Projects per year
Abstract
Understanding gravitational wave emission from core-collapse supernovae will be essential for their detection with current and future gravitational wave detectors. This requires a sample of waveforms from modern 3D supernova simulations reaching well into the explosion phase, where gravitational wave emission is expected to peak. However, recent waveforms from 3D simulations with multigroup neutrino transport do not reach far into the explosion phase, and some are still obtained from non-exploding models. We therefore calculate waveforms up to 0.9 s after bounce using the neutrino hydrodynamics code COCONUT-FMT. We consider two models with low and normal explosion energy, namely explosions of an ultra-stripped progenitor with an initial helium starmass of 3.5M⊙, and of an 18M⊙ single star. Both models show gravitational wave emission from the excitation of surface g modes in the proto-neutron star with frequencies between ∼800 and 1000 Hz at peak emission. The peak amplitudes are about 6 and 10 cm, respectively, which is somewhat higher than in most recent 3D models of the pre-explosion or early explosion phase. Using a Bayesian analysis, we determine the maximum detection distances for our models in simulated Advanced LIGO, Advanced Virgo, and Einstein Telescope (ET) design sensitivity noise. The more energetic 18M_ explosion will be detectable to about 17.5 kpc by the LIGO/Virgo network and to about 180 kpc with the ET.
Original language | English |
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Pages (from-to) | 1178-1190 |
Number of pages | 13 |
Journal | Monthly Notices of the Royal Astronomical Society |
Volume | 487 |
Issue number | 1 |
DOIs | |
Publication status | Published - Jul 2019 |
Keywords
- Gravitational waves
- Supernovae: General
Projects
- 2 Finished
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Understanding the diversity of core-collapse supernovae
Australian Research Council (ARC), Monash University
30/06/17 → 30/06/24
Project: Research
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ARC Centre of Excellence for Gravitational Wave Discovery
Bailes, M., McClelland, D. E., Levin, Y., Blair, D. G., Scott, S. M., Ottaway, D. J., Melatos, A., Veitch, P. J., Wen, L., Shaddock, D. A., Slagmolen, B. J. J., Zhao, C., Evans, R. J., Ju, L., Galloway, D., Thrane, E., Hurley, J. R., Coward, D. M., Cooke, J., Couch, W., Hobbs, G. B., Reitze, D., Rowan, S., Cai, R., Adhikari, R. X., Danzmann, K., Mavalvala, N., Kulkarni, S. R., Kramer, M., Branchesi, M., Gehrels, N., Weinstein, A. J. R., Steeghs, D., Bock, D. & Lasky, P.
Monash University – Internal University Contribution, Monash University – Internal Department Contribution
1/01/17 → 31/03/24
Project: Research