4 papers
The Sound of Noise: Leveraging the Inductive Bias of Pre-trained Audio Transformers for Glitch Identification in LIGO
Suyash Deshmukh, Chayan Chatterjee, Abigail Petulante +2
Transient noise artifacts, or glitches, fundamentally limit the sensitivity of gravitational-wave (GW) interferometers and can mimic true astrophysical signals, particularly the sh…
Machine Learning Confirms GW231123 is a "Lite" Intermediate Mass Black Hole Merger
Chayan Chatterjee, Kaylah McGowan, Suyash Deshmukh +1
The LIGO-Virgo-KAGRA Collaboration recently reported GW231123, a black hole merger with total mass of around 190-265 solar mass. This event adds to the growing evidence of "lite" i…
Pre-trained Audio Transformer as a Foundational AI Tool for Gravitational Waves
Chayan Chatterjee, Abigail Petulante, Karan Jani +7
As gravitational wave detectors become more advanced and sensitive, the number of signals recorded by Advanced LIGO and Virgo from merging compact objects is expected to rise drama…
The Clearing Timescale for Infrared-selected Star Clusters in M83 with HST
Suyash Deshmukh, Sean T. Linden, Daniela Calzetti +6
We present an analysis of Hubble Space Telescope (HST) data from WFC3/UVIS, WFC3/IR and ACS, investigating the young stellar cluster (YSC) population in the face-on spiral galaxy M…