Tanner Prestegard, Eric Thrane, Nelson L. Christensen, Michael W. Coughlin, Ben Hubbert, Shivaraj Kandhasamy, Evan MacAyeal, Vuk Mandic
We present an algorithm for the identification of transient noise artifacts
(glitches) in cross-correlation searches for long O(10s) gravitational-wave
transients. The algorithm utilizes the auto-power in each detector as a
discriminator between well-behaved Gaussian noise (possibly including a
gravitational-wave signal) and glitches. We test the algorithm with both Monte
Carlo noise and time-shifted data from the LIGO S5 science run and find that it
is effective at removing a significant fraction of glitches while keeping the
vast majority (99.6%) of the data. Using an accretion disk instability signal
model, we estimate that the algorithm is accidentally triggered at a rate of
less than 10^-5% by realistic signals, and less than 3% even for exceptionally
loud signals. We conclude that the algorithm is a safe and effective method for
cleaning the cross-correlation data used in searches for long
gravitational-wave transients.
View original:
http://arxiv.org/abs/1111.1631
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