Space-point calibration of the ALICE TPC with track residuals
Space-point calibration of the ALICE TPC with track residuals
复制标题
使用轨迹残差对 ALICE TPC 进行空间点校准
作者：
M. Schmidt
在LHC运行3中，从2021年开始，ALICE实验的升级后的时间投影室（TPC）将以连续读出模式记录最小偏压Pb-Pb碰撞，相互作用速率高达50 kHz。这对应于在检测器中的电子漂移时间期间典型地4-5次重叠碰撞。尽管对新的基于四重GEM的读出室进行了仔细的调整，以满足低于1%的离子回流的设计要求，但这些条件将导致几厘米的空间电荷失真，并随时间波动。它们将通过校准程序进行校正，该校准程序分别使用位于TPC内部的内部跟踪系统（ITS）以及位于TPC周围的跃迁辐射探测器（TRD）和飞行时间系统（TOF）的信息。通过使用这样的过程，可以恢复几百微米的TPC的固有磁道分辨率。
提出了基于卡尔曼滤波器的TRD在线跟踪算法。该过程利用GPU将外推的ITS-TPC轨迹与TRD空间点相匹配。随后，忽略TPC信息来重新拟合这些全局轨迹。TPC簇的残差到重新拟合的轨道的内插被用于创建空间电荷失真的映射。地图的定期更新补偿TPC条件的变化。在数据的最终重建中应用该映射。将显示跟踪算法的第一性能结果。
In the LHC Run 3, starting in 2021, the upgraded Time Projection Chamber (TPC) of the ALICE experiment will record minimum bias Pb–Pb collisions in a continuous readout mode at an interaction rate up to 50 kHz. This corresponds to typically 4-5 overlapping collisions during the electron drift time in the detector. Despite careful tuning of the new quadruple GEM-based readout chambers, which fulfill the design requirement of an ion backflow below 1%, these conditions will lead to space-charge distortions of several centimeters that fluctuate in time. They will be corrected via a calibration procedure that uses the information of the Inner Tracking System (ITS), which is located inside, and the Transition Radiation Detector (TRD) and Time-Of-Flight system (TOF), located around the TPC, respectively. By using such a procedure the intrinsic track resolution of the TPC of a few hundred micrometers can be restored.
The required online tracking algorithm for the TRD, which is based on a Kalman filter, is presented. The procedure matches extrapolated ITS-TPC tracks to TRD space-points utilizing GPUs. Subsequently these global tracks are refitted neglecting the TPC information. The residuals of the TPC clusters to the interpolation of the refitted tracks are used to create a map of spacecharge distortions. Regular updates of the map compensate for changes in the TPC conditions. The map is applied in the final reconstruction of the data. First performance results of the tracking algorithm will be shown.
影响因子：
8.6
作者：
Abelev, B.;Adam, J.;Zyzak, M.
通讯作者：
Zyzak, M.