Physical approach to the marginalization of LIGO calibration uncertainties
The data from ground-based gravitational-wave detectors such as Advanced LIGO and Virgo must be calibrated to convert the digital output of photodetectors into a relative displacement of the test masses in the detectors, producing the quantity of interest for inference of astrophysical gravitational-wave sources. Both statistical uncertainties and systematic errors are associated with the calibration process, which would in turn affect the analysis of detected sources, if not accounted for. Currently, source characterization algorithms either entirely neglect the possibility of calibration uncertainties or account for them in a way that does not use knowledge of the calibration process itself. We present physiCal, a new approach to account for calibration errors during the source characterization step, which directly uses all the information available about the instrument calibration process. Rather than modeling the overall detector's response function, we consider the individual components that contribute to the response. We implement this method and apply it to the compact binaries detected by LIGO and Virgo during the second observation run, as well as to simulated binary neutron stars for which the sky position and distance are known exactly. We find that the physiCal model performs as well as the method currently used within the LIGO-Virgo Collaboration, but additionally it enables improving the measurement of specific components of the instrument control through astrophysical calibration.
© 2021 American Physical Society. Received 23 September 2020; accepted 16 February 2021; published 15 March 2021. We thank Reed Essick, Paul Lasky, Ethan Payne, Colm Talbot, and Eric Thrane for useful discussion and for sharing an early version of their manuscript. We also thank the journal referees for their useful comments. S. V., C. J. H., L. S., and J. K. acknowledge support of the National Science Foundation and the LIGO Laboratory. L. S. also acknowledges the support of the Australian Research Council Centre of Excellence for Gravitational Wave Discovery (OzGrav), Project No. CE170100004. E. G. acknowledges the support of the Natural Sciences and Engineering Research Council (NSERC) of Canada. LIGO was constructed by the California Institute of Technology and Massachusetts Institute of Technology with funding from the United States National Science Foundation and operates under cooperative agreement PHY-1764464. Advanced LIGO was built under Grant No. PHY-0823459. The authors are grateful for computational resources provided by the LIGO Laboratory and supported by National Science Foundation Grants No. PHY-0757058 and No. PHY-0823459. This research has made use of data, software, and/or web tools obtained from the Gravitational Wave Open Science Center , a service of LIGO Laboratory, the LIGO Scientific Collaboration, and the Virgo Collaboration. This analysis was made possible by the lalsuite , numpy [57,58], scipy , and matplotlib  software packages. The authors thank all of the essential workers who put their health at risk during the COVID-19 pandemic, without whom we would not have been able to complete this work. This is LIGO Document No. DCC-P2000293.
Published - PhysRevD.103.063016.pdf
Accepted Version - 2009.10192.pdf