论文标题
纠正SID硅螺旋体ecal中的泄漏能量
Correcting for Leakage Energy in the SiD Silicon-Tungsten ECal
论文作者
论文摘要
对高能量（例如100 GEV）在高能量下的ECAL分辨率的主要贡献来自量量超出量热计的泄漏。我们已经研究了SID硅 - 丁香ECAL的泄漏能量，并开发了一种神经网络算法，用于估计泄漏能量并纠正能量测量。 SID TDR设计需要20个薄2.5毫米钨层，然后使用10厚的5.0毫米钨层。我们已经研究了对减少层数量的泄漏能量的影响，以及优化的中性网络分析能够以减少层数减少的泄漏以及材料厚度降低的能力。减少层数是由成本遏制的动机。
A dominant contribution to ECal resolution at high energy (eg. 100 GeV) comes from leakage beyond the containment of the calorimeter. We have studied the leakage energy for the SiD silicon-tungsten ECal and developed a neural network algorithm for estimating the leakage energy and correcting the energy measurement. The SiD TDR design calls for 20 thin 2.5 mm tungsten layers followed by 10 thick 5.0 mm tungsten layers. We have investigated the impact on the leakage energy of a reduced number of layers, and the ability of an optimized neutral network analysis to correct for the leakage with a reduced number of layers, and reduced material thickness. Reducing layer numbers is motivated by cost containment.
