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Register a new userBayesian reconstruction of gravitational wave burst signals from simulations of rotating stellar core collapse and bounce
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Added by
Christian R\\\"over
Publication date
2009
fields
Physics
and research's language is
English
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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.
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We discuss the prospects of gravitational lensing of gravitational waves (GWs) coming from core-collapse supernovae (CCSN). As the CCSN GW signal can only be detected from within our own Galaxy and the local group by current and upcoming ground-based GW detectors, we focus on microlensing. We introduce a new technique based on analysis of the power spectrum and association of peaks of the power spectrum with the peaks of the amplification factor to identify lensed signals. We validate our method by applying it on the CCSN-like mock signals lensed by a point mass lens. We find that the lensed and unlensed signal can be differentiated using the association of peaks by more than one sigma for lens masses larger than 150 solar masses. We also study the correlation integral between the power spectra and corresponding amplification factor. This statistical approach is able to differentiate between unlensed and lensed signals for lenses as small as 15 solar masses. Further, we demonstrate that this method can be used to estimate the mass of a lens in case the signal is lensed. The power spectrum based analysis is general and can be applied to any broad band signal and is especially useful for incoherent signals.
We present results from full general relativistic three-dimensional hydrodynamics simulations of stellar core collapse of a 70 M$_odot$ star with spectral neutrino transport. To investigate the impact of rotation on non-axisymmetric instabilities, we compute three models by parametrically changing the initial strength of rotation. The most rapidly rotating model exhibits a transient development of the low-$T/|W|$ instability with one-armed spiral flow at the early postbounce phase. Subsequently, the two-armed spiral flow appears, which persists during the simulation time. The moderately rotating model also shows the growth of the low-$T/|W|$ instability, but only with the two-armed spiral flow. In the nonrotating model, a vigorous activity of the standing accretion-shock instability (SASI) is only observed. The SASI is first dominated by the sloshing mode, which is followed by the spiral SASI until the black hole formation. We present a spectrogram analysis of the gravitational waves (GWs) and neutrinos, focusing on the time correlation. Our results show that characteristic time modulations in the GW and neutrino signals can be linked to the growth of the non-axisymmetric instabilities. We find that the degree of the protoneutron star (PNS) deformation, depending upon which modes of the non-axisymmetric instabilities develop, predominantly affects the characteristic frequencies of the correlated GW and neutrino signals. We point out that these signals would be simultaneously detectable by the current-generation detectors up to $sim10$ kpc. Our findings suggest that the joint observation of GWs and neutrinos is indispensable for extracting information on the PNS evolution preceding the black hole formation.
We present gravitational wave (GW) signal predictions from four 3D multi-group neutrino hydrodynamics simulations of core-collapse supernovae of progenitors with 11.2 Msun, 20 Msun, and 27 Msun. GW emission in the pre-explosion phase strongly depends on whether the post-shock flow is dominated by the standing accretion shock instability (SASI) or convection and differs considerably from 2D models. SASI activity produces a strong signal component below 250 Hz through asymmetric mass motions in the gain layer and a non-resonant coupling to the proto-neutron star (PNS). Both convection- and SASI-dominated models show GW emission above 250 Hz, but with considerably lower amplitudes than in 2D. This is due to a different excitation mechanism for high-frequency l=2 motions in the PNS surface, which are predominantly excited by PNS convection in 3D. Resonant excitation of high-frequency surface g-modes in 3D by mass motions in the gain layer is suppressed compared to 2D because of smaller downflow velocities and a lack of high-frequency variability in the downflows. In the exploding 20 Msun model, shock revival results in enhanced low-frequency emission due to a change of the preferred scale of the convective eddies in the PNS convection zone. Estimates of the expected excess power in two frequency bands suggests that second-generation detectors will only be able to detect very nearby events, but that third-generation detectors could distinguish SASI- and convection-dominated models at distances of ~10 kpc.
Within the next few years, Advanced LIGO and Virgo should detect gravitational waves from binary neutron star and neutron star-black hole mergers. These sources are also predicted to power a broad array of electromagnetic transients. Because the electromagnetic signatures can be faint and fade rapidly, observing them hinges on rapidly inferring the sky location from the gravitational-wave observations. Markov chain Monte Carlo methods for gravitational-wave parameter estimation can take hours or more. We introduce BAYESTAR, a rapid, Bayesian, non-Markov chain Monte Carlo sky localization algorithm that takes just seconds to produce probability sky maps that are comparable in accuracy to the full analysis. Prompt localizations from BAYESTAR will make it possible to search electromagnetic counterparts of compact binary mergers.
In this work we report briefly on the gravitational wave (GW) signal computed in the context of a self-consistent, 3D simulation of a core-collapse supernova (CCSN) explosion of a 15M$_odot$ progenitor star. We present a short overview of the GW signal, including signal amplitude, frequency distribution, and the energy emitted in the form of GWs for each phase of explosion, along with neutrino luminosities, and discuss correlations between them.
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