# Disturbed Cold Gas in Galaxy and Structure Formation

Siwei Zou, Robert A Simcoe, Patrick Petitjean, Céline Péroux, Jaclyn B Champagne, Feige Wang, Jinning Liang, Fangzhou Jiang, Zihao Li, Wen Sun, et al.

► To cite this version:

Siwei Zou, Robert A Simcoe, Patrick Petitjean, Céline Péroux, Jaclyn B Champagne, et al. Disturbed Cold Gas in Galaxy and Structure Formation. The Astrophysical Journal Letters, 2025, 994 (2), pp.L53. 10.3847/2041-8213/ae1234 . hal-05470302

HAL Id: hal-05470302

https://hal.science/hal-05470302v1

Submitted on 21 Jan 2026

HAL is a multi-disciplinary open access
archive for the deposit and dissemination of sci-
entific research documents, whether they are pub-
lished or not. The documents may come from
teaching and research institutions in France or
abroad, or from public or private research centers.

L'archive ouverte pluridisciplinaire HAL, est
destinée au dépôt et à la diffusion de documents
scientifiques de niveau recherche, publiés ou non,
émanant des établissements d'enseignement et de
recherche français ou étrangers, des laboratoires
publics ou privés.

<figure><img src="image_1.png" /></figure>

Distributed under a Creative Commons CC BY 4.0 - Attribution - International License
<figure><img src="image_2.png" /></figure>

# Disturbed Cold Gas in Galaxy and Structure Formation

Siwei Zou<sup>1,2</sup>, Robert A. Simcoe<sup>3</sup>, Patrick Petitjean<sup>4</sup>, Céline Péroux<sup>5,6</sup>, Jaclyn B. Champagne<sup>7</sup>, Feige Wang<sup>8</sup>, Jinning Liang<sup>9,10</sup>, Fangzhou Jiang<sup>10</sup>, Zihao Li<sup>11,12</sup>, Wen Sun<sup>10,9</sup>, Xiaohui Fan<sup>7</sup>, Jinyi Yang<sup>8</sup>, Luis C. Ho<sup>10,9</sup>, Xiaojing Lin<sup>7,13</sup>, Jianan Li<sup>13</sup>, Jianwei Lyu<sup>7</sup>, Lile Wang<sup>10</sup>, Weizhe Liu<sup>7</sup>, Emanuele Paolo Farina<sup>14</sup>, Xiangyu Jin<sup>7</sup>, and Cheng Cheng<sup>1</sup>

Received 2025 August 21; revised 2025 September 28; accepted 2025 October 12; published 2025 November 27

## Abstract

The cold gas in the circumgalactic medium (CGM) and its interaction with galaxies remain poorly understood. Strong Mg II (λλ2796, 2803) absorptions seen in background quasar spectra reveal large reservoirs of neutral hydrogen, potentially serving as progenitors of star-forming galaxies at high redshifts. In this study, we search for galaxies in the vicinity of very strong Mg II absorbers (rest-frame equivalent width $W_r > 2$ Å) with high kinematic velocities (>500 km s⁻<fnref n="1" />) at 2.0 < z < 6.0. Observations were conducted with the Very Large Telescope/MUSE, JWST/NIRCam, and the Atacama Large Millimeter/submillimeter Array to detect Lyα and nebular emission lines and dust continuum emission. We identify two Lyα emitters associated with a strong Mg II absorber pair, separated by ~1000 km s⁻<fnref n="1" /> at z ~ 4.87, in the vicinity of quasar J1306+0356. We observe relative differences in metallicity, dust content, and ionization states in this ultralarge absorption pair system, indicating potential metal and dust transfer within the system. For another strong Mg II absorber at z = 2.5662 ($W_r = 2.638 ± 0.124$ Å), toward a second quasar J0305–3150, we detect a dusty star-forming galaxy at a projected distance of D = 38 kpc. This galaxy exhibits prominent He I, [S III], and Paschen γ lines, along with significant dust continuum. It has a star formation rate of ~121 ± 33 $M_\odot$ yr⁻<fnref n="1" /> and likely harbors a rotating disk. These findings tentatively suggest that cold gas at high redshifts fuels disk formation and participates in metal and dust transfer within overdense CGM regions.

*Unified Astronomy Thesaurus concepts: Circumgalactic medium (1879); Dust continuum emission (412); Galaxy structure (622)*

## 1. Introduction

Cold and cool gas ($T \le 10^4$ K) play a key role in galaxy formation and structural evolution. Simulations predict that cold gas flows into galaxies through cosmic filaments, further driving disk formation and galaxy evolution (see the review by C.-A. Faucher-Giguère & S. P. Oh 2023 and references therein). The cold-gas accretion mode in the circumgalactic medium (CGM), and its dependence on the dark matter halo mass and redshift, remains to be fully characterized. Resolving the kiloparsec-scale kinematics and dynamics of cold gas interacting with the disk, dust, and metals in environments has also yet to be fully determined, particularly at $z > 2$.

Mg II doublet (λλ2796, 2803) absorption is ubiquitously observed in the gaseous halos in and around galaxies and is

associated with cool ($T \sim 10^4$ K) gas. Strong Mg II (rest-frame equivalent width or EW $W_r > 0.3$ Å) is detected in connection with optically thick neutral hydrogen gas ($10^{16.0} < N(HI) < 10^{22.0}$ cm⁻<fnref n="2" />) and, consequently, with star-forming activities (L. A. Barnes et al. 2014). The evolution of strong Mg II absorbers is consistent with the trend of the global cosmic star formation rate (SFR) at 2 < z < 6 (S.-F. S. Chen et al. 2017; S. Zou et al. 2021; A. M. Sebastian et al. 2024). Strong Mg II systems are detected in association with star-forming galaxies (B. Ménard et al. 2011; P. Noterdaeme et al. 2012; T.-W. Lan & H. Mo 2018; S. Zou et al. 2024a) and metal-enriched overdense regions (R. Dutta et al. 2020; Y. Wu et al. 2023; S. Zou et al. 2024a, 2024b).

Ultrastrong Mg II systems (hereafter, USMg II; $W_r(\lambda\lambda2796) > 3$ Å) can trace cold and dense gas, but their origin remains uncertain. Kinematically broad Mg II systems have been observed to be associated with highly disturbed cold (and even molecular) gas (S. Zou et al. 2018). Two primary scenarios have been proposed to explain the origin of USMg II absorbers. (a) They

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

Original content from this work may be used under the terms of the [Creative Commons Attribution 4.0 licence](https://creativecommons.org/licenses/by/4.0/). Any further distribution of this work must maintain attribution to the author(s) and the title of the work, journal citation and DOI.

<footnote n="1">¹ Chinese Academy of Sciences South America Center for Astronomy, National Astronomical Observatories, CAS, Beijing 100101, People's Republic of China; siwei1905@gmail.com</footnote>

<footnote n="2">² Departamento de Astronomía, Universidad de Chile, Casilla 36-D, Santiago, 7591245, Chile</footnote>

<footnote n="3">³ MIT Kavli Institute for Astrophysics and Space Research, 77 Massachusetts Avenue, Cambridge, MA 02139, USA</footnote>

<footnote n="4">⁴ Institut d'Astrophysique de Paris 98bis Boulevard Arago, 75014, Paris, France</footnote>

<footnote n="5">⁵ European Southern Observatory, Karl-Schwarzschild-Str. 2, 85748 Garching near Munich, Germany</footnote>

<footnote n="6">⁶ Aix Marseille Univ., CNRS, LAM (Laboratoire d'Astrophysique de Marseille), UMR 7326, F-13388 Marseille, France</footnote>

<footnote n="7">⁷ Steward Observatory, University of Arizona, 933 N Cherry Avenue, Tucson, AZ 85721, USA</footnote>

<footnote n="8">⁸ Department of Astronomy, University of Michigan, 1085 S. University Ave., Ann Arbor, MI 48109, USA</footnote>

<footnote n="9">⁹ Department of Astronomy, School of Physics, Peking University, Beijing 100871, People's Republic of China</footnote>

<footnote n="10">¹⁰ Kavli Institute for Astronomy and Astrophysics, Peking University, Beijing 100871, People's Republic of China</footnote>

<footnote n="11">¹¹ Cosmic Dawn Center (DAWN), Niels Bohr Institute, University of Copenhagen, Jagtvej 128, DK-2200, Copenhagen N, Denmark</footnote>

<footnote n="12">¹² Niels Bohr Institute, University of Copenhagen, Jagtvej 128, DK-2200, Copenhagen N, Denmark</footnote>

<footnote n="13">¹³ Department of Astronomy, Tsinghua University, Beijing 100084, People's Republic of China</footnote>

<footnote n="14">¹⁴ Gemini Observatory, NSF's NOIRLab, 670 N A'ohoku Place, Hilo, HI 96720, USA</footnote>
<figure><img src="image_4.png" /></figure>

<figure><img src="image_5.png" /><figcaption>**Figure 1.** Left: spatial distribution of the absorbing gas along J1306+0356 (located at the center of the VLT/MUSE cube) and the two LAEs, which are offset by ~200 kpc from the gas. The background image is the variance-weighted white-light image generated by MUSELET (for details, see Section 2.6). Narrowband images of the two detected LAEs are presented. The absorbing gas structure is composed of two VSMG II systems, with a total velocity width $\Delta v$ greater than 1000 km s$^{-1}$. Right: spatial distribution of the absorbing gas along the J0305–3150 sight line (upper right corner) and the host galaxy, as detected with JWST/NIRCam data. The red dashed line is the fitted galaxy major axis.</figcaption></figure>

may arise from starburst-driven outflows or tidally stripped gas resulting from a major interaction (D. B. Nestor et al. 2011). In this scenario, the $W_r$ and velocity spread ($\Delta v$) of the gas correlate with the SFR and luminosity of the host galaxy (G. G. Kacprzak et al. 2010). (b) Multiple “normal” galaxies within a galaxy group could contribute to the strong absorption strength and kinematics observed (G. G. Kacprzak et al. 2010; K. H. R. Rubin et al. 2011, 2014). Both scenarios have observational support at $z < 1$ (D. B. Nestor et al. 2007; J.-R. Gauthier 2013; L. K. Guha et al. 2022, 2024). D. B. Nestor et al. (2007) and G. E. Prochter et al. (2006) studied USMg II systems at $z < 1$ and identified bright galaxies at relatively low impact parameters relative to the absorption, supporting the outflow model. Additionally, J.-R. Gauthier (2013) reported a USMg II system at $z \sim 0.5$ associated with three galaxies within 200 kpc, suggesting the possibility of the galaxy group scenario. It is also plausible that these two mechanisms coexist.

The connections between the physical properties of the multiphase CGM and the surrounding environment have been investigated in several surveys, using MUSE, the Atacama Large Millimeter/submillimeter Array (ALMA), and JWST. The MUSE-ALMA Haloes Survey (C. Péroux et al. 2022) combined data from the Very Large Telescope (VLT)/MUSE, ALMA, and the Hubble Space Telescope (HST) to investigate strong H I and metal-absorbing gas at $0.3 < z < 1.4$. The study revealed that damped Ly$\alpha$ systems (DLAs; $\log N(HI) > 20.3$) with strong Mg II absorption at $z < 1$ are associated with multiple star-forming galaxies. The kinematics of the absorbing gas are linked to the ionized and molecular gas in the surrounding galaxies (C. Péroux et al. 2019; R. Szakacs et al. 2021; S. Weng et al. 2023). The MusE GAs FLOw and Wind survey has identified a bimodal relationship between the azimuthal angle and metallicity of cool gas at $z \sim 1$ (M. Wendt et al. 2021), suggesting that Mg II gas traces either galactic inflow (J. Zabl et al. 2019) or galactic outflow (I. Schroetter et al. 2019). The MUSE Analysis of Gas around Galaxies

(MAGG) survey investigates the connections between [O II] emission and Mg II absorbers at $z \sim 1$ (R. Dutta et al. 2021), as well as the connections between Ly$\alpha$ emission and C IV and Si IV absorbers at $z = 3-4.5$ (E. K. Lofthouse et al. 2023; M. Galbiati et al. 2024). They found that the strength and kinematics of metal-enriched absorbing gas positively correlate with the number of Ly$\alpha$ emitters (LAEs). Furthermore, ALMA observations indicate that DLAs at $z \sim 4$ are associated with [C II] emission in disk galaxies. J. X. Prochaska et al. (2019) and M. Neeleman et al. (2019) reported the detection of [C II] emission from five out of six high-metallicity ($[X/H] > -1.36$) DLAs at $z \sim 4$, suggesting a connection between the velocity of [C II] emission and DLAs at this redshift.

Recent JWST observations have identified other nebular emission lines, including H$\alpha$, [O III], and H$\beta$, near Mg II absorbers at $z = 2-7$ (R. Bordoloi et al. 2023; L. Christensen et al. 2023; Y. Wu et al. 2023; S. Zou et al. 2024b). However, the majority of Mg II absorbers in R. Bordoloi et al. (2023) are classified as weak Mg II systems.

To study the disturbed cold gas in the CGM and its interaction with galaxies and large-scale structures at $z > 2$, we conducted an initial sample. We first checked all sight lines with strong Mg II absorbers that have archival VLT/MUSE coverage, then identified those that are also covered by JWST and ALMA data. To date, no dedicated survey has focused on studying the galaxy environments around very strong and kinematically broad Mg II absorbers at $z > 2$. In this paper, we report the discovery of Ly$\alpha$ emission at $z = 4.86$ and He I, [S III], and Paschen lines and dust continuum at $z = 2.56$ around three very strong ($W_r > 2.5$ Å—see Figure 1; we refer to very strong Mg II—or VSMG II—systems throughout the paper) and kinematically complex ($\Delta v > 500$ km s$^{-1}$) Mg II systems.

The paper is structured as follows. We present the sample selection and data reduction in Section 2. We detail the detection of the LAEs around the $z \sim 4.9$ absorbing system and
<table><caption>**Table 1**
Quasar and Absorber Information about the Sample</caption><thead><tr><th>QSO</th><th>R.A.</th><th>Decl.</th><th>z<sub>abs</sub></th><th>W<sub>r</sub>(λ2796) (Å)</th><th>Δν (km s<sup>-1</sup>)</th><th>Exposure Time (hr)</th><th>PI and Project ID</th></tr></thead><tbody><tr><td>J0305–3150</td><td>03:05:16.9</td><td>-31:50:55.98</td><td>2.5662</td><td>2.869 ± 0.481</td><td>524.6</td><td>2.5</td><td>Venemans, 094.B-0893</td></tr><tr><td>J0836+0054</td><td>08:36:43.9</td><td>+00:54:53.3</td><td>3.7443</td><td>2.509 ± 0.016</td><td>510.4</td><td>5.3</td><td>Bian, 106.210Z</td></tr><tr><td>J1306+0356 sys1</td><td>13:06:08.3</td><td>+03:56:26.3</td><td>4.8634</td><td>2.891 ± 0.109</td><td>541.5</td><td>10.4</td><td>Ellis, 0103.A-0140</td></tr><tr><td>J1306+0356 sys2</td><td>13:06:08.3</td><td>+03:56:26.3</td><td>4.8821</td><td>&lt;2.959</td><td>465.9</td><td>10.4</td><td>Ellis, 0103.A-0140</td></tr><tr><td>J1509–1749</td><td>15:09:41.78</td><td>-17:49:26.80</td><td>3.3925</td><td>5.679 ± 0.056</td><td>811.5</td><td>1.0</td><td>Farina, 0101.A-0656</td></tr><tr><td>J2211–3206</td><td>22:11:12.39</td><td>-32:06:12.95</td><td>3.7144</td><td>3.505 ± 0.068</td><td>623.4</td><td>1.0</td><td>Farina, 0101.A-0656</td></tr><tr><td>J1030+0525</td><td>10:30:27.09</td><td>+05:24:55.02</td><td>2.78</td><td>2.617 ± 0.069</td><td>583.9</td><td>1.0</td><td>Karman, 095.A-0714</td></tr></tbody></table>

Note. We list the targets that have MUSE data. We remeasure the absorber rest-frame EW and velocity width for the systems toward J0305–3150 and J1306+0356. Other values are presented in S.-F. S. Chen et al. (2017). The labels “sys2” and “sys2” for J1306+0356 indicate the two metal-absorbing systems shown in Figure A4.

the dusty galaxy around the absorber at $z \sim 2.6$ in Section 3. Section 4 discusses the interpretation of these systems. Finally, we summarize our findings in Section 5. Throughout this work, we adopt the standard $\Lambda$CDM model, with the following cosmological parameters: $H_0 = 70 \text{ km s}^{-1} \text{ Mpc}^{-1}$, $\Omega_{\Lambda} = 0.69$, and $\Omega_m = 0.31$.

## 2. Sample Selection and Data Reduction

### 2.1. Sample Selection and Detection Limits

The parent sample of the Mg II absorber catalogs is from S.-F. S. Chen et al. (2017) and S. Zou et al. (2021). S.-F. S. Chen et al. (2017) offer a Magellan/FIRE sample of 100 quasars with emission redshifts between $z = 3.55$ and $z = 7.09$, with an average spectral resolution of $R \sim 6000$ (M. S. Matejek et al. 2013). S. Zou et al. (2021) include Gemini near-infrared spectroscopy of 51 quasars at $z > 5.7$, with an average spectral resolution of $R \sim 800$ (Y. Shen et al. 2019). Considering the uncertainties in the EW measurements, we preselected the initial sample based on the criteria of $W_r > 2.0$ Å and $\Delta\nu > 500 \text{ km s}^{-1}$, rather than $W_r > 3.0$ Å, to avoid missing potential targets. After this step, we checked ancillary data from three sources: archival VLT/MUSE data, the JWST GO1 survey A Spectroscopic Survey of Biased Halos in the Reionization Era (ASPIRE), and ASPIRE-ALMA data.

We list six sight lines with VSMG II absorbers and archival VLT/MUSE data, covered in Table 1. Except for the deepest 10 hr exposure data cube in the field of J1306+0356, we do not detect $\text{Ly}\alpha$ emission in the other five MUSE data cubes. The flux detection limits for the 10 hr MUSE-Deep single-point data and 1 hr MUSE-Wide data are $3.1 \times 10^{-19} \text{ erg s}^{-1} \text{ cm}^{-2}$ (R. Bacon et al. 2017) and $2.0 \times 10^{-17} \text{ erg s}^{-1} \text{ cm}^{-2}$ (T. Urrutia et al. 2019), respectively. For JWST/NIRCam WFSS data in the F356W band, the $5\sigma$ line detection limit can reach $2.0 \times 10^{-18} \text{ erg s}^{-1} \text{ cm}^{-2}$, by integrating the spectra over $50 \text{ Å}$ (F. Wang et al. 2023), which corresponds to a luminosity limit of $1.1 \times 10^{40} \text{ erg s}^{-1}$ at $z = 2.5$. Given that the second strong Mg II system toward J1306+0356 (denoted as “b” in Table 1) is not listed in S.-F. S. Chen et al. (2017), we remeasure the EW and velocity spread of the absorbing systems along the two sight lines analyzed in this work. We do not remeasure the remaining four sight lines listed in Table 1, as no associated galaxies are detected and no JWST or ALMA data are available.

### 2.2. MUSE Data Reduction

The MUSE data used to search for LAEs in the quasar field of J1306+0356 is collected from the MUSE-DEEP survey (PI: R. Ellis; Program ID: 0103.A-0140). We used the ESO MUSE data reduction pipeline (R. Bacon et al. 2017; P. M. Weilbacher et al. 2020)$^{15}$ to reduce the data cube. The ESO pipeline reduction process is briefly described as follows. First, we process the raw data cube using the ESO MUSE pipeline v2.8.9. Daily calibrations and the geometry table are used to generate pixel information, including location, wavelength, photon count, and variance estimates. Each exposure is precisely recentered to correct for derotator wobble. We then use the *scipost* recipe to perform astrometric and flux calibrations on the pixtable. The final data cube is generated using the *makecube* recipe. Sky background subtraction is performed using the Zurich Atmosphere Purge process, as described in K. T. Soto et al. (2016).

For the interstack masking, we run the *scibasic* and *scipost* recipes twice: the first time without using the specific bad-pixel table and the second time with it. Using the output of the “bad-pixel” version of the cube, we derive a new 3D mask, which we apply to the original cube, effectively removing the interstack bad data.

### 2.3. JWST Data Reduction

The JWST data are taken from the ASPIRE JWST GO1 survey (PI: F. Wang; Program ID: \#2078). The science goal of this program is driven by the study of supermassive black hole growth, its connection with the host galaxy, and metal enrichment during the reionization epoch. The full JWST/NIRCam WFSS data reduction is described in F. Wang et al. (2023) and J. Yang et al. (2023). We perform the data reduction using version 1.10.2 (H. Bushouse et al. 2025) of the JWST Calibration Pipeline. For the data calibration, we employ reference files (jwst 1080.pmap) from version 11.16.21 of the standard Calibration Reference Data System. All imaging data in this study align with Gaia Data Release 3. We adopt the method outlined in F. Sun et al. (2022), which includes a column-average correction for 1/f-noise. This model traces point sources observed in the Large Magellanic Cloud field.

<footnote>$^{15}$ https://www.eso.org/sci/software/pipelines/muse/</footnote>
<figure><img src="image_6.png" /><figcaption>**Figure 2.** Emission profiles of the Lyα lines detected with VLT/MUSE and the absorption profile of the Mg II absorber observed by Magellan/FIRE along the J1306+0356 sight line at z = 4.8651, shown in velocity space. The upper panel shows the spectra of the two LAEs, which are at distances of 201 kpc (red) and 197 kpc (blue) from the absorbing gas, respectively. LAE1 is centered at z = 4.867, at the peak of the strongest component. The gray dashed lines indicate the potential subcomponents of LAE1. The shaded regions indicate the wavelength interval used to compute the EW of the Lyα lines. For LAE1, the blue bump is tentative, therefore we do not include it in the EW measurement. The lower panels show the Mg II λ2796 and Mg II λ2803 lines, respectively, with the blue dashed line representing the zero-point at z = 4.8651, where the first major subcomponents are located. Complete Voigt profile fitting of the two systems is provided in Table A1 and Appendix Figure A4.</figcaption></figure>

## 2.4. ALMA Data Reduction

The ALMA data used in this work are from the Cycle 9 large program (PI: F. Wang; Program ID: 2022.1.01077.L) for the 25 ASPIRE quasar fields with ALMA band 6 mosaics. The data reduction was processed with the CASA pipeline v6.4.1.12. The full details of the ALMA data reduction are presented in F. Sun et al. (2025). For the continuum imaging, we flagged all spectral channels with a velocity offset smaller than 500 km s⁻¹ from the quasar [C II] line center. Noisy spectral channels caused by telluric absorption were also visually identified through plotms and flagged from the continuum imaging. We then split the measurement sets to a channel width of 125 MHz and obtained continuum imaging at native resolution (robust = 0.5 and no uv tapering; the typical beam size is about 0.7') and tapered resolution (robust = 2.0 and uv-tapered, with a Gaussian kernel FWHM of 1.0').

## 2.5. HST Archived Data

For sight line J1306+0356, we used archival HST imaging in the F775W and F850LP bands (PI: M. Stiavelli; Program ID #9777) to estimate the LAE UV continuum. For sight line J0305–3150, we used archival HST data, including WFC3 imaging (F105W, F125W, and F160W) and Advanced Camera for Surveys imaging (F606W and F814W; PI: C. Casey; Program ID #15064), for photometric measurements and the

spectral energy distribution (SED) fitting discussed in Section 3.2.3.

## 2.6. Emission-line Search

We search for Lyα emission in the MUSE field using a simple SExtractor-based Python tool, MUSELET.¹⁶MUSELET uses SExtractor<fnref n="17" /> (E. Bertin & S. Arnouts 1996) to search for emission lines in narrowband imaging. The process is as follows. First, MUSELET creates a variance-weighted white-light image and RGB images based on one-third of the wavelength range each. Next, MUSELET runs SExtractor on the narrowband files and generates a catalog that distinguishes sources with continuum emission. The continuum is extracted from a range of wavelength pixels (20) around the Lyα emission line. We then visually inspect the catalog and rule out lines at lower redshifts. The final detected two LAEs are presented in Figure 2, both exhibiting a double-peaked Lyα profile.

For the VSMG II at z = 2.5662 along the quasar sight line J0305–3150, we searched for the [S III](λ9531), He I(λ10830), and Paschen γ lines using a method similar to that used for the [O III] and Hβ lines in F. Wang et al. (2023), Section 3. We identified flux peaks with signal-to-noise ratio (S/N) > 3 from

<footnote n="16">¹⁶ https://mpdaf.readthedocs.io/en/latest/muselet.html</footnote>

<footnote n="17">¹⁷ http://www.astromatic.net/software/sextractor</footnote>
the 1D spectra and applied a Gaussian filter template for the He I and [S III] lines to select potential candidates. The selected targets were then visually inspected by more than three people to determine the final set of emission-line galaxies.

### 3. Results

#### 3.1. Absorption Profile

The VSMG II detected at $z_{abs} = 4.8651$ toward quasar J1306+0356 ($z_{em} = 6.02$, R.A. = $13^h06^m08^s27$, decl. = +03°56′26″/36) is reported with $W_r = 2.804$ Å and a velocity spread of $\Delta v = 180.8$ km s$^{-1}$ in S.-F. S. Chen et al. (2017). Al II and Fe II absorptions are reported in the same system in L. Jiang et al. (2007). After our remeasurements of $W_r$ and $\Delta v$ (see Table 1), we report a new system at $z = 4.8821$, which is offset by around 1000 km s$^{-1}$ from the system at $z = 4.8651$. The second system has $W_r(\text{Mg II}(\lambda2803)) = 2.371 \pm 0.097$ Å and $\Delta v = 421.9$ km s$^{-1}$. We redefine the centers of these two systems at the positions of the strongest Mg II ($\lambda2796$) subcomponents, with $z = 4.8634$ and $z = 4.8821$, respectively.

We present the two absorbing systems and two detected LAEs in Figure 2. In addition to Mg II, we detect Fe II, Mg I, Si II, Al II, Al III, and C IV, plus tentative detections of Zn II absorption lines. We denote the system at $z = 4.8634$ as System 1 and the system at $z = 4.8821$ as System 2. For Mg II, the Mg II ($\lambda2803$) line in System 1 is blended with the Mg II ($\lambda2796$) line in System 2. In Table A1, we present the $W_r$ of the System 1 Mg II ($\lambda2796$) line, the System 2 Mg II ($\lambda2803$) line, and the blended region. For C IV lines, there is also possible blending between C IV ($\lambda1550$) in System 1 and C IV ($\lambda1548$) in System 2. We use the red and blue shaded regions in Figure A4 to present this absorbing system pair, including the blended region. Given that the Mg II and C IV lines are likely strongly saturated, we only fit the Si II, Al II, and Al III lines with Voigt profiles including multiple subcomponents using VoigtFit (J.-K. Krogager 2018). We adopt Doppler parameters $b$ in the range 5–30 km s$^{-1}$ and present in Table A1 the best-fit results corresponding to the minimum $\chi^2$, obtained with $b = 25$ km s$^{-1}$.

From Table A1, we observe that, in general, System 2 has higher $W_r$ for most ions, except for Al III, C IV, and slightly weaker Mg I lines. Given that System 1 has weaker intermediate ions but stronger high-ionization lines, it appears to be more ionized and less dusty than System 2. We present the CLOUDY modeling of the ionization state and related discussion of these two systems in Section 4.1.2.

In Figure 3, we present the VSMg II system detected at $z = 2.5662$ alongside the Fe II ($\lambda2600$) line. Other UV lines, such as O I and Si II, are shifted into the optical spectral range and are absorbed by the intergalactic medium (IGM) because the quasar is at $z > 5$. The Mg II doublet profiles show three major subcomponents.

#### 3.2. Galaxy Properties around the VSMg II Systems

##### 3.2.1. LAEs around the Mg II Absorption Pair at $z \sim 4.86$

Using MUSELET, we obtain the initial list of $\text{Ly}\alpha$ candidates in the J1306+0356 field. We then visually inspect the candidates by examining their 2D and 1D spectra, confirming two LAEs: LAE1 at R.A., decl. = 196.5397, 3.9328; and LAE2 at R.A., decl. = 196.5312, 3.9483. The spectra of the two LAEs and the VSMG II absorber are presented in Figure 2.

$v = 0$ km s$^{-1}$ corresponds to $z = 4.8634$, at the strongest component of LAE1. Note that the redshift here is not the systematic redshift ($z_{sys}$), given that there is often a velocity shift between the $\text{Ly}\alpha$ line peak and $z_{sys}$ in previously reported LAEs (e.g., T. Hashimoto et al. 2017). We calculate the $z_{sys}$ uncertainties in Table 2, based on its relation with the red (peak) component and the blue bump velocity differences in A. Verhamme et al. (2018).

We then measure the $\text{Ly}\alpha$ EW of the $\text{Ly}\alpha$ emission. The EW of the $\text{Ly}\alpha$ line is defined as the ratio of the $\text{Ly}\alpha$ line luminosity to the UV continuum luminosity density at $\text{Ly}\alpha = 1215.67$ Å (D. Scherer 2003):

$$ \text{EW} = \int_{\lambda_2}^{\lambda_1} \frac{f_{\text{Ly}\alpha}^{\text{line}} - f_{\text{Ly}\alpha}^{\text{cont}}}{f_{\text{Ly}\alpha}^{\text{cont}}} d\lambda, \quad (1) $$

where $f_{\text{Ly}\alpha}^{\text{line}}$ and $f_{\text{Ly}\alpha}^{\text{cont}}$ are the flux densities of the $\text{Ly}\alpha$ line and the continuum, respectively. We measure the $\text{Ly}\alpha$ line flux from the extracted 1D spectra, including the blue bump. We then use archival HST F775W and F850LP data to estimate the UV continuum magnitude and flux density upper limit. From this, we calculate the EWs of LAE1 and LAE2 to be $73.15 \pm 24.05$ Å and $20.01 \pm 9.27$ Å, respectively. We correct for instrumental broadening using the MUSE line-spread function (LSF) when calculating the two FWHM of the emission line. We estimate the SFRs of the two LAEs from the $\text{Ly}\alpha$ luminosity, using the SFR-$\text{H}\alpha$ relation in R. C. J. Kennicutt (1998) and the $\text{Ly}\alpha$-$\text{H}\alpha$ emissivity ratio in D. E. Osterbrock & G. J. Ferland (2006): SFR($\text{Ly}\alpha$) = $9.1 \times 10^{-43} \times L(\text{Ly}\alpha) M_{\odot} \text{yr}^{-1}$, yielding SFR($\text{Ly}\alpha$) = $5.75 \pm 1.89 M_{\odot} \text{yr}^{-1}$ and $2.23 \pm 0.74 M_{\odot} \text{yr}^{-1}$, respectively. These SFR values are consistent with the results in D. Sobral & J. Matthee (2019), which measure SFR($\text{Ly}\alpha$) at $z > 2.1$. Details of these two LAE measurement are presented in Table 2.

##### 3.2.2. Dusty SFG around the VSMG II Absorber at $z = 2.5662$ in the J0305–3150 field

We detect a galaxy counterpart, ASPIRE J0305M31-He1-2708 (R.A., decl. = 03:05:17.09, −31:50:49.20), in the J0305–3150 field, with prominent He I ($\lambda10830$), [S III] ($\lambda9531$), [S III]($\lambda9067$), Pa$\gamma$, and Pa10 lines. Profiles of the absorbing gas and galaxy are presented in Figure 3. Full details of the galaxy’s 2D/1D spectra and emission lines are shown in Figure A1 and Table 2. The FWHM of the He I line is around 710 km s$^{-1}$, with instrument broadening corrected using the NIRCam grism LSF function (T. P. Greene et al. 2017). The flux ratio between the He I and Pa$\gamma$ lines is 2.7.

We measure the $W_r$ of the emission lines with the F115W, F200W, and F356W photometric data and the line flux. The target continuum flux densities are modeled with a power law $f_{\text{cont}} = \lambda^{\alpha}$. Then we estimate the flux densities at the emission lines and measure the $W_r$ following same method as in Equation (1).

##### 3.2.3. Stellar Mass, Dust Continuum, and SFR

We also detected dust continuum in the galaxy J0305M50-HeI-2708 using ASPIRE-ALMA data (noted as J0305M50. C04; see Figure A2). The details of the searching for the dust continuum and [C II] emitters at $z > 4$ using the ASPIRE-ALMA data are presented in F. Sun et al. (2025).
<figure><img src="image_7.png" /><figcaption>**Figure 3.** The absorption profiles of the VSMG II at $z = 2.5662$, along with the 1D spectrum of the detected galaxy, which is 4.65 (38 kpc) away from the absorber. The galaxy shows He I (with a Gaussian fit), [S III], and Paschen emission lines at $z = 2.5643$ in the JWST NIRCam F356W band. The zero-point is centered on the strongest Mg II subcomponent (the same in each panel).</figcaption></figure>

The aperture and peak fluxes of the J0305M3150.C04 source are $0.42 \pm 0.11$ mJy and $0.40 \pm 0.03$ mJy, respectively. We calculate the far-infrared SFR following the relation from E. J. Murphy et al. (2011): $\text{SFR} = 2.1 \times 10^{-10} L_{\text{FIR}}(\text{SF}) [M_{\odot} \text{yr}^{-1}]$, where $L_{\text{FIR}}$ is the far-infrared luminosity. $L_{\text{FIR}}$ is determined by the SED fitting of a blackbody in the 42.5–122.5 µm range. We adopt an average dust temperature of 35 K and a dust emissivity index $\beta$ of 1.6 (M. Neeleman et al. 2018). We then calculate the dust mass and $L_{\text{FIR}}(\text{SF})$, which are found to be $(1.98 \pm 0.55) \times 10^8 M_{\odot}$ and $(5.74 \pm 1.58) \times 10^{11} \text{ erg s}^{-1}$, respectively. The resulting SFR is $121 \pm 33 M_{\odot} \text{yr}^{-1}$, indicating intense star formation in this galaxy.

The stellar mass of the galaxy is obtained using the SED fitting tool BAGPIPES (A. C. Carnall et al. 2018). We use multiband photometry from JWST (F115W, F200W, and F356W) and HST (F105W, F125W, F160W, F606W, and F814W bands) as inputs. We adopt a constant star formation history (SFH) and the Calzetti dust law (D. Calzetti et al. 2000), allowing $A_V$ to vary between 1.0 and 5.0, the metallicity (log Z/Z$_{\odot}$) to vary between -2 and 2, and the age to vary between 100 Myr and 2.5 Gyr. The best-fitted stellar mass of the galaxy is $\log(M/M_{\odot}) = 10.73^{+0.02}_{-0.60}$ (see Figure A3). The difference in the stellar mass varies by around 0.2 dex when adopting a poststarburst SFH.

### 3.2.4. Galaxy Morphology

We use the galaxy decomposition tool GALFIT (C. Y. Peng et al. 2002, 2010)<fnref n="18" /> to fit the position angle (PA) and Sérsic index of this star-forming galaxy (SFG). We note that J0305M31-He1-2708 exhibits different morphologies in the F200W and F356W bands, so we fit the F200W and F356W bands individually. The point-spread function (PSF) was generated by stacking stars in each NIRCam filter within the same field using SourceExtractor++ (E. Bertin et al. 2020), and the model fitting was then convolved with this PSF. Prominent residuals in the F200W fit (the data minus the GALFIT model) are oriented at an angle to the projected photometric major axis, suggesting a tentative outflow. The fitted PA angles are plotted in Figure 4. The Sérsic indices in F200W and F356W are $1.16 \pm 0.02$ and $1.46 \pm 0.02$, respectively, indicating a tentative disklike structure, based on the disk galaxy classification criteria in W. Sun et al. (2024). We discuss this in detail in Section 4.2. The effective radius ($R_e$) and $b/a$ of the galaxy in F200W are $1.59 \pm 0.01$ kpc and $0.54 \pm 0.01$, respectively, and in F356W they are $0.93 \pm 0.01$ kpc and $0.54 \pm 0.01$, respectively. We compare our measured galaxy $R_e$ in F200W and stellar mass with the

<footnote n="18">¹⁸ https://usersobs.carnegiescience.edu/peng/work/galfit/galfit.html</footnote>
<table><caption>**Table 2**
Galaxy Property Measurements around the VSMG II Absorbers</caption><thead><tr><th></th><th>J1306+0356 LAE1</th></tr></thead><tbody><tr><td>z<sub>Lyα</sub></td><td>4.867 ± 0.004</td></tr><tr><td>R.A.</td><td>13:06:09.53</td></tr><tr><td>decl.</td><td>+03:55:58.08</td></tr><tr><td>D (kpc)</td><td>201</td></tr><tr><td>f<sub>L<sub>Lyα</sub></sub> (10<sup>-17</sup>erg s<sup>-1</sup> cm<sup>-2</sup>)</td><td>2.45 ± 0.81</td></tr><tr><td>L<sub>L<sub>Lyα</sub></sub> (10<sup>42</sup> erg s<sup>-1</sup>)</td><td>6.32 ± 2.08</td></tr><tr><td>EW (Å)</td><td>73.15 ± 24.05</td></tr><tr><td>FWHM (km s<sup>-1</sup>)</td><td>121</td></tr><tr><td>SFR (M<sub>☉</sub> yr<sup>-1</sup>)</td><td>5.75 ± 1.89</td></tr></tbody><thead><tr><th></th><th>J1306+0356 LAE2</th></tr></thead><tbody><tr><td>z<sub>Lyα</sub></td><td>4.865 ± 0.004</td></tr><tr><td>R.A.</td><td>13:06:07.49</td></tr><tr><td>decl.</td><td>+03:56:53.88</td></tr><tr><td>D (kpc)</td><td>197</td></tr><tr><td>f<sub>L<sub>Lyα</sub></sub> (10<sup>-17</sup>erg s<sup>-1</sup> cm<sup>-2</sup>)</td><td>0.67 ± 0.31</td></tr><tr><td>L<sub>L<sub>Lyα</sub></sub> (10<sup>42</sup> erg s<sup>-1</sup>)</td><td>2.45 ± 0.81</td></tr><tr><td>EW (Å)</td><td>20.01 ± 9.37</td></tr><tr><td>SFR (M<sub>☉</sub> yr<sup>-1</sup>)</td><td>2.23 ± 0.74</td></tr></tbody><thead><tr><th></th><th>J0305M3150-HeI-2708</th></tr></thead><tbody><tr><td>z<sub>em</sub></td><td>2.564</td></tr><tr><td>R.A.</td><td>03:05:17.11</td></tr><tr><td>decl.</td><td>-31:50:52.08</td></tr><tr><td>D (kpc)</td><td>38</td></tr><tr><td>f<sub>He I</sub> 110830 (10<sup>-17</sup>erg s<sup>-1</sup> cm<sup>-2</sup>)</td><td>1.37 ± 0.42</td></tr><tr><td>FWHM (km s<sup>-1</sup>)</td><td>710</td></tr><tr><td>f<sub>[S III]</sub>9531 (10<sup>-17</sup>erg s<sup>-1</sup> cm<sup>-2</sup>)</td><td>1.22 ± 0.52</td></tr><tr><td>f<sub>[S III]</sub>9067 (10<sup>-17</sup>erg s<sup>-1</sup> cm<sup>-2</sup>)</td><td>1.01 ± 0.49</td></tr><tr><td>f<sub>Paγ</sub> (10<sup>-17</sup>erg s<sup>-1</sup> cm<sup>-2</sup>)</td><td>1.07 ± 0.38</td></tr><tr><td>f<sub>Pa10</sub> (10<sup>-17</sup>erg s<sup>-1</sup> cm<sup>-2</sup>)</td><td>0.89 ± 0.43</td></tr><tr><td>EW<sub>He I</sub> 110830 (Å)</td><td>329.51 ± 51.0</td></tr><tr><td>EW<sub>[S III]</sub>9531 (Å)</td><td>275.31 ± 66.16</td></tr><tr><td>EW<sub>Paγ</sub> (Å)</td><td>124.19 ± 44.11</td></tr><tr><td>S<sub>cont</sub> (mJy)</td><td>424 ± 110</td></tr><tr><td>L<sub>FIR</sub> (erg s<sup>-1</sup>)</td><td>(5.74 ± 1.58) × 10<sup>11</sup></td></tr><tr><td>log M<sub>*</sub>/M<sub>☉</sub></td><td>10.73 <sup>+0.02</sup><sub>-0.06</sub></td></tr><tr><td>log M<sub>dust</sub>/M<sub>☉</sub></td><td>8.30 ± 0.11</td></tr><tr><td>SFR (M<sub>☉</sub> yr<sup>-1</sup>)</td><td>121 ± 33</td></tr></tbody></table>

empirical galaxy size–mass (the former being observed at rest frame 5000 Å) relation at $z \sim 2.7$ in A. van der Wel et al. (2014) and find that our detected dusty SFG lies between early-type and late-type galaxies.

### 3.3. Comparison with Other SFGs and DLA Hosts at Similar Redshifts

In this section, we contextualize our detected galaxies around these two VSMG II systems, by comparing their properties with those of other SFGs at similar redshifts. We first compare the Lyα emission-line flux, luminosity, and $W_r$ of the two LAEs around the $z \sim 4.86$ VSMG II pair with those from other LAE surveys, DLAs, and Mg II hosts. In the upper panel of Figure 5, we plot the Lyα line flux in the DLA host against the DLA log N(H I), with a color map of the velocity width ($\Delta v$) of Si II. The full DLA host sample is collected in J.-K. Krogager et al. (2017). We extrapolate the N(H I) of our Mg II system from the $W_r$ of Mg II (λ2796) using the relation

in T.-W. Lan & H. Mo (2018):

$$N_{H1} (\text{cm}^{-2}) = A \left( \frac{W_{\lambda2796}}{1\AA} \right)^{\alpha} (1 + z)^{\beta}, \quad (2)$$

where $A = 10^{18.96 \pm 0.10} \text{cm}^{-2}$, $\alpha = 1.69 \pm 0.13$, and $\beta = 1.88 \pm 0.29$. Except for one exceptionally bright Lyα emission from a DLA host in J.-K. Krogager et al. (2015), we find that the stronger the column density of H I is, the brighter the host’s Lyα emission. Our detected Mg II surrounding the LAEs is consistent with this trend. We also note that the strength of the Lyα emission does not show a significant correlation with the velocity width of the absorption line. In the lower panel of Figure 5, we plot the Lyα $W_r$ from the MUSE Hubble Ultra Deep Field survey (L. Wisotzki et al. 2016; T. Hashimoto et al. 2017) and the JWST Advanced Deep Extragalactic Survey (JADES; J. Witstok et al. 2024). We find that the $W_r$ of our VSMG II LAE is consistent with the median $W_r$ of the LAE measured in T. Hashimoto et al. (2017) at $z \sim 4.9$.

We then compare our detected dusty SFG around the $z = 2.5661$ VSMG II with the DLA hosts detected by ALMA at $z = 2-4$ (M. Neeleman et al. 2017, 2018; J. X. Prochaska et al. 2019). The SFR of our VSMG II counterpart is consistent with the SFR of DLA submillimeter-detected hosts ($\sim 110 \text{ M}_\odot \text{ yr}^{-1}$). J. X. Prochaska et al. (2019) report a moderate SFR ($\sim 20 \text{ M}_\odot \text{ yr}^{-1}$) for the DLA host J1201+2117, which is claimed to be undergoing a major merger at $z \sim 3.79$.

## 4. Discussion

### 4.1. J1306+0356

#### 4.1.1. Possibility of Overdensity

We first discuss the possibility that the $z = 4.8651$ VSMG II resides in an overdense region. We estimate the random field number density ($N_{gal}/c\text{Mpc}^3$) of the LAEs at $z \sim 4.8$, using the Lyα luminosity function measured from the MUSE Hubble Ultra Deep Field data in A. B. Drake et al. (2017). For $\log L_{Lyα} > 42.0$, $\Phi(\log L > 42/c\text{Mpc}^3)$ is about $10^{-2}$. Given that our two LAEs have a redshift difference of $\Delta z = 0.002$, the number density within the comoving volume (the MUSE field of view times $\Delta z$) is $1.14 \times 10^{-4} \text{ Mpc}^3$. This suggests that the two LAEs and the VSMG II gas reside in an overdense region, with $\delta \sim 10^4$.

High N(H I) gas in overdense regions has been detected at similar redshifts, suggesting that the cold-gas content needs to be increased in fiducial cosmological simulations. K. E. Heintz et al. (2025) reported 10 galaxies with strong DLA features at $z = 5.4-6.0$ from the JWST NIRSpec FRESCO (GO-18905; PI: Oesch) survey. The 10 DLA-bearing galaxies reside in a foreground protocluster with more than 25 galaxies at similar redshifts ($z = 5.35-5.40$). Such high N(H I) and nearly neutral gas content in overdense regions at the end of the reionization epoch may play a key role in cosmic assembly history and the transition phase of the IGM large-scale structure. Our detection of the metal-enriched and kinematically ultralarge system may further reveal baryonic transfer processes in these overdense regions at $z \sim 5$.
<figure><img src="image_8.png" /><figcaption>**Figure 4.** GALFIT fitting of galaxy J0305M31-He1-2708 in F200W (upper) and F356W (lower). We use GALFIT to measure the effective radius ($R_{\text{eff}}$), Sérsic index, axis ratio, and PA. The cyan dashed line marks the major axis. Each row shows (from left to right) the JWST image, GALFIT model, and residuals (data minus model).</figcaption></figure>

### 4.1.2. Metallicity and Ionization State of the Ultra-extended System

From Figure 2, we see that LAE1 exhibits an asymmetric double-peaked profile, with an extension on the red side toward the absorbing system at $z = 4.8821$. We tentatively suggest that LAE1 kinematically moves from the absorbing system at $z = 4.8634$ toward the one at $z = 4.8821$, tracing the filaments between dense and cold (probably neutral) gas in the two absorbing systems. From Figure A4, we see that the two absorbing systems share similar metal species, with the bluer system ($z = 4.8821$) exhibiting slightly higher EWs in the Fe II, Si II, and Al II lines. Given that the two systems likely share a common origin and display an extremely large combined velocity width (greater than $1000 \text{ km s}^{-1}$), we use CLOUDY (G. J. Ferland et al. 2017) to model the ionization state, metallicity, and gas density of these systems.

Although we do not have direct measurements of $N(\text{H I})$, we can still derive the relative distribution of the metallicity, dust content, gas density, and ionization state between these two absorbing systems. First, we varied the stopping column density of H I and found that when $\log N(\text{H I}) < 18.0$, even increasing the gas metallicity to solar could not reach the detected column densities of Si II, Al II, and Fe II. We then set $\log N(\text{H I})$ between 20 and 22 (i.e., DLAs) and varied the metallicity $\log(Z/Z_{\odot})$ between -3 and 1. The dust content was first scaled with metals and adjusted accordingly with changes in metallicity.

In all modeling results with varying metallicity, System 1 exhibits a metallicity that is ~1 dex lower than that of System 2 (based on $N(\text{Zn II})$). The ionization-state parameter $\log U$ of

System 1 is about 0.7 dex lower than that of System 2, as indicated by the ratio of Al II to Al III. The ionization parameter $U$ is defined as $U = \Phi(\text{H})/(n(\text{H})\times c)$, where $\Phi(\text{H})$ is the flux of the ionizing photons and $c$ is the light speed. Specifically, when $\log N(\text{H I}) = 21.0$, the $\log(Z/Z_{\odot})$s of System 1 and System 2 are -2.5 and -1.5, respectively (see Extended Data Figure A5). Such a metallicity range is also consistent with predictions of DLA at $z \sim 4.8$, from the statistical metallicity distributions of the large DLA samples presented in M. Rafelski et al. (2012). We note that Si II exhibits overabundances compared to other elements, regardless of changes in metallicity and dust content. We also find that for System 2, the modeled $\log N(\text{Fe II})$ is consistently lower than the observed value by ~0.4 dex, whereas for System 1, the modeled value is higher than the observed value by about 0.4 dex. Given that iron is more sensitive to dust depletion compared to silicon and zinc (E. B. Jenkins et al. 1986), System 2 should contain more dust than System 1.

In summary, this kinematically ultrawide ($\Delta v > 1000 \text{ km s}^{-1}$) absorbing structure consists of two systems. The bluer system has lower metallicity, less dust, and is slightly more ionized than the redder one. Both systems share similar metal species and are likely connected by the Ly$\alpha$-emitting gas residing in an overdense region at $z \sim 5$. We also maintain the possibility that fainter host galaxies or an obscured massive galaxy/galaxies are located closer to the absorbing gas structure. Based on the ASPIRE-ALMA results in F. Sun et al. (2025), $66 \pm 7\%$ of star formation at $z \sim 5$ remains obscured.
<figure><img src="image_9.png" /><figcaption>**Figure 5.** Upper: comparison of VSMG II Lyα line flux with other DLA hosts. The DLA data points are color-coded by the velocity width $v_{\text{90}}$ of the Si II (λ1808) line. The Mg II system ($W_r = 2.033 \pm 0.187$ Å and $v_{\text{90}}(\lambda2796) = 355$ km s⁻¹) at z = 3.188 in the MAGG survey (M. Galbiati et al. 2024) is plotted as a red triangle. The column density of H I for the two Mg II systems, including our z = 4.8651 VSMG II system, is extrapolated from the $W_r(\text{Mg II})$ -N(H I) relation in T.-W. Lan & H. Mo (2018). Lower: EWs of LAEs detected in the MUSE Hubble Ultra Deep Field and JADES surveys at 2 < z < 8.</figcaption></figure>

## 4.2. J0305–3150

### 4.2.1. Tentative Disk?

A DLA host harboring a rotational disk has been reported at $z \sim 3–5$ (M. Neeleman et al. 2020). Because VSMG II systems have a high probability of being associated with a high H I column density, we discuss whether our host has a similar rotational disk at cosmic noon. We first measure the velocity gradient of the He I λ10830 line, following the method in E. J. Nelson et al. (2024). For each row of the grism 2D spectra along the dispersion direction, we fit a light-weighted center using a Gaussian profile. We then calculate the differences between the light-weighted center of the He I λ10830 line and the light-weighted center of the grism image. Note that the velocity derived from these two centers reflects contributions from both the spatial and kinematic properties of the line. Since we do not have multiple medium-band images to differentiate these two contributions, we can only constrain the $v_{\text{rot}}$ limit.

The observed velocity of the He I line is then calculated as $v_{\text{obs}} = (v_{\text{max}} - v_{\text{min}})/2$ from the velocity map. The $v_{\text{max}}$ and $v_{\text{min}}$ represent the maximum and minimum velocities measured from the observed velocity field in the 2D grism data. For the He I line, we find $v_{\text{obs}} = 248 \pm 52$ km s⁻¹. The rotation velocity, $v_{\text{rot}}$, is derived from $v_{\text{rot}} = v_{\text{obs}}/\sin i$, where i is the inclination angle. As mentioned in E. J. Nelson et al. (2024), the intrinsic $q_0$ of the galaxy cannot be determined, so we

assume $0.05 < q_0 < q$ to estimate the uncertainties in $v_{\text{rot}}$, where q is the observed major-to-minor-axis ratio. We note that the velocity dispersion is contributed by both the instrument and the target. NIRCam has a resolution of R ~ 1550 at $\lambda \sim 3.5$ µm, corresponding to ~84 km s⁻¹. Considering the instrumental effect, the corrected $v_{\text{rot}}$ for the galaxy and the emission line should be below 352 km s⁻¹.

We apply a dynamical modeling approach to the He I line, to further assess $v_{\text{rot}}$, following the method described in Z. Li et al. (2023). The velocity map is obtained using a similar procedure as above, followed by Markov Chain Monte Carlo sampling to derive the best-fit kinematic parameters and their uncertainties. This method builds on the approach developed by M. Outini & Y. Copin (2020). First, we fit the 2D surface brightness in the source plane and use the derived morphological parameters to generate the velocity field. We then use the F356W imaging to construct the velocity dispersion field, assuming an intrinsically circular disk. The fitting results are presented in Figure 6. For the He I line, we derive $v_{\text{rot}} = 115_{-86}^{+97}$ km s⁻¹, indicating a tentative rotating disk.

### 4.2.2. Comparison with Cosmological Simulation

To further understand the kinematics and dynamics of metal-enriched cold gas and its role in disk and galaxy formation, we compare the H I gas distribution around similar disklike galaxies (in terms of SFR, $v_{\text{rot}}$, $M_*$, and $R_e$) in the cosmological simulation IllustrisTNG100 (hereafter, TNG100; D. Nelson et al. 2018). Disklike galaxies are identified by requiring a disk mass fraction, $f_{\text{disk}}$, greater than 0.5. The $f_{\text{disk}}$ values are obtained using the morphological decomposition method from J. Liang et al. (2025). We select 18 disklike galaxies and find that high N(H I) gas within 50 kpc of the host galaxies shows a high incidence along both the major and minor axes—i.e., it does not purely trace inflows or outflows. The angular momentum of the high N(H I) gas is not perpendicular with the disk angular momentum, indicating dynamical complexity beyond simple inflow or outflow models. We present one example in Figure 7. We plot the column density distribution of the H I gas and the angular momentum directions of the disk and H I gas. The H I gas is derived from the total hydrogen content in TNG100 using a postprocessing model based on N. Y. Gnedin & A. V. Kravtsov (2011).

From the simulation, we see that high-density H I gas penetrates the hot CGM and then accretes onto the galaxy. Analytical models predict that the mode of cold-gas accretion onto galaxies evolves with redshift. The fraction of the cold-in-hot mode increases with redshift in a large-mass halo ($M_h > 10^{12} M_\odot$) at $z > 1$ (A. Dekel & Y. Birnboim 2006). The penetrated cold flow further sustains star and disk formation. Meanwhile, the turbulence and pressure instability in the inner CGM caused by cold flows enhance the probability of galactic outflows escaping from the galaxy. Therefore, the cold flow in high-mass halos plays a critical role in the complete virialization of the CGM and, consequently, in the transition of galaxies from star-forming to quiescent.

We estimate the halo mass of our detected SFG using the stellar-halo mass relation in G. Girelli et al. (2020) and obtain $\log (M_h/M_\odot) = 12.27_{-0.60}^{+0.02}$. The virial radius is then calculated using the relation $R_{\text{vir}} = (M_h/((3/4)\pi \times 200 \times \rho_{\text{crit}}))^{1/3}$, which gives $R_{\text{vir}} = 245$ kpc. Our detected VSMG II gas resides in 0.16 $R_{\text{vir}}$. Combining the host galaxy’s outflow-like
<figure><img src="image_10.png" /><figcaption>**Figure 6.** Dynamical modeling for the He I line in J0305M31-He1-2708. We plot the galaxy’s F356W image and the He I grism spectra in the upper panel. In the lower panel, we show the rotation model of the line and the best-fit Sérsic model convolved with the PSF, following the method in Z. Li et al. (2023). In the last column of panels, we present the fitting residuals.</figcaption></figure>

<figure><img src="image_11.png" /><figcaption>**Figure 7.** Example of the H I gas column density distribution around one disk galaxy at $z \sim 3$ from TNG100, selected based on the disklike galaxy criteria in J. Liang et al. (2025). The simulated galaxy has similar stellar mass, halo mass, SFR, and $R_{\sigma}$ to our detected galaxy. The left and right panels show face-on and edge-on views, respectively, of the same galaxy on a 100 × 100 kpc scale. The zoom-in box shows the stellar+gas content of the galaxy on a 10 × 10 kpc scale. The red dashed line is the major axis of the galaxy. The blue and yellow arrows in the right panel indicate the angular momentum directions of the disk and H I gas, respectively.</figcaption></figure>

features from JWST F200W and F356W imaging, its classification as not yet early type, and the tentative rotating disk structure, we suggest that the high-velocity VSMG II gas is accreting onto the galaxy, supporting starburst and disk formation, while also being affected by the tentative galactic outflow given from the JWST (in particular, F200W) imaging morphology fitting.

To test whether the cold CGM angular momentum is corotating with the disklike host galaxy or significantly shaped by outflows, we need deep integral field unit (IFU) observations that will deliver 3D maps of CGM emission and spatially resolved kinematics for direct comparison with the galaxy rotation field.
## 5. Summary

We present two ultrastrong and kinematically broad Mg II absorbing systems that trace disturbed cold gas and their associated galaxies at $z > 2$. We search for VSMG II-absorber-galaxy counterparts using VLT/MUSE, JWST, HST, and ALMA data. One system is an ultrastrong metal-enriched absorber (comprising two VSMG IIs), with a velocity width exceeding $1000 \text{ km s}^{-1}$, accompanied by two surrounding LAEs at an impact parameter of $\sim 200 \text{ kpc}$. The two absorbing systems exhibit interactions in metals, dust, and ionization and are possibly connected by Ly$\alpha$-emitting gas. The other VSMG II system, at $z \sim 2.5$, resides in the CGM ($D = 38 \text{ kpc}$) of a massive dusty SFG, likely hosting a tentative rotating disk.

We find that the VSMG II-traced cold gas resides in complex environments, both kinematically and dynamically. This cold gas plausibly influences disk formation and evolution, as well as the large-scale structure at high redshift. Although the two systems alone cannot provide strong definitive conclusions as to whether the cold gas traces inflows, outflows, or disk formation, they shed light on the role of cold gas in feeding early disk growth and in driving metal and dust enrichment in early overdense regions, particularly with the advent of ground-based IFU instruments and JWST. Future observations of obscured and faint SFGs will further explore the connection between these processes and the cold gas-galaxy kinematics, dynamics, and metallicity.

## Acknowledgments

We thank the anonymous referee for the careful reading and constructive suggestions. We are grateful for fruitful discussions with Weichen Wang, Valentina D'Odorico, Fengwu Sun, and Pasquier Noterdaeme. S.Z. acknowledges support from the National Science Foundation of China (no. 12303011) and Chinese Academy of Sciences (no. E5295401). J.B.C. acknowledges funding from the JWST Arizona/Steward Postdoc in Early galaxies and Reionization (JASPER) scholar contract at the University of Arizona. W.S. and L.C.H. acknowledge support from the National Key R&D Program of China (2022YFF0503401), the National Science Foundation of China (11991052 and 12233001), and the China Manned

Space Project (CMS-CSST-2021-A04 and CMS-CSST-2021-A06). P.P.J. is supported in part by contract ANR-22-CE31-0009 (HZ-3D-MAP) from the Agence Nationale de la Recherche

This work is based on observations made with Magellan/FIRE, the NASA/ESA/CSA James Webb Space Telescope and Hubble Space Telescope, VLT/MUSE, and ALMA. The JWST data were obtained from the Mikulski Archive for Space Telescopes at the Space Telescope Science Institute, which is operated by the Association of Universities for Research in Astronomy, Inc., under NASA contract NAS 5-03127 for JWST. These observations are associated with program \#2078. Support for program \#2078 was provided by NASA through a grant from the Space Telescope Science Institute, which is operated by the Association of Universities for Research in Astronomy, Inc., under NASA contract NAS 5-03127. This paper makes use of the following ALMA data: ADS/JAO.ALMA\#2022.1.01077.L. ALMA is a partnership of ESO (representing its member states), NSF (USA), and NINS (Japan), together with NRC (Canada), NSTC and ASIAA (Taiwan), and KASI (Republic of Korea), in cooperation with the Republic of Chile. The Joint ALMA Observatory is operated by ESO, AUI/NRAO, and NAOJ. The National Radio Astronomy Observatory is a facility of the National Science Foundation operated under cooperative agreement by Associated Universities, Inc.

Some of the data presented in this paper 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/vt74-kd84.

Facilities: VLT: Yepun, JWST/NIRCam, ALMA, HST.

## Appendix
Figures

We present the 2D and 1D spectra of J0305M31-HeI-2807 in Figure A1, the corresponding multiband imaging in Figure A2, and its SED fitting in Figure A3. The details of the absorbing systems at $z \sim 4.8$ along the sightline of J1306 +3150 are summarized in Table A1 and illustrated in Figure A4. The CLOUDY photoionization modelling of these absorbers is shown in Figure A5.
<figure><img src="image_12.png" /><figcaption>**Figure A1.** The 2D and 1D spectra of the host galaxy of the VSMG II absorber. The cutout imaging size is 2" × 2".</figcaption></figure>

<figure><img src="image_13.png" /><figcaption>**Figure A2.** The JWST/NIRCam imaging of J0305M31-He1-2708 in the F115W, F200W, and F356W bands. The last panel shows the ALMA tapered imaging, to increase the S/N. All images are 5" × 5" in size.</figcaption></figure>
<figure><img src="image_14.png" /></figure>

**Figure A3.** SED fitting of J0305M31-He1-2708 using BAGPIPES. We use photometry from the JWST/NIRCam F115W, F200W, and F356W bands and from the HST F105W, F125W, F160W, F606W, and F814W bands, shown as the blue and black points in the upper panel, respectively. The orange ovals and curve in the upper panel represent the modeled photometry in each observed band and the SED. The lower panel shows the likelihood distributions of the fitted SFR, galaxy age, stellar mass, and specific SFR, respectively. The black dashed lines mark the 16th, 50th, and 84th percentiles of the posterior.

<table><caption>**Table A1**
Remeasurements of the Ion EWs ($W_r$) of J1306+1356 Are Presented</caption><thead><tr><th>Ions</th><th><i>W</i><sub>r</sub>(System 1)<br>(Å)</th><th><i>W</i><sub>r</sub>(System 2)<br>(Å)</th><th>log <i>N</i> (System 1)<br>(cm<sup>-2</sup>)</th><th>log <i>N</i> (System 2)<br>(cm<sup>-2</sup>)</th></tr></thead><tbody><tr><td>Mg II(λ2796)</td><td>2.891 ± 0.109</td><td>...</td><td>...</td><td>...</td></tr><tr><td>Mg II blended</td><td></td><td>2.959 ± 0.160</td><td>...</td><td>...</td></tr><tr><td>Mg II(λ2803)</td><td>...</td><td>2.371 ± 0.097</td><td>...</td><td>...</td></tr><tr><td>Mg I(λ2852)</td><td>0.391 ± 0.250</td><td>0.359 ± 0.181</td><td>&lt;13.98</td><td>&lt;13.94</td></tr><tr><td>Fe II(λ2586)</td><td>0.553 ± 0.141</td><td>1.141 ± 0.123</td><td>14.32 ± 0.02</td><td>14.60 ± 0.12</td></tr><tr><td>Si II(λ1526)</td><td>0.915 ± 0.062</td><td>1.137 ± 0.060</td><td>15.76 ± 0.03</td><td>15.82 ± 0.05</td></tr><tr><td>Al II(λ1670)</td><td>0.923 ± 0.069</td><td>0.988 ± 0.067</td><td>13.59 ± 0.11</td><td>13.726 ± 0.10</td></tr><tr><td>Al III(λ1854)</td><td>0.165 ± 0.108</td><td>0.106 ± 0.105</td><td>13.034 ± 0.01</td><td>13.649 ± 0.11</td></tr><tr><td>Zn II(λ2026)</td><td>&lt; 0.027</td><td>0.160 ± 0.092</td><td>&lt;12.237</td><td>13.056 ± 0.05</td></tr><tr><td>C IV(λ1548)</td><td>1.141 ± 0.298</td><td>0.552 ± 0.267</td><td>...</td><td>...</td></tr><tr><td>C IV(λ1550)</td><td>0.791 ± 0.358</td><td>0.435 ± 0.251</td><td>...</td><td>...</td></tr></tbody></table>

**Note.** We denote the system at $z = 4.8634$ as System 1 and the one at $z = 4.8821$ as System 2. The blended region refers to Mg II(λ2803) in System 1, which is blended with Mg II(λ2796) in System 2. Columns (4) and (5) show the Voigt-profile-fitted column densities of ions with a Doppler parameter $b = 25$ km s⁻¹. The uncertainties are given by varying the $b$ value by ±5 km s⁻¹. We do not measure the column densities of Mg II and C IV lines, due to the strong blending in these two systems.
<figure><img src="image_15.png" /><figcaption>**Figure A4.** Complete velocity profiles of the absorption lines of the two USMg II structures toward J1306+3150 at z = 4.87. System 1 at z = 4.8634 and System 2 at z = 4.8821 are plotted in blue and red shadow, respectively. The Voigt fitting profiles of the Fe II, Si II, Al II, Al III, and Zn II lines in these two systems are plotted with the green and orange dashed lines, respectively. The vertical dashed lines indicate the positions of the subcomponents in the fittings of the two systems. The quasar spectra were taken with Magellan/FIRE, with a spectral resolution of R ~ 6000.</figcaption></figure>
<figure><img src="image_16.png" /></figure>

**Figure A5.** CLOUDY modeling of two absorbing systems at $z \sim 4.9$ along the sight line J1306+3150. The observed values of System 1 at $z = 4.8634$ and System 2 at $z = 4.8821$ are plotted as the blue dashed and red dashed-dotted lines, respectively. The modeling curves are plotted with different metallicities ($\log(Z/Z_\odot)$), ranging from -2.5 to 0. From the upper left to the lower right, we plot the column density ratio of Al II to Al III against the ionization parameter and the column densities of Zn II, Si II, and Fe II against the ionization parameter, respectively.

## ORCID iDs

Siwei Zou https://orcid.org/0000-0002-3983-6484

Robert A. Simcoe https://orcid.org/0000-0003-3769-9559

Céline Péroux https://orcid.org/0000-0002-4288-599X

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

Feige Wang https://orcid.org/0000-0002-7633-431X

Jinning Liang https://orcid.org/0000-0001-8405-2921

Fangzhou Jiang https://orcid.org/0000-0001-6115-0633

Zihao Li https://orcid.org/0000-0001-5951-459X

Wen Sun https://orcid.org/0000-0003-3995-4859

Xiaohui Fan https://orcid.org/0000-0003-3310-0131

Jinyi Yang https://orcid.org/0000-0001-5287-4242

Luis C. Ho https://orcid.org/0000-0001-6947-5846

Xiaojing Lin https://orcid.org/0000-0001-6052-4234

Jianan Li https://orcid.org/0000-0002-1815-4839

Jianwei Lyu https://orcid.org/0000-0002-6221-1829

Lile Wang https://orcid.org/0000-0002-6540-7042

Weizhe Liu https://orcid.org/0000-0002-7214-5976

Emanuele Paolo Farina https://orcid.org/0000-0002-6822-2254

Xiangyu Jin https://orcid.org/0000-0002-5768-738X

Cheng Cheng https://orcid.org/0000-0003-0202-0534

## References

Bacon, R., Conseil, S., Mary, D., et al. 2017, A&A, 608, A1

Barnes, L. A., Garel, T., & Kacprzak, G. G. 2014, PASP, 126, 969

Bertin, E., & Arnouts, S. 1996, A&AS, 117, 393

Bertin, E., Schefer, M., Apostolakos, N., et al. 2020, in ASP Conf. Ser. 527, Astronomical Data Analysis Software and Systems XXIX, ed. R. Pizzo, E. R. Deul, J. D. Mol et al. (San Francisco, CA: ASP), 461, https://www.aspbooks.org/a/volumes/article_details/?paper_id=39877

Bordoloi, R., Simcoe, R. A., Matthee, J., et al. 2023, arXiv:2307.01273

Bushouse, H., Eisenhamer, J., Dencheva, N., et al. 2025, JWST Calibration Pipeline, v1.19.1, Zenodo, doi:10.5281/zenodo.6984365

Calzetti, D., Armus, L., Bohlin, R. C., et al. 2000, ApJ, 533, 682

Carnall, A. C., McLure, R. J., Dunlop, J. S., & Davé, R. 2018, MNRAS, 480, 4379

Chen, S.-F. S., Simcoe, R. A., Torrey, P., et al. 2017, ApJ, 850, 188

Christensen, L., Jakobsen, P., Willott, C., et al. 2023, A&A, 680, A82

Dekel, A., & Birnboim, Y. 2006, MNRAS, 368, 2

Drake, A. B., Garel, T., Wisotzki, L., et al. 2017, A&A, 608, A6

Dutta, R., Fumagalli, M., Fossati, M., et al. 2020, MNRAS, 499, 5022

Dutta, R., Fumagalli, M., Fossati, M., et al. 2021, MNRAS, 508, 4573

Faucher-Giguère, C.-A., & Oh, S. P. 2023, ARA&A, 61, 131

Ferland, G. J., Chatzikos, M., Guzmán, F., et al. 2017, RMxAA, 53, 385

Galbiati, M., Dutta, R., Fumagalli, M., Fossati, M., & Cantalupo, S. 2024, A&A, 690, A7

Gauthier, J.-R. 2013, MNRAS, 432, 1444

Girelli, G., Pozzetti, L., Bolzonella, M., et al. 2020, A&A, 634, A135

Gnedin, N. Y., & Kravtsov, A. V. 2011, ApJ, 728, 88

Greene, T. P., Kelly, D. M., Stansberry, J., et al. 2017, JATIS, 3, 035001

Guha, L. K., Srianand, R., Dutta, R., et al. 2022, MNRAS, 513, 3836
Guha, L. K., Srianand, R., & Petitjean, P. 2024, MNRAS, 527, 5075

Hashimoto, T., Garel, T., Guiderdoni, B., et al. 2017, A&A, 608, A10

Heintz, K. E., Brammer, G. B., Watson, D., et al. 2025, A&A, 693, A60

Jenkins, E. B., Savage, B. D., & Spitzer, L., Jr. 1986, ApJ, 301, 355

Jiang, L., Fan, X., Vestergaard, M., et al. 2007, AJ, 134, 1150

Kacprzak, G. G., Churchill, C. W., Ceverino, D., et al. 2010, ApJ, 711, 533

Kennicutt, R. C. J. 1998, ApJ, 498, 541

Krogager, J.-K. 2018, arXiv:1803.01187

Krogager, J.-K., Geier, S., Fynbo, J. P. U., et al. 2015, ApJS, 217, 5

Krogager, J.-K., Møller, P., Fynbo, J. P. U., & Noterdaeme, P. 2017, MNRAS, 469, 2959

Lan, T.-W., & Mo, H. 2018, ApJ, 866, 36

Li, Z., Cai, Z., Sun, F., et al. 2023, arXiv:2310.09327

Liang, J., Jiang, F., Mo, H., et al. 2025, MNRAS, 541, 2304

Lofthouse, E. K., Fumagalli, M., Fossati, M., et al. 2023, MNRAS, 518, 305

Matejek, M. S., Simcoe, R. A., Cooksey, K. L., & Seyffert, E. N. 2013, ApJ, 764, 9

Ménard, B., Wild, V., Nestor, D., et al. 2011, MNRAS, 417, 801

Murphy, E. J., Condon, J. J., Schinnerer, E., et al. 2011, ApJ, 737, 67

Neeleman, M., Kanekar, N., Prochaska, J. X., Rafelski, M. A., & Carilli, C. L. 2019, ApJL, 870, L19

Neeleman, M., Kanekar, N., Prochaska, J. X., et al. 2017, Sci, 355, 1285

Neeleman, M., Kanekar, N., Prochaska, J. X., et al. 2018, ApJL, 856, L12

Neeleman, M., Prochaska, J. X., Kanekar, N., & Rafelski, M. 2020, Natur, 581, 269

Nelson, D., Pillepich, A., Springel, V., et al. 2018, MNRAS, 475, 624

Nelson, E. J., Brammer, G., Gimenez-Arteaga, C., et al. 2024, ApJL, 976, L27

Nestor, D. B., Johnson, B. D., Wild, V., et al. 2011, MNRAS, 412, 1559

Nestor, D. B., Turnshek, D. A., Rao, S. M., & Quider, A. M. 2007, ApJ, 658, 185

Noterdaeme, P., Laursen, P., Petitjean, P., et al. 2012, A&A, 540, A63

Osterbrock, D. E., & Ferland, G. J. 2006, Astrophysics of Gaseous Nebulae and Active Galactic Nuclei (Univ. Science Books)

Outini, M., & Copin, Y. 2020, A&A, 633, A43

Peng, C. Y., Ho, L. C., Impey, C. D., & Rix, H.-W. 2002, AJ, 124, 266

Peng, C. Y., Ho, L. C., Impey, C. D., & Rix, H.-W. 2010, AJ, 139, 2097

Péroux, C., Weng, S., Karki, A., et al. 2022, MNRAS, 516, 5618

Péroux, C., Zwaan, M. A., Klitsch, A., et al. 2019, MNRAS, 485, 1595

Prochaska, J. X., Neeleman, M., Kanekar, N., & Rafelski, M. 2019, ApJL, 886, L35

Prochter, G. E., Prochaska, J. X., & Burles, S. M. 2006, ApJ, 639, 766

Rafelski, M., Wolfe, A. M., Prochaska, J. X., Neeleman, M., & Mendez, A. J. 2012, ApJ, 755, 89

Rubin, K. H. R., Prochaska, J. X., Koo, D. C., et al. 2014, ApJ, 794, 156

Rubin, K. H. R., Prochaska, J. X., Ménard, B., et al. 2011, ApJ, 728, 55

Schäerer, D. 2003, A&A, 397, 527

Schroetter, I., Bouché, N. F., Zabl, J., et al. 2019, MNRAS, 490, 4368

Sebastian, A. M., Ryan-Weber, E., Davies, R. L., et al. 2024, MNRAS, 530, 1829

Shen, Y., Wu, J., Jiang, L., et al. 2019, ApJ, 873, 35

Sobral, D., & Matthée, J. 2019, A&A, 623, A157

Soto, K. T., Lilly, S. J., Bacon, R., Richard, J., & Conseil, S. 2016, MNRAS, 458, 3210

Sun, F., Egami, E., Pirzkal, N., et al. 2022, ApJL, 936, L8

Sun, F., Wang, F., Yang, J., et al. 2025, ApJ, 980, 12

Sun, W., Ho, L. C., Zhuang, M.-Y., et al. 2024, ApJ, 960, 104

Szakacs, R., Péroux, C., Zwaan, M., et al. 2021, MNRAS, 505, 4746

Urrutia, T., Wisotzki, L., Kerutt, J., et al. 2019, A&A, 624, A141

van der Wel, A., Franx, M., van Dokkum, P. G., et al. 2014, ApJ, 788, 28

Verhamme, A., Garel, T., Ventou, E., et al. 2018, MNRAS, 478, L60

Wang, F., Yang, J., Hennawi, J. F., et al. 2023, ApJL, 951, L4

Weilbacher, P. M., Palsa, R., Streicher, O., et al. 2020, A&A, 641, A28

Wendt, M., Bouché, N. F., Zabl, J., Schroetter, I., & Muzahid, S. 2021, MNRAS, 502, 3733

Weng, S., Péroux, C., Karki, A., et al. 2023, MNRAS, 519, 931

Wisotzki, L., Bacon, R., Blaizot, J., et al. 2016, A&A, 587, A98

Witstok, J., Smit, R., Saxena, A., et al. 2024, A&A, 682, A40

Wu, Y., Wang, F., Cai, Z., et al. 2023, ApJL, 956, L40

Yang, J., Wang, F., Fan, X., et al. 2023, ApJL, 951, L5

Zabl, J., Bouché, N. F., Schroetter, I., et al. 2019, MNRAS, 485, 1961

Zou, S., Cai, Z., Wang, F., et al. 2024b, ApJL, 963, L28

Zou, S., Jiang, L., Shen, Y., et al. 2021, ApJ, 906, 32

Zou, S., Jiang, L., Cai, Z., et al. 2024a, ApJ, 960, 34

Zou, S., Petitjean, P., Noterdaeme, P., et al. 2018, A&A, 616, A158