Quantum Algorithms for Experimental High-Energy Physics Data Processing

Abstract:
Quantum computers can solve various problems more efficiently than classical computers. While there are still no large-scale quantum computers, one can study the complexity of quantum algorithms and understand which ones have a theoretical advantage over their classical counterparts. In this presentation, I propose new quantum algorithms for the object reconstruction problems of tracking and clustering, which occur frequently in the context of particle physics data analysis. The goal of these problems is to group the data points according to some specified geometrical rule. Using amplitude amplification routines, I show that a polynomial quantum speedup is reachable assuming coherent access to the classical input data. I will finish the presentation by mentioning undergoing work on other object reconstruction problems, both in fault-tolerant and restricted-depth settings.