Qpipeline for gravitational wave data analysis

PI: Katerina Chatziioannou, Division of Physics, Mathematics, and Astronomy (PMA)
SASE: Howard Deshong, Scholar

Einstein's General Theory of Relativity predicts that cataclysmic events, such as supernovae or collisions of neutron stars or black holes, can produce ripples in space-time known as gravitational waves. The Laser Interferometer Gravitational-Wave Observatory (LIGO) is an experiment designed to detect these waves. LIGO operates two kilometer-scale laser interferometers in Hanford, Washington and Livingston, Louisiana. In 2015, data from these interferometers contributed to the first detection of a gravitational wave.

BayesWave is a data processing pipeline for inference of LIGO data that accounts for all its real data complexities, such as instrumental artifacts, changing noise properties, and an array of astrophysical signals. It extracts gravitational wave signals present in noisy interferometer data using Bayesian statistical techniques. The pipeline has seen wide use, and over the years physicists have updated the pipeline to handle a variety of use cases.

Gravitational wave physics is advancing, and so should BayesWave. As LIGO improves its detectors' resolution, BayesWave should provide greater throughout so physicists can rapidly analyze data. Similarly, as gravitational wave physicists develop novel data analysis techniques, BayesWave should provide flexibility so physicists can easily implement those techniques and incorporate them into the existing pipeline. To those ends, the LIGO Lab at Caltech is working with the Schmidt Academy of Software Engineering to make BayesWave more efficient and more modular.


The orange signal is GW150914, the first gravitational wave directly observed. Behind the signal in gray is the processed interferometer data from which the signal was extracted. GW150914 originated from the merging of two black holes. (Credit: N. Cornish, MSU; J. Kanner, CIT; T. Littenberg, UAH; M. Millhouse, MSU; LIGO Virgo Collaboration)