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Self-calibration of Networks of Gravitational Wave Detectors

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Schutz,  B. F.
Astrophysical Relativity, AEI-Golm, MPI for Gravitational Physics, Max Planck Society;

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2009.10212.pdf
(Preprint), 248KB

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Citation

Schutz, B. F., & Sathyaprakash, B. S. (in preparation). Self-calibration of Networks of Gravitational Wave Detectors.


Cite as: https://hdl.handle.net/21.11116/0000-0007-466C-2
Abstract
As LIGO and Virgo are upgraded, improving calibration systems to keep pace
with the anticipated signal-to-noise enhancements will be challenging. We
explore here a calibration method that uses astronomical signals, namely
inspiral signals from compact-object binaries, and we show that it can in
principle enable calibration at the sub-1\% accuracy levels needed for future
gravitational wave science. We show how ensembles of these transient events can
be used to measure the calibration errors of individual detectors in a network
of three or more comparably sensitive instruments. As with telescopes, relative
calibration of gravitational-wave detectors using detected events is easier to
achieve than absolute calibration, which in principle would still need to be
done with a hardware method for at least one detector at one frequency. Our
proposed method uses the so-called null streams, the signal-free linear
combinations of the outputs of the detectors that exist in any network with
three or more differently oriented detectors. Signals do not appear in the null
stream if the signal amplitude in the detector output is faithful to that of
the real signal. Frequency-dependent calibration errors and relative
calibration and timing errors between detectors leave a residual in the null
stream. The amount of residual from each detector depends on the source
direction. We adapt the method of matched filtering to the problem of
extracting the calibration error of each detector from this residual. This
requires combining linearly the filter outputs of a sufficient number of
detected signals, and in principle it can achieve any desired accuracy in a
long enough observation run. We anticipate that A+ detector networks, expected
in 5 years, could employ this method to check anticipated hardware calibration
accuracies.