Qubits and Vacuum Amplitudes

• URL: http://arxiv.org/abs/2601.00722v1
• Date: Fri, 02 Jan 2026 15:34:42 GMT
• Title: Qubits and Vacuum Amplitudes
• Abstract summary: Potential applications range from quantum machine learning methods for collider data analysis to faster and more precise evaluations of intricate multiloop Feynman diagrams.<n>The identification of the causal structure of multiloop vacuum amplitudes is a key ingredient of the Loop-Tree Duality and an area with deep connections to graph theory.<n>The integration and sampling of high-dimensional functions is a first step toward the realization of a fully fledged quantum event generator.
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• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: High-energy colliders, such as the Large Hadron Collider (LHC) at CERN, are genuine quantum machines, so, in line with Richard Feynman's original motivation for Quantum Computing, the scattering processes that take place there are natural candidates to be simulated on a quantum system. Potential applications range from quantum machine learning methods for collider data analysis, to faster and more precise evaluations of intricate multiloop Feynman diagrams, more efficient jet clustering, improved simulations of parton showers, and many other tasks. In this work, the focus will be on two specific applications: first, the identification of the causal structure of multiloop vacuum amplitudes, a key ingredient of the Loop-Tree Duality and an area with deep connections to graph theory; and second, the integration and sampling of high-dimensional functions. The latter constitutes a first step toward the realization of a fully fledged quantum event generator operating at high perturbative orders.

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