A novel robust and efficient algorithm for charge particle tracking in high background flux

16th International workshop on Advanced Computing and Analysis Techniques in physics research

物理学;计算机科学

Fanelli, C.^1,2 ; Cisbani, E.^2 ; Dotto, A Del^3

Dipartimento di Fisica, Università la Sapienza, Rome

I-00185, Italy^1

INFN, Sezione di Roma, Istituto Superiore di Sanità, Rome

I-00161, Italy^2

Dept. of Phys. and Math. Univ. of Rome Roma Tre, INFN, Sezione di Roma Tre, Rome

I-00146, Italy^3

关键词: Gaseous electron multipliers;    High-energy particles;    Multi-step approaches;    Neural network (nn);    Particle tracking;    Physics experiments;    Rauch-tung-striebel smoothers;    Tracking algorithm;   

Others  :  https://iopscience.iop.org/article/10.1088/1742-6596/608/1/012053/pdf
DOI  :  10.1088/1742-6596/608/1/012053

学科分类：计算机科学（综合）

来源: IOP

【 摘 要 】

The high luminosity that will be reached in the new generation of High Energy Particle and Nuclear physics experiments implies large high background rate and large tracker occupancy, representing therefore a new challenge for particle tracking algorithms. For instance, at Jefferson Laboratory (JLab) (VA,USA), one of the most demanding experiment in this respect, performed with a 12 GeV electron beam, is characterized by a luminosity up to 1039cm-2s-1. To this scope, Gaseous Electron Multiplier (GEM) based trackers are under development for a new spectrometer that will operate at these high rates in the Hall A of JLab. Within this context, we developed a new tracking algorithm, based on a multistep approach: (i) all hardware - time and charge - information are exploited to minimize the number of hits to associate; (ii) a dedicated Neural Network (NN) has been designed for a fast and efficient association of the hits measured by the GEM detector; (iii) the measurements of the associated hits are further improved in resolution through the application of Kalman filter and Rauch- Tung-Striebel smoother. The algorithm is shortly presented along with a discussion of the promising first results.