Theses and Dissertations

Date of Award

5-2024

Document Type

Thesis

Degree Name

Master of Science (MS)

Department

Physics

First Advisor

Soumya D. Mohanty

Second Advisor

Soma Mukherjee

Third Advisor

Joseph Romano

Abstract

Strain data from ground-based gravitational wave detectors are regularly affected by instrumental artifacts known as glitches. Such glitches form the background of false alarms in the detection of gravitational waves from compact binary coalescences, in-turn reducing search sensitivity. If left unaccounted, these glitches along with other non-stationarity may also contribute towards a corrupted representation of the statistical properties of detector noise, subsequently affecting parameter estimation for detected gravitational wave candidates. Therefore, effective data analysis methods to veto glitches and identify non-stationarities in detector data are crucial to enhancing the sensitivity of a gravitational wave search. In this thesis, we present a novel veto method for glitches that affect matched filter searches for binary in spiral mergers and a new approach to non-parametric change point detection to detect non-stationarities using data spectrograms. We quantify the receiver-operating characteristics of the change-point detector algorithm and observe that it can detect weak and strong non-stationarities over a wide range of time scales spanning O(10) milliseconds to O(100) seconds. The veto scheme that we present uses unphysical sectors in the space of chirp time parameters as well as an extension including negative chirp times to efficiently segregate glitches from gravitational wave signals in single-detector data. The matched filter search over these different regions is facilitated without much additional computational burden via Particle Swarm Optimization. We test this veto on data taken from both LIGO detectors spanning multiple observation runs. We find that the veto is able to reject 99.9% of glitches without any loss of injected signals detected with a signal-to-noise ratio ≥ 9.0 and total mass ≤ 80 M⊙. Our results show that extending a matched filter search to unphysical parts of a signal parameter space promises to be an effective strategy for mitigating glitches.

Comments

Copyright 2024 Raghav Prafulla Girgaonkar.

https://go.openathens.net/redirector/utrgv.edu?url=https://www.proquest.com/pqdtglobal1/dissertations-theses/mitigation-methods-instrumental-artifacts/docview/3085275736/sem-2?accountid=7119

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