Bayesian reconstruction of gravitational wave burst signals from simulations of rotating stellar core collapse and bounce
arXiv:0909.1093 · doi:10.1103/PhysRevD.80.102004
Abstract
Presented in this paper is a technique that we propose for extracting the physical parameters of a rotating stellar core collapse from the observation of the associated gravitational wave signal from the collapse and core bounce. Data from interferometric gravitational wave detectors can be used to provide information on the mass of the progenitor model, precollapse rotation and the nuclear equation of state. We use waveform libraries provided by the latest numerical simulations of rotating stellar core collapse models in general relativity, and from them create an orthogonal set of eigenvectors using principal component analysis. Bayesian inference techniques are then used to reconstruct the associated gravitational wave signal that is assumed to be detected by an interferometric detector. Posterior probability distribution functions are derived for the amplitudes of the principal component analysis eigenvectors, and the pulse arrival time. We show how the reconstructed signal and the principal component analysis eigenvector amplitude estimates may provide information on the physical parameters associated with the core collapse event.
17 pages, 9 figures
References in corpus (15)
- Coherent method for detection of gravitational wave bursts
- The gravitational wave burst signal from core collapse of rotating stars
- 3D Collapse of Rotating Stellar Iron Cores in General Relativity including Deleptonization and a Nuclear Equation of State
- The path to the enhanced and advanced LIGO gravitational-wave detectors
- Generic Gravitational Wave Signals from the Collapse of Rotating Stellar Cores
- Gravitational-Wave Astronomy with Inspiral Signals of Spinning Compact-Object Binaries
- Waveless Approximation Theories of Gravity
- Coherent Bayesian inference on compact binary inspirals using a network of interferometric gravitational wave detectors
- Rotating stellar core-collapse waveform decompositon: a Principal Component Analysis approach
- Rank deficiency and Tikhonov regularization in the inverse problem for gravitational-wave bursts
- Reconstruction of source location in a network of gravitational wave interferometric detectors
- First joint search for gravitational-wave bursts in LIGO and GEO600 data
- Coherent Bayesian analysis of inspiral signals
- Gravitational Wave Burst Source Direction Estimation using Time and Amplitude Information
- A comparison of methods for gravitational wave burst searches from LIGO and Virgo
Cited by in corpus (48)
- BayesWave: Bayesian Inference for Gravitational Wave Bursts and Instrument Glitches
- The gravitational wave signal from core-collapse supernovae
- Observing Gravitational Waves From The Post-Merger Phase Of Binary Neutron Star Coalescence
- Observing Gravitational Waves from Core-Collapse Supernovae in the Advanced Detector Era
- Equation of State Effects on Gravitational Waves from Rotating Core Collapse
- Correlated Gravitational Wave and Neutrino Signals from General-Relativistic Rapidly Rotating Iron Core Collapse
- Parameter estimation with gravitational waves
- The Science of the Einstein Telescope
- Measuring the Angular Momentum Distribution in Core-Collapse Supernova Progenitors with Gravitational Waves
- Prospects For High Frequency Burst Searches Following Binary Neutron Star Coalescence With Advanced Gravitational Wave Detectors
- Gravitational Wave Extraction in Simulations of Rotating Stellar Core Collapse
- Inferring the core-collapse supernova explosion mechanism with gravitational waves
- Inferring Core-Collapse Supernova Physics with Gravitational Waves
- Gravitational wave asteroseismology with protoneutron stars
- Detection and Classification of Supernova Gravitational Waves Signals: A Deep Learning Approach
- Inference of proto-neutron star properties from gravitational-wave data in core-collapse supernovae
- Denoising of gravitational wave signals via dictionary learning algorithms
- Coherent Network Analysis of Gravitational Waves from Three-Dimensional Core-Collapse Supernova Models
- A Student-t based filter for robust signal detection
- Inferring Astrophysical Parameters of Core-Collapse Supernovae from their Gravitational-Wave Emission
- Astrophysical science metrics for next-generation gravitational-wave detectors
- Total-variation-based methods for gravitational wave denoising
- Inferring the core-collapse supernova explosion mechanism with three-dimensional gravitational-wave simulations
- Probing Rotation of Core-collapse Supernova with Concurrent Analysis of Gravitational Waves and Neutrinos
- Classifying the Equation of State from Rotating Core Collapse Gravitational Waves with Deep Learning
- Bayesian semiparametric power spectral density estimation with applications in gravitational wave data analysis
- Total-variation methods for gravitational-wave denoising: performance tests on Advanced LIGO data
- Bayesian parameter estimation of core collapse supernovae using gravitational wave simulations
- Three approaches for the classification of protoneutron star oscillation modes
- Multivariate Regression Analysis of Gravitational Waves from Rotating Core Collapse
- Classification of the core-collapse supernova explosion mechanism with learned dictionaries
- Prospects for multi-messenger extended emission from core-collapse supernovae in the Local Universe
- Reconstructing Gravitational Wave Core-Collapse Supernova Signals with Dynamic Time Warping
- Exploring Supernova Gravitational Waves with Machine Learning
- Inferring physical properties of stellar collapse by third-generation gravitational-wave detectors
- Classifying LISA gravitational wave burst signals using Bayesian evidence
- Method for estimation of gravitational-wave transient model parameters in frequency-time maps
- Multi-messenger observations of core-collapse supernovae: Exploiting the standing accretion shock instability
- The SPIIR online coherent pipeline to search for gravitational waves from compact binary coalescences
- Computational Techniques for Parameter Estimation of Gravitational Wave Signals
- Prospects for reconstructing the gravitational-wave signals from core-collapse supernovae with Advanced LIGO-Virgo and the BayesWave algorithm
- Broadband extended emission in gravitational waves from core-collapse supernovae
- Detecting and reconstructing gravitational waves from the next Galactic core-collapse supernova in the Advanced Detector Era
- Deep-Learning Classification and Parameter Inference of Rotational Core-Collapse Supernovae
- Generative adversarial network for stellar core-collapse gravitational waves
- Waveform Reconstruction of Core-Collapse Supernova Gravitational Waves with Improved Multisynchrosqueezing Transform
- Investigating Binary Black Hole Mergers with Principal Component Analysis
- Use of Singular-Value Decomposition in Gravitational-Wave Data Analysis