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arXiv 1302.1802hep-phastro-ph.CO
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s通道暗物质湮灭的Gamma-ray线和单圈连续谱

Gamma-ray lines and One-Loop Continuum from s-channel Dark Matter Annihilations

C. B. Jackson, Geraldine Servant, Gabe Shaughnessy, Tim M. P. Tait, Marco Taoso

摘要:

对暗物质进行间接探测的时代已经开始,伽马射线探测器的灵敏度现在接近与弱相互作用大质量粒子相关的参数空间。特别是,伽马射线线将是暗物质湮灭的确凿证据,尽管与连续谱相比,它们通常被抑制。在本文中,我们特别注意的1-loop连续产生的伽马射线线和调查的条件下,一个暗物质模型可以自然地导致线信号,是相对增强。我们研究通用类的模型,其中DM是一个费米子,通过S-通道介质,这是一个矢量或标量和识别的耦合和质量条件下,发生大的线信号的湮灭。我们专注于“禁止通道机制”,主张几年前在“希格斯在空间”的情况下,树级湮灭是今天的运动学禁止。详细计算了所有单回路湮没通道。我们挑选出非常简单的模型与一个大的线在连续比,并提出了一般的预测,大范围的WIMP质量,不仅是相关的费米和赫斯II,但也为下一代的望远镜,如CTA和伽玛-400。还讨论了来自遗迹丰度、直接探测和碰撞器边界的约束。

英文摘要:

The era of indirect detection searches for dark matter has begun, with the sensitivities of gamma-ray detectors now approaching the parameter space relevant for weakly interacting massive particles. In particular, gamma ray lines would be smoking gun signatures of dark matter annihilation, although they are typically suppressed compared to the continuum. In this paper, we pay particular attention to the 1-loop continuum generated together with the gamma-ray lines and investigate under which conditions a dark matter model can naturally lead to a line signal that is relatively enhanced. We study generic classes of models in which DM is a fermion that annihilates through an s-channel mediator which is either a vector or scalar and identify the coupling and mass conditions under which large line signals occur. We focus on the "forbidden channel mechanism" advocated a few years ago in the "Higgs in space" scenario for which tree level annihilation is kinematically forbidden today. Detailed calculations of all 1-loop annihilation channels are provided. We single out very simple models with a large line over continuum ratio and present general predictions for a large range of WIMP masses that are relevant not only for Fermi and Hess II but also for the next generation of telescopes such as CTA and Gamma-400. Constraints from the relic abundance, direct detection and collider bounds are also discussed.

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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