Bayesian Inference Analysis of Unmodelled Gravitational-Wave Transients

We report the results of an in-depth analysis of the parameter estimation capabilities of BayesWave, an algorithm for the reconstruction of gravitational-wave signals without reference to a specific signal model. Using binary black hole signals, we compare BayesWave's performance to the theoretical best achievable performance in three key areas: sky localisation accuracy, signal/noise discrimination, and waveform reconstruction accuracy. BayesWave is most effective for signals that have very compact time-frequency representations. For binaries, where the signal time-frequency volume decreases with mass, we find that BayesWave's performance reaches or approaches theoretical optimal limits for system masses above approximately 50 M_sun. For such systems BayesWave is able to localise the source on the sky as well as templated Bayesian analyses that rely on a precise signal model, and it is better than timing-only triangulation in all cases. We also show that the discrimination of signals against glitches and noise closely follow analytical predictions, and that only a small fraction of signals are discarded as glitches at a false alarm rate of 1/100 y. Finally, the match between BayesWave- reconstructed signals and injected signals is broadly consistent with first-principles estimates of the maximum possible accuracy, peaking at about 0.95 for high mass systems and decreasing for lower-mass systems. These results demonstrate the potential of unmodelled signal reconstruction techniques for gravitational-wave astronomy.Comment: 10 pages, 7 figure

Detection, reconstruction and interpretation of unmodelled gravitational-wave transients

In this thesis we aim to answer a number of key questions related to unmodelled gravitational-wave (GW) transients, namely: (1) how can we detect an unmodelled GW transient (‘burst’); (2) how well can we reconstruct GW burst parameters; (3) how can we infer the structure of an unmodelled GW source based on the observed signal. Chapter 1 introduces GW astronomy: how gravitational waves are produced, what are the main categories of GW sources, and how GW detectors work. We end the chapter with a summary of the Advanced LIGO (Laser Interferometer Gravitational-wave Observatory) and Virgo observing runs. In Chapter 2 we describe the most promising sources of unmodelled GW transients such as gamma-ray bursts (GRBs), supernovae (SNe), isolated neutron stars and fast radio bursts (FRBs). We focus on the short GRB–compact binary coalescence (CBC) and long GRB–supernova progenitor models. In the following chapter (Ch. 3) we present X-Pipeline, a coherent search pipeline for GW bursts. We define a theoretical framework necessary to perform a coherent analysis with X-Pipeline, and describe how X-Pipeline can be used for searches for GWs associated with GRBs. In the second part of the chapter we report results of such analyses for the LIGO–Virgo Observing runs 2 and 3a. Chapter 4 presents a study that answers the question no. 2, i.e. how well can we reconstruct GW burst parameters, especially the waveform h(t). We perform an injection study with BayesWave, a Bayesian parameter estimation algorithm, using binary black hole (BBH) signals in LIGO–Virgo data. We assess BayesWave performance against the first-principle estimates in three key areas: sky localisation accuracy, signal/noise discrimination, and waveform reconstruction accuracy. Finally, Chapter 5 introduces a novel technique to reconstruct a source mass density perturbation from the GW signal h(t). We start by deriving the algorithm and testing it with multiple sample sources. We describe in more detail why the algorithm is unable to reconstruct the radial evolution of a BBH merger, and provide a Bayesian framework that could solve this issue by including additional constraints. We end the chapter by discussing the method’s limitations, possible solutions and future development work

Antiglitch: a Quasi-physical Model for Removing Short Glitches from LIGO and Virgo Data

Gravitational-wave observatories become more sensitive with each observing run, increasing the number of detected gravitational-wave signals. A limiting factor in identifying these signals is the presence of transient non-Gaussian noise, which generates glitches that can mimic gravitational wave signals. Our work provides a quasi-physical model waveform for the four most common types of short transient glitches, which are particularly problematic in the search for high-mass black hole binaries. Our model has only a few, physically interpretable parameters: central frequency, bandwidth, phase, amplitude and time. We demonstrate the accuracy of this model by fitting and removing a large sample of glitches from a month of LIGO and Virgo data from the O3 observing run. We can effectively remove three of the four types of short transients. We finally map the ability of these glitches to mimic binary black hole signals.Comment: 13 pages, 14 Figures, Submitted to Phys.Rev.

Revisiting the evidence for precession in GW200129 with machine learning noise mitigation

GW200129 is claimed to be the first-ever observation of the spin-disk orbital precession detected with gravitational waves (GWs) from an individual binary system. However, this claim warrants a cautious evaluation because the GW event coincided with a broadband noise disturbance in LIGO Livingston caused by the 45 MHz electro-optic modulator system. In this paper, we present a state-of-the-art neural network that is able to model and mitigate the broadband noise from the LIGO Livingston interferometer. We also demonstrate that our neural network mitigates the noise better than the algorithm used by the LIGO-Virgo-KAGRA collaboration. Finally, we re-analyse GW200129 with the improved data quality and show that the evidence for precession is still observed

Search for eccentric black hole coalescences during the third observing run of LIGO and Virgo

Despite the growing number of confident binary black hole coalescences observed through gravitational waves so far, the astrophysical origin of these binaries remains uncertain. Orbital eccentricity is one of the clearest tracers of binary formation channels. Identifying binary eccentricity, however, remains challenging due to the limited availability of gravitational waveforms that include effects of eccentricity. Here, we present observational results for a waveform-independent search sensitive to eccentric black hole coalescences, covering the third observing run (O3) of the LIGO and Virgo detectors. We identified no new high-significance candidates beyond those that were already identified with searches focusing on quasi-circular binaries. We determine the sensitivity of our search to high-mass (total mass M>70 M⊙) binaries covering eccentricities up to 0.3 at 15 Hz orbital frequency, and use this to compare model predictions to search results. Assuming all detections are indeed quasi-circular, for our fiducial population model, we place an upper limit for the merger rate density of high-mass binaries with eccentricities 0<e≤0.3 at 0.33 Gpc−3 yr−1 at 90\% confidence level

Search for gravitational-lensing signatures in the full third observing run of the LIGO-Virgo network

Gravitational lensing by massive objects along the line of sight to the source causes distortions of gravitational wave-signals; such distortions may reveal information about fundamental physics, cosmology and astrophysics. In this work, we have extended the search for lensing signatures to all binary black hole events from the third observing run of the LIGO--Virgo network. We search for repeated signals from strong lensing by 1) performing targeted searches for subthreshold signals, 2) calculating the degree of overlap amongst the intrinsic parameters and sky location of pairs of signals, 3) comparing the similarities of the spectrograms amongst pairs of signals, and 4) performing dual-signal Bayesian analysis that takes into account selection effects and astrophysical knowledge. We also search for distortions to the gravitational waveform caused by 1) frequency-independent phase shifts in strongly lensed images, and 2) frequency-dependent modulation of the amplitude and phase due to point masses. None of these searches yields significant evidence for lensing. Finally, we use the non-detection of gravitational-wave lensing to constrain the lensing rate based on the latest merger-rate estimates and the fraction of dark matter composed of compact objects

Ultralight vector dark matter search using data from the KAGRA O3GK run

Among the various candidates for dark matter (DM), ultralight vector DM can be probed by laser interferometric gravitational wave detectors through the measurement of oscillating length changes in the arm cavities. In this context, KAGRA has a unique feature due to differing compositions of its mirrors, enhancing the signal of vector DM in the length change in the auxiliary channels. Here we present the result of a search for U(1)B−L gauge boson DM using the KAGRA data from auxiliary length channels during the first joint observation run together with GEO600. By applying our search pipeline, which takes into account the stochastic nature of ultralight DM, upper bounds on the coupling strength between the U(1)B−L gauge boson and ordinary matter are obtained for a range of DM masses. While our constraints are less stringent than those derived from previous experiments, this study demonstrates the applicability of our method to the lower-mass vector DM search, which is made difficult in this measurement by the short observation time compared to the auto-correlation time scale of DM