Title: Using Bayesian Inference to Distinguish Neutrino Flavor Conversion Scenarios via a Prospective Supernova Neutrino Signal Show Chinese title

Title: 利用贝叶斯推理通过超新星中微子信号区分中微子味转换情景

Abstract: The upcoming galactic core-collapse supernova is expected to produce a considerable number of neutrino events within terrestrial detectors. By using Bayesian inference techniques, we address the feasibility of distinguishing among various neutrino flavor conversion scenarios in the supernova environment, using such a neutrino signal. In addition to the conventional MSW, we explore several more sophisticated flavor conversion scenarios, such as spectral swapping, fast flavor conversions, flavor equipartition caused by non-standard neutrino interactions, magnetically-induced flavor equilibration, and flavor equilibrium resulting from slow flavor conversions. Our analysis demonstrates that with a sufficiently large number of neutrino events during the supernova accretion phase (exceeding several hundreds), there exists a good probability of distinguishing among feasible neutrino flavor conversion scenarios in the supernova environment. Show Chinese abstract

Abstract: 即将到来的星系核心坍缩超新星预计会在地球探测器中产生相当数量的中微子事件。 通过使用贝叶斯推理技术，我们探讨了利用这种中微子信号区分超新星环境中各种中微子味转换场景的可行性。 除了传统的MSW效应外，我们还研究了几种更复杂的味转换场景，如光谱交换、快速味转换、由非标准中微子相互作用引起的味平衡、磁场诱导的味平衡以及由缓慢味转换导致的味平衡。 我们的分析表明，在超新星吸积阶段具有足够数量的中微子事件（超过几百个）时，在超新星环境中区分可行的中微子味转换场景有很大的概率。