Quantum integration of elementary particle processes

TL;DR

This paper demonstrates how quantum algorithms can efficiently perform integration of particle physics scattering processes, achieving high accuracy and quadratic speed-up over classical methods, paving the way for quantum applications in high-energy physics.

Contribution

It introduces a quantum integration approach for particle physics processes using quantum GANs and Quantum Amplitude Estimation, showing potential for speed-up and accuracy improvements.

Findings

Achieved percent-level accuracy in noiseless quantum simulations.

Demonstrated quadratic speed-up over classical integration methods.

Successfully integrated distributions for processes with up to six qubits.

Abstract

We apply quantum integration to elementary particle-physics processes. In particular, we look at scattering processes such as ${\rm e}^+{\rm e}^- \to q \bar q$ and ${\rm e}^+{\rm e}^- \to q \bar q' {\rm W}$. The corresponding probability distributions can be first appropriately loaded on a quantum computer using either quantum Generative Adversarial Networks or an exact method. The distributions are then integrated sing the method of Quantum Amplitude Estimation which shows a quadratic speed-up with respect to classical techniques. In simulations of noiseless quantum computers, we obtain per-cent accurate results for one- and two-dimensional integration with up to six qubits. This work paves the way towards taking advantage of quantum algorithms for the integration of high-energy processes.