From vacuum amplitudes to qubits

TL;DR

This paper explores how collider physics can serve as a platform for quantum computing applications, focusing on vacuum amplitudes and high-dimensional integrations relevant for quantum event generators.

Contribution

It introduces novel quantum algorithms for analyzing vacuum amplitudes and high-dimensional integrations in collider physics, bridging quantum computing and high-energy physics.

Findings

Identification of causal structures in multiloop vacuum amplitudes

Application of quantum algorithms to high-dimensional function integration

Foundations for a quantum event generator at high perturbative orders

Abstract

High-energy colliders, exemplified by the CERN's Large Hadron Collider (LHC), constitute genuine quantum machines. In alignment with Richard Feynman's foundational vision for quantum computing, collider physics emerge therefore as a prime candidate for quantum simulations. Prospective applications include Quantum Machine Learning for collider data analysis, accelerated evaluation of complex multiloop Feynman diagrams, efficient jet clustering, enhanced parton shower simulations, and related computational challenges. We discuss two specific applications: the identification of causal structures in multiloop vacuum amplitudes, a fundamental component of the Loop-Tree Duality exhibiting deep connections to graph theory; and high-dimensional function integration and sampling. The latter constitutes an initial step toward realizing a fully fleged quantum event generator capable of operating at high perturbative orders.