论文标题
将通配符应用于FTK模式库的残疾模块对效率和数据流的影响
The impact of applying WildCards to disabled modules for FTK pattern banks on efficiency and data flow
论文作者
论文摘要
在线选择是从大型强子对撞机（LHC）的Atlas探测器内部大量碰撞中收集最相关的碰撞的重要步骤。快速跟踪器（FTK）是一个基于硬件的轨道查找器，旨在大大提高Atlas触发系统功能，以通过基于轨道的签名来识别有趣的物理过程。在每个级别1触发所有轨道之后，FTK正在重建所有轨道，$ p _ {\ textrm t}> 1 $ GEV，因此高级触发系统在早期阶段就可以访问跟踪信息。 FTK轨道重建从模式识别步骤开始。在八分之七的可能的检测层中发现了模式。 在LHC操作中经常遇到的残疾探测器模块会导致效率损失。为了恢复效率，在FTK系统中实现了通配符（WC）算法。 WC算法恢复了效率低下，但也会引起高组合背景，从而增加了FTK系统中的数据量，可能会超过硬件限制。为了克服这一点，在本文中开发和研究了精制算法以选择模式。
Online selection is an essential step to collect the most relevant collisions from the very large number of collisions inside the ATLAS detector at the Large Hadron Collider (LHC). The Fast TracKer (FTK) is a hardware based track finder, built to greatly improve the ATLAS trigger system capabilities for identifying interesting physics processes through track-based signatures. The FTK is reconstructing after each Level-1 trigger all tracks with $ p_{\textrm T}>1 $ GeV, such that the high-level trigger system gains access to track information at an early stage. FTK track reconstruction starts with a pattern recognition step. Patterns are found with hits in seven out of eight possible detector layers. Disabled detector modules, as often encountered during LHC operation, lead to efficiency losses. To recover efficiency, WildCards (WC) algorithms are implemented in the FTK system. The WC algorithm recovers inefficiency but also causes high combinatorial background and thus increased data volumes in the FTK system, possibly exceeding hardware limitations. To overcome this, a refined algorithm to select patterns is developed and investigated in this article.
