Related papers: Explaining the GWSkyNet-Multi machine learning cla…
The Advanced LIGO and Advanced Virgo detectors have enabled the confident detection of dozens of mergers of black holes and neutron stars. However, the presence of detector noise transients (glitches) hinders the search for these…
The simultaneous observation of gravitational waves (GW) and prompt electromagnetic counterparts from the merger of two neutron stars can help reveal the properties of extreme matter and gravity during and immediately after the final…
Gravitational waves from the coalescence of compact-binary sources are now routinely observed by Earth bound detectors. The most sensitive search algorithms convolve many different pre-calculated gravitational waveforms with the detector…
Fast and effective localization of gravitational wave (GW) events could play a crucial role in identifying possible electromagnetic counterparts, and thereby help usher in an era of GW multi-messenger astronomy. We discuss an algorithm for…
Low-latency gravitational-wave alerts provide the greater multi-messenger community with information about the candidate events detected by the International Gravitational-Wave Network (IGWN). Prompt release of data products such as the sky…
Systematic errors in the parameter estimation (PE) of gravitational wave (GW) mergers can arise from various sources, including waveform systematics, noise mischaracterization, data analysis artifacts, and other unknown factors. In this…
Gravitational waves are ripples in the space time fabric when high energy events such as black hole mergers or neutron star collisions take place. The first Gravitational Wave (GW) detection (GW150914) was made by the Laser Interferometer…
The LIGO Scientific, Virgo, and KAGRA collaboration has identified two binary neutron star merger candidates, GW170817 and GW190425, along with several binary black hole candidates. While GW170817 was confirmed as a BNS merger through its…
An observation of gravitational waves is a trigger of the multi-messenger search of an astronomical event. A combination of the data from two or three gravitational wave telescopes indicates the location of a source and low-latency data…
We present a convolutional neural network, designed in the auto-encoder configuration that can detect and denoise astrophysical gravitational waves from merging black hole binaries, orders of magnitude faster than the conventional…
Gravitational Waves (GWs) provide a powerful means for cosmological distance estimation, circumventing the systematic uncertainties associated with traditional electromagnetic (EM) indicators. This work presents a model for estimating…
The catalog of gravitational-wave events is growing, and so are our hopes of constraining the underlying astrophysics of stellar-mass black-hole mergers by inferring the distributions of, e.g., masses and spins. While conventional analyses…
One of the key challenges of real-time detection and parameter estimation of gravitational waves from compact binary mergers is the computational cost of conventional matched-filtering and Bayesian inference approaches. In particular, the…
The success of the multi-messenger astronomy relies on gravitational-wave observatories like LIGO and Virgo to provide prompt warning of merger events involving neutron stars (including both binary neutron stars and…
Gravitational wave detection has opened up new avenues for exploring and understanding some of the fundamental principles of the universe. The optimal method for detecting modelled gravitational-wave events involves template-based matched…
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 introduce deep learning time-series forecasting for gravitational wave detection of binary neutron star mergers. This method enables the identification of these signals in real advanced LIGO data up to 30 seconds before merger. When…
We explore opportunities for multi-messenger astronomy using gravitational waves (GWs) and prompt, transient low-frequency radio emission to study highly energetic astrophysical events. We review the literature on possible sources of…
Parameterised models that predict the gravitational-wave (GW) signal from merging black holes are used to extract source properties from GW observations. The majority of research in this area has focused on developing methods capable of…
The Coherent WaveBurst (cWB) search algorithm identifies generic gravitational wave (GW) signals in the LIGO-Virgo strain data. We propose a machine learning (ML) method to optimize the pipeline sensitivity to the special class of GW…