Parameter estimation with gravitational waves

Abstract

The new era of gravitational wave astronomy truly began on September 14, 2015 with the detection of GW150914, the sensational first direct observation of gravitational waves from the inspiral and merger of two black holes by the two Advanced LIGO detectors. In the subsequent first three observing runs of the LIGO/Virgo network, gravitational waves from $\sim 50$ compact binary mergers have been announced, with more results to come. The events have mostly been produced by binary black holes, but two binary neutron star mergers have so far been observed, as well as the mergers of two neutron star - black hole systems. Furthermore, gravitational waves emitted by core-collapse supernovae, pulsars and the stochastic gravitational wave background are within the LIGO/Virgo/KAGRA sensitivity band and are likely to be observed in future observation runs. Beyond signal detection, a major challenge has been the development of statistical and computational methodology for estimating the physical waveform parameters and quantifying their uncertainties in order to accurately characterise the emitting system. These methods depend on the sources of the gravitational waves and the gravitational waveform model that is used. This article reviews the main waveform models and parameter estimation methods used to extract physical parameters from gravitational wave signals detected to date by LIGO and Virgo and from those expected to be observed in the future, which will include KAGRA, and how these methods interface with various aspects of LIGO/Virgo/KAGRA science. Also presented are the statistical methods used by LIGO and Virgo to estimate detector noise, test general relativity, and draw conclusions about the rates of compact binary mergers in the universe. Furthermore, a summary of major publicly available gravitational wave parameter estimation software packages is given.

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• Astrophysics with core-collapse supernova gravitational wave signals in the next generation of gravitational wave detectors
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• Identifying and Addressing Nonstationary LISA Noise
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• Reconstructing gravitational wave signals from binary black hole mergers with minimal assumptions
• Inferring the core-collapse supernova explosion mechanism with three-dimensional gravitational-wave simulations
• Constraint on the Yukawa suppression of the Newtonian potential from the planetary ephemeris INPOP19a
• Localization of transient gravitational wave sources: beyond triangulation
• Globally coherent short duration magnetic field transients and their effect on ground based gravitational-wave detectors
• Regression methods in waveform modeling: a comparative study
• The effects of LIGO detector noise on a 15-dimensional Markov-chain Monte-Carlo analysis of gravitational-wave signals
• Rapid and Robust Parameter Inference for Binary Mergers
• Classifying the Equation of State from Rotating Core Collapse Gravitational Waves with Deep Learning
• Fortifying the characterization of binary mergers in LIGO data
• Bayesian semiparametric power spectral density estimation with applications in gravitational wave data analysis
• Exploring Multi-Modal Distributions with Nested Sampling
• Detecting very long-lived gravitational-wave transients lasting hours to weeks
• LISA source confusion: identification and characterization of signals
• Coherent Bayesian analysis of inspiral signals
• Bekenstein-Hod Universal Bound on Information Emission Rate Is Obeyed by LIGO-Virgo Binary Black Hole Remnants
• Bayesian parameter estimation of core collapse supernovae using gravitational wave simulations
• First Tests of a Newtonian Calibrator on an Interferometric Gravitational Wave Detector
• Searching for General Binary Inspirals with Gravitational Waves
• Nested Sampling with Constrained Hamiltonian Monte Carlo
• Component Separation of a Isotropic Gravitational Wave Background
• Multivariate Regression Analysis of Gravitational Waves from Rotating Core Collapse
• Search for a Radio Pulsar in the Remnant of Supernova 1987A
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• Stochastic gravitational wave background: methods and Implications
• Exploring the Impact of Microlensing on Gravitational Wave Signals: Biases, Population Characteristics, and Prospects for Detection
• VARAHA: A Fast Non-Markovian sampler for estimating Gravitational-Wave posteriors
• Gaussian Processes for Glitch-robust Gravitational-wave Astronomy
• Rapid determination of LISA sensitivity to extreme mass ratio inspirals with machine learning
• Exploring Supernova Gravitational Waves with Machine Learning
• Parameter Estimation of Gravitational Waves with a Quantum Metropolis Algorithm
• Heavy-tailed likelihoods for robustness against data outliers: Applications to the analysis of gravitational wave data
• Validating Prior-informed Fisher-matrix Analyses against GWTC Data
• Formalism for power spectral density estimation for non-identical and correlated noise using the null channel in Einstein Telescope
• Neural network time-series classifiers for gravitational-wave searches in single-detector periods
• Scalable data-analysis framework for long-duration gravitational waves from compact binaries using short Fourier transforms
• Parameter estimation of microlensed gravitational waves with Conditional Variational Autoencoders
• Follow-up analyses of the binary-neutron-star signals GW170817 and GW190425 by using post-Newtonian waveform models
• Gravitational Wave Measurement in the Mid-Band with Atom Interferometers
• Inferring the Astrophysical Population of Gravitational Wave Sources in the Presence of Noise Transients
• EMRI_MC: A GPU-based Python code for Bayesian inference of EMRI waveforms
• Inferring Binary Properties from Gravitational Wave Signals
• Likelihood for a Network of Gravitational-Wave Detectors with Correlated Noise
• Validating Sequential Monte Carlo for Gravitational-Wave Inference
• Dealing with data gaps for TianQin with massive black hole binary signal
• Next-generation global gravitational-wave detector network: Impact of detector orientation on compact binary coalescence and stochastic gravitational-wave background searches
• Impact of Bayesian Priors on the Inferred Masses of Quasi-Circular Intermediate-Mass Black Hole Binaries
• Fast and accurate parameter estimation of high-redshift sources with the Einstein Telescope
• Gravitational lensing aided luminosity distance estimation for compact binary coalescences
• Quantum Bayesian Inference with Renormalization for Gravitational Waves
• Spirals, vortices, and helicity entanglements in dynamical Sauter-Schwinger pair creation
• Calibrating approximate Bayesian credible intervals of gravitational-wave parameters
• Is GW190521 a gravitational wave echo of wormhole remnant from another universe?
• A potential third-generation gravitational-wave detector based on autocorrelative weak-value amplification
• Application of Non-Linear Noise Regression in the Virgo Detector
• Gravitational wave energy spectral density properties from BPASS Galactic binary population in the Milky Way galaxy
• Accelerating gravitational-wave parameterized tests of General Relativity using a multiband decomposition of likelihood
• Collapsar Disk Outflows III: Detectable Neutrino and Gravitational Wave Signatures
• Comparing next-generation detector configurations for high-redshift gravitational wave sources with neural posterior estimation
• Estimating quantum Markov chains using coherent absorber post-processing and pattern counting estimator
• Extending the micro-Hertz detection horizons via orbital resonance effect for geocentric gravitational wave antennas
• Quantum Search for Gravitational Wave of Massive Black Hole Binaries
• Detection of Earth's free oscillations utilizing TianQin
• Assessment of normalizing flows for parameter estimation on time-frequency representations of gravitational-wave data
• Fast Waveform Generation for Gravitational Waves using Evolutionary Algorithms
• The Sequential Monte Carlo goes NUTS: Boosting Gravitational-Wave Inference