Optimization of the Full Reconstruction Chain of the HPS Experiment w.r.t. Its 2019 and 2021 Physics Runs

The Heavy Photon Search (HPS) is an experiment built at JLab's CEBAF designed to detect heavy photon-mediated thermal relic dark matter. It consists of two silicon vertex tracker (SVT) halves inside a 1.5 T magnet, as well as an ECal and Hodoscope; these closely hug CEBAF's electron beam. From this beam, the HPS saw an accumulated 2.4e¹⁸ and 3.3e¹⁸ electrons on target during the 2019 and 2021 runs. These electrons interacted with a fixed tungsten target, and, in some cases, produced e^-e⁺ pairs that were accepted into the SVT. The SVT halves are designed with an opening angle corresponding to the decay of a 1-1000 MeV heavy photon into an e^-e⁺ pair.

In this talk, the novel optimization strategies employed by the HPS to make full use of the 2019/2021 datasets will be described. The SVT sensors closest to the target experience a high amount of radiation damage during the run, and this talk will detail techniques that extract pulse shapes faithfully despite this challenge. It will set out the necessary improvements to strip clustering needed to address hot and dead channels induced by the high radiation. Finally, the talk will conclude with ML techniques for optimizing the HPS' Kalman Tracking algorithm. We used the reconstruction optimization framework ACTS to optimize the performance of the HPS track-finding algorithm. Studies using ACTS allowed the HPS tracking efficiency to significantly improve, boosting our sensitivity to new physics.