# JWST Discovery of a High-Redshift Tidal Disruption Event Candidate in COSMOS-Web

Mitchell Karmen, Suvi Gezari, Erini Lambrides, Hollis B Akins, Colin Norman, Caitlin M Casey, Justin Pierel, David Coulter, Armin Rest, Ori Fox, et al.

► To cite this version:

Mitchell Karmen, Suvi Gezari, Erini Lambrides, Hollis B Akins, Colin Norman, et al., JWST Discovery of a High-Redshift Tidal Disruption Event Candidate in COSMOS-Web. The Astrophysical Journal, 2025, 990 (2), pp.149. 10.3847/1538-4357/adf216. hal-05097314

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# JWST Discovery of a High-redshift Tidal Disruption Event Candidate in COSMOS-Web

Mitchell Karmen<sup>1,20</sup>*, Suvi Gezari<sup>1,2</sup>*, Erini Lambrides<sup>3,21</sup>*, Hollis B. Akins<sup>4</sup>*, Colin Norman<sup>1</sup>*, Caitlin M. Casey<sup>4,5,6</sup>*, Justin Pierel<sup>7,22</sup>*, David Coulter<sup>7</sup>*, Armin Rest<sup>7</sup>*, Ori Dr. Fox<sup>7</sup>*, Yukta Ajay<sup>1</sup>*, Natalie Allen<sup>6,8</sup>*, Nicole E. Drakos<sup>9</sup>*, Seiji Fujimoto<sup>4,23</sup>*, Sebastian Gomez<sup>10</sup>*, Ghassem Gozaliasl<sup>11,12</sup>*, Olivier Ilbert<sup>13</sup>*, Jeyhan S. Kartaltepe<sup>14</sup>*, Anton M. Koekemoer<sup>7</sup>*, Zachary G. Lane<sup>15</sup>*, Henry Joy McCracken<sup>16</sup>*, Louise Paquereau<sup>16</sup>*, Jason Rhodes<sup>17</sup>*, Brant E. Robertson<sup>18</sup>*, Marko Shuntov<sup>6,8</sup>*, Matthew R. Siebert<sup>7</sup>*, Sune Toft<sup>6,8</sup>*, Thomas Wevers<sup>19</sup>*, and Yossef Zenati<sup>1,7</sup>†

¹ Department of Physics and Astronomy, Johns Hopkins University, 3400 North Charles Street, Baltimore, MD 21218, USA; mkarmen1@jhu.edu

² Department of Astronomy, University of Maryland, College Park, MD 20742-2421, USA

³ NASA-Goddard Space Flight Center, Code 662, Greenbelt, MD 20771, USA

⁴ The University of Texas at Austin, 2515 Speedway Boulevard Stop C1400, Austin, TX 78712, USA

⁵ Department of Physics, University of California, Santa Barbara, Santa Barbara, CA 93109, USA

⁶ Cosmic Dawn Center (DAWN), Denmark

⁷ Space Telescope Science Institute, Baltimore, MD 21218, USA

⁸ Niels Bohr Institute, University of Copenhagen, Jagtvej 128, DK-2200, Copenhagen, Denmark

⁹ Department of Physics and Astronomy, University of Hawaii, Hilo, 200 West Kawili Street, Hilo, HI 96720, USA

¹⁰ Center for Astrophysics | Harvard & Smithsonian, 60 Garden Street, Cambridge, MA 02138-1516, USA

¹¹ Department of Computer Science, Aalto University, P.O. Box 15400, FI-00076 Espoo, Finland

¹² Department of Physics, University of Helsinki, P.O. Box 64, FI-00014 Helsinki, Finland

¹³ Aix Marseille University, CNRS, CNES, LAM, Marseille, France

¹⁴ Laboratory for Multiwavelength Astrophysics, School of Physics and Astronomy, Rochester Institute of Technology, 84 Lomb Memorial Drive, Rochester, NY 14623, USA

¹⁵ School of Physical and Chemical Sciences—Te Kura Matū, University of Canterbury, Private Bag 4800, Christchurch 8140, New Zealand

¹⁶ Institut d'Astrophysique de Paris, UMR 7095, CNRS, and Sorbonne Université, 98 bis Boulevard Arago, F-75014 Paris, France

¹⁷ Jet Propulsion Laboratory, California Institute of Technology, 4800 Oak Grove Drive, Pasadena, CA 91001, USA

¹⁸ Department of Astronomy and Astrophysics, University of California, Santa Cruz, 1156 High Street, Santa Cruz, CA 95064, USA

¹⁹ Astrophysics & Space Institute, Schmidt Sciences, New York, NY 10011, USA

Received 2025 April 17; revised 2025 July 17; accepted 2025 July 17; published 2025 September 4

## Abstract

The rates and properties of tidal disruption events (TDEs) provide valuable insights into their host galaxy central stellar densities and the demographics of their central supermassive black holes. TDEs have been observed only at low redshifts ($z \lesssim 1$), due to the difficulty in conducting deep time-domain surveys. In this work, we present the discovery of a high-redshift TDE candidate, HZTDE-1, in the COSMOS-Web survey with JWST's NIRCam, using a novel selection technique based on color and morphology. We outline a methodology for identifying high-z TDEs in deep infrared imaging surveys, leveraging the unique spectral energy distributions and morphologies of these transients. While focused on TDEs, this methodology could also be applied to find other UV-bright transients, such as superluminous supernovae (SLSNe). We apply this technique to COSMOS-Web in filters F115W, F150W, F277W, and F444W, and identify HZTDE-1, a transient point source relative to archival UltraVISTA infrared observations. If we assume it is a TDE, we estimate a photometric redshift of $z = 5.02_{-1.11}^{+1.32}$. HZTDE-1 cannot be explained by reasonable supernova or active galactic nuclei models. However, an SLSN at $z \gtrsim 3$ can also plausibly explain this transient and would be the highest-redshift SLSN yet known. If confirmed with follow-up observations, HZTDE-1 would represent the highest-redshift TDE discovery to date, and suggest an enhancement of the TDE rate in the high-redshift Universe. Our method, which can be applied to future deep surveys with the JWST and Nancy Grace Roman Space Telescope, offers a pathway to identify TDEs at $z > 4$ and probe black hole demographics at early cosmic times.

Unified Astronomy Thesaurus concepts: Tidal disruption (1696); Supermassive black holes (1663); James Webb Space Telescope (2291)

## 1. Introduction

A tidal disruption event (TDE) occurs when a star passes close enough to a supermassive black hole (SMBH) that the tidal forces on the star overcome its self-gravity, and destroy the star (J. G. Hills 1975; M. J. Rees 1988; C. R. Evans & C. S. Kochanek 1989; A. Ulmer 1999). This process leads to a luminous flare ($\sim 10^{43}$ erg s$^{-1}$), as approximately half of the mass of the star is accreted and the other half is ejected at high velocity (L. E. Strubbe & E. Quataert 2009; S. Gezari et al. 2012). This highly transient accretion event contrasts with the

<figure><img src="image_2.png" /></figure>

<footnote n="20">²⁰ NSF Graduate Research Fellow.</footnote>

<footnote n="21">²¹ NASA Postdoctoral Program (NPP) Fellow.</footnote>

<footnote n="22">²² NASA Einstein Fellow.</footnote>

<footnote n="23">²³ Hubble Fellow.</footnote>
more long term, sustained accretion that is associated with active galactic nuclei (AGN; M. C. Begelman et al. 1984; J. H. Krolik 1999; Event Horizon Telescope Collaboration et al. 2019). Despite decades of dedicated efforts, several outstanding questions surrounding the formation and evolution of SMBHs persist. In particular, the uncertain origin of the first SMBHs has outlined the need for robustly measuring the early Universe SMBH mass distribution (M. Volonteri et al. 2003; M. C. Begelman et al. 2006). TDEs are one of the only phenomena, alongside AGN, that present a luminous observable very close to an SMBH. Unlike AGN, which prefer very massive SMBH hosts (G. Kauffmann et al. 2003), the TDEs of main-sequence stars by nonrotating (Schwarzschild) black holes (BHs) can only occur for lower-mass SMBHs because the disrupting BH has an upper mass limit of $M_{BH} < 10^8 M_{\odot}$ (J. G. Hills 1975). Beyond this mass, the tidal radius $R_t = R_*(M_{BH}/M_*)^{1/3}$ is within the Schwarzschild radius $R_s = 2GM/c^2$. The TDE rate's sensitivity to the BH mass make TDEs an excellent probe of the SMBH mass function (C. S. Kochanek 2016; N. C. Stone & B. D. Metzger 2016). The TDE rate is also affected by the stellar mass function, so a redshift-evolving TDE rate could also be sensitive to the initial mass function (IMF; J. Magorrian & S. Tremaine 1999). Additionally, stellar dynamics calculations imply that galaxies with lower-mass SMBHs have higher intrinsic TDE rates (N. C. Stone & B. D. Metzger 2016). Therefore, TDEs are ideal probes of distant, lower-mass SMBHs and the stars which surround them.

The primary tool used to measure the masses of high-redshift SMBHs, when dynamical information is not available, is spectroscopy of AGN (B. M. Peterson 1998; S. Kaspi et al. 2000). Due to Malmquist bias, the most massive tail of the high-redshift BH mass function is observed, leading to observations of SMBHs which are overmassive relative to their host galaxies (F. Pacucci & A. Loeb 2024) and their cosmic epoch (I. Juodžbalis et al. 2024). JWST observations are able to sample lower-luminosity AGN and thus lower-mass BHs (e.g., Y. Harikane et al. 2023; J. Li et al. 2025), but are prone to systematic biases in virial mass estimation methods (J. H. Krolik 2001; Y. Shen 2013; C. Bertemes et al. 2025). TDEs offer an independent tool to study the less massive end of this mass function. The peak luminosities of TDEs (B. Mockler et al. 2019), their fallback rates (A. Bandopadhyay et al. 2024), and their late-time plateau luminosities (A. Mummery et al. 2024) have all been linked to their host SMBH mass. Furthermore, TDE rates can be a strong probe of the fraction of BHs in low-mass galaxies (N. C. Stone & B. D. Metzger 2016). TDEs are transients, which makes them significantly more difficult to observe. While thousands of AGN have been observed up to $z = 11$ (R. Maiolino et al. 2024), only of order 100 TDEs have been spectroscopically confirmed at the time of writing this paper (S. Gezari 2021), with the highest-redshift TDE the jetted TDE 2022cmc at $z = 1.19$ (I. Andreoni et al. 2022).

Typically TDEs are discovered through wide-field, time-domain optical surveys (e.g., the Zwicky Transient Facility (ZTF); E. C. Bellm et al. 2019; M. J. Graham et al. 2019). They are slow (lasting 100–200 days), blue (peaking in the UV) transients that do not typically cool as they fade (S. Gezari 2021). TDEs last on scales of months, typically fading from peak in ~200 days (S. van Velzen et al. 2021). The origin of the early time UV-optical emission is debated, and still not fully understood (L. Dai et al. 2018;

N. Roth et al. 2020; T. Ryu et al. 2023). In this work, we adopt a fully empirical, observation-driven model of TDE spectra and light curves.

At higher redshifts, TDEs are fainter and therefore their light curves are more difficult to observe far from maximum brightness. They are time dilated and therefore evolve very slowly at higher redshifts. At $z > 4$, their peak emission is also redshifted into the near-infrared (NIR), which makes the both JWST Near Infrared Camera (NIRCam) and Nancy Grace Roman Space Telescope Wide-Field Instrument ideal for observing them. This makes it a possibility to serendipitously observe an ongoing TDE in deep field JWST imaging. In this work, we use the COSMOS-Web survey, the widest area deep JWST survey (C. M. Casey et al. 2023), to search for potential high-redshift TDEs. Detections of TDEs at $z > 4$ could give valuable insights into SMBH formation and growth. They would indicate within which galaxies lower-mass SMBHs exist in the early Universe, potentially distinguishing between SMBH seed models (M. Volonteri et al. 2021).

Previously, C. S. Kochanek (2016) has used semiempirical modeling of TDE rates to predict intrinsic and observed rates of TDEs as a function of redshift. They predict that, due to the observed “downsizing” of AGN mass over redshift (as modeled in F. Shankar et al. 2009), the intrinsic TDE rate will decrease by a factor of 5 by $z = 1$. As a result, they assert that the observed rate of high-redshift TDEs, given ground-based wide-field time-domain surveys (focusing on Pan-STARRS1; K. C. Chambers et al. 2016), will be even lower. Here, we extend to high redshifts by leveraging deep space-based imaging without the use of time series. We assert in a companion work M. Karmen et al. (2025, in preparation) that, given the observed evolution of galaxy and SMBH properties with redshift, the TDE rate at high redshifts is likely greatly enhanced. As a result, in upcoming surveys such as the Nancy Grace Roman Space Telescope High Latitude Time Domain Survey (HLTDS; B. M. Rose et al. 2021) and the Vera C. Rubin Observatory’s Legacy Survey of Space and Time (LSST; Ž. Ivezić et al. 2019) it may be possible to study populations of TDEs at high redshifts. K. Inayoshi et al. (2024) predict the properties of high-redshift TDEs embedded within gas-rich AGN environments, in which the TDE occurrence rates are enhanced due to their compact and dense environments, compared to typical TDEs which occur in poststarburst galaxies. In this work, we complement this by searching exclusively for TDEs in galaxies not containing luminous AGN in order to utilize observed properties from low-redshift TDE searches, which exclude all AGN-hosting galaxies.

Throughout this work we adopt a Planck cosmology (Planck Collaboration et al. 2020). We report optical magnitudes in the AB system. We correct observed photometry for Galactic extinction using the J. A. Cardelli et al. (1989) extinction law, assuming $R_V = 3.1$ and the E. F. Schlafly & D. P. Finkbeiner (2011) extinction map.

In this work, we report the discovery of a $z = 5.02^{+1.32}_{-1.11}$ TDE candidate in the COSMOS-Web survey (C. M. Casey et al. 2023). In Section 2, we present a new methodology for identifying TDE candidates in deep imaging using colors and morphology. We compare to potential contaminants, and pose methods of confirming candidate TDEs. In Section 3 we apply this methodology to the COSMOS-Web survey data, and use historic imaging of the COSMOS field to evaluate the potential
variability of objects we select. We present the properties of HZTDE-1, a transient high-redshift TDE candidate in Section 4. We compare the TDE model to potential supernova (SN) models for this object. We discuss the need for spectroscopy of this object, and its implications if validated in Section 5. We summarize our work in Section 6.

## 2. Identifying High-redshift Tidal Disruption Events in Deep Surveys

In this section, we model the signatures of TDEs similar to the local population, and develop a method for identifying them in wide-field infrared surveys using the colors and morphologies. To first order, the UV-optical spectral energy distribution (SED) of a TDE is well approximated by a blackbody with a typical temperature of ~$10^{4.3 \pm 0.15}$ K (S. van Velzen et al. 2020, 2021; E. Hammerstein et al. 2023; Y. Yao et al. 2023). We simulate TDEs with the same temperature distribution as the latest sample of spectroscopically confirmed TDEs from ZTF (Y. Yao et al. 2023), and simulate their volumetric density by integrating over a double power-law fit to the ZTF g-band luminosity function (their Equation (16)). TDEs typically do not cool as they fade, so we assume constant-temperature blackbodies for their entire evolution. Their light curves are observationally well parameterized in S. van Velzen et al. (2021) as follows:

$$L_{\nu}(t) = L_{\nu_0 \text{ peak}} \frac{B_{\nu}(T_0)}{B_{\nu_0}(T_0)} \times \begin{cases} e^{-(t-t_{\text{peak}})^2/2\sigma^2} & t \le t_{\text{peak}}, \\ e^{-(t-t_{\text{peak}})/\tau} & t > t_{\text{peak}}, \end{cases} \quad (1)$$

with a luminosity in the g band in units of erg s⁻¹ of 42.68 < log(Lg) < 44.68, a Gaussian rise time of 0.4 < log(σ) < 1.3 days, and an exponential decay time of 1.2 < log(τ) < 2.3 days from ZTF. When simulating TDEs, we step over redshift in shells of size Δz = 0.2. At a given z, we sample over their temperatures and luminosities in a grid starting with the faintest TDE at a given redshift that is visible given the survey limits. We sample their luminosities in step sizes inversely proportional to their probability densities, giving more dense sampling to the higher-probability luminosities. At each redshift and luminosity, we simulate a TDE with every temperature observed in the Y. Yao et al. (2023) ZTF TDE sample. At each given luminosity, we allow TDEs to fade as L ∝ t⁻⁵/³ until they reach the magnitude limit of the filter/survey observing them, to account for the time evolution of the TDE.

### 2.1. The Host Model

We base our predictions of properties of TDE host galaxies on local observations of TDE hosts. It has been observed that TDE hosts are disproportionately in the green valley with compact nuclei (E. Hammerstein et al. 2021), and may show a preference for poststarburst galaxies (K. D. French et al. 2016). Because of this, we base our host galaxy models on the total sample of 30 ZTF TDE hosts from E. Hammerstein et al. (2021) to capture their observed properties. To extend the observed host spectra to their rest-frame UV, we use Prospector to model their spectra and perform synthetic

<figure><img src="image_3.png" /><figcaption>**Figure 1.** Apparent magnitudes of the median TDE from our simulations (solid lines) compared to the median ZTF host galaxy (dashed lines; E. Hammerstein et al. 2021). The shaded regions represent the 5th and 95th percentiles for the TDE hosts. 95% of the hosts drop out by z ~ 2.2 in F115W, and by z ~ 4.1 in F444W.</figcaption></figure>

photometry (B. D. Johnson et al. 2021). We use the parameters from the original fits of the ZTF TDE hosts in E. Hammerstein et al. (2021), which are estimated by maximum a posteriori fits of Flexible Stellar Population Synthesis models (C. Conroy et al. 2009) to broadband photometry from the Sloan Digital Sky Survey (SDSS), Pan-STARRS, and the Galaxy Evolution Explorer. When calculating properties of TDE hosts, we simulate every TDE host from ZTF to account for their full diversity of properties. We find that, due to the k-correction and the homogeneous colors of the TDE hosts, they typically are not visible beyond z = 3.5 as seen in Figure 1.

We also use these ZTF TDE hosts as a basis for the physical sizes for typical TDE hosts. We query SDSS photometry for the TDE hosts in ZTF, and convert their angular sizes to physical sizes (M. R. Blanton et al. 2017; E. Hammerstein et al. 2023). We find that the ZTF TDE host galaxies contain 90% of Petrosian flux in a diameter of 8 ≲ D90 ≲ 20 kpc. These correspond to range of angular diameters between 1.4 and 4.7 at z = 8. These angular sizes will increase at even higher redshifts due to the decrease in angular diameter distance with increasing redshift beyond z ~ 1.5 (D. W. Hogg 1999). As NIRCam has a resolution of 0.07 pixel⁻¹ at 2 µm, all TDE host galaxies above the survey magnitude limit will be resolvable as an extended source in COSMOS-Web. At early epochs (z ~ 7), galaxies are expected to be intrinsically smaller (A. Grazian et al. 2012; R. Kawamata et al. 2018), such that even TDEs in unusually bright or blue hosts will not have spatially extended emission.

Because all of the host galaxies we observe are at z < 1, the galaxies we use are of higher mass and more luminous than those which we expect at high redshifts. High-redshift galaxies are expected to be, and now observed to be, primarily lower-mass, blue, star-forming galaxies. While there is a minority of these galaxies which are exceptionally luminous without SMBHs above the Hills mass due to extremely active star formation (e.g., C. M. Casey et al. 2024; M. Castellano et al. 2024; M. Franco et al. 2024), it would be extremely difficult to detect a UV-optical TDE in one because its star formation is bright and blue, making the TDE emission a subdominant
component of its UV SED. Therefore, we do not consider them in our analysis. However, a population of TDEs which occur primarily in star-forming galaxies have been observed to be infrared bright with no UV-optical component to their emission (M. Masterson et al. 2024), making their rates relevant to wide-field surveys using the Mid-Infrared Instrument (MIRI). For our search in COSMOS-Web, the local TDE hosts we observe are effectively upper limits for higher-redshift host galaxy luminosity. In summary, TDEs trace lower-mass SMBHs which trace, in turn, lower-mass galaxies. These are expected to be even less massive at high redshifts, therefore intrinsically fainter, and are k-corrected into the mid-infrared. We therefore expect the vast majority of TDEs at $z > 4$ to appear hostless.

## 2.2. Dust Extinction

Interstellar dust at high redshifts is something that is hotly debated and poorly understood. To first principles, high-redshift galaxies should have very low metallicity, and should therefore have less dust attenuation than galaxies today (D. B. Fisher et al. 2014). This effect is observed in local metal-poor galaxies (S. C. Madden et al. 2013), and is beginning to be seen in JWST observations of high-redshift metal-poor galaxies as well (K. E. Heintz et al. 2023). Furthermore, preliminary observations of bright $z > 10$ galaxies in the first JWST surveys can be explained by very low levels of dust (S. L. Finkelstein et al. 2023).

UV-optical TDEs are not typically observed in dusty galaxies (K. D. French et al. 2020; E. Hammerstein et al. 2021). This may be due to selection effects, or may be due to intrinsic host galaxy preferences. Our local volumetric TDE rate primarily includes TDEs which occur in local, quiescent galaxies which will decrease in number density with redshift. Combining this effect with high-redshift dust reduction, we expect that dust attenuation will have a small effect on the appearance of TDEs at high redshift. Despite this, we still include varying levels of dust in our modeling, simulating $A_V$ up to 1.2, which is the dustiest any observed TDE host is in the E. Hammerstein et al. (2023) fits to host photometry. Furthermore, the observation of a TDE implies the existence of a line of sight to the TDE emission which is not obscured by dust. Dust attenuation therefore affects the overall rates of observed TDEs more than the emission from the TDEs which are observed.

## 2.3. High-redshift Tidal Disruption Events

We find that, given our simulated TDEs and assumptions about their typical host galaxies, most high-redshift ($z > 4$) TDEs will be point sources with unique colors. At $z > 4$, a typical TDE host galaxy drops in apparent magnitude below the detection limits of the COSMOS-Web survey, as seen in Figure 2. A TDE near peak brightness is visible to beyond $z \sim 10$. The SED of a high-redshift TDE is dominated by its blackbody emission, which is redshifted from rest-frame UV to observer-frame NIR. It can been seen in Figure 3 that the blackbody approximation is, photometrically, a very good estimate of the SED. Because a redshifted blackbody is another blackbody, there is a degeneracy in color-color space between temperature and redshift, meaning all idealized TDEs lie upon a nearly straight line in 2D color-color space (slightly curved due to relativistic Doppler shift and dust extinction). In

<figure><img src="image_4.png" /><figcaption>**Figure 2.** Example spectra of modeled 15,000 K TDEs at maximum and their host galaxies at four different redshifts: $z = 1$ (dark blue), $z = 2$ (light blue), $z = 4$ (orange), and $z = 6$ (dark red). Solid lines represent the TDE spectrum, while dashed lines show the host galaxy spectrum. The COSMOS-Web magnitude limits for each NIRCam filter are indicated in gray. At higher redshifts, host galaxies typically drop below detection thresholds, leaving TDE emission as the dominant observable component.</figcaption></figure>

our selection for high-redshift TDEs, we restrict to a region that follows the color-color relationship in any given color combination. This is shown as the three dark purple lines outlining the TDE region in Figure 4. We also fit bounds to each individual color, which, together with the parabola fits, are presented in Table 1. We fit a parabola to the color-color relationship of TDEs in each filter combination through maximum likelihood optimization with the assumption of uniform uncertainties, which is mathematically equivalent to least squares fitting. Each curve is parameterized as

$$C_2 = a_1 C_1^2 + a_2 C_1 + a_3, \quad (2)$$

where $C_1$ and $C_2$ are two colors. The values of the coefficients $a_1$, $a_2$, and $a_3$ for each pair of colors are listed in Table 1, alongside the bounds on $C_1$ and $C_2$ from our simulations. We place bounds on the redshift range we simulate, on the low end by the redshift beyond which TDEs will be point sources, and on the high end by the redshift at which Lyman absorption renders them undetectable. Additionally, we fit the minimum apparent magnitude expected for a TDE at any redshift of a given color, shown in Figure 4, as

$$m_{\text{F115W}} = 2.15C_{\text{F115W}} - \text{F150W} + 24.2. \quad (3)$$

To check our blackbody idealization, we take the following TDEs that have Hubble Space Telescope (HST) UV spectroscopy, and simulate them at high redshifts: iPTF16fnl, ASASSN-150i, AT2022dsb, AT2018bsi, and ASASSN-14li (S. B. Cenko et al. 2016; J. S. Brown et al. 2018; N. Blagorodnova et al. 2019; T. Hung et al. 2019; P. Charalampopoulos et al. 2022; W. B. Hoogendam et al. 2024). The spectra used to create these templates can be accessed via doi:10.17909/9m1b-2s28. We extend the UV spectrum into the optical ($>2600 \AA$) with a blackbody with the temperature fit by A. Mummery & S. van Velzen (2025), redshift the TDE spectra, and add in Lyman absorption shortward of rest-frame 1216 Å (A. K. Inoue et al. 2014). We show these templates in Figure 3. These TDEs have colors centered on the predicted relationship, and scatter due to emission and absorption features, as well as continuum excess farther into the UV. This scatter, typically $\sim 0.2$ mag, defines the region near our idealized color-color relationships in which we expect actual TDEs to exist (the shaded region in the figure).
<figure><img src="image_5.png" /><figcaption>**Figure 3.** Example templates used to test the TDE color–magnitude cuts, shifted to the rest frame. The red line is the HST spectrum, the purple dotted line is the blackbody used to extend the spectrum, and photometry is in blue. We switch from the HST spectrum to the blackbody at a rest-frame wavelength of 2600 Å, which is shown in the changing opacity of each line. We simulate this spectrum at higher redshifts to test our color cuts.</figcaption></figure>

While we create these selection criteria for the COSMOS-Web survey, the same process can be done for any deep, wide-field infrared survey. Of particular interest is the Nancy Grace Roman High Latitude Wide Area Survey (HLWAS; D. Spergel et al. 2015). While the HLTDS is designed to identify transients (B. M. Rose et al. 2021), the HLWAS will serendipitously observe hundreds of ongoing TDEs. Using similar methodology, one could select high-redshift TDEs in the HLWAS based on their colors and morphology, and pursue follow-up to confirm them. This search serves as a first test of such a method, for application in future wide-field infrared surveys. For more intermediate-redshift hostless TDEs, this method may be possible to implement in optical wavelengths with the upcoming Vera C. Rubin Observatory coadds and deep drilling fields (Ž. Ivezić et al. 2019).

## 2.4. Alternative Tidal Disruption Event Models

By extrapolating the blackbody near-UV-optical spectrum of a TDE to the UV, we predict the spectrum of TDEs at rest-frame wavelengths at which their spectra are relatively poorly constrained, between 900 Å and 1500 Å. Furthermore, the presence of Bowen lines in TDE spectra (e.g., G. Leloudas et al. 2019) implies that the flux predicted by a blackbody at 228 Å is ~5 orders of magnitude less than what is needed in order to ionize He II and cause Bowen fluorescence. In the intermediate wavelengths that we observe, between 900 Å and 1500 Å, a blackbody may also underpredict the TDE flux.

To account for this potential discrepancy, we also consider a TDE spectrum with enough UV flux in order to trigger Bowen lines. For this test, we consider the L. Dai et al. (2018) model, which uses 3D general relativistic radiation magnetohydrodynamics simulations to simulate a super-Eddington accretion

disk, and Monte Carlo radiative transfer to simulate reprocessing; we do not claim that this model is correct but treat it as an example of a spectrum which is extremely luminous in the UV. We select emission from a viewing angle between 22.5 and 45° from a simulated spectrum which matches a blackbody spectrum of a few × 10⁴ K in the optical. This model is not used for any rate calculations or final conclusions, but is a comparison point for TDE colors and identification methodology.

We find that the L. Dai et al. (2018) model falls well within our color–color and color–magnitude bounds, typically within 0.1 mag of the central TDE color–color lines that we fit. While it would skew our fit to that of a hotter or lower-redshift TDE, spectroscopic follow-up would confirm our TDE redshift regardless of the underlying continuum model.

## 2.5. Contaminants

We model any point sources which may have similar colors to high-redshift TDEs to verify that high-redshift TDEs lie in a unique region of color–color and color–magnitude space. This varies dramatically by survey, but we demonstrate these color properties for COSMOS-Web, as the majority of future wide-field deep surveys will be in the NIR. We show examples of these color–color and color–magnitude relationships in Figure 4. In fact it may be easier to identify high-redshift sources in the Nancy Grace Roman HLTDS and HLWAS because optical imaging from these surveys means that a Lyman break will be observed to verify the redshift of a source. This breaks multiple degeneracies we see in the JWST NIRCam infrared colors. The contaminants we model are as follows.
<figure><img src="image_6.png" /><figcaption>**Figure 4.** Color–color and color–magnitude plots of high-redshift ($z > 4$) TDEs compared to potential point-source contaminants, modeled as described in Section 2.5. The purple central line is a parabola fit (Equation (2) and Table 1) to the TDE color–color relationship, and the region surrounding it is the 0.2 mag of scatter seen in the TDE template colors from Section 2.3. The unshaded regions contain 95% of contaminants of a given type. The red star is HZTDE-1, the high-redshift TDE candidate we identify in Section 3. The black $\times$ symbols are the synthetic photometry of our TDE templates at $z = 5$. HZTDE-1 is notably brighter than these templates because the majority of the template UV spectra is taken weeks to months after maximum brightness. The L. Dai et al. (2018) model is represented by the red–blue line, with the bluest end representing $z = 2$, and the reddest representing $z = 8$.</figcaption></figure>

**Lower-redshift SNe.** Type Ia SNe (SNe Ia), Type IIP SNe (SNe IIP), and Type IIn SNe (SNe IIn) at $z > 2$ may be point sources in JWST data. Already, SNe with host redshifts from 0.6461 to 3.6 have been discovered using NIRCam imaging in the JWST Advanced Deep Extragalactic Survey (JADES; C. DeCoursey et al. 2025; J. D. R. Pierel et al. 2024; M. R. Siebert et al. 2024; D. A. Coulter et al. 2025). We specifically model SNe which are point sources, so we do not consider contribution in their colors from host galaxy light. Our SN Ia models are SALT3 models, which extend into the NIR (J. D. R. Pierel et al. 2022), with parameter sweeps over $-2 \le x_1 \le 2$, $-0.3 \le c_1 \le 0.3$, and $z \le 5$, simulated at phases $-20 \le p \le 50$ days. We predict that no SNe Ia will be detected beyond $z > 5$ in COSMOS-Web. To model Type II SNe (SNe II), we use every SNANA model (R. Kessler et al. 2009) that has been implemented in *sncosmo* to represent the diversity of observed SNe II at their peak luminosities. The SNANA

models have only an amplitude parameter, so we sweep over a range of luminosities for each template. We set bounds on each SN subtype's luminosity distribution based on observed samples, $-16 < M_b < -19$ for SNe Ia (M. M. Phillips 1993), $-16 \le M_V \le -19.5$ for Type Ib/c SNe (SNe Ib/c; M. R. Drout et al. 2011), $-16 \le M_b \le -18.5$ for SNe IIP (N. E. Sanders et al. 2015), $-13 \le M_g \le -22$ for SNe IIn (A. Nyholm et al. 2020), and $-20 \le M_g \le -22$ for superluminous SNe (SLSNe; S. Gomez et al. 2024).

We find that SNe Ia are sufficiently bluer than TDEs at lower redshifts where their apparent magnitudes match, and are too faint at higher redshifts when their colors match, such that there is no confusion at any redshift as seen in Figure 4. SNe Ib/c can indeed match the colors and magnitudes of high-redshift TDEs at redshifts $z < 1$, however their hosts are expected to be detected in COSMOS-Web and previous deep optical imaging of the COSMOS field. SNe II are even bluer,
<table><caption>**Table 1**
Parabolas of the Best Fits to the High-redshift Tidal Disruption Event Color-Color Relationship, as Seen in Figure 4 and Parameterized in Equation (2)</caption><thead><tr><th>C<sub>1</sub> Color</th><th>C<sub>2</sub> Color</th><th>a<sub>1</sub></th><th>a<sub>2</sub></th><th>a<sub>3</sub></th><th>Min C<sub>1</sub> Color</th><th>Max C<sub>1</sub> Color</th><th>Min C<sub>2</sub> Color</th><th>Max C<sub>2</sub> Color</th></tr></thead><tbody><tr><td>F115W - F444W</td><td>F150W - F277W</td><td>0.0024</td><td>0.4766</td><td>0.0473</td><td>-1.4</td><td>3.5</td><td>-1.1</td><td>1.5</td></tr><tr><td>F115W - F150W</td><td>F277W - F444W</td><td>0.0242</td><td>0.5215</td><td>-0.6974</td><td>-0.4</td><td>1.3</td><td>-1.0</td><td>0.1</td></tr><tr><td>F115W - F150W</td><td>F150W - F277W</td><td>0.0605</td><td>1.3533</td><td>-0.5377</td><td>-0.4</td><td>1.3</td><td>-1.1</td><td>1.5</td></tr><tr><td>F150W - F277W</td><td>F277W - F444W</td><td>0.0005</td><td>0.3859</td><td>-0.4900</td><td>-1.1</td><td>1.5</td><td>-1.0</td><td>0.1</td></tr></tbody></table>

**Note.** Each line fit is a parabola to accurately model their slight curve in color–color space. These fits are no longer valid when there is significant Lyman dropout in the F115W band.

and at $z \sim 2$ they can pass as $z > 4$ TDEs, but would need rest-frame b-band absolute magnitudes $\lesssim -20$, which is not observed in SNe IIP. SNe IIn can become this luminous at maximum brightness, serving as our main contaminant if their hosts are not detected at $z \sim 2$. We show SNe IIn at $1.5 < z < 2.5$ in Figure 4.

**SLSNe.** SLSNe, alongside TDEs and pair-instability SNe, will be among the few transients which are visible up to very high redshifts. We model them using the templates constructed from Dark Energy Survey SLSNe, which have a blackbody continuum with UV absorption features superimposed (C. R. Angus et al. 2019). Because their absorption strengths evolve and the SLSNe cool after their explosion, we simulate them up from $-10$ to $+35$ rest-frame days from peak with early time temperatures between 5000 K and 18,000 K. We use *sncosmo* to model these and perform synthetic photometry (K. Barbary et al. 2016). Again, we do not consider a contribution from the host galaxy.

SLSNe are persistent contaminants given the low-mass nature of their typical hosts, and their colors and luminosities which significantly overlap those of TDEs (S. Schulze et al. 2018). A candidate TDE of a given high redshift could be an SLSN of comparable redshift. Time-domain information, or spectroscopy, is needed to distinguish a candidate TDE from an SLSN: SLSNe typically cool as they fade, whereas TDEs remain constant in color. A fading source with no color changes in over 2–3 rest-frame months (observer-frame 6–8 months between observations) is an extremely strong TDE candidate. Finally, spectroscopy can identify typical TDE emission lines, such as broad $H\alpha$ and He II, which can indicate a TDE (S. Gezari 2021). However, a class of spectral “featureless” TDEs also exists, which would not have any strong emission line features (E. Hammerstein et al. 2023). Therefore, a combination of time-domain and spectroscopic monitoring is necessary for this rare case.

**Quasars/AGN.** We model both Type 1 and Type 2 AGN for comparison. We use the following SWIRE Type 2 AGN templates: QSO2, Torus, and Sey2 (M. Polletta et al. 2007). We use the templates as they are integrated into the *pysynphot* Python package (STScI Development Team 2013), and renormalize them to $M_{UV} = -19.5$ mag. This is a typical absolute magnitude for a high-redshift obscured AGN given the JADES narrow-line AGN sample (J. Scholtz et al. 2025). We find, however, that our selection is relatively insensitive to the luminosity function of Type 2 AGN, and depends on their SED shape alone. Our Type 1 AGN model is a composite quasar template which combines the SDSS quasar spectral template in D. E. Vanden Berk et al. (2001) with NIR quasar spectral template constructed from IRTF spectra in E. Glikman et al. (2006). We calibrate the absolute magnitude of the model in the r band to the high-

redshift ($z = 7$) QSO luminosity function in Y. Matsuoka et al. (2023), with a break magnitude of $-25.6$ mag. We redshift this quasar model at redshifts up to $z = 8$, just beyond the highest-redshift confirmed quasar, J0313–1806 (F. Wang et al. 2021).

Type 2 AGN are universally too red to be contaminants in our TDE sample. A $z > 8$ Type 1 AGN can be similarly blue and have comparable apparent magnitude as a $z \sim 5$ TDE, but the power-law slope of its spectrum can be clearly distinguished from a blackbody given four photometric filters. Neither serves as a major contaminant in our sample.

**Stars.** We implement the PHOENIX stellar templates for stars with $0 < \log g < 5.5$, $2000 < T_{eff} < 24,000$, and $-2 < \text{Fe/H} < 1$ (T. O. Husser et al. 2013). We use *pysynphot* both to generate their spectra and to perform synthetic photometry in the NIRCam filters. We later use the same PHOENIX models to carefully simulate cool dwarf stars, such as M and L dwarfs. We simulate cool dwarfs to Milky Way halo distances, up to 20 kpc, although distances $> 5$ kpc are unlikely due to the scale height of the Milky Way, or until they are too faint for detection in COSMOS-Web.

Ultracool dwarf stars with temperatures $2000 \le T_{BB} \le 3200$ K can masquerade as high-redshift TDEs because they have predominantly thermal cool continuum emission which resembles redshifted hot thermal emission; e.g., a 2400 K local blackbody has the same spectral shape as a $z \sim 615,000$ K blackbody. While the dwarf star spectral templates we have are slightly flatter than blackbodies, they become a contaminant when searching for higher-redshift ($z > 6$), cooler ($<20,000$ K) TDEs. To distinguish these, we need to detect either time evolution, or a Lyman break to verify a candidate as an extragalactic transient. This is most prevalent when selecting bright ($>25$ mag) sources, but a halo star could hypothetically mimic a faint TDE candidate.

**Brown dwarfs.** We use the Sonora Bobcat models (M. S. Marley et al. 2021). Brown dwarfs are rare and they do not match the colors of TDEs, so this comparison is just for verification of their difference. They are omitted from Figure 4 for visual clarity, because they lie far outside the axis limits.

**Point-like galaxies.** A small fraction of very high-redshift galaxies observed in JWST are compact enough to render them point-like. We model these using the JAGUAR JWST Extragalactic Mock Catalog (C. C. Williams et al. 2018). This catalog models the evolving luminosity functions, spectroscopic properties, and morphologies of galaxies up to $z \sim 15$, and can reproduce observations up to $z \sim 10$. We specifically use simulations which use templates of expected $5 < z < 15$ galaxies. We select galaxies which will be point sources by selecting those which have an observed angular size equal to or less than the FWHM of the F115W point-spread function (PSF), $0.07$. We use the presynthesized photometry from these
catalogs for a wide range of galaxy types and redshifts, up to $z = 15$.

We find that >99% of the simulated unresolved galaxies will be too faint, given their color, to resemble a TDE as seen in Figure 4. However, rare unresolved extremely UV-bright galaxies are possible (e.g., M. W. Topping et al. 2024). In cases of excess UV emission, a flat optical continuum is still typically observed in these galaxies. A nondetection in F770W is a strong indicator that the candidate is likely not a galaxy. However, it is still valuable to obtain a spectrum or time-domain information to verify a TDE.

To summarize, our main persistent contaminants are very bright compact blue point-source galaxies, local M and T dwarf stars, and hostless SLSNe. All three contaminants can be ruled out spectroscopically. To rule out a galaxy contaminant photometrically one can use a Lyman break, and compare the absolute magnitude of the source to that of a TDE. To rule out a star contaminant photometrically, one only needs to observe the existence of a Lyman break. To rule out an SLSN photometrically a second epoch of imaging is needed to observe the decline of the source.

### 3. COSMOS-Web Search Methodology

COSMOS-Web is an ideal first test for this methodology. The COSMOS-Web survey images 0.54 deg² of the sky with NIRCam to depths of 27.45 mag in F115W, 27.66 mag in F150W, 28.28 mag in F277W, and 28.17 mag in F444W, and occasionally in the MIRI band F770W to ~26 mag (C. M. Casey et al. 2023). Decades of deep multiwavelength observations of the COSMOS field means that, for a given source, one can look back over 20 yr of observations (e.g., P. Capak et al. 2007; N. Scoville et al. 2007; A. M. Koekemoer et al. 2011). Furthermore, the discovery of a high-redshift TDE in COSMOS-Web could be evidence of the high-redshift TDE rate enhancements that we outline in M. Karmen et al. (2025, in preparation). Given a constant TDE rate in the entire Universe, M. Karmen et al. (2025, in preparation) predict 0.7 TDEs in the COSMOS-Web data set. However, given the early Universe TDE rate enhancements discussed in Section 5.1 and in K. Inayoshi et al. (2024), this rate could be much higher. We apply our method to the COSMOS-Web catalog (M. Shuntov et al. 2025), which combines new and archival imaging of the COSMOS field. Details on the NIRCam image reduction can be found in M. Franco et al. (2025).

To select point sources, we calculate the ratio between the flux in a 0.5 aperture and in a 0.25 aperture. We select stars by LePHARE template fitting (O. Ilbert et al. 2006; S. Arnouts & O. Ilbert 2011) to their SED shapes and apparent magnitudes, and find the aperture flux ratios for these sources. We calibrate our point-source flux ratios to the range of flux ratios for stars, as shown in Figure 5. We used the bounds of this relationship, the upper and lower limits on the flux ratio for a given magnitude, to select point sources in COSMOS-Web. We restrict only to objects which are point-like in F115W and F150W, the filters in which we most confidently expect no galaxy light beyond $z \sim 4$.

Once we have selected point sources, we use our simulated TDEs (Section 2) to define the region of color–color and color–magnitude space that high-redshift TDEs occupy. We apply cuts using color–color and color–magnitude relationships to restrict only to the regions where we believe high-

<figure><img src="image_7.png" /><figcaption>**Figure 5.** Flux ratio between a 0.25 aperture and a 0.5 aperture in F150W vs. magnitude for all sources in the COSMOS-Web catalog (gray points). Sources which are classified as stars via LePHARE SED fits (blue points) are used as a point-source selection guide. The black dashed lines show the region within which we select point sources.</figcaption></figure>

redshift TDEs occupy. This is shown in the purple region in Figure 4.

#### 3.1. Crossmatch with Previous Cosmos Data

The COSMOS field has been repeatedly surveyed for the past 20 yr, since the original HST COSMOS survey, which was carried out between 2003 October and 2005 November (A. M. Koekemoer et al. 2007). We use this original catalog to check the transient nature of our candidates. The HST COSMOS survey was conducted using the F814W filter, which does not overlap in wavelength with our NIRCam observations but allows an initial check for variability.

The COSMOS field also has deep optical imaging with the Hyper Suprime-Cam (HSC) on the Subaru telescope, originally in P. Capak et al. (2007), and later in M. Tanaka et al. (2017), to 5σ AB magnitude depths of 27.8 in the g band, 27.7 in the r band, 27.6 in the i band, 26.8 in the z band, and 26.2 in the y band. These observations were conducted between 2014 March and 2015 May, giving them an approximately decade-long observer-frame cadence between both the COSMOS HST Advanced Camera for Surveys (ACS) F814W observations, and the COSMOS-Web survey. These later HSC data comprise the COSMOS2015 catalog (C. Laigle et al. 2016).

In addition, there is previous NIR imaging taken in $YJHK_s$ to ~26 mag and in the narrowband NB118 to 24.6 mag taken from the UltraVISTA survey, with the VIRCAM instrument on the VISTA telescope (H. J. McCracken et al. 2012). We use stacks of UltraVISTA data observed between 2009 December and 2016 June. There are previous mid-infrared data from Spitzer Space Telescope/IRAC channel 1, 2, 3, and 4 images from the Cosmic Dawn Survey (Euclid Collaboration et al. 2022), which are stacks from all data taken up to 2020 January. However, the IRAC data do not have sufficient angular resolution to distinguish very small, crowded sources so we cannot often use them.

The COSMOS2020 catalog (J. R. Weaver et al. 2022) contains all of the data mentioned (with a summary of photometry limits in J. R. Weaver et al. 2022, Table 1), and is publicly archived. In this analysis, we use forced photometry for previous surveys at the location of a detection in COSMOS-Web, and classify a nondetection as any source with a <3σ detection in flux. Details on the forced photometry performed for all COSMOS-Web sources can be found in the
<figure><img src="image_8.png" /><figcaption>**Figure 6.** Left: color–color diagram of all sources in black, all point sources in gray, and all selected candidates in blue points. TDE candidate HZTDE-1 is overplotted as the red star. Right: color–magnitude diagram of all point sources in gray, and all selected candidates in blue points. TDE candidate HZTDE-1 is again overplotted as a red star.</figcaption></figure>

<figure><img src="image_9.png" /></figure>

COSMOS-Web catalog paper (M. Shuntov et al. 2025). This is useful when a TDE candidate is sufficiently bright such that a nondetection in shallower ground-based data is constraining; the detection image in COSMOS2020 is an izYJHKs stack. We use these data to extend the SEDs when visualizing candidates, but do not use them in our candidate selection or fitting in case of variability between the HSC observations and COSMOS-Web.

We search for our candidates from COSMOS-Web in the COSMOS2020 catalog using the IPAC COSMOS Archive, available at doi:10.26131/irsa178, for detections in existing COSMOS catalogs within a matching radius of 1". For the subset of candidates which are not in COSMOS2020, we download their cutouts and manually inspect them. We separate these cutouts into two groups: objects that have NIRCam F115W photometry that indicate they are above the HST F814W COSMOS magnitude limit of 27.8 mag, and those expected to be below the magnitude limit. In particular, we are interested in objects that would be bright enough to be detected in COSMOS2020 but were not found. If a source is detected in the HST 814W mosaics, we assume that is is not a transient source. However, we do not consider a nondetection in HST as confirmation of its transient nature. Although we are searching for high-redshift transients that are significantly time dilated, a *z* = 8 TDE would be bright for about three observer-frame years, so an ~20 yr baseline should be enough for any high-redshift TDE to rise or fade.

## 3.2. Search Results

We ultimately selected 1764 sources that passed our point-source cuts, and 117 passed our color–color and magnitude cuts. We select sources based on COSMOS-Web NIRCam colors alone, in order to prevent time evolution between different surveys from affecting the calculated colors. We visualize these candidates in color–color and color–magnitude space in Figure 6. Among these sources, 82 of them had no listing in the COSMOS2020 catalog. We divide these into “bright” and “faint” sources. “Bright” sources are sources with $M_{F115W} > 27.8$ AB mag, where 27.8 mag is the detection limit in HST F814W in COSMOS2020, the deepest imaging of this field. These filters do not overlap—the $\lambda_{max}$ of F814W is 9643 Å and the $\lambda_{min}$ of F115W is 9975 Å—but they are near enough

to where nondetection in F115W approximates a nondetection in F814W. Therefore, “bright” sources should have mostly been detected in HST. We find that our candidates contain 79 “bright” sources and three “faint” sources. For all 79 sources without HST catalog entries, we download the HST F814W cutouts, and search through them by hand for nondetections. We ultimately determine by visual inspection that 72 of the 79 “bright” sources which pass our cuts do indeed have a counterpart in the F814W images, but are excluded from COSMOS2020. We note that these sources often lie on the edge of a tile, in the masked region near a bright star, or have inaccurate astrometry. Among the sources not seen in F814W in manual inspection, six of them appear to be static, yet are too faint in F814W to be detected by previous HST imaging. We are left with one source which is detected in COSMOS-Web but not in COSMOS2020. The remaining candidate peaks at ~25 mag in F150W, which is >1 mag above the limit of previous infrared imaging with UltraVISTA. This source is not detected in UltraVISTA data to even $1\sigma$, confirming its nature as a transient and viable high-redshift TDE candidate. We will refer to this TDE candidate at HZTDE-1.

These candidates are selected only by JWST photometry, and the HSC photometry is consistent with a blackbody with the same peak as a high-redshift TDE for the vast majority of sources, as seen in Figures 7 and 8. Figure 8 shows an example fit of our simplified high-redshift TDE model to HZTDE-1, characterized only by absolute magnitude, black-body temperature, and redshift, to the photometry. We find that, while the model fits well to the majority of our data, the degeneracy between redshift and temperature means that the fits are extremely dependent on the starting guess and there is no way to discern a source’s redshift without observing a Lyman dropout. Additionally, shown as a comparison, this could also match the SED of an M dwarf star. Therefore, for these data it is essential that we utilize all previous HST imaging to check for variability and optical HSC data to look for a dropout.

Cross identification in the HST Source Catalog suggests that candidates that have Lyman dropouts are likely high-redshift galaxies. In the HST COSMOS catalog, many of our faint candidates are labeled as a “high-redshift galaxy,” some with spectra confirming these labels. This is explained by our point-
<figure><img src="image_10.png" /><figcaption>**Figure 7.** Top: example of a high-redshift TDE candidate which we believe to be a z = 3 galaxy contaminant. Despite having a blackbody-like SED shape in NIRCam, the HSC photometry shows that the SED is flat in the optical, with a Lyman break beginning in the g band. Its F770W flux greatly exceeds that of a blackbody. The source appears point-like in F115W and F150W, but in the F277W imaging it can be seen to be slightly extended, although compact. The best-fit galaxy template is plotted in red, star template is in light blue, and the quasar template is in purple. This galaxy does not have an F814W flux measurement in the COSMOS2020 catalog due to photometry flags, but manual inspection confirms it was detected. Bottom: example of a high-redshift TDE candidate which we believe to be a local cool dwarf star. The source has no listing in the HST Source Catalog, although it is detected in COSMOS2020. This source has no Lyman break, and is detected to 5σ in every HSC band.</figcaption></figure>

source selection: we select point sources based on their flux
ratios in two small apertures (See Section 3), rather than doing
actual morphological fitting. This means that a sample of
slightly lower-redshift, brighter and bluer galaxies could
contaminate the sample by having an approximate angular
size of order of the smaller aperture we use, rather than a
smaller angular size than the NIRCam PSF. Better morphology
selection could reduce this contamination, but nothing can
eliminate rare perfect contaminant compact, blue, high-redshift
galaxies other than time evolution. We show an example of
these high-redshift galaxy contaminants in Figure 7. HSC

photometry confirms that it is indeed not a blackbody, and has
a Lyman dropout in the g band. Additionally, while it appears
point-like in F115W and F150W, the F277W imaging shows
that it is an extended source. The object is just under a 5σ
detection in the HST image, but is visible in the cutout. We
also search all of our objects in the Chandra X-ray imaging of
the COSMOS field, and find no X-ray sources associated with
any object (F. Civano et al. 2016). This is expected for a high-
redshift TDE, because their soft X-ray spectrum would be
completely absorbed by the circumgalactic medium (CGM)
beyond z ~ 3.
<figure><img src="image_11.png" /><figcaption>**Figure 8.** Cutouts (top panels) and SED (bottom panel) of the high-redshift TDE candidate, HZTDE-1. The cutouts include imaging from UltraVISTA, HSC, HST/ACS, and JWST/NIRCam. The source is only detected to >3σ in the NIRCam images. The SED shows the observed SED as red circles, the best-fit SLSN spectrum (blue line) and TDE spectrum (red line), and all photometric upper limits as downward-pointing triangles. Error bars in magnitude exist for the NIRCam data but are too small to be seen. The transmission curve for each filter is plotted below it. A simulated spectrum of TDE 2019qiz at z = 4 is overplotted as a dotted line.</figcaption></figure>

Objects without a Lyman dropout are likely cool dwarf stars. Stars with temperatures 2400 K < *T* < 3500 K have blackbody peaks around 1.2 μm, the same observed wavelength as a *z* > 5 TDE. These stars are abundant in the Milky Way, although are less common when looking out of the Galactic plane. Figure 7 shows a source which we believe is a star. It has no listing in the COSMOS2020 catalog, but manual inspection can identify the corresponding object in previous COSMOS imaging.

**4. Properties of the Tidal Disruption Event Candidate HZTDE-1**

The TDE candidate HZTDE-1 is shown in Figure 8. This source was the only object which is a point source in NIRCam, has no optical counterpart, has the SED shape of a high-redshift blackbody, and does not appear in the COSMOS2020 catalog. Furthermore, HZTDE-1 is not detected in previous deep UltraVISTA imaging, which verifies the transient nature of the object. Due to possible contamination from a nearby galaxy, we verify the nondetection in HSC and UltraVISTA by performing aperture photometry to manually compare the flux at the location of HZTDE-1 to the background flux. We describe this procedure in the Appendix, and find that there truly is no detection above the background in any previous optical or NIR imaging. LePHARE spectral template fitting

does not settle on a good classification for this source given its SED: its reduced chi-squared statistic (per degree of freedom) for the best star template is $\chi^2_\nu = 477$, for an AGN template is $\chi^2_\nu = 1050$, and $\chi^2_\nu = 401$ for the best galaxy template, which fits a galaxy at $z = 7.33$. We also show in Figure 8 a composite spectrum of TDE 2019qiz, which is constructed by connecting an UV spectrum taken with HST/UVIS (T. Hung et al. 2021) and an optical spectrum taken with the X-shooter instrument on the Very Large Telescope (M. Nicholl et al. 2020). We select this TDE due to its broad wavelength coverage near maximum brightness; it best fits the HZTDE-1 photometry at $z = 4.1$ due to its lower blackbody temperature (15,000 K), but we simulate its spectrum at $z = 5$ to show the locations of common TDE emission lines.

We approximate its redshift through maximum a posteriori fitting of our blackbody TDE model with Gaussian uncertainties optimizing through Markov Chain Monte Carlo (MCMC) sampling. We utilize the ZTF TDE sample's distribution of TDE temperatures and luminosities as priors. Our prior on redshift is a uniform distribution between $z = 3.5$ and $z = 7.5$. We estimate a lower bound on the redshift through our simulations of TDE hosts; we expect that the lowest-mass TDE host would not be detected in the two short-wavelength NIRCam filters of COSMOS-Web at $z \ge 3.5$. We can set a strict upper limit on the redshift because at $z = 7.5$, the F115W
<figure><img src="image_12.png" /><figcaption>**Figure 9.** MCMC samples of the posterior distribution for each parameter in the TDE model fit to the HZTDE-1 photometry. Error bars are wide due to degeneracies between temperature, redshift, and luminosity. We use the observed temperatures and maximum luminosities of ZTF TDEs as priors. We also set bounds on the redshift fit as described in Section 4.</figcaption></figure>

emission would have been Lyman absorbed. We find our most likely TDE to have $z = 5.02_{-1.11}^{+1.33}$, $M_g = -21.15_{-0.13}^{+0.21}$, and $\log(T_{BB}) = 4.31_{-0.09}^{+0.09}$. We show the MCMC sampling of the posterior distribution in Figure 9. If HZTDE-1 were as cool as the lowest-temperature known TDEs, $\sim 10^4$ K, it could be as low redshift as $z = 2$; however, as $z = 2$ a typical $10^{10} M_\odot$ host galaxy would be resolved in COSMOS imaging.

## 4.1. Comparison to Supernova Models

There are three nearby galaxies that HZTDE-1 could belong to if it is a lower-redshift SN. We assess its possible association with the galaxy directly above it in the cutouts

shown in Figure 8, because it is the closest galaxy, with an angular separation of 0.998, the brightest galaxy with $M_{F444W} = 23.7$ AB mag, and the most extended with an effective radius $R_e = 0.20$ as modeled by GALFIT (C. Y. Peng et al. 2002). The GALFIT model for the sources in the field is shown in Figure 10, alongside the F444W image and the residuals. The best-fit galaxy spectrum to this source's SED has a photometric redshift $z_{phot} = 1.75_{-0.07}^{+0.1}$. This galaxy has a slightly above average best-fit specific star formation rate (sSFR) given its photometric redshift, of $\log(sSFR)/M_\odot$ yr$^{-1} = -8.67$. An especially high star formation rate (SFR) would support the occurrence of an SN in its outskirts (M. T. Botticella et al. 2012). The SED is well sampled from the HSC g band to NIRCam
<figure><img src="image_13.png" /><figcaption>**Figure 10.** GALFIT modeling of the morphology of the sources in the F444W imaging of HZTDE-1. We display the size of one DLR from the galaxy to the transient to show the accuracy of the modeling. The HZTDE-1 is >5 DLR from the galaxy, and thus unlikely to be associated. In shorter-wavelength filters, this DLR separation increases.</figcaption></figure>

<figure><img src="image_14.png" /><figcaption>**Figure 11.** Modeled spectra and synthetic photometry of best-fit SNe Ia, SNe Ib/c, SNe IIP, and SNe IIn compared to the SED of HZTDE-1. All SNe are within $z = 1.75 \pm 0.1$, in order to be associated with the most likely host galaxy. SNe Ia and SNe Ib cannot successfully fit the SED. A very bright SN IIP or SN IIn could fit the majority of the SED, but struggle to produce the same infrared luminosity.</figcaption></figure>

F444W, and the model spectrum fits accurately with a $\chi^2 = 1.72$ per degree of freedom. We follow the technique developed in R. R. Gupta et al. (2016) to assess host galaxy association for a given SN through calculating the directional light radius (DLR), which is the elliptical radius of a galaxy in the direction of the SN. They then calculate the $d_{DLR}$, which is the distance between the SN and the galaxy normalized by the DLR. They utilize both HST/ACS data and MICECATv2.0 simulations to show that any SN with a galaxy >5 DLR away should be assigned “hostless,” and achieve ~95% completeness with a similar cut. We calculate the unitless $d_{DLR}$ for HZTDE-1 to be 5.05 relative to the nearest galaxy, making it highly likely to be a hostless transient. This $d_{DLR}$ is even higher for the short-wavelength NIRCam filters (>6 DLR in F115W), which have higher spatial resolution.

We assume that HZTDE-1 is unlikely to be a “hostless” non-SLSN. However, given the rare case that HZTDE-1 is associated with the nearest galaxy despite extreme distance, we fit SN SEDs for each SN subtype at its photometric

redshift, $z = 1.75 \pm 0.10$. We use the full range of SN properties described in Section 2.5. For every SN subtype, we fit every available model in *sncosmo* (K. Barbary et al. 2016), extending to the infrared with a blackbody when the model has insufficient wavelength range. We do not fit models for Population III SNe, pair-instability SNe, or other exotic transients. We show our best-fit SN spectra in Figure 11, and their respective light curves in Figure 12. We find that HZTDE-1 is significantly too red to be an SN Ia at $z \sim 1.75$ and too bright to be an SN Ia at $z > 2$. HZTDE-1 is $\gtrsim 1$ mag brighter than an SN Ib/c at $z \sim 1.75$. The SED is somewhat plausibly explained by an anomalously bright SN IIP before maximum brightness or a bright SN IIn prior to maximum brightness, but both underpredict the flux in F444W at $z \sim 1.75$, which would be $1.6 \mu m$ in the rest frame. These best models are shown in Figure 11. This excess flux could be explained by a contribution from thermal dust emission, but given the extreme offset from the potential host it is unlikely
<figure><img src="image_15.png" /><figcaption>**Figure 12.** Light curves of best-fit SN models to HZTDE-1, given that they are at a redshift within 0.1 of the closest galaxy. Each panel is in a single COSMOS-Web NIRCam filter. The best-fitting models, SNe IIP and IIn, do not adequately explain the F444W flux, which would be at ~1.6 µm in the rest frame.</figcaption></figure>

that the SN would be embedded in dust. In summary, for HZTDE-1 to be an SN associated with its nearest galaxy it must be an anomalously bright SN IIn at an extreme offset with an infrared flux excess.

There is a possibility that HZTDE-1 is an SLSN, as shown in Figure 8. SLSNe have similar intrinsic luminosities to TDEs and their spectral continua are primarily blackbody thermal emission (S. Gomez et al. 2024). Their host galaxies tend to be less massive, meaning that at large enough distances ($z \gtrsim 3$) they may also outshine their hosts and be point sources. Therefore, to be certain whether HZTDE-1 is a high-redshift TDE or a high-redshift hostless SN, either follow-up spectroscopy or monitoring of its photometric evolution is necessary. With a single photometric detection, the relative rates of TDEs and SLSNe at $z > 3$ are the main factor that determines what HZTDE-1 likely is. Current best estimates of the volumetric rate of SLSNe place them somewhere between $0.91 \times 10^{-7} \text{ SNe yr}^{-1} \text{ Mpc}^{-3}$ at $z = 1$ (S. Prajs et al. 2017) and $1.99 \times 10^{-7} \text{ SNe yr}^{-1} \text{ Mpc}^{-3}$ at $z = 0.2$ (R. M. Quimby et al. 2013), as compared to the current best estimate for the local optical TDE volumetric rate of $3.1 \times 10^{-7} \text{ TDEs yr}^{-1} \text{ Mpc}^{-3}$. M. Tanaka et al. (2013) predict the volumetric rate of SLSNe at higher redshifts (up to $z \gtrsim 10$) by scaling it with the cosmic SFR density using two SFR models (A. M. Hopkins & J. F. Beacom 2006; B. E. Robertson & R. S. Ellis 2012). They calibrate to the low-redshift SLSN rate, and account for the IMF and the fraction of massive stars to find that the SLSN volumetric rate increases with redshift until $z \sim 5$, where the

SFR density peaks, and then the rate decreases with redshift indefinitely. At its maximum, $z \sim 5$, the volumetric SLSN rate is $10 \times$ the local rate. We expect the TDE rate to also be elevated by at least $10 \times$ the local rate, as shown in M. Karmen et al. (2025, in preparation). HZTDE-1 would need to be blue for an SLSN, with a best-fit temperature of 24,000 K at a best-fit redshift $z = 3.6$, but this is possible briefly before peak and during peak brightness. However, this fit was performed without a prior on SLSN behavior and a more reasonable 19,000 K SN will fit at $z = 3.2$. Indeed, because of the low-mass nature of SLSN hosts, the SN could occur in a lower-redshift, very faint host galaxy and would be intrinsically redder. Given the sample of host galaxies for the Palomar Transient Factory observed SLSNe (D. A. Perley et al. 2016), these hosts could drop out of the COSMOS-Web survey as soon as $z \sim 1.7$. This is around the peak of the cosmic SFR and would imply a reasonable number of hostless SLSNe. Therefore, without further monitoring, the possibility of a lower-$z$ SLSN is equally likely to a TDE.

**5. Discussion and Future Confirmation**

In this work, we model the properties of TDEs at high redshift assuming that their populations are similar to those at low redshift. We argue that the assumptions made about their host galaxies (Section 2.1) and TDE spectra (Section 2.3) set limits on the colors and morphologies of high-redshift TDEs. However, any number of these assumptions can be relaxed. In
future work, for example, modeling of TDEs in extended
hosts, or modeling of dust-extincted TDE emission can
increase the efficiency of searches for TDEs in wide-field
surveys. As this search offers an opportunity to study the UV
emission shortward of 2000 Å, which is usually not observed,
deviations from blackbody assumptions about TDE spectra,
such as those mentioned in Section 2.4 may emerge from
studies of high-redshift TDEs.

Either spectroscopic or photometric follow-up could be used
to confirm HZTDE-1's classification as a TDE and its redshift.
TDEs have blue spectra with blackbody continua and broad
hydrogen and/or helium emission features that narrow as the
TDE evolves. A key distinction between TDEs and SNe is
their decline: TDEs do not change temperature as they cool
(S. van Velzen et al. 2020), while SNe cool rapidly after peak,
typically 5000–8000 K (S. Gomez et al. 2024; A. Aamer et al.
2025). Without imaging of a host galaxy to verify that
HZTDE-1 is nuclear, either identification of spectroscopic
features or photometric monitoring is needed to confidently
confirm it as a TDE. However, because of the degeneracy
between redshift, luminosity, and temperature, a spectrum of
the TDE or host would be needed to calculate a redshift.
Spectroscopy, specifically in the infrared with JWST's
NIRSpec, is key to observing common TDE emission lines.
X-ray emission is not expected because, as mentioned, the
CGM will absorb all of the soft X-ray emission characteristic
of TDEs at $z > 3$. Longer wavelengths may be worth
monitoring for later-time infrared flares due to dust echoes
(S. van Velzen et al. 2016).

If HZTDE-1 is a high-redshift SLSN, its discovery and
classification will be valuable for understanding stellar
evolution at higher redshift. SLSNe are expected to result
from the explosions of massive stars (up to tens of solar
masses; P. K. Blanchard et al. 2020) and have a strong
preference for galaxies with low metallicities (D. A. Perley
et al. 2016; S. Schulze et al. 2018; C. Cleland et al. 2023). To
first order, the cosmic rates of SLSNe should follow the
cosmic SFR (M. Tanaka et al. 2013). Deviations from this
relationship could provide insight into the abundance of metal-
poor galaxies at earlier cosmic times. The methodology
outlined in this paper could identify potentially hundreds of
high-redshift SLSNe in upcoming wide-field surveys (e.g., the
Nancy Grace Roman HLWAS) and therefore could lead to
measurements of how their rates and hosts change with
redshift. This in turn can be used to study how massive stars
form and evolve as the metallicity of the Universe changes
over cosmic time.

5.1. *Tidal Disruption Event Rates in COSMOS-Web*

In the companion work (M. Karmen et al. 2025, in
preparation), we calculate observed TDE rates as a function
of redshift in the LSST, Nancy Grace Roman, and the
COSMOS-Web surveys. We find that if we simply extrapolate
the local TDE rate, scaled by the number density of SMBHs
(F. Shankar et al. 2009) that can disrupt a main-sequence star
(following I. Donnarumma et al. 2015; H. Sun et al. 2015;
C. S. Kochanek 2016), we get a 20% chance of finding a single
TDE in the COSMOS-Web survey. We show, however, that
the observed properties of high-redshift galaxies would imply
a dramatically enhanced rate of TDEs at high redshifts of
$z > 5$, and perhaps as low as $z = 2$. Namely, many galaxies are
observed to be centrally compact (J. F. W. Baggen et al. 2023;

S. L. Finkelstein et al. 2023; J. S. Kartaltepe et al. 2023; C. A. Guia et al. 2024), and may host nuclear stellar clusters (M. Ricotti et al. 2016; G. Sun et al. 2023) at high redshifts. This increases the central stellar density, $\rho_*$, by 1–2 orders of magnitude (J. F. W. Baggen et al. 2024), which in turn can easily lead to a ×100 TDE rate enhancement assuming a galaxy’s TDE rate scales as $\propto \rho_*^{0.65}$ (H. Pfister et al. 2020), or even higher given the more dramatic observed scaling with stellar density $\propto \rho_*^{0.9}$ (O. Graur et al. 2018). This enhancement is in agreement with simulations of TDEs in galaxies with nuclear stellar clusters (H. Pfister et al. 2020; K. Kritos et al. 2024). Additionally, galaxy mergers are shown to enhance TDE rates both observationally and theoretically. Host studies of optical–UV TDEs demonstrate a clear preference for galaxies which are believed to be the products of mergers (K. D. French et al. 2020; T. Wevers & K. D. French 2024), and the TDE rate is seen in hydrodynamical simulations to be enhanced by an order of magnitude for 100 Myr after a merger (H. Pfister et al. 2021). With a galaxy merger rate that increases as a function of redshift, peaking at cosmic noon (E. Ventou et al. 2017; K. Duncan et al. 2019; M. Perna et al. 2025), we predict TDE rates to be enhanced from mergers as well. In previous works (e.g., I. Donnarumma et al. 2015; C. S. Kochanek 2016), the volumetric TDE rate has been scaled with a quickly evolving SMBH mass function, and as a result, it was expected that TDE rates decrease rapidly with the SMBH mass function as a function of redshift. However, given the abundance of supermassive and overmassive BHs detected at early cosmic times (e.g., V. Kokorev et al. 2023; R. L. Larson et al. 2023; R. Maiolino et al. 2024), this phenomenon will be significantly reduced. TDEs are among the few luminous phenomena very close to an SMBH, and are believed to produce super-Eddington accretion at early times (L. E. Strubbe & E. Quataert 2009) so their study at high redshifts can give an indication to the mechanisms by which early SMBHs accrete and grow.

The TDE rate can still be enhanced at high redshifts without
the detection of an overabundance of TDEs in JWST imaging.
Samples of infrared-bright TDEs find that the majority of
TDEs with no detected optical–UV emission occur in star-
forming galaxies (M. Masterson et al. 2024). It is known that
the fraction of star-forming galaxies increases with redshift
beyond $z > 2$ (P. Madau et al. 1996). Therefore, if the majority
of high-redshift TDEs occur in star-forming galaxies, it
follows that their UV emission may be dust obscured,
reprocessed, and emitted as rest-frame infrared emission. This
possibility is supported by K. Inayoshi et al. (2024), who
consider the enhancement of the rate of TDEs in obscured
AGN. In order to detect the remainder of high-redshift TDEs,
if they reside in star-forming galaxies, one may need to look
for rest-frame infrared dust echoes. This rest-frame UV search
is a first probe of these rate enhancements. In order to confirm
the classification of HZTDE-1, spectroscopic follow-up must
be done before the source completely fades.

6. Conclusion

In this work we search the COSMOS field for ongoing high-
redshift TDEs, and successfully identify one $z \sim 5$ TDE
candidate. We summarize our findings below.

1. We show that beyond $z > 4$, given both the nature of TDE preferred host galaxies and the low masses of
galaxies at high redshift, the high-redshift counterparts to local, optical–UV TDEs will be hostless point sources. We demonstrate that they will be k-corrected into the wavelength range of JWST’s NIRCam and could be detected to $z \sim 10$.

2. We develop criteria for identifying candidate $z > 4$ TDEs given their NIRCam colors, comparing to contaminant stars, galaxies, AGN, and SNe. For regions of potential contamination, we pose methods for distinguishing TDEs from these contaminants. This methodology can be applied to any deep field survey, and will yield a wealth of high-redshift TDEs from the Nancy Grace Roman HLWAS. This methodology could also be used to identify a range of other hostless transients in upcoming surveys.

3. We apply this selection method to the COSMOS-Web catalog, and identify 117 sources among >700,000 that pass our cuts. We systematically check these sources for lack of variability using the COSMOS2020 catalog, which compiles all previous imaging of the COSMOS field, and find one source which is a confirmed transient. We call this TDE candidate HZTDE-1.

4. We model HZTDE-1 as a possible SN, both through SED modeling and host galaxy association. We find that HZTDE-1 is >5 DLR from the nearest galaxy, making an association extremely unlikely. We find that while the SED cannot be explained by an SN I, SNe II (particularly SNe IIn) at $z \sim 2$ can explain the SED mildly well, except for the farthest infrared emission. However, it is still possible that this transient is a “hostless” luminous or superluminous SN IIn.

5. We model HZTDE-1 as a possible TDE, and find that the most likely TDE has an effective blackbody temperature of $\log(T_{BB}) = 4.31 \pm 0.09$, absolute g-band magnitude of $M_g = -21.15_{-0.13}^{+0.21}$, and a redshift of $z = 5.02_{-1.11}^{+1.33}$.

Follow-up observations of HZTDE-1, for photometric fading and for spectroscopic information, are crucial for understanding its nature and confirming its redshift. If HZTDE-1 is a TDE, it could confirm an enhancement of the volumetric rate of TDEs in the high-redshift Universe. As TDEs offer a probe of central SMBH mass independently from the virial methods that use AGN emission, a population of TDEs at high redshifts could offer insight into the nature of the SMBH mass function as a function of cosmic time. This, in turn, could place additional constraints on the methods by which SMBHs seed and grow.

## Acknowledgments

The authors thank Christina Lindberg for discussions about dust, and Sean Carroll for his discussion of source selection. We also thank Muryel Guolo for his TDE wisdom and cynicism. This paper is based in part on observations with the NASA/ESA Hubble Space Telescope and James Webb Space Telescope obtained from the Mikulski Archive for Space Telescopes at STScI. This research has made use of the NASA/IPAC Infrared Science Archive, which is funded by the National Aeronautics and Space Administration and operated by the California Institute of Technology. This material is based upon work supported by the National Science Foundation Graduate Research Fellowship under grant No. DGE2139757. The French contingent of the COSMOS team is partly supported by the Centre National d'Etudes Spatiales (CNES). O.I. acknowledges the funding of the French Agence Nationale de la Recherche for the project iMAGE (grant ANR-22-CE31-0007). This work was made possible by utilizing the CANDIDE cluster at the Institut d'Astrophysique de Paris. The cluster was funded through grants from the PNCG, CNES, DIM-ACAV, the Euclid Consortium, and the Danish National Research Foundation Cosmic Dawn Center (DNRF140). It is maintained by Stephane Rouberol.

## Appendix

### Verification of Optical Nondetection

Because of the small angular distance between HZTDE-1 and the nearby galaxy, we wanted to verify that HZTDE-1 was not obscured by the galaxy in the lower-resolution UltraVISTA imaging. We use aperture photometry to test this as follows. First, in pixel space, we calculate the location of the centroid of the galaxy in each filter by fitting a 2D Gaussian to the data using the *photutils* Python package (L. Bradley et al. 2025). Filter by filter, we find the angular separation between the galaxy centroid and the PSF-modeled coordinates of HZTDE-1, which we call *d*. Starting with the location of HZTDE-1, we place a series of apertures, each with a radius of 2 pixels, at an angular distance *d* from the galaxy, offset from each other by a rotation angle of 20°, as shown in Figure 13. We calculate both the mean flux and the total flux within each aperture in UltraVISTA and find no increase in the flux at the location of HZTDE-1 compared to the background in any filter, as seen in Figure 14. We then perform the same procedure using the JWST imaging, with apertures with a radius of 3 pixels, as seen in Figure 15. As expected, we find a ×1000 increase in flux relative to the background in NIRCam, as seen in Figure 15.
UVISTA $K_s$ (2012)

<figure><img src="image_16.png" /></figure>

**Figure 13.** Left: UltraVISTA $K_s$-band imaging of galaxy near HZTDE-1, surrounded by the apertures described in here in the Appendix. The red aperture is centered on HZTDE-1. Right: JWST/NIRCam F150W imaging of the same galaxy and HZTDE-1, surrounded by apertures in the same location. Again, visibly, the red aperture contains HZTDE-1. For visualization purposes and because JWST has a very high angular resolution, the JWST apertures are slightly smaller.

JWST F150W (2024)

<figure><img src="image_17.png" /></figure>

<figure><img src="image_18.png" /></figure>

**Figure 14.** Flux from UltraVISTA imaging in the apertures from Figure 13, with 0° corresponding to the location of HZTDE-1. The left figure is the mean flux within each aperture for each filter, and the right figure is the total flux within each aperture. Neither has an increase in flux at the location of HZTDE-1 in any filter.

<figure><img src="image_19.png" /></figure>

**Figure 15.** Flux from JWST imaging using apertures in the same locations as for UltraVISTA relative to the nearby galaxy. For visualization purposes and because JWST has a very high angular resolution, the apertures are slightly smaller. 0° corresponds to the location of HZTDE-1. Using NIRCam, there is a clear detection of HZTDE-1 with respect to the background.

## ORCID iDs

Mitchell Karmen https://orcid.org/0000-0003-2495-8670

Suvi Gezari https://orcid.org/0000-0003-3703-5154

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

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

Colin Norman https://orcid.org/0000-0002-5222-5717

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

Justin Pierel https://orcid.org/0000-0002-2361-7201

David Coulter https://orcid.org/0000-0003-4263-2228

Armin Rest https://orcid.org/0000-0002-4410-5387

Ori Dr. Fox https://orcid.org/0000-0003-2238-1572

Yukta Ajay https://orcid.org/0009-0007-8764-9062

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

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

Seiji Fujimoto https://orcid.org/0000-0001-7201-5066

Sebastian Gomez https://orcid.org/0000-0001-6395-6702

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

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

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

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

Zachary G. Lane https://orcid.org/0009-0003-8380-4003

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

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

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

Matthew R. Siebert https://orcid.org/0000-0003-2445-3891

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

Thomas Wevers https://orcid.org/0000-0002-4043-9400

Yossef Zenati https://orcid.org/0000-0002-0632-8897

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