Diffuse neutrino background from past core-collapse supernovae

TL;DR

The review formulates a comprehensive framework to predict the Diffuse Supernova Neutrino Background (DSNB) as the integrated flux of neutrinos from all past core-collapse supernovae, linking it to the cosmic SN rate and per-event spectra through a kinetic equation in a flat $\Lambda$CDM universe. It surveys the theoretical ingredients—cosmic SN rate density, progenitor diversity, neutrino emission and oscillations, and black-hole formation—and the associated uncertainties, including dust extinction and stellar initial mass function. The article then assesses the DSNB spectrum across flavors, discusses tests of neutrino physics and cosmology, and analyzes current and future detection prospects, highlighting the role of gadolinium upgrades in Super-Kamiokande and upcoming detectors like JUNO and Hyper-Kamiokande. The work emphasizes that, with improved statistics and more precise modeling, the first DSNB detection is within reach and will illuminate past stellar explosions, neutrino properties, and the history of star formation across cosmic time.

Abstract

Core-collapse supernovae are among the most powerful explosions in the universe, emitting thermal neutrinos that carry away the majority of the gravitational binding energy released. These neutrinos create a diffuse supernova neutrino background (DSNB), one of the largest energy budgets among all radiation backgrounds. Detecting the DSNB is a crucial goal of modern high-energy astrophysics and particle physics, providing valuable insights in both core-collapse modeling, neutrino physics, and cosmic supernova rate history. In this review, we discuss the key ingredients of DSNB calculation and what we can learn from future detections, including black-hole formation and non-standard neutrino interactions. Additionally, we provide an overview of the latest updates in neutrino experiments, which could lead to the detection of the DSNB in the next decade. With the promise of this breakthrough discovery on the horizon, the study of DSNB holds enormous potential for advancing our understanding of the Universe.

Figures (8)

• Figure 1: Star formation rate density (SFRD) as a function of redshift. SFRD points collected from the right panel of Figure 6 of Audcent-Ross et al. 2018Audcent_Ross_2018, entitled "Near-identical star formation rate densities from H$\alpha$ and FUV at redshift zero", published in MNRAS volume 480 no. 1. Fits to other data sets performed in Madau and Dickinson 2014Madau:2014bja and Yuksel et al. 2008Yuksel:2008cu with Horiuchi et al. 2008Horiuchi:2008jz parameters are plotted for comparison. All assume the Salpeter IMF.
• Figure 2: DSNB spectra of different models for the hydrodynamic phase of protoneutron star evolution; each model shown here has been integrated up to the first $300\,{\rm ms}$ of each simulation for $20\,M_{\odot}$ progenitors (except for Bollig et al. 2016Mirizzi:2015eza which is a $27\,M_{\odot}$ progenitor and the Nakazato et al. 2013Nakazato:2012qf model has metallicity $Z=0.02$). We compare these against the Fornax 2021Burrows:2020qrpNagakura:2021lma, Kuroda et al. 2020Kuroda:2020pta, and Tamborra et al. 2014Tamborra:2014hga models.
• Figure 3: DSNB spectra for the Fermi-Dirac model with parameters derived from the model of Ekanger et al.Ekanger:2022neg which have $E_{\nu,e} = 5.8\times10^{52}\,{\rm erg}$, $E_{\bar{\nu},e} = 6\times10^{52}\,{\rm erg}$, and $E_{\nu,x} = 5\times10^{52}\,{\rm erg}$, and temperatures $T_{\nu,e} = 3.4\,{\rm MeV}$ and $T_{\bar{\nu}_e} = T_{\nu,x} = 4.1\,{\rm MeV}$. Because $\bar{\nu}_e$ and $\nu_x$ have very similar temperatures, the spectrum after oscillation due to the MSW effect looks very similar for normal and inverted hierarchies.
• Figure 4: Comparison of the DNSB spectrum from the early hydrodynamic, late cooling, and total phases of the Nakazato et al.Nakazato:2012qf (or N13) model. This assumes a revival time of $300\,{\rm ms}$, metallicity of $Z=0.02$, and progenitor mass of $20\,M_{\odot}$.
• Figure 5: Comparison of the DSNB spectrum of the sum of early hydrodynamic phase plus four different late phase strategies. The data from the hydrodynamic phase is from N13 in this figure, using the same revival time, metallicity, and progenitor mass as Fig. \ref{['fig:n13_phases']}.