Gravitational Wave Data Research Articles

Searching for Asymmetric and Heavily Precessing Binary Black Holes in the Gravitational Wave Data from the LIGO Third Observing Run

Searching for Asymmetric and Heavily Precessing Binary Black Holes in the Gravitational Wave Data from the LIGO Third Observing Run

Joint Observations of Late Universe Probes: Cosmological Parameter Constraints from Gravitational Wave and Type Ia Supernova Data

The growing tensions between the early Universe and the late Universe increasingly highlight the importance of developing precise probes for late cosmology. As significant late-Universe probes, Type Ia supernovae (SNe Ia) and gravitational waves (GWs) can provide measurements of relative and absolute distances, respectively. Their complementary nature is likely to break the degeneracies among cosmological parameters, thereby yielding more precise constraints. In this study, we use 43 gravitational-wave sources from the Third LIGO–Virgo–KAGRA Gravitational-Wave Transient Catalog (GWTC-3) and 1590 light curves from Pantheon+ compilation to constrain the dark energy models, as an attempt to achieve precise late-Universe cosmological constraints. For the dark siren GW event, we estimate the corresponding redshift using the binary black hole redshift distribution model. The combination of GW and SNe Ia data could provide the precision on the Hubble constant H 0 and the present matter density Ω m of approximately 16% and 8% for the ΛCDM model. If we consider the equation of state of dark energy w, the combination sample constrains the precision of w to approximately 24%. Although the combination of GWs and SNe Ia observations effectively breaks degeneracies among various cosmological parameters, yielding more stringent constraints, the precision of these constraints still does not meet the stringent standards required by precision cosmology. However, it is reasonable to anticipate that, in the near future, the joint observations of GWs and SNe Ia will become a powerful tool, particularly in the late Universe, for the precise measurement of cosmological parameters.

Ringing Out General Relativity: Quasinormal Mode Frequencies for Black Holes of Any Spin in Modified Gravity.

After black holes collide, the remnant settles to a stationary state by emitting gravitational waves. Once nonlinearities subside, these ringdown waves are dominated by exponentially damped sinusoids, or quasinormal modes. We develop a general method using perturbative spectral expansions to calculate the quasinormal-mode frequencies and damping times in a wide class of modified gravity theories for black holes with any subextremal spin. We apply this method to scalar-Gauss-Bonnet gravity to show its accuracy, thus enabling robust ringdown tests with gravitational wave data.

Detection prospects of gravitational waves from SU(2) axion inflation

We study detection prospects of a gravitational-wave background (GWB) sourced by SU(2) gauge fields considering all possible observational constraints. More precisely, we consider bounds set by cosmic microwave background measurements, primordial black hole overproduction, as well as backreaction of the gauge fields on the background evolution. Gravitational-waves data from the first three observing runs of the LIGO-Virgo-KAGRA Collaboration show no evidence for a GWB contribution from axion inflation. However, we are able to place conservative constraints on the parameters of the SU(2) inflation with current data. We investigate conditions on the inflationary potential that would lead to a detectable signal that evades astrophysical and cosmological constraints and discuss detection prospects for third generation networks. Published by the American Physical Society 2024

Maximum entropy spectral analysis: an application to gravitational waves data analysis

The maximum entropy spectral analysis (MESA) method, developed by Burg, offers a powerful tool for spectral estimation of a time-series. It relies on Jaynes’ maximum entropy principle, allowing the spectrum of a stochastic process to be inferred using the coefficients of an autoregressive process AR(p) of order p. A closed-form recursive solution provides estimates for both the autoregressive coefficients and the order p of the process. We provide a ready-to-use implementation of this algorithm in a Python package called memspectrum, characterized through power spectral density (PSD) analysis on synthetic data with known PSD and comparisons of different criteria for stopping the recursion. Additionally, we compare the performance of our implementation with the ubiquitous Welch algorithm, using synthetic data generated from the GW150914 strain spectrum released by the LIGO-Virgo-Kagra collaboration. Our findings indicate that Burg’s method provides PSD estimates with systematically lower variance and bias. This is particularly manifest in the case of a small (O(5000)) number of data points, making Burg’s method most suitable to work in this regime. Since this is close to the typical length of analysed gravitational waves data, improving the estimate of the PSD in this regime leads to more reliable posterior profiles for the system under study. We conclude our investigation by utilising MESA, and its particularly easy parametrisation where the only free parameter is the order p of the AR process, to marginalise over the interferometers noise PSD in conjunction with inferring the parameters of GW150914

Observable signatures of no-scale supergravity in NANOGrav

In light of NANOGrav data, we provide for the first time possible observational signatures of Superstring theory. First, we work with inflection-point inflationary potentials naturally realized within Wess–Zumino-type no-scale Supergravity, which give rise to the formation of microscopic primordial black holes (PBHs) triggering an early matter-dominated era (eMD) and evaporating before big bang nucleosynthesis (BBN). Remarkably, we obtain an abundant production of primordial gravitational waves (PGW) at the frequency ranges of nHz, Hz and kHz and in strong agreement with pulsar time array (PTA) gravitational wave (GW) data. This PGW background could serve as a compelling observational signature for the presence of quantum gravity via no-scale Supergravity.

Inferring Binary Properties from Gravitational-Wave Signals

This review provides a conceptual and technical survey of methods for parameter estimation of gravitational-wave signals in ground-based interferometers such as Laser Interferometer Gravitational-Wave Observatory (LIGO) and Virgo. We introduce the framework of Bayesian inference and provide an overview of models for the generation and detection of gravitational waves from compact binary mergers, focusing on the essential features that are observable in the signals. Within the traditional likelihood-based paradigm, we describe various approaches for enhancing the efficiency and robustness of parameter inference. This includes techniques for accelerating likelihood evaluations, such as heterodyne/relative binning, reduced-order quadrature, multibanding, and interpolation. We also cover methods to simplify the analysis to improve convergence, via reparameterization, importance sampling, and marginalization. We end with a discussion of recent developments in the application of likelihood-free (simulation-based) inference methods to gravitational-wave data analysis.

Navigating Unknowns: Deep Learning Robustness for Gravitational-wave Signal Reconstruction

We present a rapid and reliable deep-learning-based method for gravitational-wave (GW) signal reconstruction from elusive, generic binary black hole mergers in LIGO data. We demonstrate that our model, AWaRe, effectively recovers GWs with parameters it has not encountered during training. This includes features like higher black hole masses, additional harmonics, eccentricity, and varied waveform systematics, which introduce complex modulations in the waveform’s amplitudes and phases. The accurate reconstructions of these unseen signal characteristics demonstrate AWaRe's ability to handle complex features in the waveforms. By directly incorporating waveform reconstruction uncertainty estimation into the AWaRe framework, we show that for real GW events, the uncertainties in AWaRe's reconstructions align closely with those achieved by benchmark algorithms like BayesWave and coherent WaveBurst. The robustness of our model to real GW events and its ability to extrapolate to unseen data open new avenues for investigations in various aspects of GW astrophysics and data analysis, including tests of general relativity and the enhancement of current GW search methodologies.

Gravitational-Wave Data Analysis with High-Precision Numerical Relativity Simulations of Boson Star Mergers.

Gravitational-wave signals detected to date are commonly interpreted under the paradigm that they originate from pairs of black holes or neutron stars. Here, we explore the alternative scenario of boson-star signals being present in the data stream. We perform accurate and long (∼20 orbits) numerical simulations of boson-star binaries and inject the resulting strain into LIGO noise. Our Bayesian inference reveals that some boson-star signals are degenerate with current approximants, albeit with biased parameters, while others exhibit smoking-gun signatures leaving behind conspicuous residuals.

Identifying noise transients in gravitational-wave data arising from nonlinear couplings

Abstract Noise in various interferometer systems can sometimes couple non-linearly to create excess noise in the gravitational wave (GW) strain data. Third-order statistics, such as bicoherence and biphase, can identify these couplings and help discriminate those occurrences from astrophysical GW signals. However, the conventional analysis can yield large bicoherence values even when no phase-coupling is present, thereby, resulting in false identifications. Introducing artificial phase randomization in computing the bicoherence reduces such occurrences with negligible impact on its effectiveness for detecting true phase-coupled disturbances. We demonstrate this property with simulated disturbances – focusing only on short-duration ones (lasting up to a few seconds) in this work. Statistical hypothesis testing is used for distinguishing phase-coupled disturbances from non-phase coupled ones when employing the phase-randomized bicoherence. We also obtain an expression for the bicoherence value that minimizes the sum of the probabilities of false positives and false negatives. This can be chosen as a threshold for shortlisting bicoherence triggers for further scrutiny for the presence of non-linear coupling. Finally, the utility of the phase-randomized bicoherence analysis in GW time-series data is demonstrated for the following three scenarios: (1) Finding third-order statistical similarities within categories of noise transients, such as blips and koi fish. If these non-Gaussian noise transients, or glitches, have a common source, their bicoherence maps can have similarities arising from common bifrequencies related to that source. (2) Differentiating linear or non-linear phase-coupled glitches from compact binary coalescence signals through their bicoherence maps. This is explained with a simulated signal. (3) Identifying repeated bifrequencies in the second and third observation runs (i.e., O2 and O3) of LIGO and Virgo.

Demonstration of machine learning-assisted low-latency noise regression in gravitational wave detectors

Abstract Low-latency noise regression algorithms are crucial for maximizing the science outcomes of the LIGO, Virgo, and KAGRA gravitational-wave detectors. This includes improvements in the detectability, source localization and pre-merger detectability of signals thereby enabling rapid multi-messenger follow-up. In this paper, we demonstrate the effectiveness of DeepClean, a convolutional neural network architecture that uses witness sensors to estimate and subtract non-linear and non-stationary noise from gravitational-wave strain data. Our study uses LIGO data from the third observing run with injected compact binary signals. As a demonstration, we use DeepClean to subtract the noise at 60 Hz due to the power mains and their sidebands arising from non-linear coupling with other instrumental noise sources. Our parameter estimation study on the injected signals shows that DeepClean does not do any harm to the underlying astrophysical signals in the data while it can enhance the signal-to-noise ratio of potential signals. We show that DeepClean can be used for low-latency noise regression to produce cleaned output data at latencies ~1–2 s. We also discuss various considerations that may be made while training DeepClean for low latency applications.

Differentiable and hardware-accelerated waveforms for gravitational wave data analysis

We propose the use of automatic differentiation through the programming framework for accelerating a variety of analysis tasks throughout gravitational wave (GW) science. Firstly, we demonstrate that complete waveforms which cover the inspiral, merger, and ringdown of binary black holes (i.e., IMRPhenomD) can be written in and demonstrate that the serial evaluation speed of the waveform (and its derivative) is similar to the implementation in . Moreover, allows for graphics processing unit–accelerated waveform calls which can be over an order of magnitude faster than serial evaluation on a CPU. We then focus on three applications where efficient and differentiable waveforms are essential. Firstly, we demonstrate how gradient descent can be used to optimize the ∼200 coefficients that are used to calibrate the waveform model. In particular, we demonstrate that the typical with numerical relativity waveforms can be improved by more than 50%. Secondly, we show that Fisher forecasting calculations can be sped up by ∼3–5× (on a CPU) with no loss in accuracy. This increased speed makes Fisher forecasting for a population of events substantially simpler. Finally, we show that gradient-based samplers like Hamiltonian Monte Carlo lead to significantly reduced autocorrelation values when compared to traditional Monte Carlo methods. Since differentiable waveforms have substantial advantages for a variety of tasks throughout GW science, we propose that waveform developers use to build new waveforms moving forward. Our waveform code, , can be found on GitHub website and will continue to be updated with new waveforms as they are implemented. Published by the American Physical Society 2024

Dissipative tidal effects to next-to-leading order and constraints on the dissipative tidal deformability using gravitational wave data

Dissipative tidal effects to next-to-leading order and constraints on the dissipative tidal deformability using gravitational wave data

GW230529_181500: a potential primordial binary black hole merger in the mass gap

During the fourth observing run of the LIGO-Virgo-KAGRA detector network, the LIGO Livingston observatory detected a coalescing compact binary, GW230529_181500, with component masses of 2.5–4.5 M ⊙ and 1.2–2.0 M ⊙ at the 90% credible level. The gravitational-wave data alone is insufficient to determine whether the components are neutron stars or black holes. In this paper, we propose that GW230529_181500 originated from the merger of two primordial black holes (PBHs). We estimate a merger rate of 5.0+47.0 -4.9 Gpc-3 yr-1 for compact binary coalescences with properties similar to GW230529_181500. Assuming the source is a PBH-PBH merger, GW230529_181500-like events lead to approximately 1.7+36.2 -1.5 × 10-3 of the dark matter in the form of PBHs. The required abundance of PBHs to explain this event is consistent with existing upper limits derived from microlensing, cosmic microwave background observations and the null detection of gravitational-wave background by LIGO-Virgo-KAGRA.

Observation of Gravitational Waves from the Coalescence of a 2.5–4.5 M ⊙ Compact Object and a Neutron Star

We report the observation of a coalescing compact binary with component masses 2.5–4.5 M ⊙ and 1.2–2.0 M ⊙ (all measurements quoted at the 90% credible level). The gravitational-wave signal GW230529_181500 was observed during the fourth observing run of the LIGO–Virgo–KAGRA detector network on 2023 May 29 by the LIGO Livingston observatory. The primary component of the source has a mass less than 5 M ⊙ at 99% credibility. We cannot definitively determine from gravitational-wave data alone whether either component of the source is a neutron star or a black hole. However, given existing estimates of the maximum neutron star mass, we find the most probable interpretation of the source to be the coalescence of a neutron star with a black hole that has a mass between the most massive neutron stars and the least massive black holes observed in the Galaxy. We provisionally estimate a merger rate density of 55−47+127Gpc−3yr−1 for compact binary coalescences with properties similar to the source of GW230529_181500; assuming that the source is a neutron star–black hole merger, GW230529_181500-like sources may make up the majority of neutron star–black hole coalescences. The discovery of this system implies an increase in the expected rate of neutron star–black hole mergers with electromagnetic counterparts and provides further evidence for compact objects existing within the purported lower mass gap.

What no one has seen before: gravitational waveforms from warp drive collapse

Despite originating in science fiction, warp drives have a concrete description in general relativity, with Alcubierre first proposing a spacetime metric that supported faster-than-light travel. Whilst there are numerous practical barriers to their implementation in real life, including a requirement for negative energy, computationally, one can simulate their evolution in time given an equation of state describing the matter. In this work, we study the signatures arising from a warp drive “containment failure”, assuming a stiff equation of state for the fluid. We compute the emitted gravitational-wave signal and track the energy fluxes of the fluid. Apart from its rather speculative application to the search for extraterrestrial life in gravitational-wave detector data, this work is interesting as a study of the dynamical evolution and stability of spacetimes that violate the null energy condition. Our work highlights the importance of exploring strange new spacetimes, to (boldly) simulate what no one has seen before.

Constraining gravitational wave velocities using gravitational and electromagnetic wave observations of white dwarf binaries

ABSTRACT Although the general theory of relativity (GR) predicts that gravitational waves (GWs) have exactly the same propagation velocity as electromagnetic (EM) waves, many theories of gravity beyond GR expect otherwise. Accurate measurement of the difference in their propagation speed, or a tight constraint on it, could be crucial to validate or put limits on theories beyond GR. The proposed future space-borne GW detectors are poised to detect a substantial number of Galactic white dwarf binaries (GWDBs), which emit the GW as semimonochromatic signals. Concurrently, these GWDBs can also be identified as optical variable sources. Here we proposed that allocating a GWDB’s optical light curve and contemporaneous GW signal can be used to trace the difference between the velocity of GW and EM waves. Simulating GW and EM wave data from 14 verification binaries (VBs), our method constrains propagation-originated phase differences, limiting the discrepancy between the speed of light (c) and GW ($c_{GW}$). Through the utilization of LISA’s design sensitivity and the current precision in optical observation on GWDB, our study reveals that a four-year observation of the 14 recognized VBs results in a joint constraint that confines $\Delta c/c$ ($\Delta c = c_{\mathrm{GW}} - c$) to the range of $-2.1\times 10^{-12}$ and $4.8\times 10^{-12}$. Additionally, by incorporating this constraint on $c_{\mathrm{GW}}$, we are able to establish boundaries for the mass of the graviton, limiting it to $m_{\mathrm{g}}\le 3\times 10^{-23}\, e\mathrm{V}\,c^{-2}$, and for the parameter associated with local Lorentz violation, $\bar{s}_{00}$, constrained within the range of $-3.4\times 10^{-11}\le \bar{s}_{00}\le 1.5\times 10^{-11}$.

A comprehensive forecast for cosmological parameter estimation using joint observations of gravitational waves and short γ\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\gamma $$\\end{document}-ray bursts

In the third-generation (3G) gravitational-wave (GW) detector era, multi-messenger GW observation for binary neutron star (BNS) merger events can exert great impacts on exploring cosmic expansion history. In this work, we comprehensively explore the potential of 3G GW standard siren observations in cosmological parameter estimations by considering 3G GW detectors and the future short γ\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\gamma $$\\end{document}-ray burst (GRB) detector THESEUS-like telescope joint observations. Based on a 10-year observation of different detection strategies, we predict that the numbers of detectable GW-GRB events are 334–674 with the redshifts z<3.5\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$z<3.5$$\\end{document} and the inclination angles ι<15∘\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\iota <15^{\\circ }$$\\end{document}. For the cosmological analysis, we consider the Λ\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\Lambda $$\\end{document}CDM, wCDM, w0wa\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$w_0w_a$$\\end{document}CDM, and interacting dark energy (IDE) models. We find that GW can tightly constrain the Hubble constant with precision of 0.345–0.065%, but does not perform well in constraining other cosmological parameters. Fortunately, GW detection could effectively break the cosmological parameter degeneracies generated by the mainstream EM observations, CMB + BAO + SN (CBS). When combining mock GW data with CBS data, CBS + GW can tightly constrain the equation of state of dark energy w with a precision of 1.26%, close to the standard of precision cosmology. Meanwhile, the addition of GW to CBS could improve constraints on cosmological parameters by 34.2–94.9%. In conclusion, GW standard siren observations from 3G GW detectors could play a crucial role in helping solve the Hubble tension and probe the fundamental nature of dark energy.

Automated evaluation of environmental coupling for Advanced LIGO gravitational wave detections

The extreme sensitivity required for direct observation of gravitational waves by the Advanced LIGO detectors means that environmental noise is increasingly likely to contaminate Advanced LIGO gravitational wave signals if left unaddressed. Consequently, environmental monitoring efforts have been undertaken and novel noise mitigation techniques have been developed which have reduced environmental coupling and made it possible to analyze environmental artifacts with potential to affect the 90 gravitational wave events detected from 2015–2020 by the Advanced LIGO detectors. So far, there is no evidence for environmental contamination in gravitational wave detections. However, automated, rapid ways to monitor and assess the degree of environmental coupling between gravitational wave detectors and their surroundings are needed as the rate of detections continues to increase. We introduce a computational tool, PEMcheck, for quantifying the degree of environmental coupling present in gravitational wave signals using data from the extant collection of environmental monitoring sensors at each detector. We study its performance when applied to 79 gravitational waves detected in LIGO’s third observing run and test its performance in the case of extreme environmental contamination of gravitational wave data. We find that PEMcheck’s automated analysis identifies only a small number of gravitational waves that merit further study by environmental noise experts due to possible contamination, a substantial improvement over the manual vetting that occurred for every gravitational wave candidate in the first two observing runs. Building on a first attempt at automating environmental coupling assessments used in the third observing run, this tool represents an improvement in accuracy and interpretability of coupling assessments, reducing the time needed to validate gravitational wave candidates. With the validation provided herein; PEMcheck will play a critical role in event validation during LIGO’s fourth observing run as an integral part of the data quality report produced for each gravitational wave candidate.

Challenges in space-based gravitational wave data analysis and applications of artificial intelligence

Challenges in space-based gravitational wave data analysis and applications of artificial intelligence