Environmentally induced nonstationarity in LIGO science run data

摘要

NoiseFloorMon is a data monitoring tool (DMT) implemented at the LIGOsites to monitor instances of non-stationarity in the gravitational-wave datathat are correlated with physical environmental monitors. An analysis of thefifth science run is nearly complete, and test runs preceding the sixth sciencerun have also been analyzed. These analyses have identified time intervalsin the gravitational-wave channel that indicate non-stationarity due to seismicactivity, and these intervals are referred to as data quality flags. In the analysesconducted to date the majority of time segments identified as non-stationarywere 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 anon-site pipeline that automatically generates data quality flags for use in futuredata runs.