arXiv subjects

Anshika Gupta

Publications and source records attributed to Anshika Gupta.

3 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↗

arXiv2025

SN 2024aecx: a fast-evolving Type IIb supernova with a prominent shock-cooling peak

SN 2024aecx is a nearby ($\sim$11 Mpc) Type IIb SN discovered within $\sim$1 d after explosion. In this paper we report high-cadence photometric (typically 0.5$\sim$1 day) and spectroscopic follow-up observations, conducted from as early as 0.27 d post discovery out to the nebular phase at 158.4 d. We analyze the environment of SN 2024aecx and derive a new distance (11.3$\pm$1.1 Mpc), metallicity and host extinction. The light curve exhibits a hot and luminous shock-cooling peak at the first few days, followed by a main peak with very rapid post-maximum decline. The earliest spectra are blue and featureless, while from 2.3 d after discovery prominent P-Cygni profiles emerge. At nebular phase, the emission lines exhibit asymmetric and double-peaked profiles, indicating asphericity and/or early dust formation in the ejecta. Nebular spectral modelling indicates a blueshifted O-rich clump moving toward observer, and the $[\text{OI}]/[\text{CaII}]$ line ratio suggests an intermediate-mass progenitor. We simulated the progenitor and explosion using a two-component model of shock cooling and radioactive $^{56}$Ni heating; our model favors an extended, low-mass H-rich envelope with $M_{\mathrm{e}} = 0.04\pm{0.01} M_{\odot}$ and a low ejecta mass of$M_{\mathrm{ej}} = 1.55^{+0.18}_{-0.14} M_{\odot}$. And the nebular-phase spectra and light-curve modelling both suggest that it most likely originated from an intermediate-mass binary progenitor system. The comprehensive monitoring of SN 2024aecx, coupled with the detailed characterization of its local environment, establishes it as a benchmark event for probing the progenitors and explosion mechanisms of Type IIb SNe.

astro-ph.SR↗

arXiv2023

Rhetorical Role Labeling of Legal Documents using Transformers and Graph Neural Networks

A legal document is usually long and dense requiring human effort to parse it. It also contains significant amounts of jargon which make deriving insights from it using existing models a poor approach. This paper presents the approaches undertaken to perform the task of rhetorical role labelling on Indian Court Judgements as part of SemEval Task 6: understanding legal texts, shared subtask A. We experiment with graph based approaches like Graph Convolutional Networks and Label Propagation Algorithm, and transformer-based approaches including variants of BERT to improve accuracy scores on text classification of complex legal documents.

cs.CL↗