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最小化事件大小,最大化物理:包括LHCb第三次运行中的粒子隔离

Marta Calvi¹, Tommaso Fulghesu², George Hallett³

¹University of Milan-Bicocca, Milan, Italy.

The European physical journal. C, Particles and fields

|March 12, 2026

概括

一个新的包含多变量隔离 (IMI) 算法显著减少了45%的LHCb事件数据大小,同时保持了高物理性能. 这种方法有效地选择信号粒子,对于大型强子对撞机的重味物理至关重要.

科学领域:

高能粒子物理学高能粒子物理学
检测器数据处理数据处理.
计算物理学的计算物理.

背景情况:

大强子对撞机 (LHC) 运行3产生了巨大的数据量,挑战了探测器事件重建.
带电粒子信息占事件大小的大部分,需要减少数据.
强烈的物理课程需要有效的事件选择,而不会影响物理的范围.

研究的目的:

开发和验证LHCb.的新型数据减少技术.
为了解决LHC碰撞中高粒子多样性引起的数据大小不平衡.
为了提高重味物理事件重建的效率和稳定性.

主要方法:

开发一套包容性隔离工具,包括经典方法和一个新的包容性多变量隔离 (IMI) 算法.
IMI算法统一了传统隔离技术的优势,用于对各种衰变拓和动力学进行强大的处理.
在现实条件下对运行3 LHCb 数据IMI算法的验证.

主要成果:

通过只保留基本粒子,IMI算法实现了事件数据大小减少45%.
信号粒子以99%的效率被选择,在背景排斥方面表现优于传统方法.
在各种衰变通道和事件多重性中,IMI表现出卓越的性能.

结论:

IMI算法是一种强大而有效的方法,用于降低高能物理实验中的事件数据大小.
它保留了重要的物理信息,使得有效的重味物理分析成为可能.
在高亮度LHC环境中,IMI为数据选择提供了潜在的长期解决方案.

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