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Another Approach to Track Reconstruction: Cluster Analysis

机译:跟踪重建的另一种方法:聚类分析

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A novel combination of data analysis techniques is introduced for the reconstruction of primary charged particles and of daughters of photon conversions, created in high energy collisions. Instead of performing a classical trajectory building or an image transformation, efficient use of both local and global information is undertaken while keeping competing choices open. The measured hits in silicon-based tracking detectors are clustered with the help of a k -medians clustering. It proceeds by alternating between the hit-to-track assignment and the track-fit update steps, until convergence. The clustering is complemented with the possibility of adding new track hypotheses or removing unnecessary ones. A simplified model of a silicon tracker is employed to test the performance of the proposed method, showing good efficiency and purity characteristics.
机译:引入了一种新的数据分析技术组合,用于重建在高能碰撞中产生的初级带电粒子和光子转换子代。与其进行经典的轨迹构建或图像转换,不如进行局部和全局信息的有效利用,同时保持开放的竞争选择。借助k中值聚类,对基于硅的跟踪检测器中测得的命中进行聚类。它通过在命中至曲目分配和曲目适合更新步骤之间交替进行,直到收敛。聚类还可以添加新的轨迹假设或删除不必要的轨迹假设。硅跟踪器的简化模型用于测试所提出方法的性能,显示出良好的效率和纯度特性。

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