arXiv subjects

Neev Shah

Publications and source records attributed to Neev Shah.

6 recordsLinked to original sources

arXiv2026

Can LLMs Produce Original Astronomy Research in a Semester? A Graduate Class Experiment

We discuss the results of using large language models (LLMs) to conduct original scientific research in an unfamiliar subject area during the Fall 2025 semester. Students in a graduate astronomy and astrophysics course were asked to test whether LLMs could help them complete research tasks faster and at a level of detail and accuracy required for scientific publication. Most students employed LLMs for a total of 5-10 hours. While all students completed a draft paper on an unsolved problem related to galaxies by semester's end, their impressions of the models' value varied. About half thought that the models saved them time. Many noted that LLMs failed to provide appropriately detailed insights or steps to addressing open, niche questions over a several-month timeframe. The LLMs also frequently (about 20% of the time) returned false citations, links, or summaries of papers. The models struggled with generating complex functional code, accessing online packages or Application Programming Interfaces (APIs), and retrieving astronomical datasets from existing archives. In writing code and in chats, the LLMs made implicit, overly simplifying assumptions and often doubled down even after being corrected. Given the rapid pace of LLM development, new models may soon address at least some of these issues and thus significantly enhance research productivity. Yet students expressed concerns about how LLM use might dampen creativity and reflection during the research process. To improve learning experiences in future semesters, the class will first discuss LLM best practices and limitations. Students will be encouraged to explore free online resources for tips for generative model applications and will decide for themselves whether to use LLMs for their research project. This white paper was not written using LLMs.

astro-ph.IM↗

arXiv2026

Unraveling the Origin of Unequal Mass Gravitational Wave Events: Insights from a Galactic High Mass X-ray Binary

The catalog of Gravitational Wave (GW) events is rapidly growing, providing key insights into the evolution of massive binaries and compact object formation. However, a key challenge is to explain the origin of exceptional events such as GW190814, among the most asymmetric mass-ratio mergers to date ($q\approx 0.1$). We show that it shares an evolutionary pathway with the most unequal mass Galactic High Mass X-ray Binary (HMXB) 4U 1700-37/ HD 153919. We demonstrate this unique connection by utilizing a rich set of existing observational constraints for the HMXB and compute detailed binary evolution models to explain its formation history. We find that conservative mass transfer, along with a directed natal kick are essential to explain its current state. We show that this system is unlikely to form a GW source due to a failed Common Envelope (CE) phase in the future, in agreement with previous work. With additional models, we show that a similar pathway naturally forms GW190814-like events, provided the first phase of mass transfer remains conservative, and the first-born (lower mass) compact object receives a large natal kick ($\gtrsim 100\,\mathrm{km/s}$) for the subsequent CE phase to be successful and form a asymmetric mass-ratio GW source. Anchored by the number of analogous Galactic HMXBs, we estimate rates for such GW events, which broadly agree with their observed rate. Our work demonstrates a unified formation pathway for highly asymmetric mass-ratio HMXBs and GW events. Moreover, it highlights the critical role of finding and characterizing local analogs in different evolutionary phases, and using them as a bridge to understand the origin of GW sources, especially the outliers like GW190814.

astro-ph.HE↗

arXiv2025

Interacting binaries on the Main Sequence as in-situ tracers of mass transfer efficiency and stability

Understanding the transfer of mass and angular momentum in binary interactions is crucial for modelling the evolution of any interacting binary after the first mass transfer phase. Mass transfer physics assumptions shape the predictions for later stages of binary evolution, such as the immediate progenitors of stripped-envelope supernovae and gravitational wave mergers. We constrain the efficiency and stability of thermal timescale mass transfer in massive binary evolution using the observed population of 62 massive interacting binaries on the Main Sequence (`Algols') in the Milky Way, Large and Small Magellanic Clouds. We find that purely conservative or non-conservative mass transfer cannot explain the current mass ratio and orbital period of all massive Algols. Angular momentum conservation rules out conservative mass transfer in $\sim$28\,\% of massive Algols in the SMC. About three-quarters of all massive Algols are consistent with having undergone inefficient mass transfer ($\lesssim$\,50\,\%), while the remaining systems, mostly residing in the LMC and Milky Way, require mass transfer to have been more efficient than 25\%. For our fiducial assumption on the extent of envelope stripping, the current sample of massive Algols does not require mass transfer to be efficient at the shortest orbital periods ($\sim$2\,d) at any metallicity. We find evidence that mass transfer on the Main Sequence needs to be stable for initial accretor-to-donor mass ratios as unequal as $\sim 0.6$. Unless biased by observational selection effects, the massive Algols in the SMC seem to have undergone less efficient mass transfer than those in the LMC and Milky Way.

astro-ph.SR↗

arXiv2023

Detecting Detached Black Hole binaries through Photometric Variability

Understanding the connection between the properties of black holes (BHs) and their progenitors is interesting in many branches of astrophysics. Discovering BHs in detached orbits with luminous companions (LCs) promises to help create this map since the LC and BH progenitor are expected to have the same metallicity and formation time. We explore the possibility of detecting BH-LC binaries in detached orbits using photometric variations of the LC flux, induced by tidal ellipsoidal variation, relativistic beaming, and self-lensing. We create realistic present-day populations of detached BH-LC binaries in the Milky Way (MW) using binary population synthesis where we adopt observationally motivated initial stellar and binary properties, star formation history and present-day distribution of these sources in the MW based on detailed cosmological simulations. We test detectability of these sources via photometric variability by Gaia and TESS missions by incorporating their respective detailed detection biases as well as interstellar extinction. We find that Gaia is expected to resolve 300--1,000 (700--1,500) detached BH--LC binaries with SNR>10 (1) depending on the photometric precision and details of supernova physics. Similarly, the number of resolved BH--LC binaries with TESS are ~50--200 (140--350). We find that 136^{+15}_{-15} BH--LC binaries would be common between Gaia and TESS. Moreover, between ~60--70 (50--200) BH--LC binaries identifiable using photometry with SNR >10 may also be resolved using Gaia's radial velocity (astrometry).

astro-ph.GA↗

arXiv2023

The abundance of core--collapsed subhalos in SIDM: insights from structure formation in $\Lambda$CDM

Dark matter halos can enter a phase of gravothermal core--collapse in the presence of self-interactions. This phase that follows a core--expansion phase is thought to be subdominant due to the long time-scales involved. However, it has been shown that the collapse can be accelerated in tidal environments particularly for halos that are centrally concentrated. Cosmological simulations in $\Lambda$CDM give us the full distribution of satellite orbits and halo profiles in the universe. We use properties of the orbits and profiles of subhalos from simulations to estimate the fraction of the subhalos in different host halo environments, ranging from the Large Magellanic cloud(LMC)--like hosts to clusters, that are in the core--collapse phase. We use fluid simulations of self--interacting dark matter (SIDM) to evolve subhalos in their hosts including the effect of tidal truncation at the time of their pericenter crossing. We find that for parameters that allow the interaction cross-section to be high at dwarf scales, at least $10~\%$ of all subhalos are expected to have intrinsically collapsed within Hubble time up to the group mass host scales. This fraction increases significantly, becoming at least 20$\%$ when tidal interactions are considered. To identify these objects we find that we either need to measure their densities at very small radial scales, where the subhalos show a bimodal distribution of densities, or alternatively we need to measure the slopes of their inner density profiles near the scale radius, which are much steeper than NFW slopes expected in cold dark matter halos. Current measurements of central slopes of classical dwarfs do not show a preference for collapsed objects, however this is consistent with an SIDM scenario where the classical dwarfs are expected to be in a cored phase.

astro-ph.CO↗

arXiv2023

Waves in a Forest: A Random Forest Classifier to Distinguish between Gravitational Waves and Detector Glitches

The LIGO-Virgo-KAGRA (LVK) network of gravitational-wave (GW) detectors have observed many tens of compact binary mergers to date. Transient, non-Gaussian noise excursions, known as "glitches", can impact signal detection in various ways. They can imitate true signals as well as reduce the confidence of real signals. In this work, we introduce a novel statistical tool to distinguish astrophysical signals from glitches, using their inferred source parameter posterior distributions as a feature set. By modelling both simulated GW signals and real detector glitches with a gravitational waveform model, we obtain a diverse set of posteriors which are used to train a random forest classifier. We show that random forests can identify differences in the posterior distributions for signals and glitches, aggregating these differences to tell apart signals from common glitch types with high accuracy of over 93%. We conclude with a discussion on the regions of parameter space where the classifier is prone to making misclassifications, and the different ways of implementing this tool into LVK analysis pipelines.

gr-qc↗