A New Track Reconstruction Algorithm suitable for Parallel Processing based on Hit Triplets and Broken Lines

TL;DR

This paper introduces a fast, parallelizable track reconstruction algorithm based on hit triplets, incorporating a 3D fit model with multiple scattering, suitable for high-rate particle physics experiments.

Contribution

A novel hit triplet-based track reconstruction method that is highly parallelizable and includes a comprehensive 3D fit model with multiple scattering from the start.

Findings

Requires fewer operations than standard methods

Highly parallelizable and suitable for modern architectures

Validated in Mu3e and LHC experiment contexts

Abstract

Track reconstruction in high track multiplicity environments at current and future high rate particle physics experiments is a big challenge and very time consuming. The search for track seeds and the fitting of track candidates are usually the most time consuming steps in the track reconstruction. Here, a new and fast track reconstruction method based on hit triplets is proposed which exploits a three-dimensional fit model including multiple scattering and hit uncertainties from the very start, including the search for track seeds. The hit triplet based reconstruction method assumes a homogeneous magnetic field which allows to give an analytical solutions for the triplet fit result. This method is highly parallelizable, needs fewer operations than other standard track reconstruction methods and is therefore ideal for the implementation on parallel computing architectures. The proposed track reconstruction algorithm has been studied in the context of the Mu3e-experiment and a typical LHC experiment.