2016
DOI: 10.1088/0264-9381/33/22/224003
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Subtraction of correlated noise in global networks of gravitational-wave interferometers

Abstract: The recent discovery of merging black holes suggests that a stochastic gravitational-wave background is within reach of the advanced detector network operating at design sensitivity. However, correlated magnetic noise from Schumann resonances threatens to contaminate observation of a stochastic background. In this paper, we report on the first effort to eliminate intercontinental correlated noise from Schumann resonances using Wiener filtering. Using magnetometers as proxies for gravitational-wave detectors, w… Show more

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Cited by 52 publications
(58 citation statements)
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“…about 0.6 for the dominant harmonic. This is similar to what was achieved from the last data set [14]. The middle of Fig.…”
Section: Coherence Measurementssupporting
confidence: 88%
See 3 more Smart Citations
“…about 0.6 for the dominant harmonic. This is similar to what was achieved from the last data set [14]. The middle of Fig.…”
Section: Coherence Measurementssupporting
confidence: 88%
“…We then determine the level of reduction of correlated noise in two magnetometers, which is important for SGWB searches. We made an attempt at global magnetometer subtraction in [14], predominantly using previously deployed magnetometers to construct a toy-model gravitational-wave network. In this analysis, with the previously deployed magnetometers and dedicated on-site measurements, we provide results we can expect for on-site magnetometer based subtraction with a realistic network of magnetometers.…”
Section: Wiener Filteringmentioning
confidence: 99%
See 2 more Smart Citations
“…Subtraction and mitigation of the correlated noise is therefore very important issue, and combining the geophysical data monitored outside the GW detectors, a more efficient methodology needs to be developed, together with the experimental efforts on reducing the coupling with magnetic fields (see e.g., Refs. [20,21] along this direction).…”
Section: Introductionmentioning
confidence: 99%