A quantum algorithm for track reconstruction in the LHCb vertex detector

Abstract

High-energy physics is facing increasingly computational challenges in real-time event reconstruction for the near-future high-luminosity era. Using the LHCb vertex detector as a use-case, we explore a new algorithm for particle track reconstruction based on the minimisation of an Ising-like Hamiltonian with a linear algebra approach. The use of a classical matrix inversion technique results in tracking performance similar to the current state-of-the-art but with worse scaling complexity in time. To solve this problem, we also present an implementation as quantum algorithm, using the Harrow-Hassadim-Lloyd (HHL) algorithm: this approach can potentially provide an exponential speedup as a function of the number of input hits over its classical counterpart, in spite of limitations due to the well-known HHL Hamiltonian simulation and readout problems. The findings presented in this paper shed light on the potential of leveraging quantum computing for real-time particle track reconstruction in high-energy physics.

arXiv comment23 pages, 10 figures

References in corpus (22)

• PYTHIA 6.4 Physics and Manual
• PYTHIA 6.2 Physics and Manual
• Quantum algorithm for solving linear systems of equations
• LHCb Detector Performance
• Efficient quantum algorithms for simulating sparse Hamiltonians
• Quantum Simulation for High Energy Physics
• Exponential improvement in precision for simulating sparse Hamiltonians
• Conceptual Design Report for the LUXE Experiment
• Quantum Hopfield neural network
• A quantum algorithm for high energy physics simulations
• Quantum Machine Learning in High Energy Physics
• Allen: A high level trigger on GPUs for LHCb
• Simulating sparse Hamiltonians with star decompositions
• Event Classification with Quantum Machine Learning in High-Energy Physics
• Open quantum generalisation of Hopfield neural networks
• Quantum Machine Learning for $b$-jet charge identification
• Quantum speedup for track reconstruction in particle accelerators
• Speeding up Particle Track Reconstruction using a Parallel Kalman Filter Algorithm
• Studying quantum algorithms for particle track reconstruction in the LUXE experiment
• Timing performance of the LHCb VELO Timepix3 Telescope
• Search by triplet: An efficient local track reconstruction algorithm for parallel architectures
• Future Physics Prospects with the CMS Detector at the High-Luminosity LHC

Cited by in corpus (4)

• Quantum-Annealing-Inspired Algorithms for Track Reconstruction at High-Energy Colliders
• Charged particle reconstruction for future high energy colliders with Quantum Approximate Optimization Algorithm
• Quantum-annealing-inspired algorithms for multijet clustering
• TrackHHL: A Quantum Computing Algorithm for Track Reconstruction at the LHCb