Parameter Estimation for Gravitational-wave Bursts with the BayesWave Pipeline
We provide a comprehensive multi-aspect study of the performance of a pipeline used by the LIGO-Virgo Collaboration for estimating parameters of gravitational-wave bursts. We add simulated signals with four different morphologies (sine-Gaussians (SGs), Gaussians, white-noise bursts, and binary black...
| Main Authors: | , , , , , , , , |
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| Other Authors: | |
| Format: | Article |
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IOP Publishing
2017
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| Online Access: | http://hdl.handle.net/1721.1/111964 https://orcid.org/0000-0001-8196-9267 https://orcid.org/0000-0001-6550-3045 https://orcid.org/0000-0003-2700-0767 |
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| author | Bécsy, Bence Raffai, Peter Cornish, Neil J. Kanner, Jonah Littenberg, Tyson B. Millhouse, Margaret Essick, Reed Clasey Katsavounidis, Erotokritos Vitale, Salvatore |
| author2 | Massachusetts Institute of Technology. Department of Physics |
| author_facet | Massachusetts Institute of Technology. Department of Physics Bécsy, Bence Raffai, Peter Cornish, Neil J. Kanner, Jonah Littenberg, Tyson B. Millhouse, Margaret Essick, Reed Clasey Katsavounidis, Erotokritos Vitale, Salvatore |
| author_sort | Bécsy, Bence |
| collection | MIT |
| description | We provide a comprehensive multi-aspect study of the performance of a pipeline used by the LIGO-Virgo Collaboration for estimating parameters of gravitational-wave bursts. We add simulated signals with four different morphologies (sine-Gaussians (SGs), Gaussians, white-noise bursts, and binary black hole signals) to simulated noise samples representing noise of the two Advanced LIGO detectors during their first observing run. We recover them with the BayesWave (BW) pipeline to study its accuracy in sky localization, waveform reconstruction, and estimation of model-independent waveform parameters. BW localizes sources with a level of accuracy comparable for all four morphologies, with the median separation of actual and estimated sky locations ranging from 25.°1 to 30.°3. This is a reasonable accuracy in the two-detector case, and is comparable to accuracies of other localization methods studied previously. As BW reconstructs generic transient signals with SG wavelets, it is unsurprising that BW performs best in reconstructing SG and Gaussian waveforms. The BW accuracy in waveform reconstruction increases steeply with the network signal-to-noise ratio (S/N), reaching a 85% and 95% match between the reconstructed and actual waveform below S/N and S/N, respectively, for all morphologies. The BW accuracy in estimating central moments of waveforms is only limited by statistical errors in the frequency domain, and is also affected by systematic errors in the time domain as BW cannot reconstruct low-amplitude parts of signals that are overwhelmed by noise. The figures of merit we introduce can be used in future characterizations of parameter estimation pipelines. |
| first_indexed | 2024-09-23T15:52:11Z |
| format | Article |
| id | mit-1721.1/111964 |
| institution | Massachusetts Institute of Technology |
| last_indexed | 2024-09-23T15:52:11Z |
| publishDate | 2017 |
| publisher | IOP Publishing |
| record_format | dspace |
| spelling | mit-1721.1/1119642022-09-29T16:40:53Z Parameter Estimation for Gravitational-wave Bursts with the BayesWave Pipeline Bécsy, Bence Raffai, Peter Cornish, Neil J. Kanner, Jonah Littenberg, Tyson B. Millhouse, Margaret Essick, Reed Clasey Katsavounidis, Erotokritos Vitale, Salvatore Massachusetts Institute of Technology. Department of Physics MIT Kavli Institute for Astrophysics and Space Research Essick, Reed Clasey Katsavounidis, Erotokritos Vitale, Salvatore We provide a comprehensive multi-aspect study of the performance of a pipeline used by the LIGO-Virgo Collaboration for estimating parameters of gravitational-wave bursts. We add simulated signals with four different morphologies (sine-Gaussians (SGs), Gaussians, white-noise bursts, and binary black hole signals) to simulated noise samples representing noise of the two Advanced LIGO detectors during their first observing run. We recover them with the BayesWave (BW) pipeline to study its accuracy in sky localization, waveform reconstruction, and estimation of model-independent waveform parameters. BW localizes sources with a level of accuracy comparable for all four morphologies, with the median separation of actual and estimated sky locations ranging from 25.°1 to 30.°3. This is a reasonable accuracy in the two-detector case, and is comparable to accuracies of other localization methods studied previously. As BW reconstructs generic transient signals with SG wavelets, it is unsurprising that BW performs best in reconstructing SG and Gaussian waveforms. The BW accuracy in waveform reconstruction increases steeply with the network signal-to-noise ratio (S/N), reaching a 85% and 95% match between the reconstructed and actual waveform below S/N and S/N, respectively, for all morphologies. The BW accuracy in estimating central moments of waveforms is only limited by statistical errors in the frequency domain, and is also affected by systematic errors in the time domain as BW cannot reconstruct low-amplitude parts of signals that are overwhelmed by noise. The figures of merit we introduce can be used in future characterizations of parameter estimation pipelines. 2017-10-23T19:43:48Z 2017-10-23T19:43:48Z 2017-04 2017-02 2017-10-19T14:23:08Z Article http://purl.org/eprint/type/JournalArticle 1538-4357 0004-637X http://hdl.handle.net/1721.1/111964 Bécsy, Bence et al. “Parameter Estimation for Gravitational-Wave Bursts with the BayesWave Pipeline.” The Astrophysical Journal 839, 1 (April 2017): 15 © 2017 The American Astronomical Society. All rights reserved https://orcid.org/0000-0001-8196-9267 https://orcid.org/0000-0001-6550-3045 https://orcid.org/0000-0003-2700-0767 http://dx.doi.org/10.3847/1538-4357/AA63EF Astrophysical Journal Article is made available in accordance with the publisher's policy and may be subject to US copyright law. Please refer to the publisher's site for terms of use. application/pdf IOP Publishing IOP Publishing |
| spellingShingle | Bécsy, Bence Raffai, Peter Cornish, Neil J. Kanner, Jonah Littenberg, Tyson B. Millhouse, Margaret Essick, Reed Clasey Katsavounidis, Erotokritos Vitale, Salvatore Parameter Estimation for Gravitational-wave Bursts with the BayesWave Pipeline |
| title | Parameter Estimation for Gravitational-wave Bursts with the BayesWave Pipeline |
| title_full | Parameter Estimation for Gravitational-wave Bursts with the BayesWave Pipeline |
| title_fullStr | Parameter Estimation for Gravitational-wave Bursts with the BayesWave Pipeline |
| title_full_unstemmed | Parameter Estimation for Gravitational-wave Bursts with the BayesWave Pipeline |
| title_short | Parameter Estimation for Gravitational-wave Bursts with the BayesWave Pipeline |
| title_sort | parameter estimation for gravitational wave bursts with the bayeswave pipeline |
| url | http://hdl.handle.net/1721.1/111964 https://orcid.org/0000-0001-8196-9267 https://orcid.org/0000-0001-6550-3045 https://orcid.org/0000-0003-2700-0767 |
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