Anomaly Detection in Gravitational Waves data using Convolutional AutoEncoders. (arXiv:2103.07688v2 [astro-ph.IM] UPDATED)
<a href="http://arxiv.org/find/astro-ph/1/au:+Morawski_F/0/1/0/all/0/1">Filip Morawski</a>, <a href="http://arxiv.org/find/astro-ph/1/au:+Bejger_M/0/1/0/all/0/1">Michał Bejger</a>, <a href="http://arxiv.org/find/astro-ph/1/au:+Cuoco_E/0/1/0/all/0/1">Elena Cuoco</a>, <a href="http://arxiv.org/find/astro-ph/1/au:+Petre_L/0/1/0/all/0/1">Luigia Petre</a>
As of this moment, fifty gravitational waves (GW) detections have been
announced, thanks to the observational efforts of the LIGO-Virgo Collaboration,
working with the Advanced LIGO and the Advanced Virgo interferometers. The
detection of signals is complicated by the noise-dominated nature of the data.
Conventional approaches in GW detection procedures require either precise
knowledge of the GW waveform in the context of matched filtering searches or
coincident analysis of data from multiple detectors. Furthermore, the analysis
is prone to contamination by instrumental or environmental artifacts called
glitches which either mimic astrophysical signals or reduce the overall quality
of data. In this paper, we propose an alternative generic method of studying GW
data based on detecting anomalies. The anomalies we study are transient
signals, different from the slow non-stationary noise of the detector.
Presented in the manuscript anomalies are mostly based on the GW emitted by the
mergers of binary black hole systems. However, the presented study of anomalies
is not limited only to GW alone, but also includes glitches occurring in the
real LIGO/Virgo dataset available at the Gravitational Waves Open Science
Center.
As of this moment, fifty gravitational waves (GW) detections have been
announced, thanks to the observational efforts of the LIGO-Virgo Collaboration,
working with the Advanced LIGO and the Advanced Virgo interferometers. The
detection of signals is complicated by the noise-dominated nature of the data.
Conventional approaches in GW detection procedures require either precise
knowledge of the GW waveform in the context of matched filtering searches or
coincident analysis of data from multiple detectors. Furthermore, the analysis
is prone to contamination by instrumental or environmental artifacts called
glitches which either mimic astrophysical signals or reduce the overall quality
of data. In this paper, we propose an alternative generic method of studying GW
data based on detecting anomalies. The anomalies we study are transient
signals, different from the slow non-stationary noise of the detector.
Presented in the manuscript anomalies are mostly based on the GW emitted by the
mergers of binary black hole systems. However, the presented study of anomalies
is not limited only to GW alone, but also includes glitches occurring in the
real LIGO/Virgo dataset available at the Gravitational Waves Open Science
Center.
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