论文标题
使用明确的概况可能性更快地找到暗物质
Finding Dark Matter Faster with Explicit Profile Likelihoods
论文作者
论文摘要
液体氙气对腔室是世界上最敏感的探测器，用于广泛的暗物质候选者。我们表明，可以通过以同等的确定性计算替换检测器响应蒙特卡洛模拟来改进其数据的统计分析。这允许使用高维的未保留模型，最多可产生$ \ sim \！ 2 $倍更好地歧视主要背景。反过来，这可能会大大扩大诸如Xenonnt和LZ之类的实验的物理覆盖范围，并将潜在的$5σ$暗物质发现提升到一年多。
Liquid xenon time-projection chambers are the world's most sensitive detectors for a wide range of dark matter candidates. We show that the statistical analysis of their data can be improved by replacing detector response Monte Carlo simulations with an equivalent deterministic calculation. This allows the use of high-dimensional undiscretized models, yielding up to $\sim\! 2$ times better discrimination of the dominant backgrounds. In turn, this could significantly extend the physics reach of upcoming experiments such as XENONnT and LZ, and bring forward a potential $5 σ$ dark matter discovery by over a year.
