Searching for Gravitational Waves from Compact Binary Coalescences and Stochastic Backgrounds in the LIGO–Virgo Detector Network

Author: Xiao, Liting

Year: 2023

Degree: Dissertation (Ph.D.)

Advisor: Weinstein, Alan Jay

Committee Members: Chen, Yanbei; Weinstein, Alan Jay; Reitze, David H.; Bouman, Katherine L.

Option: Physics

DOI: 10.7907/zgtx-0582

Abstract

Gravitational waves (GWs) are ripples in spacetime generated by accelerating masses, carrying away information about the underlying processes. There are four main astrophysical sources detectable in the sensitive band of the LIGO–VIRGO–KAGRA (LVK) GW detector network: compact binary coalescences, burst sources, continuous waves and stochastic gravitational-wave backgrounds. This thesis focuses on the detection methods of two of these categories, coalescing compact binaries and stochastic backgrounds, and their search results across LIGO–Virgo’s first three observing runs spanning from 2015 to 2020.

Compact binary coalescences of black holes and/or neutron stars are the only type of GW sources detected so far in the LVK frequency band. Such binary systems lose orbital energy via GW emission and are compact enough to merge within the age of the Universe. PyCBC is a matched-filter, all-sky pipeline for GW signals from compact binary mergers using a bank of modeled gravitational waveform templates. We describe the methods employed in PyCBC and present the developmental updates both in its archival and low-latency configurations for LIGO–Virgo’s third observing run. Using PyCBC to analyze the data from LIGO–Virgo’s first three observing runs, we summarize our results of the searches in gravitational-wave transient catalogs and characterize some exceptional events.

A stochastic gravitational-wave background consists of a large number of weak, independent and uncorrelated events of astrophysical or cosmological origin. The GW power on the sky is assumed to contain anisotropies on top of an isotropic component, i.e., the angular monopole. Complementary to the LVK searches, we develop an efficient analysis pipeline to compute the maximum-likelihood anisotropic sky maps in stochastic backgrounds directly in the sky pixel domain using data folded over one sidereal day. We invert the full pixel-pixel correlation matrix in map-making of the GW sky, up to an optimal eigenmode cutoff decided systematically using simulations. In addition to modeled mapping, we implement a model-independent method to probe spectral shapes of stochastic backgrounds. Using data from LIGO–Virgo's first three observing runs, we obtain upper limits on anisotropies as well as the isotropic monopole as a limiting case, consistent with the LVK results. We also set constraints on the spectral shape of the stochastic background using this novel model-independent method.

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