Computer Science – Performance
Scientific paper
Oct 2009
adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2009cqgra..26t4021s&link_type=abstract
Classical and Quantum Gravity, Volume 26, Issue 20, pp. 204021 (2009).
Computer Science
Performance
1
Scientific paper
NoiseFloorMon is a data monitoring tool (DMT) implemented at the LIGO sites to monitor instances of non-stationarity in the gravitational-wave data that are correlated with physical environmental monitors. An analysis of the fifth science run is nearly complete, and test runs preceding the sixth science run have also been analyzed. These analyses have identified time intervals in the gravitational-wave channel that indicate non-stationarity due to seismic activity, and these intervals are referred to as data quality flags. In the analyses conducted to date the majority of time segments identified as non-stationary were due to seismic activity at the corner station and the x-arm end station. We present the algorithm and its performance, and discuss the potential for an on-site pipeline that automatically generates data quality flags for use in future data runs.
Mukherjee Soma
Stone Robert
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