Related papers: Convolutional neural network for gravitational-wav…
Many continuous gravitational wave searches are affected by instrumental spectral lines that could be confused with a continuous astrophysical signal. Several techniques have been developed to limit the effect of these lines by penalising…
Multimessenger observations of the binary neutron star merger GW170817 have enabled the discovery of a diverse array of electromagnetic counterparts to compact binary mergers, including an unambiguous kilonova, a short gamma-ray burst, and…
Accurate information from gravitational wave signals from coalescing binary neutron stars provides essential input to downstream interpretations, including inference of the neutron star population and equation of state. However, even…
Gravitational wave astronomy has set in motion a scientific revolution. To further enhance the science reach of this emergent field, there is a pressing need to increase the depth and speed of the gravitational wave algorithms that have…
The phenomenon of Gravitational Wave (GW) analysis has grown in popularity as technology has advanced and the process of observing gravitational waves has become more precise. Although the sensitivity and the frequency of observation of GW…
We report on the methods and results of the first dedicated search for gravitational waves emitted during the inspiral of compact binaries with spinning component bodies. We analyze 788 hours of data collected during the third science run…
Deep learning can be used to drastically decrease the processing time of parameter estimation for coalescing binaries of compact objects including black holes and neutron stars detected in gravitational waves (GWs). As a first step, we…
We present an effective, low-dimensionality frequency-domain template for the gravitational wave signal from the stellar remnants from binary neutron star coalescence. A principal component decomposition of a suite of numerical simulations…
On the 17th of August, 2017 came the simultaneous detections of GW170817, a gravitational wave that originated from the coalescence of two neutron stars, along with the gamma-ray burst GRB170817A, and the kilonova counterpart AT2017gfo.…
We present a robust method to characterize the gravitational wave emission from the remnant of a neutron star coalescence. Our approach makes only minimal assumptions about the morphology of the signal and provides a full posterior…
We present the results of a blind all-sky search for continuous gravitational-wave signals from neutron stars in binary systems using data from the first part of the fourth observing run (O4a) using LIGO detectors data. Rapidly rotating,…
Advanced LIGO's second observing run (O2), conducted from November 30, 2016 to August 25, 2017, combined with Advanced Virgo's first observations in August 2017 witnessed the birth of gravitational-wave multi-messenger astronomy. The first…
In this work, we explore a possible application of a machine learning classifier for candidate events in a template-based search for gravitational-wave (GW) signals from various compact system sources. We analyze data from the O3a and O3b…
Continuous gravitational waves are nearly monochromatic signals emitted by asymmetries in rotating neutron stars. These signals have not yet been detected. Deep all-sky searches for continuous gravitational waves from isolated neutron stars…
Gravitational waves generated by the final merger of compact binary systems depend on the structure of the binary's members. If the binary contains neutron stars, measuring such waves can teach us about the properties of matter at extreme…
Recent developments in deep learning techniques have offered an alternative and complementary approach to traditional matched filtering methods for the identification of gravitational wave (GW) signals. The rapid and accurate identification…
We discuss the gravitational lensing of gravitational waves from merging neutron star binaries, in the context of advanced LIGO type gravitational wave detectors. We consider properties of the expected observational data with cut on the…
Signal extraction out of background noise is a common challenge in high precision physics experiments, where the measurement output is often a continuous data stream. To improve the signal to noise ratio of the detection, witness sensors…
This thesis presents advancements in the detection of gravitational waves from compact binary coalescences, utilising the most sensitive observatories constructed to date. The research focuses on enhancing gravitational-wave signal searches…
Deep learning method develops very fast as a tool for data analysis these years. Such a technique is quite promising to treat gravitational wave detection data. There are many works already in the literature which used deep learning…