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arXiv 2610.13634hep-exphysics.ins-det
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一种用于估计被误判为强子化τ轻子衰变的喷注本底的机器学习方法

A machine-learning method for the estimation of the background from jets misidentified as hadronic tau lepton decays

CERN（欧洲核子研究组织）

CMS Collaboration

备注：
Submitted to the Journal of Instrumentation. All figures and tables can be found at http://cms-results.web.cern.ch/cms-results/public-results/publications/TAU-25-001 (CMS Public Pages)
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AI总结：

针对喷注被误判为强子化τ轻子衰变的本底问题，提出MUFFIN机器学习方法，利用CMS实验数据验证其可降低70%相关系统不确定度，适用于τ轻子相关的精确测量与新物理搜索。

摘要：

由夸克和胶子引发的喷注被误判为强子化τ轻子衰变产生的本底，是涉及τ轻子的分析中面临的主要实验挑战。本文提出了多变量假因子推断（MUFFIN）方法，这是一种直接从观测事件中估计该本底的机器学习方法。该方法采用提升决策树重加权，直接从观测数据中学习多维、逐对象的修正因子，从而在运动学和拓扑相空间中对喷注到强子化τ轻子的误判概率进行建模，无需依赖低维参数化。利用欧洲核子研究中心大型强子对撞机（LHC）的CMS实验采集的质心系能量√s=13.6 TeV的质子-质子碰撞数据（对应积分亮度为62.4 fb⁻¹）开展性能研究。与低维参数化方法相比，该方法实现了对关键运动学可观测量的更优建模，尤其在高横动量（p_T）区域表现突出。这种更优的建模使得与喷注被误判为强子化τ轻子衰变相关的系统不确定度降低了多达70%。MUFFIN方法为涉及τ轻子末态的精确测量和超出标准模型的物理现象搜索提供了一种稳健且可扩展的本底估计方法。

英文摘要：

Backgrounds arising from quark- and gluon-initiated jets misidentified as hadronically decaying tau leptons constitute a major experimental challenge for analyses involving tau leptons. The MUltivariate Fake-Factor INference (MUFFIN) approach, a machine-learning-based method for estimating this background directly from observed events, is presented. Boosted decision tree reweighting is used to learn multidimensional, per-object correction factors directly from observed data, thereby modelling the jet to hadronic tau lepton misidentification probability across the kinematic and topological phase space without relying on low-dimensional parametrisations. Performance studies are presented using proton-proton collision data collected by the CMS experiment at the CERN LHC at $\sqrt{s}$ = 13.6 TeV, corresponding to an integrated luminosity of 62.4 fb$^{-1}$. Compared to low-dimensional parametrisation methods, improved modelling of key kinematic observables is achieved, particularly in regions of high $p_\mathrm{T}$. The improved modelling leads to a reduction of up to 70% in the systematic uncertainty associated with jets being misidentified as hadronically decaying tau leptons. The MUFFIN method provides a robust and scalable method for background estimation in precision measurements and searches for beyond-the-standard-model physics involving tau lepton final states.

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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