Related papers: CoBiTS: Single-detector discrimination of binary b…
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.…
We present a computational method to identify glitches in gravitational-wave data that occur nearby gravitational-wave signals from compact binary coalescences. The Q-transform, an established tool in LIGO-Virgo-KAGRA data analysis,…
Space-based gravitational wave (GW) detection is one of the most anticipated GW detection projects in the next decade, which promises to detect abundant compact binary systems. At present, deep learning methods have not been widely explored…
"Glitches" -- transient noise artifacts in the data collected by gravitational wave interferometers like LIGO and Virgo -- are an ever-present obstacle for the search and characterization of gravitational wave signals. With some having…
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…
We introduce $\texttt{WaveletNet}$, a wavelet-based neural network architecture to identify and reduce non-Gaussian noise in gravitational wave data. Traditionally, convolutional neural networks (CNNs) have been widely used as a flexible…
The Advanced LIGO and Virgo detectors opened a new era to study black holes (BHs) in our Universe. A population of stellar-mass binary BHs (BBHs) are discovered to be heavier than previously expected. These heavy BBHs provide us an…
The detection of gravitational waves from compact binary coalescence by Advanced LIGO and Advanced Virgo provides an opportunity to study the strong-field, highly relativistic regime of gravity. Gravitational-wave tests of general…
Binary black holes are thought to form primarily via two channels: isolated evolution and dynamical formation. The component masses, spins, and eccentricity of a binary black hole system provide clues to its formation history. We focus on…
Matched filtering is a common method for detecting gravitational waves. However, the computational costs of searching large template banks limit the efficiency of classical algorithms when searching for massive black hole binary (MBHB)…
In this work, we apply Convolutional Neural Networks (CNNs) to detect gravitational wave (GW) signals of compact binary coalescences, using single-interferometer data from LIGO detectors. As novel contribution, we adopted a resampling…
Black holes, the simplest solution to Einstein's field equations, do not emit light, making their observations a major challenge for researchers. However, discovery of binary black holes (BBHs) in 2015 by LIGO has transformed the study of…
Based on the prior O1-O2 observing runs, about 30% of the data collected by Advanced LIGO and Virgo in the next observing runs are expected to be single-interferometer data, i.e., they will be collected at times when only one detector in…
Binary black holes (BBHs) in eccentric orbits produce distinct modulations in gravitational waves (GWs); measuring orbital eccentricity provides evidence for dynamical binary formation channels. We analyze 57 GW events from the…
Binary black holes (BBHs) exhibiting spin-induced orbital precession offer unique insight into compact-binary formation channels, cosmology, and tests of general relativity. We conduct a dedicated search for precessing BBHs with unequal…
The expected volume of data from the third-generation gravitational waves (GWs) Einstein Telescope (ET) detector would make traditional GWs search methods such as match filtering impractical. This is due to the large template bank required…
The recent advanced LIGO detections of gravitational waves from merging binary black holes enhance the prospect of exploring binary evolution via gravitational-wave observations of a population of compact-object binaries. In the face of…
Convolutional Neural Networks (CNNs) have demonstrated potential for the real-time analysis of data from gravitational-wave detector networks for the specific case of signals from coalescing compact-object binaries such as black-hole…
The sensitivity of gravitational wave searches for binary black holes is estimated via the injection and posterior recovery of simulated gravitational wave signals in the detector data streams. When a search reports no detections, the…
Due to their small mass, subsolar mass black hole binaries would have to be primordial in origin instead of the result of stellar evolution. Soon after formation in the early universe, primordial black holes can form binaries after…