Deep Neuron Networks on Gravitational Wave Data Analysis

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dc.contributor林豐利zh_TW
dc.contributorLin, Feng-Lien_US
dc.contributor.author許緯仁zh_TW
dc.contributor.authorXu, Wei-Renen_US
dc.date.accessioned2020-10-19T06:54:53Z
dc.date.available2024-02-03
dc.date.available2020-10-19T06:54:53Z
dc.date.issued2020
dc.description.abstractnonezh_TW
dc.description.abstractAs the increasing sensitivity of gravitational wave detectors, the detection of gravitational wave events will be more and more frequent. Due to the fact that the gravitational waves of BNS and NSBH will arrive at the earth before the electromagnetic wave counterparts. The gravitational wave-triggered multi- messenger observation becomes a promising region of Astronomy. To meet the requirements of multi-messenger observation, the latency of search algorithm must be within few seconds. In this thesis, we constructed two convolutional neuron networks, one for detecting the present of the gravitational waves and the other for estimating physical parameters of the gravitational waves. Our neuron networks take only 4 seconds to process 3944 seconds data. The accuracy of our neuron network is larger than 99 % for detection when the SNR is larger than 12, and the mean relative errors are less than 10 % when the SNR is larger than 9. We also tested our DNNs with four gravitational wave events: GW150914, GW151226, GW170104 and GW170814. Keywords: Gravitational wave, Deep neural network.en_US
dc.description.sponsorship物理學系zh_TW
dc.identifierG060541012S
dc.identifier.urihttp://etds.lib.ntnu.edu.tw/cgi-bin/gs32/gsweb.cgi?o=dstdcdr&s=id=%22G060541012S%22.&%22.id.&
dc.identifier.urihttp://rportal.lib.ntnu.edu.tw:80/handle/20.500.12235/111363
dc.language英文
dc.subjectNonezh_TW
dc.subjectGravitational waveen_US
dc.subjectDeep neural networken_US
dc.titleDeep Neuron Networks on Gravitational Wave Data Analysiszh_TW
dc.titleDeep Neuron Networks on Gravitational Wave Data Analysisen_US

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