Aryamann Rao | Searcharxiv

arXiv2026

A pipeline for identifying astrophysical signals and instrumental glitches in LISA data

The Laser Interferometer Space Antenna (LISA) is a space-based gravitational wave detector scheduled for launch in the 2030s by the European Space Agency. Operating in the 0.1 mHz to 0.1 Hz band, LISA will observe a variety of astrophysical sources including but not limited to supermassive black hole mergers, extreme mass ratio inspirals, and white dwarf binaries. LISA will yield new insights, including supermassive black hole formation, new tests of general relativity, population studies of white dwarfs and others. Like all interferometric gravitational wave detectors, LISA data is expected to contain non-astrophysical transients, commonly referred to as glitches. We introduce a two step pipeline that consists of a search algorithm for detecting potential transients in simulated LISA data followed by a machine learning model that classifies the detected transients as gravitational waves or instrumental glitches. This is important for MBHBs with very high masses (around $10^6\ M_{\odot}$) which are transients that could be morphologically similar to LISA glitches in the data. Initial results demonstrate a promising ability to classify detected events with an accuracy close to $98\%$. The pipeline also shows the ability to analyze a month of data in under 2 minutes on a laptop. This shows an eventual utility of our pipeline for enabling accurate rapid alerts from low latency searches. It could also support model selection in global-fit analyses by providing an initial summary of the location and type of individual signals. This paper also discusses challenges encountered during training, including limitations of the current framework.

gr-qc↗

arXiv2025

Predicting the rate of fast radio bursts in globular clusters from binary black hole observations

The repeating fast radio burst (FRB) source in an old globular cluster (GC) in M81 proves that FRBs, which are typically associated with young magnetars, can also occur in old stellar populations. A potential explanation is super-Chandrasekhar binary white dwarf (BWD) coalescences, which may produce FRB-emitting neutron stars. GCs can also give rise to binary black hole (BBH) mergers detectable with gravitational waves, and the BWD coalescence rate from GCs is correlated with their BBH merger rate. For the first time, we combine independent observations of gravitational waves and FRBs to infer the origins of FRB sources. We use GC formation histories inferred from BBH observations to predict the rate of super-Chandrasekhar BWD coalescences originating from GCs as a function of redshift. We explore mass-loss and mass-conserved scenarios for BWD coalescences and find that the coalescence rates evolve differently across redshift in these two cases. In the mass-loss scenario, the BWD coalescence rates decrease with increasing redshift, similar to some recent measurements of the FRB rate as a function of redshift. We show that GCs could contribute $\lesssim 1\%$ to the total FRB source formation rates in the local Universe. Our multi-messenger approach also offers a novel method to better constrain the GC population using both FRB and gravitational wave observations.

astro-ph.HE↗