arXiv subjects

Benjamin Schneider

Publications and source records attributed to Benjamin Schneider.

At least 19 recordsLinked to original sources

arXiv2026

Failed jet breakout in the metal-poor broad-lined type Ic supernova 2026gzf

A long-standing question in the death of massive stars is the role of relativistic jets. While many gamma-ray bursts and some fast X-ray transients seem to be associated with broad-lined type Ic supernovae, the opposite is not true. The lack of observable jet emission in those Ic-BL SNe can be explained by invoking off-axis jets, choked jets that inject all their energy into the stellar envelope, baryon-loaded jets for which the prompt high-energy emission is strongly suppressed, or non-jetted SNe. The lack of exact explosion time in the majority of SNe presents an obstacle to distinguish between these scenarios. Here we report the properties of SN 2026gzf associated with the X-ray thermal Einstein Probe shock-breakout EP260321a at z=0.0343. The absence of compelling shocked cocoon and radio emission up to 54 days, combined with initial expansion velocities of ~30,000 km/s and a circumstellar shell of ~0.07 M$_\odot$, favour a scenario for SN 2026gzf in which a jet was choked in the circumstellar shell. Our high-spatial resolution images of the SN environment show that the progenitor was located between two highly star-forming regions with a metallicity lower than any previously known Ic-BL SN. As the first case of a Ic-BL SN associated with high-energy prompt emission without the signature of a jet, SN 2026gzf provides a unique perspective to understand the successful launch of relativistic jets during the deaths of massive stars.

astro-ph.HE↗

arXiv2026

GRB 260310A / SN 2026fgk: A Multi-Wavelength Study of a Nearby Underluminous Long GRB and SN with a Complex Afterglow

We present a comprehensive multi-wavelength study of GRB 260310A / SN 2026fgk, a nearby ($z=0.153$), long-duration gamma-ray burst (GRB) with an exceptionally underluminous prompt $\gamma$-ray emission and a Comptonized spectrum. The burst occurred at the edge of a blue host galaxy at a projected distance of 15 kpc, which is one of the largest offsets reported for a long GRB. The bright optical afterglow, with dense coverage from COLIBR\'I, likely peaked at a few to several hours post-burst, followed by a shallow decay not expected from canonical afterglow models. Both the optical and X-ray light curves show a brief chromatic plateau from $4-7$ days. We show that the subsequent rebrightening observed at $\sim20$ days is best explained by the combined contribution of the associated Type Ic-BL supernova, identified in GTC spectra, and a late-time refreshed shock. The broadband optical to X-ray spectral energy distribution is well described by synchrotron emission from the forward shock, while the radio observations demand an additional emission component. We model the afterglow using (a) an on-axis uniform jet from a dirty fireball with late-time energy injection and (b) a misaligned jet with power-law angular structure, both having material emitting along our line-of-sight (LOS) moving with an initial Lorentz factor of $\Gamma_0\sim20-35$. We conclude that at more typical GRB distances ($z\gtrsim0.5$) the prompt $\gamma$-ray emission from this source would likely have escaped detection, whereas its optical afterglow would have remained observable, making the event appear as an orphan afterglow or a gamma-ray quiet fast X-ray transient.

astro-ph.HE↗

arXiv2026

ASH: Agents that Self-Hone via Embodied Learning

Long-horizon embodied tasks remain a fundamental challenge in AI, as current methods rely on hand-engineered rewards or action-labeled demonstrations, neither of which scales. We introduce ASH, an agentic system that learns an embodied policy from unlabeled, noisy internet video, without reward shaping or expert annotation. ASH follows a self-improvement loop; when it gets stuck, ASH learns an Inverse Dynamics Model (IDM) from its own trajectories, and uses its IDM to extract supervision from relevant internet video. ASH uses unsupervised learning to identify key moments from large-scale internet video and retains them as long-term memory -- allowing it to tackle long-horizon problems. We evaluate ASH on two complementary environments demanding multi-hour planning: Pokemon Emerald, a turn-based RPG, and The Legend of Zelda: The Minish Cap, a real-time action-adventure game. In both games, behavioral cloning, retrieval-augmented and zero-shot foundation-model baselines plateau, while ASH sustains progression across our 8-hour evaluation. ASH reaches an average of $11.2/12$ milestones in Pokemon Emerald and $9.9/12$ in Legend of Zelda, while the strongest baseline gets stuck in both environments at an average of $6.5/12$ and $6.0/12$ milestones, respectively. We demonstrate that self-improving agents are a scalable recipe for long-horizon embodied learning.

cs.AI↗

arXiv2026

SWE-QA-Pro: A Representative Benchmark and Scalable Training Recipe for Repository-Level Code Understanding

Agentic repository-level code understanding is essential for automating complex software engineering tasks, yet the field lacks reliable benchmarks. Existing evaluations often overlook the long tail topics and rely on popular repositories where Large Language Models (LLMs) can cheat via memorized knowledge. To address this, we introduce SWE-QA-Pro, a benchmark constructed from diverse, long-tail repositories with executable environments. We enforce topical balance via issue-driven clustering to cover under-represented task types and apply a rigorous difficulty calibration process: questions solvable by direct-answer baselines are filtered out. This results in a dataset where agentic workflows significantly outperform direct answering (e.g., a ~13-point gap for Claude Sonnet 4.5), confirming the necessity of agentic codebase exploration. Furthermore, to tackle the scarcity of training data for such complex behaviors, we propose a scalable synthetic data pipeline that powers a two-stage training recipe: Supervised Fine-Tuning (SFT) followed by Reinforcement Learning from AI Feedback (RLAIF). This approach allows small open models to learn efficient tool usage and reasoning. Empirically, a Qwen3-8B model trained with our recipe surpasses GPT-4o by 2.3 points on SWE-QA-Pro and substantially narrows the gap to state-of-the-art proprietary models, demonstrating both the validity of our evaluation and the effectiveness of our agentic training workflow.

cs.SE↗

arXiv2025

First Results from the PanRadio Gamma-Ray Burst Collaboration: The 400-day Afterglow of GRB 230815A

We introduce the PanRadio Gamma-ray Burst (GRB) program carried out on the Australia Telescope Compact Array: a systematic, multi-year, radio survey of all southern $\textit{Swift}$ GRB events, comprehensively following the multi-frequency evolution of their afterglows from within an hour to years post-burst. We present the results of the 400-day observing campaign following the afterglow of the long-duration (collapsar) GRB 230815A, the first one detected through this program. Typically, GRB 230815A would not otherwise receive traditional radio follow-up, given it has no known redshift and lacks comprehensive multi-wavelength follow-up due to its high line-of-sight extinction with $A_V=2.3$. We found its early X-ray jet break at ${\sim}0.1$ days post-burst to be at odds with the evolution of the multi-frequency radio light curves that were traced over an unusually long duration of $400$ days. The radio light curves approximately evolved (with minor deviations) according to the standard self-similar expansion for a relativistic blast wave in a homogeneous environment prior to the jet break, showing no evidence for evolutions of the microphysical parameters describing the electron acceleration processes. We reconcile these features by proposing a two-component jet: the early X-ray break originates from a narrow component with a half-opening angle ${\sim}2.1^{\circ}$, while the evolution of the radio afterglow stems from a wider component with a half-opening angle of $\gtrapprox 35^{\circ}$. The PanRadio GRB program will establish a sample of comprehensively followed GRBs, where a rigorous inspection of their microphysical and dynamical parameters can be performed, thereby revealing the diversity of features in their outflows and environments.

astro-ph.HE↗

arXiv2025

HOLISMOKES XIX: SN 2025wny at $z=2$, the first strongly lensed superluminous supernova

We present imaging and spectroscopic observations of supernova SN 2025wny, associated with the lens candidate PS1 J0716+3821. Photometric monitoring from the Lulin and Maidanak observatories confirms multiple point-like images, consistent with SN 2025wny being strongly lensed by two foreground galaxies. Optical spectroscopy of the brightest image with the Nordic Optical Telescope and the University of Hawaii 88-inch Telescope allows us to determine the redshift to be z_s = 2.008 +- 0.001, based on narrow absorption lines originating in the interstellar medium of the supernova host galaxy. At this redshift, the spectra of SN 2025wny are consistent with those of superluminous supernovae of Type I. We find a high ejecta temperature and depressed spectral lines compared to other similar objects. We also measure, for the first time, the redshift of the fainter of the two lens galaxies (the "perturber") to be z_p = 0.375 +- 0.001, fully consistent with the DESI spectroscopic redshift of the main deflector at z_d = 0.3754. SN 2025wny thus represents the first confirmed galaxy-scale strongly lensed supernova with time delays likely in the range of days to weeks, as judged from the image separations. This makes SN 2025wny suitable for cosmography, offering a promising new system for independent measurements of the Hubble constant. Following a tradition in the field of strongly-lensed SNe, we give SN 2025wny the nickname SN Winny.

astro-ph.CO↗

arXiv2025

Evidence of Energy Injection in the Short and Distant GRB 250221A in a High Density Environment

We present the photometric and spectroscopic analysis of the short-duration GRB 250221A ($T_{90}=1.80\pm0.32$ s), using a data set from the optical facilities COLIBR\'I, the Harlingten 50~cm Telescope, and the Very Large Telescope. We complement these observations with data from the Neil Gehrels Swift Observatory and the Einstein Probe, as well as radio observations from the Very Large Array. GRB 250221A is among the few short GRBs with direct afterglow spectroscopy, which gives a secure redshift determination of $z=0.768$ and allows the unambiguous identification of the host as a galaxy with a star-formation rate of $\sim3\,M_\odot\,{\rm yr}^{-1}$. The X-ray and optical light curves up to $T_0+3\times 10^4$ s (where $T_0$ refers to the GRB trigger time) are well described by forward-shock synchrotron emission in the slow-cooling regime within the standard fireball framework. However, at $T_0 \sim 5\times 10^4$ s, both the X-ray and optical bands exhibit an excess over the same interval, which we interpret as evidence of energy injection into a jet with a half-opening angle of $\theta_j=11.5^{\circ}$ through a refreshed shock powered by late central engine activity or a radially stratified ejecta. The burst properties (duration, spectral hardness, peak energy, and location in the Amati plane) all favour a compact binary merger origin. However, our modelling of the afterglow suggests a dense circumburst medium ($n\sim80$ cm$^{-3}$), which is more typical of a collapsar environment.

astro-ph.HE↗

arXiv2025

JWST Spectroscopy of GRB 250702B: An Extremely Rare and Exceptionally Energetic Burst in a Dusty, Massive Galaxy at $z=1.036$

We present follow-up observations of the day-long, repeating GRB 250702B with the Near Infrared Spectrograph (NIRSpec) on board the James Webb Space Telescope (JWST). Through the identification of narrow hydrogen emission lines at a consistent redshift of $z = 1.036 \pm 0.004$, we calibrate the distance scale, and therefore the energetics, of this unique extragalactic transient. At this distance, the resulting $\gamma$-ray energy release is at least $E_{\gamma,\rm iso} = 2.2 \times 10^{54}$\,erg. We find no evidence for ongoing transient emission at the GRB position, and exclude any accompanying supernova with a luminosity comparable to the Type Ic broad-line SN 2023lcr, though we are unable to constrain fainter events. The inferred rate of such events, assuming at most one in the lifetime of {\em Fermi}, suggests that such bursts are very rare, with volumetric rates $>1,000$ times lower than normal high luminosity long GRBs and $> 10^5$ times lower than core collapse supernovae when corrected for beaming. Furthermore, we find that the host galaxy is unique amongst GRB host galaxies, and extremely rare in the general galaxy population, being extremely large, dusty and with high stellar mass. The identification of such an exotic GRB in such an unusual galaxy raises the possibility that the environment was important in the progenitor channel for this event.

astro-ph.HE↗

arXiv2025

VideoScore2: Think before You Score in Generative Video Evaluation

Recent advances in text-to-video generation have produced increasingly realistic and diverse content, yet evaluating such videos remains a fundamental challenge due to their multi-faceted nature encompassing visual quality, semantic alignment, and physical consistency. Existing evaluators and reward models are limited to single opaque scores, lack interpretability, or provide only coarse analysis, making them insufficient for capturing the comprehensive nature of video quality assessment. We present VideoScore2, a multi-dimensional, interpretable, and human-aligned framework that explicitly evaluates visual quality, text-to-video alignment, and physical/common-sense consistency while producing detailed chain-of-thought rationales. Our model is trained on a large-scale dataset VideoFeedback2 containing 27,168 human-annotated videos with both scores and reasoning traces across three dimensions, using a two-stage pipeline of supervised fine-tuning followed by reinforcement learning with Group Relative Policy Optimization (GRPO) to enhance analytical robustness. Extensive experiments demonstrate that VideoScore2 achieves superior performance with 44.35 (+5.94) accuracy on our in-domain benchmark VideoScore-Bench-v2 and 50.37 (+4.32) average performance across four out-of-domain benchmarks (VideoGenReward-Bench, VideoPhy2, etc), while providing interpretable assessments that bridge the gap between evaluation and controllable generation through effective reward modeling for Best-of-N sampling. Project Page: https://tiger-ai-lab.github.io/VideoScore2/

cs.CV↗

arXiv2025

The day-long, repeating GRB 250702BDE / EP250702a: A unique extragalactic transient

Gamma-ray bursts (GRBs) are singular outbursts of high-energy radiation with durations typically lasting from milliseconds to minutes and, in extreme cases, a few hours. They are attributed to the catastrophic outcomes of stellar-scale events and, as such, are not expected to recur. Here, we present observations of an exceptional GRB\,250702BDE which triggered the {\em Fermi} gamma-ray burst monitor on three occasions over several hours, and which was detected in soft X-rays by the \textit{Einstein Probe} a day before the $\gamma$-ray triggers (EP250702a). We present the discovery of an extremely red infrared counterpart of the event with the VLT, as well as radio observations from MeerKAT. Hubble Space Telescope observations pinpoint the source to a non-nuclear location in a host galaxy with complex morphology, implying GRB 250702BDE is an extragalactic event. The multi-wavelength counterpart is well described with standard afterglow models at a relatively low redshift $z \sim 0.2$, but the prompt emission does not readily fit within the expectations for either collapsar or merger-driven GRBs. Indeed, a striking feature of the multiple prompt outbursts is that the third occurs at an integer multiple of the interval between the first two. Although not conclusive, this could be indicative of periodicity in the progenitor system. We discuss several possible scenarios to explain the exceptional properties of the burst, which suggest that either a very unusual collapsar or the tidal disruption of a white dwarf by an intermediate-mass black hole are plausible explanations for this unprecedented GRB.

astro-ph.HE↗

arXiv2025

GRB 240825A: Early Reverse Shock and Its Physical Implications

Early multiwavelength observations offer crucial insights into the nature of the relativistic jets responsible for gamma-ray bursts and their interaction with the surrounding medium.We present data of GRB 240825A from 17 space- and ground-based telescopes/instruments, covering wavelengths from NIR/optical to X-ray and GeV, and spanning from the prompt emission to the afterglow phase triggered by Swift and Fermi. The early afterglow observations were carried out by SVOM/C-GFT, and spectroscopic observations of the afterglow by GTC, VLT, and TNG determined the redshift of the burst ($z = 0.659$) later.A comprehensive analysis of the prompt emission spectrum observed by Swift-BAT and Fermi-GBM/LAT reveals a rare and significant high-energy cutoff at ~76 MeV. Assuming this cutoff is due to $\gamma\gamma$ absorption allows us to place an upper limit on the initial Lorentz factor, $\Gamma_0 < 245$. The optical/NIR and GeV afterglow light curves be described by the standard external shock model, with early-time emission dominated by a reverse shock (RS) and a subsequent transition to forward shock (FS) emission. Our afterglow modelling yields a consistent estimate of the initial Lorentz factor ($\Gamma_{\rm 0} \sim 234$). Furthermore, the RS-to-FS magnetic field ratio ($\mathcal{R}_B \sim 302$) indicates that the reverse shock region is significantly more magnetized than the FS region. An isotropic-equivalent kinetic energy of $E_{\text{k,iso}} = 5.25 \times 10^{54}$ erg is derived, and the corresponding $\gamma$-ray radiation efficiency is estimated to be $\eta_{\gamma}$ = 3.1%. On the other hand, the standard afterglow model can not reproduce the X-ray light curve of GRB 240825A, calling for improved models to characterize all multiwavelength data.

astro-ph.HE↗

arXiv2025

StructEval: Benchmarking LLMs' Capabilities to Generate Structural Outputs

As Large Language Models (LLMs) become integral to software development workflows, their ability to generate structured outputs has become critically important. We introduce StructEval, a comprehensive benchmark for evaluating LLMs' capabilities in producing both non-renderable (JSON, YAML, CSV) and renderable (HTML, React, SVG) structured formats. Unlike prior benchmarks, StructEval systematically evaluates structural fidelity across diverse formats through two paradigms: 1) generation tasks, producing structured output from natural language prompts, and \textbf{2)} conversion tasks, translating between structured formats. Our benchmark encompasses 18 formats and 44 types of task, with novel metrics for format adherence and structural correctness. Results reveal significant performance gaps-even state-of-the-art models like o1-mini achieve only 75.58 average score, with open-source alternatives lagging approximately 10 points behind. We find generation tasks more challenging than conversion tasks, and producing correct visual content more difficult than generating text-only structures.

cs.SE↗

arXiv2025

QuickVideo: Real-Time Long Video Understanding with System Algorithm Co-Design

Long-video understanding has emerged as a crucial capability in real-world applications such as video surveillance, meeting summarization, educational lecture analysis, and sports broadcasting. However, it remains computationally prohibitive for VideoLLMs, primarily due to two bottlenecks: 1) sequential video decoding, the process of converting the raw bit stream to RGB frames can take up to a minute for hour-long video inputs, and 2) costly prefilling of up to several million tokens for LLM inference, resulting in high latency and memory use. To address these challenges, we propose QuickVideo, a system-algorithm co-design that substantially accelerates long-video understanding to support real-time downstream applications. It comprises three key innovations: QuickDecoder, a parallelized CPU-based video decoder that achieves 2-3 times speedup by splitting videos into keyframe-aligned intervals processed concurrently; QuickPrefill, a memory-efficient prefilling method using KV-cache pruning to support more frames with less GPU memory; and an overlapping scheme that overlaps CPU video decoding with GPU inference. Together, these components infernece time reduce by a minute on long video inputs, enabling scalable, high-quality video understanding even on limited hardware. Experiments show that QuickVideo generalizes across durations and sampling rates, making long video processing feasible in practice.

cs.CV↗

arXiv2025

ScholarCopilot: Training Large Language Models for Academic Writing with Accurate Citations

Academic writing requires both coherent text generation and precise citation of relevant literature. Although recent Retrieval-Augmented Generation (RAG) systems have significantly improved factual accuracy in general-purpose text generation, their ability to support professional academic writing remains limited. In this work, we introduce ScholarCopilot, a unified framework designed to enhance existing large language models for generating professional academic articles with accurate and contextually relevant citations. ScholarCopilot dynamically determines when to retrieve scholarly references by generating a retrieval token [RET], which is then used to query a citation database. The retrieved references are fed into the model to augment the generation process. We jointly optimize both the generation and citation tasks within a single framework to improve efficiency. Our model is built upon Qwen-2.5-7B and trained on 500K papers from arXiv. It achieves a top-1 retrieval accuracy of 40.1% on our evaluation dataset, outperforming baselines such as E5-Mistral-7B-Instruct (15.0%) and BM25 (9.8%). On a dataset of 1,000 academic writing samples, ScholarCopilot scores 16.2/25 in generation quality -- measured across relevance, coherence, academic rigor, completeness, and innovation -- significantly surpassing all existing models, including much larger ones like the Retrieval-Augmented Qwen2.5-72B-Instruct. Human studies further demonstrate that ScholarCopilot, despite being a 7B model, significantly outperforms ChatGPT, achieving 100% preference in citation quality and over 70% in overall usefulness.

cs.CL↗

arXiv2025

EP240801a/XRF 240801B: An X-ray Flash Detected by the Einstein Probe and Implications of its Multiband Afterglow

We present multiband observations and analysis of EP240801a, a low-energy, extremely soft gamma-ray burst (GRB) discovered on August 1, 2024 by the Einstein Probe (EP) satellite, with a weak contemporaneous signal also detected by Fermi/GBM. Optical spectroscopy of the afterglow, obtained by GTC and Keck, identified the redshift of $z = 1.6734$. EP240801a exhibits a burst duration of 148 s in X-rays and 22.3 s in gamma-rays, with X-rays leading by 80.61 s. Spectral lag analysis indicates the gamma-ray signal arrived 8.3 s earlier than the X-rays. Joint spectral fitting of EP/WXT and Fermi/GBM data yields an isotropic energy $E_{\gamma,\rm{iso}} = (5.57^{+0.54}_{-0.50})\times 10^{51}\,\rm{erg}$, a peak energy $E_{\rm{peak}} = 14.90^{+7.08}_{-4.71}\,\rm{keV}$, a fluence ratio $\rm S(25-50\,\rm{keV})/S(50-100\,\rm{keV}) = 1.67^{+0.74}_{-0.46}$, classifying EP240801a as an X-ray flash (XRF). The host-galaxy continuum spectrum, inferred using Prospector, was used to correct its contribution for the observed outburst optical data. Unusual early $R$-band behavior and EP/FXT observations suggest multiple components in the afterglow. Three models are considered: two-component jet model, forward-reverse shock model and forward-shock model with energy injection. Both three provide reasonable explanations. The two-component jet model and the energy injection model imply a relatively small initial energy and velocity of the jet in the line of sight, while the forward-reverse shock model remains typical. Under the two-component jet model, EP240801a may resemble GRB 221009A (BOAT) if the bright narrow beam is viewed on-axis. Therefore, EP240801a can be interpreted as an off-beam (narrow) jet or an intrinsically weak GRB jet. Our findings provide crucial clues for uncovering the origin of XRFs.

astro-ph.HE↗

arXiv2025

Using the XMM-Newton small window mode to investigate systematic uncertainties in the particle background of X-ray charge-coupled device detectors

The level and uncertainty of the particle induced background in CCD detectors plays a crucial role for future X-ray instruments, such as the Wide Field Imager (WFI) onboard Athena. To mitigate the background systematic uncertainties, which will limit the Athena science goals, we aim to understand the relationship between the energetic charged particles interacting in the detector and satellite, and the instrumental science background to an unprecedented level. These particles produce easily identified "cosmic-ray tracks" along with less easily identified signals produced by secondary particles, e.g., X-rays generated by particle interactions with the instrument and indistinguishable from genuine sky X-rays. We utilize the Small Window Mode of the PN camera onboard XMM-Newton to understand the time, spatial and energy dependence of the various background components, particularly the particle induced background. While the distribution of particle events follows expected detector readout patterns, we find a particle track length distribution inconsistent with the simple, isotropic model. We also find that the detector mode-specific readout results in a shifted Cu fluorescent line. We illustrate that on long timescales the variability of the particle background correlates well with the solar cycle. This 20-year lightcurve, can be reproduced by a particle detector onboard Chandra, the HRC anti-coincidence shield. We conclude that the self-anti-coincidence method of removing X-ray-like events near detected particle tracks in the same frame can be optimized with the inclusion of additional information, such as the energy of the X-ray. The results presented here are relevant for any future pixelated X-ray imaging detector, and could allow the WFI to probe to truly faint X-ray surface brightness.

astro-ph.IM↗

arXiv2025

ABC: Achieving Better Control of Multimodal Embeddings using VLMs

Visual embedding models excel at zero-shot tasks like visual retrieval and classification. However, these models cannot be used for tasks that contain ambiguity or require user instruction. These tasks necessitate an embedding model which outputs can use a natural language instruction to control the representation of a visual embedding. Existing CLIP-based approaches embed images and text independently, and fuse the result. We find that this results in weak interactions between modalities, and poor user control over the representation. We introduce ABC, an open-source multimodal embedding model that uses a vision-language model backbone to deeply integrate image features with natural language instructions. ABC achieves best-for-size performance on MSCOCO image-to-text retrieval and is the top performing model on classification and VQA tasks in the Massive Multimodal Embedding Benchmark. With a strongly unified vision-language representation, ABC can use natural language to solve subtle and potentially ambiguous visual retrieval problems. To evaluate this capability, we design CtrlBench, a benchmark that requires interleaving textual instructions with image content for correct retrieval. ABC advances the state of visual embeddings, outputting high-quality visual representations with natural language control. Our model and datasets are available at our project page: https://tiger-ai-lab.github.io/ABC/

cs.CV↗

arXiv2025

Pearls on a string: Dark and bright galaxies on a strikingly straight and narrow filament

We identify a chain of galaxies along an almost straight line in the nearby Universe with a projected length of ~5 Mpc. The galaxies are distributed within projected distances of only 7-105 kpc from the axis of the identified filament. They have redshifts in a very small range of z=0.0361-0.0370 so that their radial velocities are consistent with galaxy proper motions. The filament galaxies are mainly star-forming and have stellar masses in a range of $\rm 10^{9.1}-10^{10.7}\,M_{\odot}$. We search for systems with similar geometrical properties in the full-sky mock galaxy catalogue of the MillenniumTNG simulations and find that although such straight filaments are unusual and rare, they are predicted by $\Lambda$CDM simulations (4% incidence). We study the cold HI gas in a 1.3 Mpc section of the filament through HI-21cm emission line observations and detect eleven HI sources, many more than expected from the HI mass function in a similar volume. They have HI masses $\rm 10^{8.5}-10^{9.5}\,M_{\odot}$ and are mostly within ~120 kpc projected distance from the filament axis. None of these HI sources has a confirmed optical counterpart. Their darkness together with their large HI-21cm line-widths indicate that they contain gas that might not yet be virialized. These clouds must be marking the peaks of the dark matter and HI distributions over large scales within the filament. The presence of such gas clouds around the filament spines is predicted by simulations, but this is the first time that the existence of such clouds in a filament is observationally confirmed.

astro-ph.GA↗