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Normal/independent noise in VIRGO data

F. Acernese P. Amico M. Alshourbagy F. Antonucci S. Aoudia 1 S. Avino D. Babusci G. Ballardin F. Barone L. Barsotti M. Barsuglia 2 F. Beauville 3 S. Bigotta S. Birindelli M.A Bizouard 2 C. Boccara 4 François Bondu 1 L. Bosi C. Bradaschia S. Braccini A. Brillet 1 V. Brisson 2 L. Brocco D. Buskulic 3 E. Calloni E. Campagna F. Cavalier 2 R. Cavalieri G. Cella E. Cesarini E. Chassande-Mottin 1 C. Corda F. Cottone A.-C. Clapson 2 F. Cleva 1 J.-P. Coulon 1 E. Cuoco A. Dari V. Dattilo M. Davier 2 R. de Rosa L. Di Fiore A. Di Virgilio B. Dujardin 1 A. Eleuteri D. Enard I. Ferrante F. Fidecaro I. Fiori R. Flaminio 3 J.-D. Fournier 1 O. Francois S. Frasca F. Frasconi A. Freise L. Gammaitoni F. Garufi A. Gennai A. Giazotto G. Giordano L. Giordano R. Gouaty 3 D. Grosjean 3 G. Guidi S. Hebri H. Heitmann 1 P. Hello 2 L. Holloway S. Karkar 3 S. Kreckelbergh 2 P. La Penna M. Laval 1 N. Leroy N. Letendre 3 M. Lorenzini V. Loriette 4 M. Loupias G. Losurdo J.-M. Mackowski 5 E. Majorana C.N. Man 1 M. Mantovani F. Marchesoni F. Marion 3 J. Marque F. Martelli A. Masserot 3 M. Mazzoni L. Milano C. Moins Julien Moreau 6 N. Morgado 5 B. Mours 3 A. Pai C. Palomba F. Paoletti S. Pardi A. Pasqualetti R. Passaquieti D. Passuello B. Perniola F. Piergiovanni L. Pinard 5 R. Poggiani M. Punturo P. Puppo K. Qipiani P. Rapagnani V. Reita 4 A. Remillieux 5 F. Ricci I. Ricciardi P. Ruggi G. Russo S. Solimeno Alessandro D.A.M. Spallicci 1 R. Stanga R. Taddei M. Tonelli A. Toncelli E. Tournefier 3 F. Travasso G. Vajente D. Verkindt 3 F. Vetrano A. Viceré J.-Y. Vinet 1 H. Vocca M. Yvert 3 Zhen Zhang
Abstract : The analysis of data taken during the C7 VIRGO commissioning run showed strong deviations from Gaussian noise. In this work, we explore a family of distributions, derived from the hypothesis that heavy tails are an effect of a particular kind of nonstationarity, heterocedasticity (i.e. nonuniform variance), that appear to fit VIRGO noise better than a model based on the assumption of Gaussian noise. To estimate the parameters of the noise process (including the heterogeneous variance) we derived an expectation-maximization algorithm. We show the consequences of non-Gaussianity on the fitting of autoregressive filters and on the derivation of test statistics for matched filter operation. Finally, we apply the new noise model to the fitting of an autoregressive filter for whitening of data.
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Submitted on : Wednesday, October 25, 2006 - 11:18:48 AM
Last modification on : Monday, September 21, 2020 - 11:56:10 AM

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F. Acernese, P. Amico, M. Alshourbagy, F. Antonucci, S. Aoudia, et al.. Normal/independent noise in VIRGO data. 10th Gravitational Wave Data Analysis Workshop, Dec 2005, Brownsville, United States. pp.S829-S836, ⟨10.1088/0264-9381/23/19/S21⟩. ⟨in2p3-00109665⟩

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