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Gravitational wave signal recognition of O1 data by deep learning

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arxiv 1909.13442 v1 pith:OHMQL2DU submitted 2019-09-30 astro-ph.IM gr-qc

classification astro-ph.IMgr-qc
keywords datadeepgravitationallearningwaverecognitionsignaladjusted
verification ladder T0 review T1 audit T2 compute T3 formal
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Deep learning method develops very fast as a tool for data analysis these years. Such a technique is quite promising to treat gravitational wave detection data. There are many works already in the literature which used deep learning technique to process simulated gravitational wave data. In this paper we apply deep learning to LIGO O1 data. In order to improve the weak signal recognition we adjust the convolutional neural network (CNN) a little bit. Our adjusted convolutional neural network admits comparable accuracy and efficiency of signal recognition as other deep learning works published in the literature. Based on our adjusted CNN, we can clearly recognize the eleven confirmed gravitational wave events included in O1 and O2. And more we find about 2000 gravitational wave triggers in O1 data.

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Cited by 1 Pith paper

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