相关论文: Deep learning merger masses estimation from gravit…
The gravitational waveform of merging binary neutron stars encodes information about extreme states of matter. Probing these gravitational emissions requires the gravitational-wave detectors to have high sensitivity above 1 kHz. Fortunately…
The pre-merger detection of gravitational waves from the early inspiral phase of compact binary coalescence events would allow the observation of the earlier stages of the merger in the electromagnetic band. This would significantly impact…
Continuous gravitational-wave (CW) signals such as emitted by spinning neutron stars are an important target class for current detectors. However, the enormous computational demand prohibits fully coherent broadband all-sky searches for…
Because of the electromagnetic radiation produced during the merger, compact binary coalescences with neutron stars may result in multi-messenger observations. In order to follow up on the gravitational-wave signal with electromagnetic…
Computing signal-to-noise ratios (SNRs) is one of the most common tasks in gravitational-wave data analysis. While a single SNR evaluation is generally fast, computing SNRs for an entire population of merger events could be time consuming.…
Gravitational wave (GW) observations probe both a diffuse, stochastic gravitational wave background (SGWB) as well as individual cataclysmic events such as the merger of two compact objects. The detection and description of the…
We present the implementation of an anomaly-detection algorithm based on a deep convolutional autoencoder for the search for gravitational waves (GWs) in time-frequency spectrograms. Our method targets short-duration ($\lesssim…
This is a collection of literature reviews and some initial work on the estimation of the frequency of gravitational waves from a binary black hole merger for low SNR. This document provides a starting point, with a broad overview of the…
We discuss gravitational waves from merging binaries using a Newtonian approach with some inputs from the Post-Newtonian formalism. We show that it is possible to understand the key features of the signal using fundamental physics and also…
Minute-long Gravitational Wave (GW) transients are events lasting from few to hundreds of seconds. In opposition to compact binary mergers, their GW signals cover a wide range of poorly understood astrophysical phenomena such as accretion…
Mergers of binary neutron stars and black hole-neutron star binaries are one of the most promising sources for the ground-based gravitational-wave (GW) detectors and also a high-energy astrophysical phenomenon as illustrated by the…
This study explores the integration of quantum algorithms, specifically Grover's algorithm, with quantum metrology to enhance the efficiency and sensitivity of gravitational-wave detection. By combining quantum matched filtering with…
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…
We apply common gravitational wave inference procedures on binary black hole merger waveforms beyond general relativity. We consider dynamical Chern-Simons gravity, a modified theory of gravity with origins in string theory and loop quantum…
Neutron star mergers are among the most promising sources of gravitational waves for advanced ground-based detectors. These mergers are also expected to power bright electromagnetic signals, in the form of short gamma-ray bursts,…
Unlike ground-based gravitational wave detectors, space-based gravitational wave detectors can detect the ringdown signals from massive black hole mergers with large signal-to-noise ratios, help to localize sources and extract their…
Recent multi-dimensional (multi-D) core-collapse supernova (CCSN) simulations characterize gravitational waves (GWs) and neutrino signals, offering insight into universal properties of CCSN independent of progenitor. Neutrino analysis in…
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…
Mergers of binary neutron stars and black hole-neutron star binaries produce gravitational-wave (GW) emission and outflows with significant kinetic energies. These outflows result in radio emissions through synchrotron radiation. We explore…
The detection and characterization of post-merger gravitational wave signals from binary neutron star mergers remains challenging with current ground-based detectors. We present a convolutional neural network framework designed for…