Alina Volnova | Searcharxiv

arXiv2026

SNAD: enabling discovery in the era of big data

In the era of wide-field surveys and big data in astronomy, the SNAD team is exploiting the potential of modern datasets for discovering new, unforeseen, or rare astrophysical objects and phenomena with machine learning (ML). The SNAD pipeline was built under the hypothesis that, although automatic ML algorithms have a crucial role to play in this task, the scientific discovery is only completely realized when such systems are designed to boost the impact of domain knowledge experts. Our key contributions include the development of the Coniferest Python library, which offers implementations of two active learning algorithms with an ``expert in loop'', and the creation of the SNAD Transient Miner, facilitating the search for specific types of transients. We have also developed the SNAD Viewer, a web portal that provides a centralized view of individual objects from the Zwicky Transient Facility's (ZTF) data releases, making the analysis of potential anomalies more efficient. Finally, when applied to ZTF data, our approach has resulted in more than a hundred new supernova (SN) candidates, along with a few other non-catalogued objects, such as red dwarf flares, superluminous SNe, RS CVn type variables, and young stellar objects.

astro-ph.HE↗

arXiv2025

Deciphering the Physical Origin of GRB 240825A: A Long GRB Lacking a Bright Supernova

We present a comprehensive multiwavelength analysis of GRB 240825A, a bright gamma-ray burst (GRB) detected by Fermi and Swift, with a prompt duration ($T_{\rm 90}$ ~ 4 sec in 50-300 keV) near the boundary separating short and long GRBs, prompting a detailed investigation into its classification and progenitor. Using classical prompt metrics (duration, minimum variability timescale (MVT), lag, and spectral hardness) and modern classification techniques (machine-learning (ML) based t-SNE, support vector machine, energy-hardness-duration, and $\epsilon \equiv E_{\gamma,\mathrm{iso},52} / E_{p,z,2}^{5/3}$), we find GRB 240825A exhibits hybrid characteristics. The short MVT (13.830 $\pm$ 1.574 ms), rest-frame duration, and ML-based classification indicate a merger-like or ambiguous nature, while its energetics and position on the Amati relation favor a collapsar origin. We conducted deep optical and NIR photometric and spectroscopic late-time search for an associated supernova (SN)/kilonova (KN) and the host galaxy using 10.4 m GTC and 8.4 m binocular LBT telescopes. No bright SN (like SN 1998bw) is detected down to stringent limits (e.g., $m_r > 26.1$ mag at 17.59 days), despite a redshift of $z$ = 0.659 measured from GTC spectroscopy. Host galaxy SED modeling with Prospector indicates a massive, dusty, and star-forming galaxy-typical of collapsar GRB hosts, though with low sSFR and large offset. We compare these findings with hybrid events like GRB 211211A, GRB 230307A, GRB 200826A, including SNe-GRBs, and conclude that GRB 240825A likely originated from a massive star collapse, with the associated supernova obscured by a dusty host environment or low luminosity SN with absolute magnitude M$_{V}$ fainter than -18.0. This study emphasizes the need for multiwavelength follow-up and a multi-layered classification to determine GRB progenitors.

astro-ph.HE↗