Ray-Tracing Analysis of Anisotropic Neutrino Radiation for Estimating Gravitational Waves in Core-Collapse Supernovae
Kei Kotake, Wakana Iwakami, Naofumi Ohnishi, and Shoichi Yamada

TL;DR
This paper introduces a ray-tracing method to accurately estimate gravitational waves from anisotropic neutrino emissions in supernovae, revealing complex waveform features and smaller amplitudes than previous models, impacting detection prospects.
Contribution
The paper develops an analytic, three-dimensional applicable ray-tracing approach to compute neutrino anisotropies and resulting gravitational waveforms in supernova simulations.
Findings
Waveforms show more variety than previous estimates.
Negative growth features in waveforms due to lateral neutrino emission.
Wave amplitudes are over an order of magnitude smaller than earlier predictions.
Abstract
We propose a ray-tracing method to estimate gravitational waves (GWs) generated by anisotropic neutrino emission in supernova cores. To calculate the gravitational waveforms, we derive analytic formulae in a useful form, which are applicable also for three-dimensional computations. Pushed by evidence of slow rotation prior to core-collapse, we focus on asphericities in neutrino emission and matter motions outside the protoneutron star. Based on the two-dimensional (2D) models, which mimic SASI-aided neutrino heating explosions, we compute the neutrino anisotropies via the ray-tracing method in a post-processing manner and calculate the resulting waveforms. With these computations, it is found that the waveforms exhibit more variety in contrast to the ones previously estimated by the ray-by-ray analysis (e.g., Kotake et al. (2007)). In addition to a positively growing feature, which was…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
