论文标题
标准和双重塌陷模型中的弥漫性超新星中微子背景
The Diffuse Supernova Neutrino Background in the Standard and Double Collapse Models
论文作者
论文摘要
弥漫性超新星中微子背景（DSNB）是一种强大的未来工具，可在不观察附近事件的情况下限制核心折叠爆炸机制，并且已经计算出各种崩溃模型的相应信号。对于Supernova（SN）1987a，检测到一个奇特的双中微子爆发，但是在DSNB环境中从未研究过双重崩溃的模型。在这里，我们填补了这一空白，并比较了标准崩溃（SC）中预期的DSNB信号和各种未来探测器中的双重崩溃（DC）模型，包括Hyper-Kamiokande，Juno，Dune和大型Baksan Neutmrino望远镜（LBNT）。我们在DC模型中计算了弥漫性中微子和抗神经纤维的光谱，并考虑了检测器参数，确定了注册事件的速率，这是检测到的粒子能量的函数。对于每个检测器，我们估计相应的不确定性和背景，并比较SC和DC模型的预期信号。我们得出的结论是，沙丘和LBNT数据的组合将具有区分SC和DC模型的最高敏感性。
The diffuse supernova neutrino background (DSNB) is a powerful future tool to constrain core-collapse explosion mechanisms without observation of a nearby event, and the corresponding signal has been calculated for a variety of collapse models. For Supernova (SN) 1987A, a peculiar double neutrino burst was detected, but models for the double collapse have never been studied in the DSNB context. Here, we fill this gap and compare the DSNB signal expected in the Standard Collapse (SC) and the Double Collapse (DC) models in various future detectors, including Hyper-Kamiokande, JUNO, DUNE and the Large Baksan Neutrino Telescope (LBNT). We calculate the spectra of diffuse neutrinos and antineutrinos in the DC model and determine the rate of registered events as a function of energy of the detected particle, taking into account detector parameters. For each detector, we estimate the corresponding uncertainties and the background and compare the signals expected for the SC and DC models. We conclude that the combination of DUNE and LBNT data will have the highest sensitivity to discriminate between the SC and DC models.
