A Generalized Approach to Longitudinal Momentum Determination in Cylindrical Straw Tube Detectors

TL;DR

This paper introduces a versatile method for reconstructing longitudinal track parameters in the PANDA Straw Tube Tracker, enhancing online event filtering by improving track reconstruction efficiency and quality.

Contribution

It presents a novel, general approach for longitudinal momentum determination that can be integrated into existing track finding algorithms, with a systematic comparison of three pattern recognition methods.

Findings

Recursive annealing fit outperforms other methods in all quality metrics.

Achieves a track reconstruction efficacy of 95% or higher.

Method is adaptable for use in other tracking algorithms.

Abstract

The upcoming PANDA experiment at FAIR will be among a new generation of particle physics experiments to employ a novel event filtering system realised purely in software, i.e. a software trigger. To educate its triggering decisions, online reconstruction algorithms need to offer outstanding performance in terms of efficiency and track quality. We present a method to reconstruct longitudinal track parameters in PANDA's Straw Tube Tracker, which is general enough to be easily added to other track finding algorithms that focus on transversal reconstruction. For the pattern recognition part of this method, three approaches are employed and compared: A combinatorial path finding approach, a Hough transformation, and a recursive annealing fit. In a systematic comparison, the recursive annealing fit was found to outperform the other approaches in every category of quality parameters and reaches a reconstruction efficacy of 95% and higher.