论文标题
使用GPU的MU3E的在线活动选择
Online Event Selection for Mu3e using GPUs
论文作者
论文摘要
在搜索超出标准模型的物理学时，MU3E实验试图观察Lepton风味违反衰减$μ^+ \ rightarrow E^+ E^+ E^ - e^+ $。通过观察$ 1 \ cdot 10^8μ$/s的衰减产物，其目的是观察该过程，或者对其估计的分支比率设定新的上限。高个子率导致高数据速率为$ 80 $ \，Gbpps，由通过背景过程产生的数据主导。我们介绍在线活动选择，这是在$ 12 $ MU3E滤清器农场计算机的图形处理单元（GPU）上运行的三个步骤算法。 通过使用简单而快速的几何选择标准，该算法首先将可能的事件候选者的量减少到初始集合的$ 5 \％$以下。然后，这些候选人用于重建完整的粒子轨道，正确地重建了超过$ 97 \％的信号轨道。最后，使用简单的几何考虑而不是完整的重建来重建一个可能的衰减顶点，并正确识别了$ 94 \％$ $的信号事件。 我们还提供了算法的全面实施，以目标的amuon速率满足了所有绩效要求，并成功地将数据速率降低了200美元。
In the search for physics beyond the Standard Model the Mu3e experiment tries to observe the lepton flavor violating decay $μ^+ \rightarrow e^+ e^- e^+$. By observing the decay products of $1 \cdot 10^8μ$/s it aims to either observe the process, or set a new upper limit on its estimated branching ratio. The high muon rates result in high data rates of $80$\,Gbps, dominated by data produced through background processes. We present the Online Event Selection, a three step algorithm running on the graphics processing units (GPU) of the $12$ Mu3e filter farm computers. By using simple and fast geometric selection criteria, the algorithm first reduces the amount of possible event candidates to below $5\%$ of the initial set. These candidates are then used to reconstruct full particle tracks, correctly reconstructing over $97\%$ of signal tracks. Finally a possible decay vertex is reconstructed using simple geometric considerations instead of a full reconstruction, correctly identifying over $94\%$ of signal events. We also present a full implementation of the algorithm, fulfilling all performance requirements at the targeted muon rate and successfully reducing the data rate by a factor of $200$.
