论文标题
用CMD-3检测器的液体氙量热仪的带电颗粒鉴定
Charged particle identification with the liquid xenon calorimeter of the CMD-3 detector
论文作者
论文摘要
本文描述了一种为\ mbox {cmd-3}检测器开发的带电粒子标识的方法，该方法安装在VEPP-2000 $ e^{+} e^{ - } $ collider上。该方法基于增强决策树分类器的应用，该分类器在动量中接受了电子，MUON，PION和KAON的最佳分离训练，范围从100到$ 1200〜 {\ rm Mev}/c $。分类器的输入变量是\ Mbox {CMD-3}的12层带电颗粒的能量沉积的线性组合。用于分类器训练的事件样本是从模拟中获取的。考虑到量热计带通道的模拟和校准中检测器响应调整的各种问题。该方法的应用由$ e^+e^ - （γ）$和$π^+π^ - （γ）$最终状态以及$ k^+k^ - 最终状态的选择。
The paper describes a method of the charged particle identification, developed for the \mbox{CMD-3} detector, installed at the VEPP-2000 $e^{+}e^{-}$ collider. The method is based on the application of the boosted decision trees classifiers, trained for the optimal separation of electrons, muons, pions and kaons in the momentum range from 100 to $1200~{\rm MeV}/c$. The input variables for the classifiers are linear combinations of the energy depositions of charged particles in 12 layers of the liquid xenon calorimeter of the \mbox{CMD-3}. The event samples for training of the classifiers are taken from the simulation. Various issues of the detector response tuning in simulation and calibration of the calorimeter strip channels are considered. Application of the method is illustrated by the examples of separation of the $e^+e^-(γ)$ and $π^+π^-(γ)$ final states and of selection of the $K^+K^-$ final state at high energies.
