相关论文: PINCH: Pipeline-Informed Noise Characterization in…
Detection confidence of the source-agnostic gravitational-wave burst search pipeline BayesWave is quantified by the log signal-versus-glitch Bayes factor, $\ln\mathcal{B}_{\mathcal{S},\mathcal{G}}$. A recent study shows that…
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…
To evaluate the probability of a gravitational-wave candidate originating from noise, GstLAL collects noise statistics from the data it analyzes. Gravitational-wave signals of astrophysical origin get added to the noise statistics, harming…
Data recorded by gravitational wave detectors includes many non-astrophysical transient noise bursts, the most common of which is caused by scattered-light within the detectors. These so-called ``glitches'' in the data impact the ability to…
This work investigates the temporal distribution of glitches detected by LIGO, focusing on the morphological classification provided by the Gravity Spy project. Starting from the hypothesis that these events follow a Poisson process, we…
We present an algorithm for the identification of transient noise artifacts (glitches) in cross-correlation searches for long O(10s) gravitational-wave transients. The algorithm utilizes the auto-power in each detector as a discriminator…
An important goal for LIGO (the Laser Interferometer Gravitational-Wave Observatory) and Virgo is to find periodic sources of gravitational waves. The LIGO and Virgo detectors are sensitive to a variety of noise of non-astrophysical origin,…
The sensitivity of searches for astrophysical transients in data from the LIGO is generally limited by the presence of transient, non-Gaussian noise artifacts, which occur at a high-enough rate such that accidental coincidence across…
One class of gravitational wave signals LIGO is searching for consists of short duration bursts of unknown waveforms. Potential sources include core collapse supernovae, gamma ray burst progenitors, and mergers of binary black holes or…
Gravitational wave detection requires sophisticated signal processing to identify weak astrophysical signals buried in instrumental noise. Traditional matched filtering approaches face computational challenges with diverse signal…
Gravitational wave interferometers are disrupted by various types of nonstationary noise, referred to as glitch noise, that affect data analysis and interferometer sensitivity. The accurate identification and classification of glitch noise…
We present a new method for the classification of transient noise signals (or glitches) in advanced gravitational-wave interferometers. The method uses learned dictionaries (a supervised machine learning algorithm) for signal denoising, and…
We investigate the use of Convolutional Neural Networks (including the modern ConvNeXt network family) to classify transient noise signals (i.e.~glitches) and gravitational waves in data from the Advanced LIGO detectors. First, we use…
We investigate the effect of an important class of glitches occurring in the detector data on matched filter searches of gravitational waves from coalescing compact binaries in the advanced detector era. The glitches, which can be modeled…
A central open question in gravitational-wave detector characterization is whether the O4a observing run has introduced glitch morphologies not present in earlier runs. We present gravi-signal-ml, an open-source pipeline for unsupervised…
Gravitational-wave observatories become more sensitive with each observing run, increasing the number of detected gravitational-wave signals. A limiting factor in identifying these signals is the presence of transient non-Gaussian noise,…
Machine learning can be a powerful tool to discover new signal types in astronomical data. We here apply it to search for long-duration transient gravitational waves triggered by pulsar glitches, which could yield physical insight into the…
The detection of gravitational waves with LIGO and Virgo requires a detailed understanding of the response of these instruments in the presence of environmental and instrumental noise. Of particular interest is the study of anomalous…
Gravitational-wave (GW) interferometers are able to detect a change in distance of $\sim$ 1/10,000th the size of a proton. Such sensitivity leads to large appearance rates of non-Gaussian transient noise bursts in the main detector strain,…
In recent years, much work have studied the use of convolutional neural networks for gravitational-wave detection. However little work pay attention to whether the transient noise can trigger the CNN model or not. In this paper, we study…