Related papers: Deep learning merger masses estimation from gravit…
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…
The matched filtering paradigm is the mainstay of gravitational wave (GW) searches from astrophysical coalescing compact binaries. The compact binary coalescence (CBC) search pipelines perform the matched filter between the GW detector's…
Gravitational Waves (GWs) from coalescing binaries carry crucial information about their component sources, like mass, spin and tidal effects. This implies that the analysis of GW signals from binary neutron star mergers can offer unique…
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…
In recent years, convolutional neural network (CNN) and other deep learning models have been gradually introduced into the area of gravitational-wave (GW) data processing. Compared with the traditional matched-filtering techniques, CNN has…
We explore machine learning methods to detect gravitational waves (GW) from binary black hole (BBH) mergers using deep learning (DL) algorithms. The DL networks are trained with gravitational waveforms obtained from BBH mergers with…
Mergers of binary neutron stars (BNSs) emit signals in both the gravitational-wave (GW) and electromagnetic (EM) spectra. Famously, the 2017 multi-messenger observation of GW170817 led to scientific discoveries across cosmology, nuclear…
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…
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…
In recent years, improvements in Deep Learning (DL) techniques towards Gravitational Wave (GW) astronomy have led to a significant rise in the development of various classification algorithms that have been successfully employed to extract…
The detection of gravitational waves (GWs) from binary neutron stars (BNSs) with possible telescope follow-ups opens a window to ground-breaking discoveries in the field of multi-messenger astronomy. With the improved sensitivity of current…
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 present a robust and efficient methodology for parameter estimation of gravitational waves generated during the post-merger phase of binary neutron star mergers. Our approach leverages an analytic waveform model combined with empirical…
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…
Clustering measurements of Gravitational Wave (GW) mergers in Luminosity Distance Space can be used in the future as a powerful tool for Cosmology. We consider tomographic measurements of the Angular Power Spectrum of mergers both in an…
As two neutron stars merge, they emit gravitational waves that can potentially be detected by earth bound detectors. Matched-filtering based algorithms have traditionally been used to extract quiet signals embedded in noise. We introduce a…
The recent Nobel-prize-winning detections of gravitational waves from merging black holes and the subsequent detection of the collision of two neutron stars in coincidence with electromagnetic observations have inaugurated a new era of…
We describe a stream-based analysis pipeline to detect gravitational waves from the merger of binary neutron stars, binary black holes, and neutron-star-black-hole binaries within ~ 1 minute of the arrival of the merger signal at Earth.…
Binary neutron star mergers are expected to be one of the most promising source of gravitational waves (GW) for the network of laser interferometric and bar detectors becoming operational in the next few years. The merger wave signal is…
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…