相关论文: Ninja data analysis with a detection pipeline base…
With increasing sensitivity of the gravitational wave (GW) detectors, we expect a significant rise in the detectable GW events. To process, analyse and identify such large amounts of GW signals arising from mergers of Binary Black Holes…
The search for gravitational-wave signals is limited by non-Gaussian transient noises that mimic astrophysical signals. Temporal coincidence between two or more detectors is used to mitigate contamination by these instrumental glitches.…
We propose a new model of Bayesian Neural Networks to not only detect the events of compact binary coalescence in the observational data of gravitational waves (GW) but also identify the full length of the event duration including the…
We introduce the use of deep learning ensembles for real-time, gravitational wave detection of spinning binary black hole mergers. This analysis consists of training independent neural networks that simultaneously process strain data from…
Using the IceCube Neutrino Observatory, we search for high-energy neutrino emission coincident with compact binary mergers observed by the LIGO and Virgo gravitational wave (GW) detectors during their first and second observing runs. We…
We present a neural-network-based data processing pipeline for Baikal-GVD, designed to improve event reconstruction quality and accelerate neutrino candidates selection. The pipeline comprises three stages: fast suppression of extensive air…
This paper proposes a machine learning-assisted channel estimation approach for massive MIMO systems, leveraging DNNs to outperform traditional LS and MMSE methods. In 5G and beyond, accurate channel estimation mitigates pilot contamination…
We investigate the ability of the Large Synoptic Survey Telescope (LSST) to discover kilonovae (kNe) from binary neutron star (BNS) and neutron star-black hole (NSBH) mergers, focusing on serendipitous detections in the Wide-Fast-Deep (WFD)…
Merger rates of binary black holes, binary neutron stars, and neutron star-black hole binaries in the local Universe (i.e., redshift $z=0$), inferred from the Laser Interferometer Gravitational Wave Observatory (LIGO) and Virgo, are…
This work presents the first demonstration of non-linear noise regression in the Virgo detector using deep learning techniques. We use DeepClean, a convolutional autoencoder previously shown to be effective in denoising LIGO data, as our…
Transient noise glitches in gravitational-wave detector data limit the sensitivity of searches and contaminate detected signals. In this Paper, we show how glitches can be simulated using generative adversarial networks. We produce hundreds…
The exquisite sensitivity of the advanced LIGO detectors has enabled the detection of multiple gravitational wave signals. The sophisticated design of these detectors mitigates the effect of most types of noise. However, advanced LIGO data…
Accelerating Human Action Recognition (HAR) efficiently for real-time surveillance and robotic systems on edge chips remains a challenging research field, given its high computational and memory requirements. This paper proposed an…
We present a new class of AI models for the detection of quasi-circular, spinning, non-precessing binary black hole mergers whose waveforms include the higher order gravitational wave modes $(l, |m|)=\{(2, 2), (2, 1), (3, 3), (3, 2), (4,…
Initial orbital eccentricities of gravitational wave (GW) events associated with merging binary black holes (BBHs) should provide clues to their formation scenarios, mainly because various BBH formation channels predict distinct…
The gravitational wave sky is starting to become very crowded, with the fourth science run (O4) at LIGO expected to detect $\mathcal{O}(100)$ compact object coalescence signals. Data analysis issues start to arise as we look further…
The detection of a secular post-merger gravitational wave (GW) signal in a binary neutron star (BNS) merger serves as strong evidence for the formation of a long-lived post-merger neutron star (NS), which can help constrain the maximum mass…
Inspirals and mergers of black hole (BHs) and/or neutron star (NSs) binaries are expected to be abundant sources for ground-based gravitational-wave (GW) detectors. We assess the capabilities of Advanced LIGO and Virgo to measure component…
We present a novel machine learning framework tailored to detect massive black hole binaries observed by spaceborne gravitational wave detectors like the Laser Interferometer Space Antenna (LISA) and predict their future merger times. The…
Activities in data analysis and numerical simulation of gravitational waves have to date largely proceeded independently. In this work we study how waveforms obtained from numerical simulations could be effectively used within the data…