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General Relativity and Gravitation
Article
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arXiv.org e-Print Archive
Preprint . 2016
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General Relativity and Gravitation
Article . 2016 . Peer-reviewed
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https://dx.doi.org/10.48550/ar...
Article . 2016
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http://export.arxiv.org/pdf/16...
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General Relativity and Gravitation
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Parameter estimates in binary black hole collisions using neural networks

descriptionPublicationkeyboard_double_arrow_right Article , Preprint , Other literature type 28 Sep 2016Embargo end date: 01 Jan 2016Publisher:Springer Science and Business Media LLCJournal:General Relativity and Gravitation, volume 48 (issn: 0001-7701, eissn: 1572-9532, Copyright policy )
Authors: F. S. Guzmán; M. Carrillo; M. Gracia-Linares; José A. González;

doi: 10.1007/s10714-016-2136-0 , 10.48550/arxiv.1608.02491

arXiv: http://arxiv.org/abs/1608.02491

Parameter estimates in binary black hole collisions using neural networks

Abstract

We present an algorithm based on artificial neural networks (ANNs), that estimates the mass ratio in a binary black hole collision out of given Gravitational Wave (GW) strains. In this analysis, the ANN is trained with a sample of GW signals generated with numerical simulations. The effectiveness of the algorithm is evaluated with GWs generated also with simulations for given mass ratios unknown to the ANN. We measure the accuracy of the algorithm in the interpolation and extrapolation regimes. We present the results for noise free signals and signals contaminated with Gaussian noise, in order to foresee the dependence of the method accuracy in terms of the signal to noise ratio.

7 pages, 9 eps figures

Related Organizations
Keywords

High Energy Astrophysical Phenomena (astro-ph.HE), FOS: Physical sciences, General Relativity and Quantum Cosmology (gr-qc), Astrophysics - Instrumentation and Methods for Astrophysics, Astrophysics - High Energy Astrophysical Phenomena, Instrumentation and Methods for Astrophysics (astro-ph.IM), General Relativity and Quantum Cosmology

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    This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    		 10
    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    		 Top 10%
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    		 Top 10%
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citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
10
Top 10%
Average
Top 10%
Green
bronze