论文标题
沙丘的tau中微子：新策略，新机会
Tau neutrinos at DUNE: new strategies, new opportunities
论文作者
论文摘要
我们提出了一种新的分析策略，该策略利用了沙丘实验的独特能力来研究tau中微子。我们将撞机物理思想（例如，与机器学习技术结合使用的JET聚集算法）整合到中微子测量中。通过构建一组可观察的物品和运动学削减，我们在后台（$ b $）获得了对信号（$ s $）的优越歧视。在一年中，使用名义中微子束模式，沙丘可以分别为tau的耐药和松弛衰减频道而实现$ 3.3 $和$ 2.3 $的$ s/\ sqrt {b} $。在tau优化的光束模式下运行将增加$ s/\ sqrt {b} $到$ 8.8 $，每个渠道中的$ 11 $。我们首映的是使用分析软件铆钉，这是LHC实验在中微子物理学中普遍使用的工具。对于更广泛的可访问性，我们提供分析代码。
We propose a novel analysis strategy, that leverages the unique capabilities of the DUNE experiment, to study tau neutrinos. We integrate collider physics ideas, such as jet clustering algorithms in combination with machine learning techniques, into neutrino measurements. Through the construction of a set of observables and kinematic cuts, we obtain a superior discrimination of the signal ($S$) over the background ($B$). In a single year, using the nominal neutrino beam mode, DUNE may achieve $S/\sqrt{B}$ of $3.3$ and $2.3$ for the hadronic and leptonic decay channels of the tau respectively. Operating in the tau-optimized beam mode would increase $S/\sqrt{B}$ to $8.8$ and $11$ for each of these channels. We premier the use of the analysis software Rivet, a tool ubiquitously used by the LHC experiments, in neutrino physics. For wider accessibility, we provide our analysis code.
