42 citations · 131 across the 13 of their papers we have counts for
13 papers
A Neural Network-Based Search for Unmodeled Transients in LIGO-Virgo-KAGRA's Third Observing Run
Ryan Raikman, Eric A. Moreno, Katya Govorkova +13
This paper presents the results of a Neural Network (NN)-based search for short-duration gravitational-wave transients in data from the third observing run of LIGO, Virgo, and KAGR…
Application of Non-Linear Noise Regression in the Virgo Detector
R. Weizmann Kiendrebeogo, Muhammed Saleem, Marie Anne Bizouard +8
This work presents the first demonstration of non-linear noise regression in the Virgo detector using deep learning techniques. We use DeepClean, a convolutional autoencoder previo…
A machine-learning pipeline for real-time detection of gravitational waves from compact binary coalescences
Ethan Marx, William Benoit, Alec Gunny +12
The promise of multi-messenger astronomy relies on the rapid detection of gravitational waves at very low latencies ((1\,s)) in order to maximize the amount of time av…
Joint gravitational wave-short GRB detection of Binary Neutron Star mergers with existing and future facilities
Soumyadeep Bhattacharjee, Smaranika Banerjee, Varun Bhalerao +6
We explore the joint detection prospects of short gamma-ray bursts (sGRBs) and their gravitational wave (GW) counterparts by the current and upcoming high-energy GRB and GW facilit…
Effect of double spin-precession and higher harmonics on spin-induced quadrupole moment measurements
Divyajyoti, N. V. Krishnendu, Muhammed Saleem +4
We investigate the prospect of performing a null test of binary black hole (BBH) nature using spin-induced quadrupole moment (SIQM) measurements. This is achieved by constraining a…
GWAK: Gravitational-Wave Anomalous Knowledge with Recurrent Autoencoders
Ryan Raikman, Eric A. Moreno, Ekaterina Govorkova +10
Matched-filtering detection techniques for gravitational-wave (GW) signals in ground-based interferometers rely on having well-modeled templates of the GW emission. Such techniques…
Demonstration of Machine Learning-assisted real-time noise regression in gravitational wave detectors
Muhammed Saleem, Alec Gunny, Chia-Jui Chou +17
Real-time noise regression algorithms are crucial for maximizing the science outcomes of the LIGO, Virgo, and KAGRA gravitational-wave detectors. This includes improvements in the…
Multiparameter tests of general relativity using principal component analysis with next-generation gravitational wave detectors
Sayantani Datta, M. Saleem, K. G. Arun +1
Principal Component Analysis (PCA) is an efficient tool to optimize the multiparameter tests of general relativity (GR) where one tests for simultaneous deviations in multiple post…
Population inference of spin-induced quadrupole moments as a probe for non-black hole compact binaries
Muhammed Saleem, N. V. Krishnendu, Abhirup Ghosh +4
Gravitational-wave (GW) measurements of physical effects such as spin-induced quadrupole moments can distinguish binaries consisting of black holes from non-black hole binaries. Wh…
Parametrized tests of post-Newtonian theory using principal component analysis
Muhammed Saleem, Sayantani Datta, K. G. Arun +1
Searching for departures from general relativity (GR) in more than one post-Newtonian (PN) phasing coefficients, called a \emph{multi-parameter test}, is known to be ineffective gi…
Investigating the relation between gravitational wave tests of general relativity
Nathan K. Johnson-McDaniel, Abhirup Ghosh, Sudarshan Ghonge +3
Gravitational wave observations of compact binary coalescences provide precision probes of strong-field gravity. There is thus now a standard set of null tests of general relativit…
Hardware-accelerated Inference for Real-Time Gravitational-Wave Astronomy
Alec Gunny, Dylan Rankin, Jeffrey Krupa +7
The field of transient astronomy has seen a revolution with the first gravitational-wave detections and the arrival of multi-messenger observations they enabled. Transformed by the…
Inferring kilonova population properties with a hierarchical Bayesian framework I : Non-detection methodology and single-event analyses
Siddharth R. Mohite, Priyadarshini Rajkumar, Shreya Anand +17
We present : a hierarchical Bayesian framework to infer the intrinsic luminosity parameters of kilonovae (KNe) associated with gravitational-wave (GW) events, based…