Using machine learning to separate hadronic and electromagnetic interactions in the GlueX forward calorimeter
Using machine learning to separate hadronic and electromagnetic interactions in the GlueX forward calorimeter
复制标题
使用机器学习分离 GlueX 正向热量计中的强子和电磁相互作用
DOI：
10.1088/1748-0221/15/05/p05021
复制
发表时间：
2020
影响因子：
1.3
通讯作者：
Shepherd, M.R.
中科院分区：
文献类型：
--
作者：
Barsotti, R.;Shepherd, M.R.
前向量热计是一个由2800个铅玻璃模块组成的阵列，用于探测强子衰变中产生的光子。这个过程的背景来自量热计中的强子相互作用，在某些情况下，很难与低能光子相互作用区分开来。将机器学习技术应用于GSTX前向量热计中粒子相互作用的分类。这些算法使用ω介子的衰变数据进行训练，ω介子包含与量热计相互作用的真实光子和带电粒子。算法的效率，误报率，运行时间和实现复杂性进行了评估。一种利用多层感知器神经网络的算法被部署在GSPEX软件栈中，并为中间质量约束的包含π 0数据样本提供85%的信号效率和60%的背景抑制。
The GlueX forward calorimeter is an array of 2800 lead glass modules that was constructed to detect photons produced in the decays of hadrons. A background to this process originates from hadronic interactions in the calorimeter, which, in some instances, can be difficult to distinguish from low energy photon interactions. Machine learning techniques were applied to the classification of particle interactions in the GlueX forward calorimeter. The algorithms were trained on data using decays of the ω meson, which contain both true photons and charged particles that interact with the calorimeter. Algorithms were evaluated on efficiency, rate of false positives, run time, and implementation complexity. An algorithm that utilizes a multi-layer perceptron neural net was deployed in the GlueX software stack and provides a signal efficiency of 85% with a background rejection of 60% for an inclusive π 0 data sample for an intermediate quality constraint.
使用电子束测量 GlueX 正向热量计的能量和时间分辨率
DOI：
10.1016/j.nima.2013.05.109
发表时间：
2013
影响因子：
1.4
作者：
K. Moriya;J. Leckey;M. Shepherd;K. Bauer;D. Bennett;J. Frye;J. González;S. Henderson;D. Lawrence;R. Mitchell;E. Smith;Paul Smith;A. Somov;H. Egiyan
通讯作者：
H. Egiyan
铅玻璃热量计增益校准和分辨率确定的自举法
DOI：
10.1016/j.nima.2006.07.061
发表时间：
2006
影响因子：
1.4
作者：
R. Jones;M. Kornicer;A. Dzierba;J. Gunter;R. Lindenbusch;E. Scott;P. Smith;C. Steffen;S. Teige;P. Rubin;E. Smith
通讯作者：
E. Smith