arXiv subjects

Yashasvi Moon

Publications and source records attributed to Yashasvi Moon.

4 recordsLinked to original sources

arXiv2026

The Delay Time Distribution of Quasi-Periodic Eruptions

Quasi-periodic eruptions (QPEs) are quasi-periodic X-ray bursts observed in the nucleus of a galaxy. Multiple pieces of observational evidence link QPEs to tidal disruption events (TDEs), which occur when stars are disrupted after approaching a supermassive black hole too closely. Post-starburst galaxies are overrepresented among the host galaxies of both TDEs and QPEs, though the mechanism causing this overrepresentation is unknown. While their physical origin is unclear, the delay time distribution (DTD) of QPEs, or rate of QPEs as a function of time since a burst of star formation, can constrain what mechanisms influence the QPE rate and possible QPE formation channels. We compile a catalog of 10 QPE host galaxies with optical spectra, model the stellar populations with Bagpipes, and retrieve the age of the most recent burst of star formation to construct the DTD of QPEs. We find that the QPE rate increases with post-burst age to reach a peak at ~1 Gyr relative to a control sample, similar to the observational TDE DTD, though we cannot rule out a flat distribution of burst ages relative to a control sample. However, the fraction of QPE host galaxies with high (>1%) burst mass fractions is larger than the fraction of galaxies with high burst mass fractions in either a sample of TDE host galaxies or a sample of control galaxies. If the preferred QPE formation channel requires extreme mass ratio inspirals (EMRIs), then such EMRIs may be more readily produced by large, ~1-Gyr-old bursts of star formation.

astro-ph.GA↗

arXiv2026

NAPTIME: A Neural-Process Framework for Rubin Alert Classification

The Vera C. Rubin Observatory Legacy Survey of Space and Time will produce a high-volume stream of irregularly sampled multiband alerts for which spectroscopic confirmation will be available only for a small minority of sources. Tidal disruption events are rare phenomena that provide a direct probe of dormant massive black holes, but their light curves can be confused with nuclear variability and other transient subclasses. We present NAPTIME (Neural Astrophysical Photometric Transient Identification and Modeling Engine), a neural-process framework for photometric transient classification under sparse and partial observational context. NAPTIME models irregular multiband light curves directly, combining probabilistic light-curve reconstruction with classification and optional host-galaxy context, as well as photometric-redshift information. We evaluate on two simulated benchmarks: ELAsTiCC2, our primary Rubin-like broad-classification benchmark, and MALLORN, a photometry-only TDE-focused benchmark. On the 15-family ELAsTiCC2 task, the metadata-aware model reaches macro $\mathrm{F1} = 0.903$ and macro $\mathrm{AUROC} = 0.991$, while a matched photometry-only variant reaches 0.874 and 0.986. Viewed as a TDE-versus-rest ranking model, the classifier yields TDE average precision 0.985 with metadata and 0.979 without. Metadata is most valuable in the low-context regime. Using only the earliest 10\% of detected observations, macro F1 is $\sim$0.42 with metadata and $\sim$0.34 without it. On MALLORN, NAPTIME reaches macro $\mathrm{F1} = 0.693$ and macro $\mathrm{AUROC} = 0.958$. These results show that neural processes provide a practical probabilistic framework for Rubin-like transient classification and remain effective for TDE-focused candidate recovery.

astro-ph.IM↗

arXiv2026

Identifying Changing-Look AGN Transitions in Light Curve Data with the Zwicky Transient Facility

Changing-Look AGN (CL-AGN) are AGN which transition between Seyfert types, challenging AGN unification models. Most CL-AGN have been identified via repeat spectroscopy, making it difficult to determine the duration and magnitude of the CL-AGN transition. As such, the physical mechanisms behind this transition are still unknown. We use synthetic photometry in combination with ZTF light curve data to develop a new criterion to identify photometric CL-AGN transitions based on changes in g-band magnitude and g-r color. We find that a CL-AGN criterion of $| \Delta g| > 0.4$ mag and $| \Delta (g-r)| > 0.2$ mag recovers a photometric transition in $9.6^{+4.9}_{-3.4}\%$ of CL-AGN hosts over the six-year ZTF survey, including a candidate repeating changing-look event in SDSS J084957.78+274728.9. Using simulated AGN light curves, we estimate the false positive rate among the simulated Seyferts to be $1.6^{+0.19}_{-0.17}\%$. We find that the rate of similar flares among Type 1 Seyferts is $1.2^{+0.87}_{-0.50}\%$ , and among Type 2 Seyferts is $\leq 0.39\%$ over six years. Photometric CL-AGN transitions last between 21 and 560 days, with a median duration of 360 days, consistent with the thermal or orbital timescales for AGN disks. We do not detect a correlation between black hole mass and transition duration, likely due to the small sample of detected photometric transitions. This method can be applied to the upcoming Legacy Survey of Space and Time to identify CL-AGN candidates and test theories of their origins

astro-ph.GA↗

arXiv2025

FEADME: Fast Elliptical Accretion Disk Modeling Engine

We present FEADME (Fast Elliptical Accretion Disk Modeling Engine), a GPU-accelerated Python framework for modeling broad Balmer-line emission using a relativistic elliptical accretion-disk formalism. Leveraging JAX and NumPyro for differentiable forward modeling and efficient Bayesian inference, FEADME enables large-sample, reproducible analyses of disk-dominated emission-line profiles. We apply the framework to 237 double-peaked emitters (DPEs) from the literature and to five tidal disruption events (TDEs) with disk-like H$\alpha$ emission, fitting three physically motivated model families per spectrum and selecting the preferred model using the widely applicable information criterion (WAIC). After posterior-quality filtering, the disk-bearing active galactic nuclei (AGN) analysis sample contains 165 sources and the TDE sample contains 27 usable epochs. We find that AGN occupy a broad, continuous distribution of disk geometries and kinematics that is usefully summarized by five phenomenological Gaussian-mixture morphology bins. The TDE disk parameters overlap substantially with the AGN population in radial scale, local broadening, and emissivity slope, but TDEs are systematically less eccentric and show broader non-disk Gaussian components. The majority of both AGN and TDEs favor models that include both a disk and an additional broad-line component, suggesting that disk emission commonly coexists with more isotropic or wind-driven gas. These results indicate that once a line-emitting disk forms, its spectroscopic appearance is governed by similar physical processes in both persistent AGN and transient TDE accretion flows, and they demonstrate the utility of FEADME for population-level studies of disk structure in galactic nuclei.

astro-ph.HE↗