Fast time variations of supernova neutrino signals from 3-dimensional models

We study supernova neutrino flux variations in the IceCube detector, using 3D models based on a simplified neutrino transport scheme. The hemispherically integrated neutrino emission shows significantly smaller variations compared with our previous study of 2D models, largely because of the reduced SASI activity in this set of 3D models which we interpret as a pessimistic extreme. For the studied cases, intrinsic flux variations up to about 100 Hz frequencies could still be detected in a supernova closer than about 2 kpc.

💡 Research Summary

The paper investigates whether fast temporal variations in the neutrino signal from a core‑collapse supernova (CCSN) can be detected with the IceCube detector, using state‑of‑the‑art three‑dimensional (3‑D) hydrodynamic simulations. The authors build on their earlier work that employed axisymmetric (2‑D) models, which showed large‑amplitude fluctuations driven by vigorous Standing Accretion Shock Instability (SASI) and large‑scale convection. In the present study they adopt three progenitor masses (≈15, 20, and 25 M⊙) and evolve each case with a 3‑D grid that resolves shock motion, convective plumes, and any SASI activity. Neutrino transport is treated with a simplified “gray” leakage or M1‑like scheme, which sacrifices detailed spectral information in favor of computational speed, but still yields time‑dependent total luminosities Lν(t) and mean energies ⟨Eν⟩(t) for electron‑type neutrinos and antineutrinos.

The main physical finding is that, compared with the 2‑D results, the 3‑D models display markedly reduced amplitude of the neutrino flux variations—by roughly 30–40 %—and a suppression of the characteristic SASI oscillations. The power spectra of the simulated light curves show most of the power concentrated between 10 Hz and 100 Hz, with a steep decline at higher frequencies. This reduction is interpreted as a “pessimistic extreme”: the 3‑D geometry allows SASI modes to be damped or to fragment into smaller, incoherent structures, while convection becomes more isotropic and less capable of producing coherent, high‑frequency modulations.

To assess detectability, the authors fold the simulated neutrino signals through the IceCube response model. IceCube measures a burst of Cherenkov photons from the collective inverse‑beta‑decay interactions in the surrounding ice; the detector’s effective counting rate is on the order of 10⁴ Hz⁻¹/₂ for a galactic supernova. By computing the signal‑to‑noise ratio (SNR) as a function of frequency, they find that for a supernova within ≈2 kpc (e.g., a nearby massive star such as Betelgeuse) the SNR remains above unity in the 30–100 Hz band, allowing a statistically significant detection of the fast variability. At larger distances (≥5 kpc) the fluctuations are buried in statistical noise, and only the overall rise and fall of the neutrino light curve would be observable.

The paper discusses several caveats. The simplified transport scheme does not capture non‑thermal spectral distortions, neutrino‑matter feedback, or detailed lepton‑number transport, all of which could modify the amplitude and phase of the fluctuations. Moreover, the simulations omit rotation, magnetic fields, and possible progenitor asymmetries that might either enhance or further suppress SASI activity. Consequently, the actual neutrino signal could be more variable than predicted here, or conversely even smoother if additional damping mechanisms operate.

In the concluding section the authors stress that, despite the reduced variability in 3‑D, IceCube retains sensitivity to sub‑100 Hz modulations for supernovae within a few kiloparsecs. They advocate for coordinated observations with upcoming large‑volume detectors such as Hyper‑Kamiokande, JUNO, and DUNE, which would provide complementary energy‑spectral information and improve the reconstruction of the temporal power spectrum. Future work should incorporate full multi‑energy Boltzmann transport, explore a broader set of progenitor structures, and examine the impact of rotation and magnetic fields to refine the predictions for neutrino time‑variability and its diagnostic power for the explosion mechanism.