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Register a new userGravitational Waves from Axisymmetric, Rotational Stellar Core Collapse
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Christian D. Ott
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We have carried out an extensive set of two-dimensional, axisymmetric, purely-hydrodynamic calculations of rotational stellar core collapse with a realistic, finite-temperature nuclear equation of state and realistic massive star progenitor models. For each of the total number of 72 different simulations we performed, the gravitational wave signature was extracted via the quadrupole formula in the slow-motion, weak-field approximation. We investigate the consequences of variation in the initial ratio of rotational kinetic energy to gravitational potential energy and in the initial degree of differential rotation. Furthermore, we include in our model suite progenitors from recent evolutionary calculations that take into account the effects of rotation and magnetic torques. For each model, we calculate gravitational radiation wave forms, characteristic wave strain spectra, energy spectra, final rotational profiles, and total radiated energy. In addition, we compare our model signals with the anticipated sensitivities of the 1st- and 2nd-generation LIGO detectors coming on line. We find that most of our models are detectable by LIGO from anywhere in the Milky Way.
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The next galactic core-collapse supernova (CCSN) has already exploded, and its electromagnetic (EM) waves, neutrinos, and gravitational waves (GWs) may arrive at any moment. We present an extensive study on the potential sensitivity of prospective detection scenarios for GWs from CCSNe within 5Mpc, using realistic noise at the predicted sensitivity of the Advanced LIGO and Advanced Virgo detectors for 2015, 2017, and 2019. We quantify the detectability of GWs from CCSNe within the Milky Way and Large Magellanic Cloud, for which there will be an observed neutrino burst. We also consider extreme GW emission scenarios for more distant CCSNe with an associated EM signature. We find that a three detector network at design sensitivity will be able to detect neutrino-driven CCSN explosions out to ~5.5 kpc, while rapidly rotating core collapse will be detectable out to the Large Magellanic Cloud at 50kpc. Of the phenomenological models for extreme GW emission scenarios considered in this study, such as long-lived bar-mode instabilities and disk fragmentation instabilities, all models considered will be detectable out to M31 at 0.77 Mpc, while the most extreme models will be detectable out to M82 at 3.52 Mpc and beyond.
Using predictions from three-dimensional (3D) hydrodynamics simulations of core-collapse supernovae (CCSNe), we present a coherent network analysis to detection, reconstruction, and the source localization of the gravitational-wave (GW) signals. We use the {tt RIDGE} pipeline for the analysis, in which the network of LIGO Hanford, LIGO Livingston, VIRGO, and KAGRA is considered. By combining with a GW spectrogram analysis, we show that several important hydrodynamics features in the original waveforms persist in the waveforms of the reconstructed signals. The characteristic excess in the spectrograms originates not only from rotating core-collapse, bounce and the subsequent ring down of the proto-neutron star (PNS) as previously identified, but also from the formation of magnetohydrodynamics jets and non-axisymmetric instabilities in the vicinity of the PNS. Regarding the GW signals emitted near at the rotating core bounce, the horizon distance extends up to $sim$ 18 kpc for the most rapidly rotating 3D model in this work. Following the rotating core bounce, the dominant source of the GW emission shifts to the non-axisymmetric instabilities. The horizon distances extend maximally up to $sim$ 40 kpc seen from the spin axis. With an increasing number of 3D models trending towards explosion recently, our results suggest that in addition to the best studied GW signals due to rotating core-collapse and bounce, the time is ripe to consider how we can do science from GWs of CCSNe much more seriously than before. Particularly the quasi-periodic signals due to the non-axisymmetric instabilities and the detectability should deserve further investigation to elucidate the inner-working of the rapidly rotating CCSNe.
We summarize our current understanding of gravitational wave emission from core-collapse supernovae. We review the established results from multi-dimensional simulations and, wherever possible, provide back-of-the-envelope calculations to highlight the underlying physical principles. The gravitational waves are predominantly emitted by protoneutron star oscillations. In slowly rotating cases, which represent the most common type of the supernovae, the oscillations are excited by multi-dimensional hydrodynamic instabilities, while in rare rapidly rotating cases, the protoneutron star is born with an oblate deformation due to the centrifugal force. The gravitational wave signal may be marginally visible with current detectors for a source within our galaxy, while future third-generation instruments will enable more robust and detailed observations. The rapidly rotating models that develop non-axisymmetric instabilities may be visible up to a megaparsec distance with the third-generation detectors. Finally, we discuss strategies for multi-messenger observations of supernovae.
In this paper, we seek to answer the question given a rotating core collapse gravitational wave signal, can we determine its nuclear equation of state?. To answer this question, we employ deep convolutional neural networks to learn visual and temporal patterns embedded within rotating core collapse gravitational wave (GW) signals in order to predict the nuclear equation of state (EOS). Using the 1824 rotating core collapse GW simulations by Richers et al. (2017), which has 18 different nuclear EOS, we consider this to be a classic multi-class image classification and sequence classification problem. We attain up to 72% correct classifications in the test set, and if we consider the top 5 most probable labels, this increases to up to 97%, demonstrating that there is a moderate and measurable dependence of the rotating core collapse GW signal on the nuclear EOS.
While gravitational waves have been detected from mergers of binary black holes and binary neutron stars, signals from core collapse supernovae, the most energetic explosions in the modern Universe, have not been detected yet. Here we present a new method to analyse the data of the LIGO, Virgo and KAGRA network to enhance the detection efficiency of this category of signals. The method takes advantage of a peculiarity of the gravitational wave signal emitted in the core collapse supernova and it is based on a classification procedure of the time-frequency images of the network data performed by a convolutional neural network trained to perform the task to recognize the signal. We validate the method using phenomenological waveforms injected in Gaussian noise whose spectral properties are those of the LIGO and Virgo advanced detectors and we conclude that this method can identify the signal better than the present algorithm devoted to select gravitational wave transient signal.
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