample, that subset is quite representative of the entire sample in terms of observed colors/magnitudes and derived redshifts/luminosities. The shallow Herschel limits, however, provide little constraints on warm dust ~100–200 K. We include in the dark-red model SED a dust component with a Gaussian distribution of temperatures, with a mean of 200 K and a standard deviation of 75 K. We do not impose any energy balance with the rest-frame optical, instead adopting a luminosity of $2 \times 10^{12} L_{\odot}$, which falls just below the stacked 5σ limits from Herschel. With the available limits, in the maximal SED model, the vast majority of the bolometric luminosity could be emitted in the far-IR and still result in nondetections. We note that the bolometric luminosity inferred from $L_{3000}$, $L_{bol} \approx 7.4 \times 10^{11} L_{\odot}$ (using a bolometric correction

of 5.15; G. T. Richards et al. 2006) is still less than the maximal luminosity allowed in the FIR, though only by a factor of ~3— the current FIR limits are consistent with a standard bolometric correction for LRDs.

Finally, in the radio, we adopt a power-law slope of $\alpha = -1.5$, consistent with radio-loud AGNs at high redshift (R. Endsley et al. 2022; E. Lambrides et al. 2023). The normalization is set by the luminosity density at 1.4 GHz, $L_{\nu, 1.4 GHz} = 5.2 \times 10^{23} W Hz^{-1}$. This is quite a bit lower than we would expect for radio-loud AGNs; in terms of the ratio of the 1.4 GHz luminosity to the optical B-band luminosity, $R_{1.4}^* = L_{\nu, 1.4 GHz}/L_{\nu, 4400} = 30$ defines the boundary between radio-loud and radio-quiet AGNs (M. Cirasuolo et al. 2003, 2006; R. Wang et al. 2007). Our radio limits constrain $R_{1.4}^* < 10$, at the 5σ level, suggesting that the average LRD is inconsistent with a radio-loud AGN.

**6. Discussion**

Our results do not necessarily favor one interpretation over the other for the origin of the LRDs, and they present challenges to our understanding of early galaxy/SMBH growth in either case. Under the AGN interpretation, our estimate of the bolometric luminosity function is consistent with the lower limits provided by recent spectroscopic observations, with a ~2 dex excess relative to blue quasars across $log L_{bol} \sim 45–47$. Under the galaxy interpretation, our stellar mass function estimate is consistent with $\Lambda$CDM limits, but implies that the LRDs would dominate the high-mass end of the SMF, and have central stellar mass densities
significantly greater than the maximum observed at lower redshift. In reality, neither interpretation is likely 100% true; both galaxy and AGN components will contribute to the SED. Moreover, the mechanisms that trigger compact nuclear starbursts (i.e., those in local LIRGs or URLIRGs) are thought to be the same mechanisms that trigger quasars; specifically, gas-rich major mergers or disk instabilities (e.g., P. F. Hopkins et al. 2008). Distinguishing between these two possibilities will inevitably require more data, both to examine subpopulations and decompose individual SEDs.

## 6.1. What Dominates the Continuum?

The major remaining uncertainty surrounding the LRDs is whether the red optical continuum emission is dominated by stellar light or the AGN accretion disk. This directly impacts the measured stellar masses and AGN bolometric luminosities, and, to a lesser degree, the black hole masses. On the one hand, the broad-line EWs measured for LRDs with JWST spectroscopy have been found to be largely consistent with local calibrations, i.e., the continuum is consistent with being dominated by the accretion disk (J. E. Greene et al. 2024). However, it is possible that the broad lines are unusually strong relative to the accretion disk continuum in these objects. This could be due to different AGN physics (such as a higher BLR covering factor; e.g., R. Maiolino et al. 2025), differential attenuation between a spatially extended BLR and the accretion disk (as has been suggested for red quasars and DOGs; e.g., F. Hamann et al. 2017; A. Noboriguchi et al. 2022), or kinematically broadened lines in a multiphase ISM, even without an AGN (e.g., N. Roy et al. 2025, in preparation). While the likelihood of these scenarios is unclear, and will need to be examined in more depth in future work, each would imply that the rest-optical continuum emission is not necessarily dominated by the accretion disk, resulting in lower bolometric luminosity estimates. Lower AGN luminosities would be more consistent with the mid-IR limits from MIRI imaging surveys (C. C. Williams et al. 2023; P. G. Pérez-González et al. 2024) and X-ray limits from Chandra (T. T. Ananna et al. 2024; M. Yue et al. 2024). This may also bring the luminosity function into closer agreement with the quasar luminosity function, though, as we note in Section 4.1, it would require a factor of ~100 reduction in order to match the bolometric luminosity function from UV-selected quasars. The bolometric LF could also come down if the bolometric correction were found to be lower than the nominal value, e.g., due to the lack of hot dust in this population. We note, though, that the current FIR data are not sufficient to constrain this; our stack gives an upper limit on the 3000 Å bolometric correction of ≲15, entirely consistent with the nominal value of 5.15 (G. T. Richards et al. 2006).

While reducing the AGN contribution to the continuum may alleviate the tension with AGN models and the quasar LF, if the rest-optical continuum is instead dominated by stellar light, it implies a significant contribution of these objects to the stellar mass function. As we show in Section 4.2, the LRDs could dominate the stellar mass function at the high-mass end, particularly at $z > 7$. This is true even with the MIRI data generally preferring solutions in which a recent, young starburst dominates the mass, which effectively represent a lower limit on the mass. Recent JWST/NIRSpec results have identified LRDs with clear Balmer breaks, indicating the presence of old stellar populations alongside broad emission

lines (B. Wang et al. 2024a); if ubiquitous in LRDs, this would raise their contribution to the stellar mass function. However, even with high-S/N spectroscopy from 1–5 µm, the relative contribution from a Balmer break as opposed to a reddened power-law continuum is degenerate, with derived stellar masses ranging from $10^9–10^{11} M_\odot$ depending on the breakdown of the two components (B. Wang et al. 2024a).

While we leave the effort to conduct a comprehensive decomposition of the LRDs into AGN/galaxy components to future work, our approach here—considering the LRDs as either entirely stars or entirely AGNs—allows us to comment on the implications even in realistic mixture scenarios. In particular, in the galaxy scenario, we find that the median central stellar mass surface density exceeds the maximum observed in the local Universe by a factor ~3, though the dispersion is large, with some objects reaching ~100×. This effectively sets a cap on the contribution of stars to the total continuum: roughly 30% for a typical LRD in our sample. The remaining ~70% of the continuum luminosity must be AGNs. We can correct our luminosity/mass functions for the contribution of the other component, though crucially, these corrections are not uniform. That is, correcting for the AGN fraction would shift the stellar mass function to lower masses by ~0.5 dex, bringing it significantly below limits from ΛCDM. By contrast, the correction to the AGN bolometric luminosity function would only be ~0.2 dex. This is similar to the findings of B. Wang et al. (2024a) and J. F. W. Baggen et al. (2024); adopting their fiducial decomposition between stellar/AGN components, the central stellar mass density falls just at the maximum observed in the local Universe, and the AGN still dominates the continuum at optical wavelengths.

Future efforts to characterize the LRD luminosity/mass functions, accounting for realistic decomposition of galaxy/AGN components, will certainly require better data. Deep spectroscopy covering the Balmer break will be key to characterize the stellar contribution (e.g., B. Wang et al. 2024a), and photoionization modeling may be able to reveal distinct galaxy/AGN components in individual objects (e.g., H. B. Akins et al. 2025a). MIRI imaging will likely be useful to break degeneracies in SED fits and identify MIR emission from hot dust (e.g., G. C. K. Leung et al. 2024). Our results emphasize the need to better characterize the physical nature of LRDs, to better understand their role in the galaxy evolution and early SMBH assembly.

## 6.2. What Is the Origin of the Dust Obscuration?

Whether the LRDs represent star-forming galaxies or AGNs, their dust-reddening provides a view into the physics of AGN/ISM dust at high-z. Despite SED-derived attenuation $A_V \gtrsim 2$, the LRDs entirely lack submillimeter or millimeter detections with SCUBA, ALMA, or otherwise, even in our deep stacks of hundreds of objects. Their submillimeter faintness has been interpreted as evidence in favor of an AGN interpretation, as the ALMA limits are inconsistent with energy-balance models in which the attenuated starlight is reprocessed in the submillimeter (I. Labbé et al. 2025). However, in a given bandpass, submillimeter observations are extremely sensitive to the temperature ($S_\nu \propto T^{-3.5}$ for fixed $L_{IR}$), such that the difference between $T = 25$ K and $T = 75$ K represents ~100 times fainter emission (see C. M. Casey et al. 2014a). The typical assumption of a cold temperature ($T \sim 25–35$ K) may not apply in these systems; in fact, hotter
dust is expected at high redshift, as the increased CMB temperature, $T_{CMB} = 2.73\,\text{K} \times (1+z)$, sets an absolute floor on the dust temperature. Moreover, a simple application of the Stefan-Boltzmann law ($L_{IR} = 4\pi R_e^2 \sigma T^4$) would predict higher dust temperatures for a more compact IR-emitting region (see, e.g., A. D. Burnham et al. 2021). As we show in Figure 13, even a substantial luminosity of warm dust ($T \sim 150\,\text{K}$) would be completely missed at the current limits of our samples, but would be expected if the obscuration originates on small scales. This warm dust could be heated by the AGN, either directly or by successive absorption/re-emission (J. McKinney et al. 2021), or from intense star formation, similar to what is seen in local ULIRGS (e.g., Arp 220; C. D. Wilson et al. 2014).

At the same time, the lack of mid-IR detections in LRDs appears at odds with the AGN interpretation. The one object in our sample individually detected in MIRI/F1800W (COS-105829) exhibits a flat SED from ~7 to 18 µm, as does the median stack. Similar results have been reported for LRDs covered by the SMILES and JADES programs, with deep MIRI imaging in multiple bands (C. C. Williams et al. 2023; P. G. Pérez-González et al. 2024). As discussed in Section 6.1, this may indicate minimal contribution from hot dust in the torus, which in turn may imply that the AGN contribution is overestimated. However, an alternative explanation is that significant torus dust is not common in this sample, despite being ubiquitous in lower-redshift AGNs. Dust-deficient quasars are known to exist both in the local Universe (J. Lyu et al. 2017; H. Hao et al. 2010) and at $z \sim 6$ (L. Jiang et al. 2010), though these objects are typically blue in the rest-frame optical, lacking significant dust attenuation. Given that the LRDs exhibit significant attenuation, the dust deficit is rather a hot dust deficit—a lack of dust at temperatures $\gtrsim 500\,\text{K}$.

Perhaps a natural explanation is that the remarkable abundance and characteristic dust-reddening of the LRDs is directly related to their missing mid-IR emission. In the canonical picture of obscured AGNs, the hot dust emitting in the mid-IR is also the material obscuring the AGN, with $A_V \gtrsim 10$ mag across the lines of sight blocked by the torus (R. C. Hickox & D. M. Alexander 2018). In the LRDs, this obscuring material may instead be located in clouds farther from the central source, with colder dust. These may originate from nuclear starburst disks (e.g., T. A. Thompson et al. 2005), or from “polar dust” in the NLR, ejected via winds (e.g., J. Lyu & G. H. Rieke 2018). The hottest dust, in the clouds at the sublimation radius, may itself be optically thick, or be heated inefficiently due to obscuration by the (dust-free) BLR clouds (see R. Maiolino et al. 2025). Regardless, if the colder obscuring clouds have a high covering factor, i.e., a roughly isotropic distribution, it could explain the ubiquity of reddened AGNs at a given luminosity.

Such a geometry may be expected if these objects are in a nascent evolutionary stage. At $z < 2$, red quasars are thought to be in the blowout phase; as the “effective Eddington ratio” is lower for dusty gas, as opposed to pure ionized hydrogen, moderate column densities of dusty gas around the accretion disk can be easily blown out via radiative feedback (A. C. Fabian et al. 2006, 2008; C. Ricci et al. 2017; E. Glikman et al. 2024). In this case, the AGN effectively goes super-Eddington, blowing out its obscuring material, clearing lines of sight directly to the accretion disk. In addition to radiatively driven outflows, MHD winds driven off the

accretion disk may present the right conditions for dust formation, and may even be linked to the formation of the dust torus (A. Sarangi et al. 2019). In fact, even the simplest models for torus formation begin with a larger, isotropic distribution of clouds, which form into a torus via anisotropic radiatively driven winds (Y. Liu & S. N. Zhang 2011; E. Y. Bannikova & A. V. Sergeyev 2017). The mid-IR deficit in the LRDs may therefore indicate that dynamic feedback/winds are at play, regulating the dust content at the sublimation radius, or that the torus has not fully formed at this epoch.

Finally, we note that the characteristic red SED shape of LRDs may not be driven by dust-reddening at all. Consistent with our stacked SED, recent deep ALMA observations suggest the LRDs exhibit very little (if any) dust emission in the far-infrared/submillimeter (C. M. Casey et al. 2025; K. Chen et al. 2025; H. B. Akins et al. 2025c; D. J. Setton et al. 2025; M. Xiao et al. 2025). Moreover, despite the strong Balmer breaks observed in many LRDs with deep PRISM spectroscopy (e.g., I. Labbe et al. 2024; D. J. Setton et al. 2024; B. Wang et al. 2024a), environmental/dynamical evidence suggests that the host galaxies of LRDs are actually quite low-mass (H. B. Akins et al. 2025c; J. Matthee et al. 2025), perhaps inconsistent with the high stellar masses inferred from the Balmer break. Recent work has presented an alternative model to explain the red optical continuum, driven by absorption from dense gas nuclear to the AGN (K. Inayoshi & R. Maiolino 2025), which is supported by the identification of several extreme objects with Balmer breaks that are too steep to arise from stellar populations alone (e.g., A. de Graaff et al. 2025; X. Ji et al. 2025; R. P. Naidu et al. 2025; A. J. Taylor et al. 2025). If the LRDs indeed generally exhibit less dust attenuation than inferred from SED fitting, this may help to reduce their extreme bolometric luminosities.

### 6.3. Where There Are AGNs, There Are Galaxies

Finally, we want to emphasize that despite the focus of this paper on the two extreme physical interpretations of the LRDs, neither is likely completely true. The physical mechanisms that trigger starbursts and AGNs are similar, and we would expect that where there is early AGN growth, there is also significant star formation (T. A. Thompson et al. 2005; P. F. Hopkins et al. 2008; R. I. Davies et al. 2009). Already, we have clear evidence for AGNs in the LRDs in the form of ubiquitous broad lines (J. E. Greene et al. 2024), and also evidence for evolved stellar populations with clear Balmer breaks (B. Wang et al. 2024a). Where these objects fit into the picture of black hole galaxy coevolution is yet to be determined.

It is widely believed that submillimeter galaxies at $z > 2$ (i.e., 850 µm selected dusty star-forming galaxies) represent the progenitors of massive $z \sim 1–2$ elliptical galaxies (e.g., S. Toft et al. 2014; A. S. Long et al. 2023). Stellar age gradients in quiescent galaxies imply an inside-out formation scenario, in which the central cores formed in early, rapid starbursts, consistent with the compact sizes of SMGs (P. Lang et al. 2014; K. A. Suess et al. 2020).

Extending this framework to higher redshift, the LRDs at $z \sim 5–9$ could represent the progenitors of at least some of the first compact quiescent galaxies at $z \sim 3–4$. Recent JWST observations find evidence for an overabundance of massive quiescent galaxies at $z \sim 3–5$ (A. C. Carnall et al. 2023b; F. Valentino et al. 2023), including several that are quite compact (K. Ito et al. 2024; L. Wright et al. 2024) or
maximally old, with formation redshifts $\gtrsim 10$ (A. C. Carnall et al. 2024; A. de Graaff et al. 2025; K. Glazebrook et al. 2024). The overall volume density of the LRDs in our sample is $n \sim 2 \times 10^{-5}$ Mpc$^{-3}$, similar to the overall volume density of massive ($\log M_*/M_{\odot} > 10.6$) quiescent galaxies presented in F. Valentino et al. (2023). Given also their compact sizes and similar formation redshifts, the LRDs may therefore be a natural progenitor population for these early quiescent galaxies. Simulations predict that AGN feedback drives quenching (e.g., R. Davé et al. 2017; R. Weinberger et al. 2018; S. Kurinchi-Vendhan et al. 2023), and A. C. Carnall et al. (2023a) found significant broad H$\alpha$ emission in the spectrum of an otherwise quiescent galaxy at $z = 4.5$. However, a number of complicating factors muddy any conclusions regarding the connections between LRDs and quiescent galaxies. Samples of quiescent galaxies and LRDs are not mass-matched (nor are the stellar masses of LRDs well constrained), and cover different redshift ranges. Moreover, the duty cycle of the LRD phase would have to be of order unity if they are the direct progenitors of massive quiescent galaxies. Understanding any potential evolutionary connection between LRDs and lower-redshift compact quiescent galaxies will require systematic follow-up and careful analysis to constrain the stellar contribution to the continuum.

## 7. Conclusions

We have presented a large sample of compact, extremely red objects/LRDs in COSMOS-Web.

1. We present a sample of 434 LRDs selected based on their F444W compactness and F277W - F444W color >1.5, after removing likely brown dwarfs. By selection, we focus on the reddest subset of the LRD population, biasing our sample toward higher redshifts ($z \gtrsim 5$) but mitigating contamination from EELGs.

2. We fit each candidate to both galaxy and quasar SED models to explore the two “edge cases,” or the two alternatively physical interpretations of the LRDs: either they are dominated by galaxy light from a compact, dusty starburst, or AGN light from a reddened quasar. While neither scenario is likely completely true, the thought experiment allows us to consider the implications at either extreme, bracketing the range of realistic possibilities.

3. We report the spectroscopic confirmation of one source, COS-756434, at $z = 6.9993 \pm 0.0001$, from public JWST/NIRSpec PRISM data. The source exhibits clear broad lines in H$\alpha$ and H$\beta$, indicating strong AGN contribution.

4. Under the interpretation of the LRDs as red quasars, we measure bolometric luminosities $\sim 10^{45-47}$ erg s$^{-1}$, spanning the gap between other JWST-selected AGNs and low-luminosity UV-selected quasars. We infer a bolometric luminosity function $\sim 100$ times higher than that for UV-selected quasars, consistent with lower limits from spectroscopic observations, implying a black hole accretion rate density at $z \sim 5-9$ rivaling that at cosmic noon.

5. Under the alternative interpretation of the LRDs as massive/compact galaxies, perhaps hosting AGNs but not dominated by their light, we measure stellar masses

$\sim 10^{9-11} M_{\odot}$. While many of the LRDs have masses too large to be found in this volume in a $\Lambda$CDM cosmology, when focusing on the subset of the sample with MIR/F770W coverage, no source violates the limits imposed by $\Lambda$CDM. However, they dominate the high-mass end of the stellar mass function, and based on their compact sizes, must approach or exceed the maximal stellar mass surface densities observed in the local Universe.

6. We search all available X-ray, mid-IR, far-IR/submillimeter, and radio data in the COSMOS field to examine the multiwavelength properties of the LRDs. No source is individually detected, and stacks of the full sample yield nondetections in all bands except HST/JWST. We provide the median-stacked limits and a model for the maximal SED consistent with the stacked constraints. This maximal SED model requires an anomalously low X-ray normalization ($\alpha_{OX} \lesssim -2$) or Compton-thick absorption ($\log N_H \gtrsim 24.5$) and is radio-quiet ($R_{1.4}^* \lesssim 10$). The model also allows for a substantial warm dust component with $T_{dust} \sim 200 \pm 75$ K, despite nondetections in the mid-IR and millimeter wavelengths.

The interpretation of the LRDs as a population of reddened AGNs has important implications for our understanding of black hole growth in the early Universe. In particular, it is important to note that the LRDs cannot represent the entirety of the AGN population: faint, unobscured Type I AGNs (e.g., R. Maiolino et al. 2023) or highly obscured Type II AGNs (e.g., R. Endsley et al. 2022; E. Lambrides et al. 2023) would not be selected via this simple photometric criteria. Future large spectroscopic surveys will be needed to conduct a comprehensive census of LRDs and to elucidate their true nature at a population level, and deeper observations in the X-ray, mid/far-IR, and radio will be needed to determine their true properties and draw connections to the full AGN population.

## Acknowledgments

We thank the anonymous referee for providing suggestions that greatly improved this manuscript. The authors thank Gene Leung, Ryan Endsley, Jenny Greene, and Ignas Juodžbalis for useful discussions on the nature of the “little red dots.” Support for this work was provided by NASA through grant JWST-GO-01727 and HST-AR-15802 awarded by the Space Telescope Science Institute, which is operated by the Association of Universities for Research in Astronomy, Inc., under NASA contract NAS 5-26555. The JWST data presented in this article were obtained from the Mikulski Archive for Space Telescopes (MAST) at the Space Telescope Science Institute. The specific observations analyzed can be accessed via doi: 10.17909/jt67-3z02. H.B.A. acknowledges the support of the UT Austin Astronomy Department and the UT Austin College of Natural Sciences through Harrington Graduate Fellowship, as well as the National Science Foundation for support through the NSF Graduate Research Fellowship Program. C.M.C. thanks the National Science Foundation for support through grants AST-1814034 and AST-2009577 as well as the University of Texas at Austin College of Natural Sciences for support; C.M.C. also acknowledges support from the Research Corporation for Science Advancement from a 2019 Cottrell Scholar Award sponsored by IF/THEN, an initiative of Lyda Hill Philanthropies. F.G. acknowledges the support from grant PRIN
MIUR 2017-20173ML3WW_001. "Opening the ALMA window on the cosmic evolution of gas, stars, and supermassive black holes." H.B.A. and others at UT-Austin acknowledge that they work at an institution that sits on indigenous land. The Tonkawa lived in central Texas, and the Comanche and Apache moved through this area. We pay our respect to all of the Native American and Indigenous Peoples and communities who have been or have become a part of these lands and territories in Texas.

*Facilities:* HST (ACS), JWST (NIRCam, NIRSpec, and MIRI).

*Software:* bagpipes (A. C. Carnall et al. 2018), SEP (K. Barbary 2016), SourceExtractor (E. Bertin & S. Arnouts 1996), astropy (Astropy Collaboration et al. 2013, 2018, 2022), matplotlib (J. D. Hunter 2007), numpy (C. R. Harris et al. 2020), photutils (L. Bradley et al. 2022), scipy (P. Virtanen et al. 2020), STScI JWST Calibration Pipeline (https://jwst-pipeline.readthedocs.io/en/latest/; J. Rigby et al. 2023).

## ORCID iDs

Hollis B. Akins https://orcid.org/0000-0003-3596-8794

Caitlin M. Casey https://orcid.org/0000-0002-0930-6466

Erini Lambrides https://orcid.org/0000-0003-3216-7190

Natalie Allen https://orcid.org/0000-0001-9610-7950

Irham T. Andika https://orcid.org/0000-0001-6102-9526

Malte Brinch https://orcid.org/0000-0002-0245-6365

Jaclyn B. Champagne https://orcid.org/0000-0002-6184-9097

Olivia Cooper https://orcid.org/0000-0003-3881-1397

Xuheng Ding https://orcid.org/0000-0002-0786-7307

Nicole E. Drakos https://orcid.org/0000-0003-4761-2197

Andreas Faisst https://orcid.org/0000-0002-9382-9832

Steven L. Finkelstein https://orcid.org/0000-0001-8519-1130

Maximilien Franco https://orcid.org/0000-0002-3560-8599

Seiji Fujimoto https://orcid.org/0000-0002-7530-8857

Fabrizio Gentile https://orcid.org/0000-0002-8008-9871

Steven Gillman https://orcid.org/0000-0001-9885-4589

Ghassem Gozaliasl https://orcid.org/0000-0002-0236-919X

Santosh Harish https://orcid.org/0000-0003-0129-2079

Christopher C. Hayward https://orcid.org/0000-0003-4073-3236

Michaela Hirschmann https://orcid.org/0000-0002-3301-3321

Olivier Ilbert https://orcid.org/0000-0002-7303-4397

Jeyhan S. Kartaltepe https://orcid.org/0000-0001-9187-3605

Dale D. Kocevski https://orcid.org/0000-0002-8360-3880

Anton M. Koekemoer https://orcid.org/0000-0002-6610-2048

Vasily Kokorev https://orcid.org/0000-0002-5588-9156

Daizhong Liu https://orcid.org/0000-0001-9773-7479

Arianna S. Long https://orcid.org/0000-0002-7530-8857

Henry Joy McCracken https://orcid.org/0000-0002-9489-7765

Jed McKinney https://orcid.org/0000-0002-6149-8178

Masafusa Onoue https://orcid.org/0000-0003-2984-6803

Louise Paquereau https://orcid.org/0000-0003-2397-0360

Alvio Renzini https://orcid.org/0000-0002-7093-7355

Jason Rhodes https://orcid.org/0000-0002-4485-8549

Brant E. Robertson https://orcid.org/0000-0002-4271-0364

Marko Shuntov https://orcid.org/0000-0002-7087-0701

John D. Silverman https://orcid.org/0000-0002-0000-6977

Takumi S. Tanaka https://orcid.org/0009-0003-4742-7060

Sune Toft https://orcid.org/0000-0003-3631-7176

Benny Trakhtenbrot https://orcid.org/0000-0002-3683-7297

Francesco Valentino https://orcid.org/0000-0001-6477-4011

Jorge Zavala https://orcid.org/0000-0002-7051-1100

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