English(EN) Mono-Z Dark Matter Search with Neural Spline Flows Using CMS Run 2015D Open Data

暗物质搜索在CMS数据上使用神经样条流

作者 PulseAugur 编辑部 · [2 个来源] · 2026-07-15 12:31

研究人员使用CMS 2015D开放数据，对与Z玻色子联合产生的暗物质进行了搜索。该研究采用神经样条流来模拟背景和信号密度，将观测数据降维到37维特征向量。虽然分析未发现暗物质证据，但为标量、矢量和轴矢量介子的信号强度参数设定了上限，并指出由于背景建模差异，观测到的上限弱于预期。 AI

影响该研究将先进的机器学习技术，特别是神经样条流，应用于粒子物理数据，有可能为复杂科学领域的更复杂分析铺平道路。

排序理由该集群包含一篇详细介绍科学研究方法和发现的arXiv论文。

AI 生成摘要 · Google Gemini · 来自 2 个来源。我们如何撰写摘要 →

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arXiv cs.LG TIER_1 English(EN) · Hitesh Rasineni (VIT-AP University, Amaravati, India), Bhavishya Chebrolu (Mohan Babu University, Tirupati, India) · 2026-07-16 04:00

使用CMS 2015D开放数据，通过神经样条流进行Mono-Z暗物质搜索

arXiv:2607.13771v1 Announce Type: new Abstract: We report a search for dark matter (DM) produced in association with a leptonically decaying \(Z\) boson at \(\sqrt{s}=13\) TeV using CMS Run 2015D open data corresponding to an integrated luminosity of \(2.32\,\mathrm{fb}^{-1}\) to…
arXiv cs.LG TIER_1 English(EN) · Bhavishya Chebrolu · 2026-07-15 12:31

使用 CMS 2015D 开放数据，通过神经样条流进行 Mono-Z 暗物质搜索

We report a search for dark matter (DM) produced in association with a leptonically decaying \(Z\) boson at \(\sqrt{s}=13\) TeV using CMS Run 2015D open data corresponding to an integrated luminosity of \(2.32\,\mathrm{fb}^{-1}\) together with simplified-model Monte Carlo simulat…