arXiv subjects

Nikhil Garuda

Publications and source records attributed to Nikhil Garuda.

14 recordsLinked to original sources

arXiv2026

The Koi Pond: A Strongly Lensed Protocluster Core hosting a Diverse Population of DSFGs

We present James Webb Space Telescope (JWST) and Atacama Large Millimeter Array (ALMA) observations of PJ0846+15, \textit{The Koi Pond}, a strongly lensed protocluster core at Cosmic Noon. This field offers a magnified view of 11 dusty star-forming galaxies (DSFGs) all at $z=2.67$ (within $\Delta V=800$ km s$^{-1}$) spanning a projected extent of $>300$ kpc lensed by a $z=0.77$ foreground cluster. NIRCam and ALMA Band 6 continuum measurements map the stellar distribution and thermal dust emission respectively at a spatial resolution of $\sim$0.15$^{\prime\prime}$. This analysis reveals a diverse population of DSFGs, with evidence of both interacting and non-interacting systems exhibiting a wide range of morphological features including spiral arms, bars, bulges, clumps/stellar clusters, tidal tails/debris and displaced molecular gas reservoirs. Comparing the rest-frame J- band continuum (F444W) vs (i-J) color (F277W$-$F444W), we find a wide range of values, suggesting a $>$1-dex spread in stellar mass and a dust attenuation reddening of $\Delta A_{\mathrm{V}} > 1$ mag. The DSFG members exhibit varying dust sizes relative to the stellar emission, ranging from compact dusty cores to galaxy-wide emission. Resolved color maps of individual sources showing a spread as high as F277W$-$F444W$=2$ mag suggesting complex stellar-to-dust geometry. Although gas-rich mergers are identified in the core, the most red and dust emitting members are disks exhibiting clumpy structure indicating secular growth can drive these starburst events. Such a remarkable range in properties within this sample suggest DSFGs in protocluster core environments follow diverse evolutionary pathways towards their transition into quiescent, elliptical cluster galaxies.

astro-ph.GA↗

arXiv2026

Hidden in Plain Sight: Searching for Globular Clusters Within JWST Observations of the PLCK G165.7+67.0 Galaxy Cluster

Although the James Webb Space Telescope (JWST) has received much attention for its ability to search deeper into the cosmos than ever before, it also enhances our capability to study objects closer to us in the Universe. We apply a methodology of subtracting intracluster light to the PLCK G165.7+67.0 (G165; $z$ = 0.35) cluster, revealing a population of unresolved point-like sources including globular clusters (GCs). By applying a fitting algorithm in color space used to select galaxy cluster members, we uncover over 900 globular cluster candidates from our point source sample. We also identify candidates by estimating the contribution of interlopers to the point source sample, yielding an estimate of 793$\pm$ 83 globular cluster candidates. We find the color-selected sources to be approximately correlated spatially with the intracluster light and lensing mass of the cluster. The observed luminosity function of the sources shows a turnover point fainter than the completeness limit, so we use fixed-parameter curve fitting models to predict a K-corrected turnover point between $-9.4 \leq M_{\rm F200W} \leq -10.7$ mag, although we predict the expected K-corrected turnover point should be closer to $-7.7 \leq M_{\rm F200W} \leq -8.4$ mag. We discuss the dynamical state of this disturbed galaxy cluster with a bimodal mass distribution using the spatial distribution of GC candidates and find that the radial profiles of our color-selected GC candidates are very consistent with the lensing-derived surface mass density at $>$50 kpc.

astro-ph.GA↗

arXiv2026

HaloFlow II: Robust Galaxy Halo Mass Inference with Domain Adaptation

Precise halo mass ($M_h$) measurements are crucial for cosmology and galaxy formation. HaloFlow introduced a simulation-based inference (SBI) framework that uses state-of-the-art simulated galaxy images to precisely infer $M_h$. However, for HaloFlow to be applied to observations, it must be generalizable even when the underlying galaxy formation physics differ from those in the simulations on which it was trained. Without this generalization, HaloFlow produces biased and overconfident $M_h$ posteriors when applied to simulations with different physics. We introduce HaloFlow$^{\rm DA}$, an extension of HaloFlow that integrates domain adaptation (DA) with SBI to mitigate these cross-simulation shifts. Using synthetic galaxy images forward-modeled from the IllustrisTNG, EAGLE, and SIMBA simulations, we test two DA methods: Domain-Adversarial Neural Networks (DANN) and Maximum Mean Discrepancy (MMD). Incorporating DA significantly reduces bias and improves calibration, with MMD achieving the most stable performance, lowering the normalized residual metric, $\beta$, by an average of 31% and up to 57% when trained and tested on different simulations. Overall, HaloFlow$^{\rm DA}$ produces more robust, less biased with similar precision, $M_h$ constraints than the standard approach using the stellar-to-halo mass relation. HaloFlow$^{\rm DA}$ enables consistent, simulation-trained inference models to generalize across domains, establishing a foundation for robust $M_h$ inference from real HSC-SSP observations.

astro-ph.GA↗

arXiv2025

Testing Lens Models of PLCK G165.7+67.0 Using Lensed SN H0pe

Supernova H0pe is a multiply-imaged Type Ia supernova (SN~Ia) and the second lensed SN to yield a measurement of the Hubble constant by the time-delay cosmography method, finding $H_0 = 75.4^{+8.1}_{-5.5} \text{km s}^{-1} \text{Mpc}^{-1}$ (Pascale et. al 2025). We investigate the seven lens modeling approaches used to derive $H_0$, assessing their agreement with $\Lambda \text{CDM}$ constraints from SN~Ia surveys through a purely observational comparison. \textbf{We test each lens model by combining its predicted magnifications with the observed time delays to reconstruct the intrinsic SN~Ia luminosity and corresponding distance modulus.} While photometrically derived magnifications yield distance moduli in line with $\Lambda \text{CDM}$ expectations, our comparison reveals that lens model predictions, even the most precise ones, \textbf{consistently overestimate the magnification, with an offset $> 1$~mag}. This known bias, already appreciated by modeling teams, is independently confirmed through our analysis and highlights the value of lensed SNe as a tool to test model accuracy. If unaccounted for, such magnification biases can propagate into uncertainties in derived cosmological parameters, including $H_0$, a critical challenge for precision cosmology using strongly lensed transients.

astro-ph.CO↗

arXiv2025

Forecasting the Observable Rates of Gravitationally Lensed Supernovae for the PASSAGES Dusty Starbursts

More than 60 years have passed since the first formal suggestion to use strongly-lensed supernovae to measure the expansion rate of the Universe through time-delay cosmography. Yet, fewer than 10 such objects have ever been discovered. We consider the merits of a targeted strategy focused on lensed hyperluminous infrared galaxies -- among the most rapidly star-forming galaxies known in the Universe. With star formation rates (SFRs) $\sim {200 - 6000}~\textrm{M}_\odot~\textrm{yr}^{-1}$, the $\sim 30$ objects in the Planck All-Sky Survey to Analyze Gravitationally-lensed Extreme Starbursts (PASSAGES) are excellent candidates for a case study, in particular, and have already led to the discovery of the multiply-imaged SN H0pe. Considering their lens model-corrected SFRs, we estimate their intrinsic supernova rates to be an extraordinary ${1.8 - 65}~\textrm{yr}^{-1}$ (core-collapse) and ${0.2 - 6.4}~\textrm{yr}^{-1}$ (Type Ia). Moreover, these massive starbursts typically have star-forming companions which are unaccounted for in this tally. We demonstrate a strong correlation between Einstein radius and typical time delays, with cluster lenses often exceeding several months (and therefore most favorable for high-precision $H_0$ inferences). A multi-visit monitoring campaign with a sensitive infrared telescope (namely, JWST) is necessary to mitigate dust attenuation. Still, a porous interstellar medium and clumpy star formation in these extreme galaxies might produce favorable conditions for detecting supernovae as transient point sources. Targeted campaigns of known lensed galaxies to discover new lensed supernovae can greatly complement wide-area cadenced surveys. Increasing the sample size helps to realize the potential of supernova time-delay cosmography to elucidate the Hubble tension through a single-step measurement, independent of other $H_0$ techniques.

astro-ph.GA↗

arXiv2025

PASSAGES: The Discovery of a Strongly Lensed Protocluster Core Candidate at Cosmic Noon

Investigating the processes by which galaxies rapidly build up their stellar mass during the peak of their star formation ($z=2-3$) is crucial to advancing our understanding of the assembly of large-scale structures. We report the discovery of one of the most gas- and dust-rich protocluster core candidates, PJ0846+15 (J0846), from the Planck All-Sky Survey to Analyze Gravitationally lensed Extreme Starbursts (PASSAGES) sample. The exceedingly high total star formation rate (SFR) uncorrected for lensing magnification ($\mu$) of $\mu\text{SFR} = 39900^{+23000}_{-12900} \text{ M}_\odot\text{ yr}^{-1}$ is the result of a foreground cluster lensing at least 11 dusty star-forming galaxies between $z=2.660-2.669$, where the intrinsic value is estimated to be $\text{SFR} = 5200^{+3200}_{-2000} \text{ M}_\odot\text{ yr}^{-1}$. Atacama Large Millimeter Array (ALMA) observations uncovered 18 CO(3--2) emission-line detections, some of which are multiply-imaged systems, lensed by a foreground cluster at $z=0.77$. We present the first multi-wavelength characterization of this field, constructing a lens model that predicts that these 11 galaxies ($\mu \simeq 1.5-25$) are contained within a projected physical extent of $280 \times 150 \text{ kpc}$, with a velocity dispersion of $\sigma_{v} = 246 \pm 72 \text{ km s}^{-1}$. J0846 exhibits the rare case of a protocluster candidate whose core is strongly-lensed, offering a magnified view of the rapid stellar buildup within an overdense environment at Cosmic Noon.

astro-ph.GA↗

arXiv2025

A Survey on Hypothesis Generation for Scientific Discovery in the Era of Large Language Models

Hypothesis generation is a fundamental step in scientific discovery, yet it is increasingly challenged by information overload and disciplinary fragmentation. Recent advances in Large Language Models (LLMs) have sparked growing interest in their potential to enhance and automate this process. This paper presents a comprehensive survey of hypothesis generation with LLMs by (i) reviewing existing methods, from simple prompting techniques to more complex frameworks, and proposing a taxonomy that categorizes these approaches; (ii) analyzing techniques for improving hypothesis quality, such as novelty boosting and structured reasoning; (iii) providing an overview of evaluation strategies; and (iv) discussing key challenges and future directions, including multimodal integration and human-AI collaboration. Our survey aims to serve as a reference for researchers exploring LLMs for hypothesis generation.

cs.CL↗

arXiv2024

Using Large Language Models for Automated Grading of Student Writing about Science

Assessing writing in large classes for formal or informal learners presents a significant challenge. Consequently, most large classes, particularly in science, rely on objective assessment tools such as multiple-choice quizzes, which have a single correct answer. The rapid development of AI has introduced the possibility of using large language models (LLMs) to evaluate student writing. An experiment was conducted using GPT-4 to determine if machine learning methods based on LLMs can match or exceed the reliability of instructor grading in evaluating short writing assignments on topics in astronomy. The audience consisted of adult learners in three massive open online courses (MOOCs) offered through Coursera. One course was on astronomy, the second was on astrobiology, and the third was on the history and philosophy of astronomy. The results should also be applicable to non-science majors in university settings, where the content and modes of evaluation are similar. The data comprised answers from 120 students to 12 questions across the three courses. GPT-4 was provided with total grades, model answers, and rubrics from an instructor for all three courses. In addition to evaluating how reliably the LLM reproduced instructor grades, the LLM was also tasked with generating its own rubrics. Overall, the LLM was more reliable than peer grading, both in aggregate and by individual student, and approximately matched instructor grades for all three online courses. The implication is that LLMs may soon be used for automated, reliable, and scalable grading of student science writing.

cs.CL↗

arXiv2024

Estimating Dark Matter Halo Masses in Simulated Galaxy Clusters with Graph Neural Networks

Galaxies grow and evolve in dark matter halos. Because dark matter is not visible, galaxies' halo masses ($\rm{M}_{\rm{halo}}$) must be inferred indirectly. We present a graph neural network (GNN) model for predicting $\rm{M}_{\rm{halo}}$ from stellar mass ($\rm{M}_{*}$) in simulated galaxy clusters using data from the IllustrisTNG simulation suite. Unlike traditional machine learning models like random forests, our GNN captures the information-rich substructure of galaxy clusters by using spatial and kinematic relationships between galaxy neighbour. A GNN model trained on the TNG-Cluster dataset and independently tested on the TNG300 simulation achieves superior predictive performance compared to other baseline models we tested. Future work will extend this approach to different simulations and real observational datasets to further validate the GNN model's ability to generalise.

astro-ph.GA↗

arXiv2024

Grading Massive Open Online Courses Using Large Language Models

Massive open online courses (MOOCs) offer free education globally. Despite this democratization of learning, the massive enrollment in these courses makes it impractical for an instructor to assess every student's writing assignment. As a result, peer grading, often guided by a straightforward rubric, is the method of choice. While convenient, peer grading often falls short in terms of reliability and validity. In this study, we explore the feasibility of using large language models (LLMs) to replace peer grading in MOOCs. To this end, we adapt the zero-shot chain-of-thought (ZCoT) prompting technique to automate the feedback process once the LLM assigns a score to an assignment. Specifically, to instruct LLMs for grading, we use three distinct prompts based on ZCoT: (1) ZCoT with instructor-provided correct answers, (2) ZCoT with both instructor-provided correct answers and rubrics, and (3) ZCoT with instructor-provided correct answers and LLM-generated rubrics. We tested these prompts in 18 different scenarios using two LLMs, GPT-4 and GPT-3.5, across three MOOCs: Introductory Astronomy, Astrobiology, and the History and Philosophy of Astronomy. Our results show that ZCoT, when augmented with instructor-provided correct answers and rubrics, produces grades that are more aligned with those assigned by instructors compared to peer grading. Finally, our findings indicate a promising potential for automated grading systems in MOOCs, especially in subjects with well-defined rubrics, to improve the learning experience for millions of online learners worldwide.

cs.CL↗

arXiv2024

Birds of a Feather: Resolving Stellar Mass Assembly With JWST/NIRCam in a Pair of Kindred $z \sim 2$ Dusty Star-forming Galaxies Lensed by the PLCK G165.7+67.0 Cluster

We present a new parametric lens model for the G165.7+67.0 galaxy cluster, which was discovered with $Planck$ through its bright submillimeter flux, originating from a pair of extraordinary dusty star-forming galaxies (DSFGs) at $z\approx 2.2$. Using JWST and interferometric mm/radio observations, we characterize the intrinsic physical properties of the DSFGs, which are separated by only $\sim 1^{\prime\prime}$ (8 kpc) and a velocity difference $\Delta V \lesssim 600~{\rm km}~{\rm s}^{-1}$ in the source plane, and thus likely undergoing a major merger. Boasting intrinsic star formation rates ${\rm SFR}_{\rm IR} = 320 \pm 70$ and $400 \pm 80~ M_\odot~{\rm yr}^{-1}$, stellar masses ${\rm log}[M_\star/M_\odot] = 10.2 \pm 0.1$ and $10.3 \pm 0.1$, and dust attenuations $A_V = 1.5 \pm 0.3$ and $1.2 \pm 0.3$, they are remarkably similar objects. We perform spatially-resolved pixel-by-pixel SED fitting using rest-frame near-UV to near-IR imaging from JWST/NIRCam for both galaxies, resolving some stellar structures down to 100 pc scales. Based on their resolved specific SFRs and $UVJ$ colors, both DSFGs are experiencing significant galaxy-scale star formation events. If they are indeed interacting gravitationally, this strong starburst could be the hallmark of gas that has been disrupted by an initial close passage. In contrast, the host galaxy of the recently discovered triply-imaged SN H0pe has a much lower SFR than the DSFGs, and we present evidence for the onset of inside-out quenching and large column densities of dust even in regions of low specific SFR. Based on the intrinsic SFRs of the DSFGs inferred from UV through FIR SED modeling, this pair of objects alone is predicted to yield an observable $1.1 \pm 0.2~{\rm CCSNe~yr}^{-1}$, making this cluster field ripe for continued monitoring.

astro-ph.GA↗

arXiv2024

Large Language Models As MOOCs Graders

Massive open online courses (MOOCs) unlock the doors to free education for anyone around the globe with access to a computer and the internet. Despite this democratization of learning, the massive enrollment in these courses means it is almost impossible for one instructor to assess every student's writing assignment. As a result, peer grading, often guided by a straightforward rubric, is the method of choice. While convenient, peer grading often falls short in terms of reliability and validity. In this study, using 18 distinct settings, we explore the feasibility of leveraging large language models (LLMs) to replace peer grading in MOOCs. Specifically, we focus on two state-of-the-art LLMs: GPT-4 and GPT-3.5, across three distinct courses: Introductory Astronomy, Astrobiology, and the History and Philosophy of Astronomy. To instruct LLMs, we use three different prompts based on a variant of the zero-shot chain-of-thought (Zero-shot-CoT) prompting technique: Zero-shot-CoT combined with instructor-provided correct answers; Zero-shot-CoT in conjunction with both instructor-formulated answers and rubrics; and Zero-shot-CoT with instructor-offered correct answers and LLM-generated rubrics. Our results show that Zero-shot-CoT, when integrated with instructor-provided answers and rubrics, produces grades that are more aligned with those assigned by instructors compared to peer grading. However, the History and Philosophy of Astronomy course proves to be more challenging in terms of grading as opposed to other courses. Finally, our study reveals a promising direction for automating grading systems for MOOCs, especially in subjects with well-defined rubrics.

cs.CL↗

arXiv2023

The JWST Discovery of the Triply-imaged Type Ia "Supernova H0pe" and Observations of the Galaxy Cluster PLCK G165.7+67.0

A Type Ia supernova (SN) at $z=1.78$ was discovered in James Webb Space Telescope Near Infrared Camera imaging of the galaxy cluster PLCK G165.7+67.0 (G165; $z = 0.35$). The SN is situated 1.5-2 kpc from the host-galaxy nucleus and appears in three different locations as a result of gravitational lensing by G165. These data can yield a value for Hubble's constant using time delays from this multiply-imaged SN Ia that we call "SN H0pe." Over the cluster, we identified 21 image multiplicities, confirmed five of them using the Near-Infrared Spectrograph, and constructed a new lens model that gives a total mass within 600 kpc of ($2.6 \pm 0.3) \times 10^{14}$ $M_{\odot}$. The photometry uncovered a galaxy overdensity coincident with the SN host galaxy. NIRSpec confirmed six member galaxies, four of which surround the SN host galaxy with relative velocity $\lesssim$900 km s$^{-1}$ and projected physical extent $\lesssim$33 kpc. This compact galaxy group is dominated by the SN host galaxy, which has a stellar mass of $(5.0 \pm 0.1) \times 10^{11}$ $M_{\odot}$. The group members have specific star-formation rates of 2-260 Gyr$^{-1}$ derived from the H$\alpha$-line fluxes corrected for stellar absorption, dust extinction, and slit losses. Another group centered on a strongly-lensed dusty star forming galaxy is at $z=2.24$. The total (unobscured and obscured) SFR of this second galaxy group is estimated to be ($\gtrsim$100 $M_{\odot}$ yr$^{-1}$), which translates to a supernova rate of $\sim$1 SNe yr$^{-1}$, suggesting that regular monitoring of this cluster may yield additional SNe.

astro-ph.GA↗

arXiv2023

Paper 1: The JWST PEARLS View of the El Gordo Galaxy Cluster and of the Structure It Magnifies

The massive galaxy cluster El Gordo (z=0.87) imprints multitudes of gravitationally lensed arcs onto James Webb Space Telescope (JWST) Near-Infrared Camera (NIRCam) images. Eight bands of NIRCam imaging were obtained in the ``Prime Extragalactic Areas for Reionization and Lensing Science'' (``PEARLS'') program. PSF-matched photometry across Hubble Space Telescope (HST) and NIRCam filters supplies new photometric redshifts. A new light-traces-mass lens model based on 56 image multiplicities identifies the two mass peaks and yields a mass estimate within 500 kpc of ~(7.0 +/- 0.30) x 10^14 Msun. A search for substructure in the 140 cluster members with spectroscopic redshifts confirms the two main mass components. The southeastern mass peak that contains the BCG is more tightly bound than the northwestern one. The virial mass within 1.7 Mpc is (5.1 +/- 0.60) x 10^14 Msun, lower than the lensing mass. A significant transverse velocity component could mean the virial mass is underestimated. We contribute one new member to the previously known z=4.32 galaxy group. Intrinsic (delensed) positions of the five secure group members span a physical extent of ~60 kpc. Thirteen additional candidates selected by spectroscopic/photometric constraints are small and faint with a mean intrinsic luminosity ~2.2 mag fainter than L*. NIRCam imaging admits a fairly wide range of brightnesses and morphologies for the group members, suggesting a more diverse galaxy population in this galaxy overdensity.

astro-ph.GA↗