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conda-forge.org : cwb
Coherent network analysis is addressing the problem of detection and reconstruction of gravitational waves (GW) with networks of detectors. It has been extensively studied in the literature in application to detection of bursts signals, which may be produced by numerous gravitational wave sources in the Universe. In coherent methods, a statistic is built up as a coherent sum over detector responses. In general, it is expected to be more optimal (better sensitivity at the same false alarm rate) than the detection statistics of the individual detectors that make up the network. Also coherent methods provide estimators for the GW waveforms and the source coordinates in the sky. The method we present (called coherent WaveBurst) is significantly different from the traditional burst detection methods. Unlike coincident methods, which first identify events in individual detectors by using an excess power statistic and than require coincidence between detectors, the coherent WaveBurst method combines all data streams into one coherent statistic constructed in the framework of the constrained maximum likelihood analysis. Such an approach has significant advantages over the coincident methods. First, the sensitivity of the method is not limited by the least sensitive detector in the network. In the coherent WaveBurst method the detection is based on the maximum likelihood ratio statistic which represents the total signal-to-noise ratio of the GW signal detected in the network. Second, other coherent statistics, such as the null stream and the network correlation coefficient can be constructed to distinguish genuine GW signals from the environmental and instrumental artifacts. Finally, the source coordinates of the GW waveforms can be reconstructed.
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purl: pkg:conda/cwb
License: CNRI-Python-GPL-Compatible
Latest release: almost 2 years ago
First release: almost 2 years ago
Last synced: 22 days ago