Calibration samples to measure particle identification performance in the LHCb experiment

在发表的新作品中EPJ技术和仪器, Marianna Fontana and Donal Hilldescribe the methodto create calibration samples that help determine the accuracy of the detector in the Large Hadron Collider beauty experiment in identifying different particles.

这篇文章已经从SpringerOpen blog

在CERN的大型强子对撞机的地下深处,质子的光束几乎以光速在碰撞之前,以圆形的速度绕着。这些高能量碰撞会产生大量的短寿命颗粒,这些颗粒迅速腐烂成更轻,更稳定的颗粒。研究这些粒子衰变使物理学家可以瞥见宇宙的早期历史。

Capturing information about high-energy particle decays is a huge technological challenge, which requires the use of a vast 3D detector built around the collision point. As particles are produced and travel through the detector, they leave traces of their presence behind. Since particles are too tiny to be seen by eye, scientists must measure and interpret these traces in order to determine their identities.

Understanding precisely how well a detector can differentiate between different particles is vital for any particle physics experiment

痕迹提供的粒子识别(PID)信息充当每个粒子的护照照片。不同的颗粒具有相当不同的PID护照。例如,电子及其沉重的表亲妈妈留下的痕迹看起来彼此不同。

Particles made of quarks, such a pions and kaons, can also be distinguished well by the detector, even though their traces are more similar. Understanding precisely how well a detector can differentiate between different particles is vital for any particle physics experiment. At the Large Hadron Collider beauty experiment (LHCb), this process is called PID calibration.

测量粒子识别精度

To measure the PID accuracy, one must start with samples of particles whose identities are known without looking at their PID passports. Special types of particle decays, which can be reconstructed, selected, and stored in real time without the use of PID information, provide just such samples.

Thousands of these decays occur every second at LHCb, and it is important to be able to select them quickly while rejecting a large number of background events. This is achieved by selecting the calibration samples using the LHCb trigger framework, which reconstructs the decays using high quality algorithms, such that the data are immediately usable in subsequent analysis.

使用这些PID校准样品,可以精确测量LHCB在区分粒子类型时的良好方式。

It is crucial to measure this performance accurately when making physics measurements

例如,可以将PID要求应用于MUON的校准样本,并计算通过此要求的MUON的百分比;这是PID效率。人们还可以将相同的PID要求应用于PION的校准样品,并计算错误地识别为MUON的乳头的百分比;这是错误识别率。综上所述,PID效率和错误识别率定义了PID性能。

It is crucial to measure this performance accurately when making physics measurements, for example in the search for the extremely rare B-meson decay Bs0to μ+μ。该衰减涉及两种muons,并且必须在很高的水平上拒绝包含硫酸酯的背景,以隔离并正确识别信号。

Our approach

没有出色的PID性能,LHCB将无法在风味物理领域进行世界领先的测量

In the study published inEPJ技术和仪器,we presentthe strategy used for the trigger selection and processing of PID calibration samples during Run 2 of the LHCb experiment (2015-2018). We describe the framework used to statistically subtract background events from the selected calibration samples, in order to provide analysts with pure samples of decays that can be used to measure the PID performance. Python-based tools have been made available to all LHCb analysts, enabling them to easily measure PID efficiencies and misidentification rates. This ensures continuity of the approach across many different physics measurements.

如果没有出色的PID性能,LHCB将无法在风味物理领域进行世界领先的测量。在运行2期间实施的PID校准框架将继续为LHCB提供良好的升级时代,在该时代,数据将比以往任何时候都以更高的能量和速率收集数据。我们希望我们的论文中描述的工作将有助于保证LHCB的多年高质量物理学结果。

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