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arXiv 2007.15010hep-phastro-ph.HE
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$χ$ aro $ν$:一个从WIMP产生中微子通量的工具

$χ$aro$ν$: a tool for neutrino flux generation from WIMPs

Qinrui Liu, Jeffrey Lazar, Carlos A. Argüelles, Ali Kheirandish

摘要:

对微粒暗物质特征的间接搜索已经使用了所有的宇宙信使:伽马射线、宇宙射线和中微子。从中微子中寻找暗物质具有特别重要的意义,因为它们是唯一能够从致密环境中(如太阳或地球的核心,或从可观测宇宙的边缘)的暗物质过程到达探测器的信使。在这项工作中,我们介绍了$χ$ aro $ν$,一个软件包,在其希腊神话同名$χ\acuteαρων$的精神,桥梁的黑暗部门和标准模型预测中微子通量从不同的天体暗物质凝聚。生产点的通量由$χ$ aro $ν$内部计算或从用户提供的表格中获取。然后,$χ$ aro $ν$通过真空或稠密介质传播该通量,并在观测者的位置返回预期的中微子产额。在开发$χ$和$ν$的过程中,我们重新审视和更新了稠密介质中中微子的产生,更新了高能中微子的传播,并研究了中微子输运中不确定性的来源。这个软件包是耦合到一个新的计算,包括电弱校正导致最新的和完整的存储库的中微子通量从暗物质衰变和湮灭的能量范围为1 GeV至10 PeV来自地球,太阳和星系晕。

英文摘要:

Indirect searches for signatures of corpuscular dark matter have been performed using all cosmic messengers: gamma rays, cosmic rays, and neutrinos. The search for dark matter from neutrinos is of particular importance since they are the only courier that can reach detectors from dark matter processes in dense environments, such as the core of the Sun or Earth, or from the edge of the observable Universe. In this work, we introduce $χ$aro$ν$, a software package that, in the spirit of its mythological Greek namesake $χ\acuteαρων$, bridges the dark sector and Standard Model by predicting neutrino fluxes from different celestial dark matter agglomerations. The flux at the point of production is either computed internally by $χ$aro$ν$ or is taken from user supplied tables. $χ$aro$ν$ then propagates this flux through vacuum or dense media and returns the expected neutrino yield at an observer's location. In developing $χ$aro$ν$, we have revisited and updated the production of neutrinos in dense media, updated the propagation of high-energy neutrinos, and studied the sources of uncertainty in neutrino transport. This package is coupled to a new calculation that includes electroweak corrections resulting in the most up-to-date and complete repository of neutrino fluxes from dark matter decay and annihilation over the energy range of 1 GeV to 10 PeV coming from the Earth, the Sun, and the Galactic halo.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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