Frontiers in Artificial Intelligence (May 2024)

Quantum pathways for charged track finding in high-energy collisions

  • Christopher Brown,
  • Michael Spannowsky,
  • Alexander Tapper,
  • Simon Williams,
  • Simon Williams,
  • Ioannis Xiotidis

DOI
https://doi.org/10.3389/frai.2024.1339785
Journal volume & issue
Vol. 7

Abstract

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In high-energy particle collisions, charged track finding is a complex yet crucial endeavor. We propose a quantum algorithm, specifically quantum template matching, to enhance the accuracy and efficiency of track finding. Abstracting the Quantum Amplitude Amplification routine by introducing a data register, and utilizing a novel oracle construction, allows data to be parsed to the circuit and matched with a hit-pattern template, without prior knowledge of the input data. Furthermore, we address the challenges posed by missing hit data, demonstrating the ability of the quantum template matching algorithm to successfully identify charged-particle tracks from hit patterns with missing hits. Our findings therefore propose quantum methodologies tailored for real-world applications and underline the potential of quantum computing in collider physics.

Keywords