Supernova neutrino signals based on long-term axisymmetric simulations

Abstract

We study theoretical neutrino signals from core-collapse supernova (CCSN) computed using axisymmetric CCSN simulations that cover the post-bounce phase up to ∼4 s. We provide basic quantities of the neutrino signals such as event rates, energy spectra, and cumulative number of events at some terrestrial neutrino detectors, and then discuss some new features in the late phase that emerge in our models. Contrary to popular belief, neutrino emissions in the late phase are not always steady, but rather have temporal fluctuations, the vigor of which hinges on the CCSN model and neutrino flavor. We find that such temporal variations are not primarily driven by proto-neutron star (PNS) convection, but by fallback accretion in exploding models. We assess the detectability of these temporal variations, and find that IceCube is the most promising detector with which to resolve them. We also update fitting formulae first proposed in our previous paper for which the total neutrino energy (TONE) emitted at the CCSN source is estimated from the cumulative number of events in each detector. This will be a powerful technique with which to analyse real observations, particularly for low-statistics data.

Magnetic support for neutrino-driven explosion of 3D non-rotating core-collapse supernova models

“…The magnetic field is accumulated and amplified to the magnetar level, that is, O(10 14 ) G, in the convectively stable shell in the vicinity of the PNS surface. Apparently, a much long-term simulation is needed (as recently done in 2D HD case (Nagakura et al 2021) though in different context) to clarify how the global magnetic configuration obtained in this study focusing on the (early) pre-explosion phase would evolve with time to account for the dipolar (or even the subdominant, non-dipolar) configurations of the observed neutron stars/pulsars (e.g., Enoto et al 2019 for a review). To tackle with this question, interesting physics ingredients including the effect of fall-back (e.g., Ho 2011;Viganò & Pons 2012;Torres-Forné et al 2016;Shigeyama & Kashiyama 2018), magneto-thermal evolution, not to mention the non-ideal MHD effects (see, Pons & Viganò 2019 for collective references therein) should be carefully treated in numerical computations.…”

Efficient estimation method for time evolution of proto-neutron star mass and radius from supernova neutrino signal

“…In both axisymmetric and full 3D CCSN models, we found that the cumulative number of neutrino events in each detector has a strong correlation to the total emitted neutrino energy (TONE) 1 . The fitting function for the correlation was provided in Nagakura et al (2021b), but it was updated in the subsequent paper (Nagakura et al 2021c) (see also , which covers the longer post-bounce time (up to ∼ 4s after bounce) than the former. We also note that the correlation is insensitive to progenitors.…”

“…The initial conditions for the stellar progenitors are provided in Sukhbold et al (2018), and 2D simulations were calculated, following the stellar collapse and postbounce evolution through ∼ 4 s. Among the (18) models, shock revival is achieved for all except for the 12-and 15 M models. The detailed analysis of their CCSN dynamics can be found in (Burrows & Vartanyan 2021), and that of the neutrino signal are presented in (Nagakura et al 2021c).…”

“…Another caveat in current theoretical models is that the fall-back accretion component is completely neglected, which also potentially alters the neutrino emission. Indeed, we have witnessed fall-back accretion in the late post-bounce phase ( 1 s) in many multi-D CCSN models (see, e.g., Young et al 2006;Fryer 2009;Wongwathanarat et al 2010;Chan et al 2018;Müller et al 2019;Chan et al 2020;Nagakura et al 2021c). These findings suggest that deciphering the neutrino signal requires multi-D CCSN models with taking into account potentially long-lasting accretion components.…”

Prospects for Distinguishing Supernova Models Using a Future Neutrino Signal

“…Since the observation of Supernova 1987A (SN 1987A) and its associated neutrino signal, theoretical work on core-collapse SNe and their neutrino emission has advanced significantly (see, e.g., [1,2] for recent reviews). Today, both one-dimensional (1D) and multi-D (2D and 3D) models of SN neutrino emission can be simulated beyond ∼ 1 s (e.g., [2,3]). In [4], we took the Bayesian approach to compare three 1D models provided by the Garching group [5] with the SN 1987A data from the Kamiokande II (KII) detector [6,7].…”