Reducing scattered light in LIGO's third observing run
S. Soni, Louisiana State University
C. Austin, Louisiana State University
A. Effler, LIGO Livingston
R. M.S. Schofield, University of Oregon
G. González, Louisiana State University
V. V. Frolov, LIGO Livingston
J. C. Driggers, LIGO Hanford
A. Pele, LIGO Livingston
A. L. Urban, Louisiana State University
G. Valdes, Louisiana State University
R. Abbott, California Institute of Technology
C. Adams, LIGO Livingston
R. X. Adhikari, California Institute of Technology
A. Ananyeva, California Institute of Technology
S. Appert, California Institute of Technology
K. Arai, California Institute of Technology
J. S. Areeda, California State University, Fullerton
Y. Asali, Columbia University
S. M. Aston, LIGO Livingston
A. M. Baer, Christopher Newport University
M. Ball, University of Oregon
S. W. Ballmer, Syracuse University
S. Banagiri, University of Minnesota Twin Cities
D. Barker, LIGO Hanford
L. Barsotti, LIGO, Massachusetts Institute of Technology
J. Bartlett, LIGO Hanford
B. K. Berger, Stanford University
J. Betzwieser, LIGO Livingston
D. Bhattacharjee, Missouri University of Science and Technology
G. Billingsley, California Institute of Technology
S. Biscans, California Institute of Technology
C. D. Blair, LIGO Livingston
R. M. Blair, LIGO Hanford
Abstract
Noise due to scattered light has been a frequent disturbance in the advanced LIGO gravitational wave detectors, hindering the detection of gravitational waves. The non stationary scatter noise caused by low frequency motion can be recognized as arches in the time-frequency plane of the gravitational wave channel. In this paper, we characterize the scattering noise for LIGO and Virgo's third observing run O3 from April, 2019 to March, 2020. We find at least two different populations of scattering noise and we investigate the multiple origins of one of them as well as its mitigation. We find that relative motion between two specific surfaces is strongly correlated with the presence of scattered light and we implement a technique to reduce this motion. We also present an algorithm using a witness channel to identify the times this noise can be present in the detector.
