Efficient Glitch Detection in Gravitational Wave Data using Particle Swarm Optimization

The direct detection of Gravitational Waves (GWs) starting in 2015 has opened a new window on the observable Universe. It has uncovered previously unseen but extremely violent phenomena such as the mergers of Black Holes and Neutron Stars, also known as Compact Binary Coalescences (CBCs). However, the distance to which such CBCs can be detected is currently limited by the large false alarm rate arising from transient interference of instrumental origin, or “glitches”, in gravitational wave data. To address this problem, we propose a novel approach enabled by Particle Swarm Optimization (PSO), a nature-inspired global optimization metaheuristic. PSO offers computational efficiency surpassing traditional grid-based matched-filtering searches, allowing the search for GW signals to be expanded to unphysical sectors of the signal parameter space. While a CBC is physically characterized by the masses of the component stars (among other parameters) the preferred parameters for defining the GW signal from a CBC are the so-called chirp time parameters obtained under a non-linear transformation of the component masses. The chirp time parameter space is larger than the mass space and separates into a physical and unphysical region. We find that searching for the signals across both the regions is a very effective strategy in separating the glitch population from the astrophysical one. We observe that the glitches tend to have unphysical estimated chirp times while the astrophysical signals do not. This novel strategy can address both strong and weak glitches unlike existing strategies that are mostly effective for the former. Our method is demonstrated on 10 hours of real GW data from the LIGO detectors using a pipeline implemented on Lonestar6. On this data, we were able to identify and veto over 98% of the glitches present in GW detector data, offering a robust and efficient solution to enhance GW search sensitivity.Texas Advanced Computing Center (TACC