相关论文: Ninja data analysis with a detection pipeline base…
Gravitational waves (GWs) from massive black hole (MBH) mergers will provide a novel way to probe the high-redshift universe and are key to understanding galactic dynamics and evolution. In this work, we analyze MBH mergers, their GW…
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…
By the end of the next decade, we hope to have detected strongly lensed gravitational waves by galaxies or clusters. Although there exist optimal methods for identifying lensed signal, it is shown that machine learning (ML) algorithms can…
Electromagnetic observations of gravitational wave and high-energy neutrino events are crucial in understanding the physics of their astrophysical sources. X-ray counterparts are especially useful in studying the physics of the jet, the…
Low-latency analyses of gravitational-wave (GW) data from LIGO, Virgo, and KAGRA enable rapid detection of compact binary coalescences (CBC) and prompt sky localization, essential for electromagnetic follow-up in multi-messenger astronomy.…
The ongoing LIGO-Virgo-KAGRA observing run O4 provides an opportunity to discover new multi-messenger events, including binary neutron star (BNS) mergers such as GW170817, and the highly anticipated first detection of a multi-messenger…
Advanced LIGO and Virgo have so far detected gravitational waves from 10 binary black hole mergers (BBH) and 1 binary neutron star merger (BNS). In the future, we expect the detection of many more marginal sources, since compact binary…
The ability of deep learning (DL) approaches to learn generalised signal and noise models, coupled with their fast inference on GPUs, holds great promise for enhancing gravitational-wave (GW) searches in terms of speed, parameter space…
Parameter estimation of binary-black-hole merger events in gravitational-wave data relies on matched-filtering techniques, which, in turn, depend on accurate model waveforms. Here we characterize the systematic biases introduced in…
Gravitational waves from binary neutron star mergers can be used as alerts to enable prompt follow-up observations. In particular, capturing prompt electromagnetic and astroparticle emissions from the moment of a binary merger presents…
The detection of an electromagnetic transient which may originate from a binary neutron star merger can increase the probability that a given segment of data from the LIGO-Virgo ground-based gravitational-wave detector network contains a…
We describe the Multi-Band Template Analysis (MBTA) search for gravitational waves signals from coalescences of compact objects in the LIGO-Virgo data, at the time of the third observing run (2019-2020), both for low-latency detections and…
The mergers of massive black hole binaries could generate rich electromagnetic emissions, which allow us to probe the environments surrounding these massive black holes and gain deeper insights into the high energy astrophysics. However,…
We present a novel machine-learning approach to estimate selection effects in gravitational-wave observations. Using techniques similar to those commonly employed in image classification and pattern recognition, we train a series of…
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…
Determining the Hubble constant (H0), a fundamental parameter describing cosmic expansion, remains a challenge due to conflicting measurements from the early and late universe. Gravitational wave (GW) observations from binary neutron star…
Presented in this paper is a detailed and direct comparison of the LIGO and Virgo binary neutron star detection pipelines. In order to test the search programs, numerous inspiral signals were added to 24 hours of simulated detector data.…
[Abridged] We introduce an improved version of the Eccentric, Non-spinning, Inspiral-Gaussian-process Merger Approximant (ENIGMA) waveform model. We find that this ready-to-use model can: (i) produce physically consistent signals when…
Compact object mergers which produce both detectable gravitational waves and electromagnetic emission can provide valuable insights into the neutron star equation of state, the tension in the Hubble constant, and the origin of the r-process…
The speed-up of parameter estimation is an active field of research in gravitational-wave data analysis. In this paper we present GP15, a deep-learning method that merges residual networks and normalizing flows into a general-purpose,…