TY - JOUR
T1 - Identification of noise artifacts in searches for long-duration gravitational-wave transients
AU - Prestegard, Tanner
AU - Thrane, Eric
AU - Christensen, Nelson L.
AU - Coughlin, Michael W.
AU - Hubbert, Ben
AU - Kandhasamy, Shivaraj
AU - MacAyeal, Evan
AU - Mandic, Vuk
PY - 2012/5/7
Y1 - 2012/5/7
N2 - We present an algorithm for the identification of transient noise artifacts (glitches) in cross-correlation searches for long gravitational-wave (GW) transients lasting seconds to weeks. The algorithm utilizes the auto-power in each detector as a discriminator between well-behaved stationary noise (possibly including a GW signal) and non-stationary noise transients. We test the algorithm with both Monte Carlo noise and time-shifted data from the LIGO S5 science run and find that it removes a significant fraction of glitches while keeping the vast majority (99.6%) of the data. We show that this cleaned data can be used to observe GW signals at a significantly lower amplitude than can otherwise be achieved. 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 GW transients.
AB - We present an algorithm for the identification of transient noise artifacts (glitches) in cross-correlation searches for long gravitational-wave (GW) transients lasting seconds to weeks. The algorithm utilizes the auto-power in each detector as a discriminator between well-behaved stationary noise (possibly including a GW signal) and non-stationary noise transients. We test the algorithm with both Monte Carlo noise and time-shifted data from the LIGO S5 science run and find that it removes a significant fraction of glitches while keeping the vast majority (99.6%) of the data. We show that this cleaned data can be used to observe GW signals at a significantly lower amplitude than can otherwise be achieved. 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 GW transients.
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U2 - 10.1088/0264-9381/29/9/095018
DO - 10.1088/0264-9381/29/9/095018
M3 - Article
AN - SCOPUS:84860163250
SN - 0264-9381
VL - 29
JO - Classical and Quantum Gravity
JF - Classical and Quantum Gravity
IS - 9
M1 - 095018
ER -