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A cluster-finding algorithm for free-streaming data

机译:一种用于自由流数据的聚类查找算法

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In position-sensitive detectors with segmented readout (pixels or strips), charged particles activate in general several adjacent read-out channels. The first step in the reconstruction of the hit position is thus to identify clusters of active channels associated to one particle crossing the detector. In conventionally triggered systems, where the association of raw data to events is given by a hardware trigger, this is an easy-to-solve problem. It, however, becomes more involved in untriggered, free-streaming read-out systems like the one employed by the CBM experiment. Here, the time coordinate of the single-channel measurement must be taken into account to decider whether neighbouring active channels belong to a cluster. A simple extension of well-known cluster finding algorithms is not satisfactory because of involving increasing combinatorics, which are prohibitive for reconstruction in real-time. In this article, a cluster-finding solution for the Silicon Tracking System of the CBM experiment is presented which avoids any combinatorics or loops over detector channels. Its execution time is thus independent on the size of the data packages (time slices) delivered by the data acquisition, making it suitable for being used in online reconstruction.
机译:在具有分段读出(像素或条带)的位置敏感检测器中,带电粒子通常会激活几个相邻的读出通道。因此,命中位置的重建的第一步是识别与穿过检测器的一个粒子相关的有效通道的簇。在常规触发的系统中,原始数据与事件的关联由硬件触发器提供,这是一个易于解决的问题。但是,它越来越涉及未触发的,自由流式的读出系统,例如CBM实验所采用的系统。在此,必须考虑单通道测量的时间坐标,以确定相邻的活动通道是否属于一个集群。由于涉及不断增加的组合技术,而不能实时重建,因此对众所周知的聚类发现算法的简单扩展并不令人满意。在本文中,提出了一种用于CBM实验的硅跟踪系统的集群查找解决方案,该解决方案避免了任何组合器或探测器通道上的环路。因此,其执行时间与数据采集所传递的数据包(时间片)的大小无关,从而使其适合用于在线重建。

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