The search for charged particle tracks in detectors with linear sensing elements, such as wire chambers, strip silicon detectors etc., starts with identification of straight track segments. The latter are deduced by constructing all possible combinations of activated detector elements. In the high multiplicity environment, with many activated detector elements, this causes large combinatorics and significantly reduces the performance of the track finding algorithms. In this report we trace this problem back to determination of the parameters of a straight line build from a number of skew lines (sensing elements of a detector) in space. Based on the intersection points of two hyperbolas, we demonstrate an analytic solution in the case of four skew detector elements.The procedure can also be applied as a first approximation to the more general case of curved track finding.
NuMI离轴现象（英语：NuMI Off-Axis v Appearance，缩写：NOvA）实验是一个长基线中微子振荡实验，使用的是费米实验室的NuMI光束线产生的中微子源。该实验将使用两个功能相同的塑料液体闪烁体填充探测器研究μ子中微子到电子中微子的振荡，该探测器放置在离轴14毫弧度的NuMI光束上。带电中微子相互作用将被用来观察中微子味从识别的最终状态轻子。μ子带电粒子径迹的重建在探测器对准和校准的短期目标以及通过识别μ子带电电流事件的长期振荡分析中起着重要作用。提出了一种基于卡尔曼滤波的μ子径迹识别和径迹拟合的初步方法。
Impact of Cold Noise on the tracking performance of ATLAS ITk short strip barrel modules using a charged particle beam
Santa Cruz Institute for Particle Physics, University of California Santa Cruz（加州大学圣克鲁兹分校圣克鲁兹粒子物理研究所）；Deutsches Elektronen-Synchrotron DESY（德国电子同步加速器中心）；Lunds universitet（隆德大学）；University of Birmingham（伯明翰大学）；Charles University（查理大学）；Rutherford Appleton Laboratory（卢瑟福阿普尔顿实验室）；University of British Columbia（不列颠哥伦比亚大学）；TRIUMF（特里姆夫实验室）
Graph Neural Networks for Charged Particle Tracking on FPGAs
University of Pennsylvania（宾夕法尼亚大学）；University of California San Diego（加州大学圣地亚哥分校）；National Yang Ming Chiao Tung University（国立阳明交通大学）；University of Illinois at Urbana-Champaign（伊利诺伊大学厄巴纳-香槟分校）；Princeton University（普林斯顿大学）；University of Washington（华盛顿大学）
Charged particle tracking without magnetic field: optimal measurement of track momentum by a Bayesian analysis of the multiple measurements of deflections due to multiple scattering
Accelerated Charged Particle Tracking with Graph Neural Networks on FPGAs
University of California San Diego（加州大学圣地亚哥分校）；Princeton University（普林斯顿大学）；University of Illinois at Urbana-Champaign（伊利诺伊大学厄巴纳-香槟分校）；Fermi National Accelerator Laboratory（费米国家加速器实验室）；Massachusetts Institute of Technology（麻省理工学院）；Institute of Physics Belgrade（贝尔格莱德物理研究所）；European Organization for Nuclear Research (CERN)（欧洲核子研究组织（CERN））；California Institute of Technology（加州理工学院）；Purdue University（普渡大学）；HawkEye360；University of Illinois at Chicago（伊利诺伊大学芝加哥分校）
Physics Informed Neural Networks for design optimisation of diamond particle detectors for charged particle fast-tracking at high luminosity hadron colliders
Istituto Nazionale di Fisica Nucleare, Sezione di Firenze（意大利佛罗伦萨核物理研究所）；ICSC - Centro Nazionale di Ricerca in High Performance Computing, Big Data & Quantum Computing（高性能计算、大数据与量子计算国家研究中心）
