arXiv subjects

Harsh Kumar

Publications and source records attributed to Harsh Kumar.

At least 37 records · Page 2Linked to original sources

arXiv2025

When IIb Ceases To Be: Bridging the Gap Between IIb and Short-plateau Supernovae

Hydrogen-rich supernovae (SNe) span a range of hydrogen envelope masses at core collapse, producing diverse light curves from extended plateaus in Type II SNe to double-peaked Type IIb SNe. Recent hydrodynamic modeling predicts a continuous sequence of light-curve morphologies as hydrogen is removed, with short plateau SNe (plateau durations ~50--70 days) emerging as a transitional class. However, the observational boundary between IIb and short-plateau remains poorly defined, and thus far unobserved. We report on extensive photometric and spectroscopic follow-up of SN 2023wdd and SN 2022acrv, candidate transitional events on the low-mass end of the short-plateau class. Both exhibit weak, double-peaked light curves which we interpret as exceptionally short plateaus (10--20 days), and hybrid spectral features: persistent H$α$ absorption with He I contamination, but without the helium dominance characteristic of IIb SNe. Using analytic shock-cooling models and numerical light curve fitting, we estimate hydrogen-rich envelope masses of ~0.6--0.8 $M_\odot$ -- significantly larger than canonical IIb values ($\lesssim0.1\,M_\odot$) but consistent with the ${\sim}0.9\,M_\odot$ threshold predicted for short-plateau behavior. Although the progenitor radii inferred from analytic and numerical methods differ by factors of 2--5, envelope mass estimates are consistent across approaches. Comparisons to well-studied IIb (SN 2016gkg, SN 2022hnt), short-plateau (SN 2023ufx, SN 2006ai, SN 2016egz, SN 2006Y), and II SNe (SN 2023ixf, SN 2013ej) suggest a monotonic relationship between hydrogen envelope mass and plateau length consistent with analytic and numerical expectations. These findings provide additional evidence for a continuous distribution of envelope stripping in hydrogen-rich core-collapse progenitors and place SN 2023wdd and SN 2022acrv along the IIb/short-plateau boundary.

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arXiv2025

Lense-Thirring precessing magnetar engine drives a superluminous supernova

Type I superluminous supernovae (SLSNe-I) are at least an order of magnitude brighter than standard supernovae, with the internal power source for their luminosity still unknown. The central engines of SLSNe-I are hypothesized to be magnetars, but the majority of SLSNe-I light curves have multiple bumps or peaks that are unexplained by the standard magnetar model. Existing explanations for the bumps either modulate the central engine luminosity or invoke interactions with material in the circumstellar environment. Systematic surveys of the limited sample of SLSNe-I light curves find no compelling evidence favoring either scenario, leaving both the nature of the light-curve fluctuations and the applicability of the magnetar model unresolved. Here, we report high-cadence multiband observations of an SLSN-I with clear "chirped" (i.e., decreasing period) light-curve bumps that can be directly linked to the properties of the magnetar central engine. Our observations are consistent with a tilted, infalling accretion disk undergoing Lense-Thirring precession around a magnetar centrally located within the expanding supernova ejecta. Our model demonstrates that the overall light curve and bump frequency independently and self-consistently constrain the spin period and the magnetic field strength of the magnetar. Assuming standard accretion disk parameters, we constrain the accretion rate onto the magnetar. Our results provide the first observational evidence of the Lense-Thirring effect in the environment of a magnetar, and confirm the magnetar spin-down model as an explanation for the extreme luminosity observed in SLSNe-I. We anticipate this discovery will create avenues for testing general relativity in a new regime -- the violent centers of young supernovae.

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arXiv2025

Radio Emission from the Infrared Tidal Disruption Event WTP14adeqka: The First Directly Resolved Delayed Outflow from a TDE

We present detailed radio observations of the mid-infrared (MIR) tidal disruption event (TDE) WTP14adeqka. We detect rising radio emission starting $\approx 4$ years after the discovery of the MIR emission (and about 2 years after its peak), peaking at $\approx 6.5$ years and declining thereafter, reminiscent of the delayed radio emission recently identified in optically discovered TDEs. The peak radio luminosity, $νL_ν\approx 2\times 10^{39}$ erg s$^{-1}$, is comparable to the brightest radio emission in optical TDEs. Multi-frequency radio observations at 8.9 and 9.7 years reveal a non-relativistic outflow with a mean expansion velocity of $\approx 0.021c$ (for an assumed launch at the time of disruption) and an energy of $\approx 10^{50.7}$ erg, about an order of magnitude larger than in typical optical TDEs. More importantly, Very Long Baseline Array (VLBA) observations at the same epochs directly resolve the radio source and reveal an increase in size from approximately 0.11 pc to 0.13 pc (with no apparent astrometric shift), corresponding to an expansion velocity of $\approx 0.05c$, and a likely delayed launch by about 2 years. The VLBA size measurements rule out an off-axis jet launched at the time of disruption, which would have an expected size of $\gtrsim {\rm pc}$ on these timescales; the possibility of a delayed jet can be evaluated with future VLBA observations. We conclude that MIR TDEs can launch energetic, delayed outflows. Ongoing radio observations of the full MIR TDE sample will reveal whether this behavior is ubiquitous.

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arXiv2025

Efficacy of Galaxy Catalogues for following up gravitational wave events

The detection of gravitational waves (GW) by the LIGO-Virgo-KAGRA (LVK) network has opened up a new era in astrophysics. The identification of the electromagnetic counterparts of GW sources is crucial for multi-messenger astronomy, one way of which is to use galaxy catalogues to guide optical follow-up observations. In this paper, we test the utility of galaxy-targeted approach with mass prioritised galaxy ranking for the ongoing LIGO O4 run. We have used the simulated results for the expected LIGO O4 events and the NED-LVS galaxy catalogue and based our study for small field of view telescopes, specifically the GROWTH-India Telescope (GIT). With the increase in sensitivity of LIGO/Virgo in the ongoing observing run O4, the expected number of total detections have gone up but most of these are also now poorly localised. We show that a larger volume covered in the same field-of-view (FoV) on the sky results in a large increase in the total number of galaxies in each FoV. A significant top-heaviness is observed in the mass-ranked list of galaxies, which still number to a few thousand in most cases. At larger distances, such high numbers of deep follow-up observations are infeasible in most cases rendering galaxy catalogues useful in limited cases, but these are still useful at lower distances where LVK detectors are currently sensitive and where galaxy completeness is higher. We also explore the effect of mass-filling to account for galaxy catalogue incompleteness at large distances. If mass-filled probabilities are considered as the metric for ranking and coverage, we find that the conventional 2D probability search performs better than a 3D galaxy catalogue (without mass-filling) based search at distances larger than 300 Mpc (upto which NED-LVS is ~70% complete), and using 3D mass times probability in each tile performs better for nearby events.

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arXiv2025

James Webb Space Telescope Observations of the Nearby and Precisely-Localized FRB 20250316A: A Potential Near-IR Counterpart and Implications for the Progenitors of Fast Radio Bursts

We present deep James Webb Space Telescope near-infrared imaging to search for a quiescent or transient counterpart to FRB 20250316A, which was precisely localized with the CHIME/FRB Outriggers array to an area of $11\times13$ pc in the outer regions of NGC 4141 at $d\approx40$ Mpc. Our F150W2 image reveals a faint source near the center of the FRB localization region ("NIR-1"; $M_{\rm F150W2}\approx-2.5$ mag; probability of chance coincidence $\approx0.36$), the only source within $\approx2.7σ$. We find that it is too faint to be a globular cluster, young star cluster, red supergiant star, or a giant star near the tip of the red giant branch (RGB). It is instead consistent with a red giant near the RGB "clump" or a massive ($\gtrsim20$ M$_{\odot}$) main sequence star, although the latter explanation is less likely. The source is too bright to be a supernova remnant, Crab-like pulsar wind nebula, or isolated magnetar. Alternatively, NIR-1 may represent transient emission, namely a dust echo from an energetic outburst associated with the FRB, in which case we would expect it to fade in future observations. We explore the stellar population near the FRB and find that it is composed of a mix of young massive stars ($\sim10-100$ Myr) in a nearby HII region that extends to the location of FRB 20250316A, and old evolved stars ($\gtrsim$ Gyr). The overlap with a young stellar population, containing stars of up to $\approx20$ M$_\odot$, may implicate a neutron star / magnetar produced in the core collapse of a massive star as the source of FRB 20250316A.

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arXiv2025

The Jetted Tidal Disruption Event AT2022cmc: Investigating Connections to the Optical Tidal Disruption Event Population and Spectral Subclasses Through Late-Time Follow-up

AT2022cmc is the first on-axis jetted tidal disruption event (TDE) to be discovered at optical wavelengths. The optically bright nature of AT2022cmc presents an unprecedented opportunity to place this jetted TDE in the context of the larger optically selected thermal TDE population and explore potential connections to optical TDE subclasses, particularly the class of luminous TDEs that lack optical spectral features. In this work we present late-time optical observations of AT2022cmc, both imaging and spectroscopy, that extend the optical dataset to $\sim 160$ days from the first detection in the observed frame. The light curve clearly evolves from red to blue, which we interpret as a transition from a non-thermally dominated spectral energy distribution (SED) to thermally dominated SED. By accounting for the non-thermal emission evident in the optical SED at early times, we extract the properties of the thermal emission and compare to a sample of optically selected thermal TDEs. We find that the properties of AT2022cmc are consistent with previous correlations found for the evolution and properties of thermal TDEs, with the thermal properties of AT2022cmc aligning with the class of featureless and luminous TDEs. The confirmation of this similarity motivates the importance of prompt and multi-wavelength follow-up of featureless and luminous TDEs in order to further explore the connection they have with jetted TDEs.

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arXiv2025

A Detection of Helium in the Bright Superluminous Supernova SN 2024rmj

We present extensive ultraviolet (UV), optical, and near-infrared (NIR) photometric and spectroscopic observations of the nearby hydrogen-poor superluminous supernova (SLSN-I) SN2024rmj at z = 0.1189. SN 2024rmj reached a peak absolute magnitude of Mg $\approx$ -21.9, placing it at the luminous end of the SLSN-I distribution. The light curve exhibits a pronounced pre-peak bump ($\approx$ 60 d before the main peak) and a post-peak bump ($\approx$ 55 d after the main peak). The bulk of the light curve is otherwise well fit by a magnetar spin-down model, with typical values (spin: $\approx$ 2.1 ms; magnetic field: $\approx$ 6 $\times$ 10$^{13}$ G; ejecta mass: $\approx$ 12 M$_\odot$). The optical spectra exhibit characteristic SLSN-I features and evolution, but with a relatively high velocity of $\approx$ 8,000 km s$^{-1}$ post-peak. Most significantly, we find a clear detection of helium in the NIR spectra at He I $λ$1.083 $μ$m and $λ$2.058 $μ$m, blueshifted by $\approx$ 15,000 km s$^{-1}$ (13 d before peak) and $\approx$ 13,000 km s$^{-1}$ (40 d after peak), indicating that helium is confined to the outermost ejecta; based on these NIR detections, we also identify likely contribution from He I $λ$5876 Å in the optical spectra on a similar range of timescales. This represents the most definitive detection of helium in a bright SLSN-I to date, and indicates that progenitors with a thin helium layer can still explode as SLSNe.

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arXiv2025

Chronocept: Instilling a Sense of Time in Machines

Human cognition is deeply intertwined with a sense of time, known as Chronoception. This sense allows us to judge how long facts remain valid and when knowledge becomes outdated. Despite progress in vision, language, and motor control, AI still struggles to reason about temporal validity. We introduce Chronocept, the first benchmark to model temporal validity as a continuous probability distribution over time. Using skew-normal curves fitted along semantically decomposed temporal axes, Chronocept captures nuanced patterns of emergence, decay, and peak relevance. It includes two datasets: Benchmark I (atomic facts) and Benchmark II (multi-sentence passages). Annotations show strong inter-annotator agreement (84% and 89%). Our baselines predict curve parameters - location, scale, and skewness - enabling interpretable, generalizable learning and outperforming classification-based approaches. Chronocept fills a foundational gap in AI's temporal reasoning, supporting applications in knowledge grounding, fact-checking, retrieval-augmented generation (RAG), and proactive agents. Code and data are publicly available.

cs.CL↗

arXiv2025

The Nature of Optical Afterglows Without Gamma-ray Bursts: Identification of AT2023lcr and Multiwavelength Modeling

In the past few years, the improved sensitivity and cadence of wide-field optical surveys have enabled the discovery of several afterglows without associated detected gamma-ray bursts (GRBs). We present the identification, observations, and multiwavelength modeling of a recent such afterglow (AT2023lcr), and model three literature events (AT2020blt, AT2021any, and AT2021lfa) in a consistent fashion. For each event, we consider the following possibilities as to why a GRB was not observed: 1) the jet was off-axis; 2) the jet had a low initial Lorentz factor; and 3) the afterglow was the result of an on-axis classical GRB (on-axis jet with physical parameters typical of the GRB population), but the emission was undetected by gamma-ray satellites. We estimate all physical parameters using afterglowpy and Markov Chain Monte Carlo methods from emcee. We find that AT2023lcr, AT2020blt, and AT2021any are consistent with on-axis classical GRBs, and AT2021lfa is consistent with both on-axis low Lorentz factor ($Γ_0 \approx 5 - 13$) and off-axis ($θ_\text{obs}=2θ_\text{jet}$) high Lorentz factor ($Γ_0 \approx 100$) jets.

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arXiv2025

Investigating the Role of Situational Disruptors in Engagement with Digital Mental Health Tools

Challenges in engagement with digital mental health (DMH) tools are commonly addressed through technical enhancements and algorithmic interventions. This paper shifts the focus towards the role of users' broader social context as a significant factor in engagement. Through an eight-week text messaging program aimed at enhancing psychological wellbeing, we recruited 20 participants to help us identify situational engagement disruptors (SEDs), including personal responsibilities, professional obligations, and unexpected health issues. In follow-up design workshops with 25 participants, we explored potential solutions that address such SEDs: prioritizing self-care through structured goal-setting, alternative framings for disengagement, and utilization of external resources. Our findings challenge conventional perspectives on engagement and offer actionable design implications for future DMH tools.

cs.HC↗

arXiv2025

Human Creativity in the Age of LLMs: Randomized Experiments on Divergent and Convergent Thinking

Large language models are transforming the creative process by offering unprecedented capabilities to algorithmically generate ideas. While these tools can enhance human creativity when people co-create with them, it's unclear how this will impact unassisted human creativity. We conducted two large pre-registered parallel experiments involving 1,100 participants attempting tasks targeting the two core components of creativity, divergent and convergent thinking. We compare the effects of two forms of large language model (LLM) assistance -- a standard LLM providing direct answers and a coach-like LLM offering guidance -- with a control group receiving no AI assistance, and focus particularly on how all groups perform in a final, unassisted stage. Our findings reveal that while LLM assistance can provide short-term boosts in creativity during assisted tasks, it may inadvertently hinder independent creative performance when users work without assistance, raising concerns about the long-term impact on human creativity and cognition.

cs.HC↗

arXiv2025

The Luminous, Slow-Rising Orphan Afterglow AT2019pim as a Candidate Moderately Relativistic Outflow

Classical gamma-ray bursts (GRBs) have two distinct emission episodes: prompt emission from ultrarelativistic ejecta and afterglow from shocked circumstellar material. While both components are extremely luminous in known GRBs, a variety of scenarios predict the existence of luminous afterglow emission with little or no associated high-energy prompt emission. We present AT2019pim, the first spectroscopically confirmed afterglow with no observed high-energy emission to be identified. Serendipitously discovered during follow-up observations of a gravitational-wave trigger and located in a contemporaneous TESS sector, it is hallmarked by a fast-rising (t ~ 2 hr), luminous (M_UV,peak ~ -24.4 mag) optical transient with accompanying luminous X-ray and radio emission. No gamma-ray emission consistent with the time and location of the transient was detected by Fermi-GBM or by Konus, placing constraining limits on an accompanying GRB. We investigate several independent observational aspects of the afterglow in the context of constraints on relativistic motion and find all of them are consistent with an initial Lorentz factor of Gamma_0 ~ 10-30 for the on-axis material, significantly lower than in any well-observed GRB and consistent with the theoretically predicted "dirty fireball" scenario in which the high-energy prompt emission is stifled by pair production. However, we cannot rule out a structured jet model in which only the line-of-sight material was ejected at low-Gamma, off-axis from a classical high-Gamma jet core, and an on-axis GRB with below-average gamma-ray efficiency also remains a possibility. This event represents a milestone in orphan afterglow searches, demonstrating that luminous optical afterglows lacking detected GRB counterparts can be identified and spectroscopically confirmed in real time.

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arXiv2025

Multi-Wavelength Analysis of AT 2023sva: a Luminous Orphan Afterglow With Evidence for a Structured Jet

We present multi-wavelength analysis of ZTF23abelseb (AT 2023sva), an optically discovered fast-fading ($Δm_r = 2.2$ mag in $Δt = 0.74 $ days), luminous ($M_r \sim -30.0$ mag) and red ($g-r = 0.50$ mag) transient at $z = 2.28$ with accompanying luminous radio emission. AT 2023sva does not possess a $γ$-ray burst (GRB) counterpart to an isotropic equivalent energy limit of $E_{\rm{γ, \, iso}} < 1.6 \times 10^{52}$ erg, determined through searching $γ$-ray satellite archives between the last non-detection and first detection, making it the sixth example of an optically-discovered afterglow with a redshift measurement and no detected GRB counterpart. We analyze AT 2023sva's optical, radio, and X-ray observations to characterize the source. From radio analyses, we find the clear presence of strong interstellar scintillation (ISS) 72 days after the initial explosion, allowing us to place constraints on the source's angular size and bulk Lorentz factor. When comparing the source sizes derived from ISS of orphan events to those of the classical GRB population, we find orphan events have statistically smaller source sizes. We also utilize Bayesian techniques to model the multi-wavelength afterglow. Within this framework, we find evidence that AT 2023sva possesses a shallow power-law structured jet viewed slightly off-axis ($θ_{\rm{v}} = 0.07 \pm 0.02$) just outside of the jet's core opening angle ($θ_{\rm{c}} = 0.06 \pm 0.02$). We determine this is likely the reason for the lack of a detected GRB counterpart, but also investigate other scenarios. AT 2023sva's evidence for possessing a structured jet stresses the importance of broadening orphan afterglow search strategies to a diverse range of GRB jet angular energy profiles, to maximize the return of future optical surveys.

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arXiv2025

A Near-IR Search for Helium in the Superluminous Supernova SN 2024ahr

We present a detailed study of SN 2024ahr, a hydrogen-poor superluminous supernova (SLSN-I), for which we determine a redshift of $z=0.0861$. SN 2024ahr has a peak absolute magnitude of $M_g\approx M_r\approx -21$ mag, rest-frame rise and decline times (50$\%$ of peak) of about 40 and 80 days, respectively, and typical spectroscopic evolution in the optical band. Similarly, modeling of the UV/optical light curves with a magnetar spin-down engine leads to typical parameters: an initial spin period of $\approx 3.3$ ms, a magnetic field strength of $\approx 6\times 10^{13}$ G, and an ejecta mass of $\approx 9.5$ M$_\odot$. Due to its relatively low redshift we obtained a high signal-to-noise ratio near-IR spectrum about 43 rest-frame days post-peak to search for the presence of helium. We do not detect any significant feature at the location of the He I $\,λ2.058$ $μ$m feature, and place a conservative upper limit of $\sim 0.05$ M$_\odot$ on the mass of helium in the outer ejecta. We detect broad features of Mg I $\,λ1.575$ $μ$m and a blend of Co II $\,λ2.126$ $μ$m and Mg II, $λ2.136$ $μ$m, which are typical of Type Ic SNe, but with higher velocities. Examining the sample of SLSNe-I with NIR spectroscopy, we find that, unlike SN 2024ahr, these events are generally peculiar. This highlights the need for a large sample of prototypical SLSNe-I with NIR spectroscopy to constrain the fraction of progenitors with helium (Ib-like) and without helium (Ic-like) at the time of the explosion, and hence the evolutionary path(s) leading to the rare outcome of SLSNe-I.

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arXiv2024

Performance Characterization and Optimizations of Traditional ML Applications

Even in the era of Deep Learning based methods, traditional machine learning methods with large data sets continue to attract significant attention. However, we find an apparent lack of a detailed performance characterization of these methods in the context of large training datasets. In this work, we study the system's behavior of a number of traditional ML methods as implemented in popular free software libraries/modules to identify critical performance bottlenecks experienced by these applications. The performance characterization study reveals several interesting insights on the performance of these applications. Then we evaluate the performance benefits of applying some well-known optimizations at the levels of caches and the main memory. More specifically, we test the usefulness of optimizations such as (i) software prefetching to improve cache performance and (ii) data layout and computation reordering optimizations to improve locality in DRAM accesses. These optimizations are implemented as modifications to the well-known scikit-learn library, and hence can be easily leveraged by application programmers. We evaluate the impact of the proposed optimizations using a combination of simulation and execution on a real system. The software prefetching optimization results in performance benefits varying from 5.2%-27.1% on different ML applications while the data layout and computation reordering approaches yield 6.16%-28.0% performance improvement.

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arXiv2024

Using Images to Find Context-Independent Word Representations in Vector Space

Many methods have been proposed to find vector representation for words, but most rely on capturing context from the text to find semantic relationships between these vectors. We propose a novel method of using dictionary meanings and image depictions to find word vectors independent of any context. We use auto-encoder on the word images to find meaningful representations and use them to calculate the word vectors. We finally evaluate our method on word similarity, concept categorization and outlier detection tasks. Our method performs comparably to context-based methods while taking much less training time.

cs.CL↗

arXiv2024

Impact of Guidance and Interaction Strategies for LLM Use on Learner Performance and Perception

Personalized chatbot-based teaching assistants can be crucial in addressing increasing classroom sizes, especially where direct teacher presence is limited. Large language models (LLMs) offer a promising avenue, with increasing research exploring their educational utility. However, the challenge lies not only in establishing the efficacy of LLMs but also in discerning the nuances of interaction between learners and these models, which impact learners' engagement and results. We conducted a formative study in an undergraduate computer science classroom (N=145) and a controlled experiment on Prolific (N=356) to explore the impact of four pedagogically informed guidance strategies on the learners' performance, confidence and trust in LLMs. Direct LLM answers marginally improved performance, while refining student solutions fostered trust. Structured guidance reduced random queries as well as instances of students copy-pasting assignment questions to the LLM. Our work highlights the role that teachers can play in shaping LLM-supported learning environments.

cs.HC↗

arXiv2024

Understanding Help-Seeking Behavior of Students Using LLMs vs. Web Search for Writing SQL Queries

Growth in the use of large language models (LLMs) in programming education is altering how students write SQL queries. Traditionally, students relied heavily on web search for coding assistance, but this has shifted with the adoption of LLMs like ChatGPT. However, the comparative process and outcomes of using web search versus LLMs for coding help remain underexplored. To address this, we conducted a randomized interview study in a database classroom to compare web search and LLMs, including a publicly available LLM (ChatGPT) and an instructor-tuned LLM, for writing SQL queries. Our findings indicate that using an instructor-tuned LLM required significantly more interactions than both ChatGPT and web search, but resulted in a similar number of edits to the final SQL query. No significant differences were found in the quality of the final SQL queries between conditions, although the LLM conditions directionally showed higher query quality. Furthermore, students using instructor-tuned LLM reported a lower mental demand. These results have implications for learning and productivity in programming education.

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