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Subtraction of Newtonian noise using optimized sensor arrays

Driggers, Jennifer C. and Harms, Jan and Adhikari, Rana X. (2012) Subtraction of Newtonian noise using optimized sensor arrays. Physical Review D, 86 (10). Art. No. 102001. ISSN 2470-0010.

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Fluctuations in the local Newtonian gravitational field present a limit to high precision measurements, including searches for gravitational waves using laser interferometers. In this work, we present a model of this perturbing gravitational field and evaluate schemes to mitigate the effect by estimating and subtracting it from the interferometer data stream. Information about the Newtonian noise is obtained from simulated seismic data. The method is tested on causal as well as acausal implementations of noise subtraction. In both cases it is demonstrated that broadband mitigation factors close to 10 can be achieved removing Newtonian noise as a dominant noise contribution. The resulting improvement in the detector sensitivity will substantially enhance the detection rate of gravitational radiation from cosmological sources.

Item Type:Article
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URLURL TypeDescription
Harms, Jan0000-0002-7332-9806
Adhikari, Rana X.0000-0002-5731-5076
Additional Information:© 2012 American Physical Society. Received 27 July 2012; published 1 November 2012. We thank the National Science Foundation for support under Grant No. PHY-0555406. J.C.D. also acknowledges the support of the NSF.We thank R. Schofield and A. Effler for their help with the measurements presented in Sec. II. LIGO was constructed by the California Institute of Technology and Massachusetts Institute of Technology with funding from the National Science Foundation and operates under cooperative agreement PHY-0107417. This article has LIGO internal Document No. P1200017.
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Other Numbering System NameOther Numbering System ID
LIGO internal DocumentNo. P1200017
Issue or Number:10
Classification Code:PACS: 04.80.Nn, 95.55.Ym, 07.60.Ly, 42.62.Eh
Record Number:CaltechAUTHORS:20121129-084419241
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Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:35720
Deposited By: Jason Perez
Deposited On:29 Nov 2012 20:51
Last Modified:09 Mar 2020 13:18

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