Progress in developing a hybrid deep learning algorithm for identifying and locating primary vertices
Progress in developing a hybrid deep learning algorithm for identifying and locating primary vertices
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用于识别和定位主要顶点的混合深度学习算法的开发进展
DOI：
10.1051/epjconf/202125104012
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发表时间：
2021
影响因子：
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通讯作者：
Williams, Mike
中科院分区：
文献类型：
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作者：
Akar, Simon;Atluri, Gowtham;Boettcher, Thomas;Peters, Michael;Schreiner, Henry;Sokoloff, Michael;Stahl, Marian;Tepe, William;Weisser, Constantin;Williams, Mike
大型强子对撞机实验中质子-质子碰撞点的位置称为主顶点（PV）。用于识别和定位这些物质的混合深度学习算法（针对 LHCb 的 Run 3 化身）的初步结果已在 2019 年和 2020 年的会议上进行了描述。在过去的一年中，我们在多个相关领域取得了重大进展。使用两个较新的核密度估计器 (KDE) 作为输入特征集可以提高模型的保真度，就像使用完整的 LHCb 模拟而不是最初（并且仍然）用于开发模型的“玩具蒙特卡罗”一样。我们还建立了一个深度学习模型来根据赛道信息计算 KDE。将 Tracks-to-KDE 模型连接到用于查找 PV 的 KDE-to-hists 模型提供了一个概念验证，即单个深度学习模型可以使用跟踪信息以高效率和高保真度查找 PV。我们系统地研究了各种模型，以了解其架构的变化如何影响性能。虽然这里报告的研究特定于 LHCb 几何结构和操作条件，但结果表明 ATLAS 和 CMS 实验可以使用相同的方法。
The locations of proton-proton collision points in LHC experiments are called primary vertices (PVs). Preliminary results of a hybrid deep learning algorithm for identifying and locating these, targeting the Run 3 incarnation of LHCb, have been described at conferences in 2019 and 2020. In the past year we have made significant progress in a variety of related areas. Using two newer Kernel Density Estimators (KDEs) as input feature sets improves the fidelity of the models, as does using full LHCb simulation rather than the “toy Monte Carlo” originally (and still) used to develop models. We have also built a deep learning model to calculate the KDEs from track information. Connecting a tracks-to-KDE model to a KDE-to-hists model used to find PVs provides a proof-of-concept that a single deep learning model can use track information to find PVs with high efficiency and high fidelity. We have studied a variety of models systematically to understand how variations in their architectures affect performance. While the studies reported here are specific to the LHCb geometry and operating conditions, the results suggest that the same approach could be used by the ATLAS and CMS experiments.
LHC Run 3 的 ATLAS 主要顶点重建开发
DOI：
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发表时间：
2019
期刊：
影响因子：
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作者：
I. Sanderswood
通讯作者：
I. Sanderswood
DOI：
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发表时间：
2011
期刊：
影响因子：
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作者：
Sumimoto H;Minakami R;Miyano K
通讯作者：
Miyano K