Recent progresses in model-independent detection of gravitational-wave transients: the case of hyperbolic encounters between compact objects
ORAL
Abstract
Since the first observation in 2015, the LIGO-Virgo-KAGRA (LVK) collaboration reported hundreds of gravitational wave (GW) events. These observations provide
invaluable tests of the General Relativity and are unveiling compact objects' nature. The totality of GW events detected so far originated from the coalescence
of compact binary systems. However, GW transients are expected also from other sources as core collapse supernovae, isolated neutron stars, and cosmic
strings. For these sources, the GW waveforms are not known accurately, or their availability is limited, and so they are searched for by looking for excess of
power coherent in multiple GW detectors, using only weak assumptions about the GW signal.
In this talk, I will overview the state-of-the-art of the model-independent search software Coherent WaveBurst (cWB). First, I will show the latest methodological developments, such as the application of autoencoder and decision-tree learning algorithms. These machine-learning techniques improve significantly the separation between potential signals and noises, but their application to model-independent searches is challenging and requires particular caution in the selection of the training procedure. Next, I will present the search for GWs from close hyperbolic encounters of stellar mass compact objects in the data of the third LVK observing run. For the first time, we report the sensitivity volume achieved for such sources, and we compare our findings with astrophysical models.
invaluable tests of the General Relativity and are unveiling compact objects' nature. The totality of GW events detected so far originated from the coalescence
of compact binary systems. However, GW transients are expected also from other sources as core collapse supernovae, isolated neutron stars, and cosmic
strings. For these sources, the GW waveforms are not known accurately, or their availability is limited, and so they are searched for by looking for excess of
power coherent in multiple GW detectors, using only weak assumptions about the GW signal.
In this talk, I will overview the state-of-the-art of the model-independent search software Coherent WaveBurst (cWB). First, I will show the latest methodological developments, such as the application of autoencoder and decision-tree learning algorithms. These machine-learning techniques improve significantly the separation between potential signals and noises, but their application to model-independent searches is challenging and requires particular caution in the selection of the training procedure. Next, I will present the search for GWs from close hyperbolic encounters of stellar mass compact objects in the data of the third LVK observing run. For the first time, we report the sensitivity volume achieved for such sources, and we compare our findings with astrophysical models.
*I gratefully acknowledge the LIGO-Virgo-KAGRA collaboration
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Publication: 1. PhD thesis, Sophie Bini 2024 "Enhancing the detection and the reconstruction of gravitational-wave transients in the LIGO-Virgo-KAGRA data using weak assumptions on the astrophysical sources"
2. Bini, Sophie, et al. "Search for hyperbolic encounters of compact objects in the third LIGO-Virgo-KAGRA observing run." Physical Review D 109.4 (2024): 042009.
Presenters
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Sophie Bini
- LIGO Laboratory, Caltech