Theory of Nature: Unified Properties of Magnetism, Electricity, and Light
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Special Issue - European cooperation in nuclear fusion research: from history to future policy design
Publishing Model: Hybrid
Deadline: Aug 31, 2026
Quantum Advances in Particle Physics and High-Energy Colliders
Particle Physics is an area intrinsically tied to quantum science, where Quantum Mechanics provides the fundamental framework for Quantum Field Theory on which all theoretical predictions are based. High-energy colliders, such as the CERN’s Large Hadron Collider, serve as large-scale quantum machines, enabling the exploration of quantum phenomena at unprecedented energy scales. As quantum systems, high-energy colliders exemplify the foundational vision of quantum computing proposed by Richard P. Feynman, claiming that quantum simulations would capture their behaviour more faithfully and efficiently than classical approaches.
The rapid advancement of quantum technologies in recent years, combined with the significant challenges faced by collider physics in the near future, has sparked tremendous interest within the scientific community to explore and harness quantum methodologies in this domain. This Collection will focus on applications of quantum technologies to particle physics where a quantum approach could provide a computational advantage once fault-tolerant devices are available, and on fundamental aspects of quantum science that can only be investigated at high-energy colliders.
A non-exhaustive list of topics includes:
- Numerical integration of Feynman diagrams: employing quantum algorithms to speed up the evaluation of complex integrals from phase-space and multiloop Feynman diagrams, a central component of precise theoretical predictions.
- Optimization in experimental particle physics: applying quantum approaches to optimize tasks such as track reconstruction, jet clustering, and detector simulation.
- Quantum sampling: the use of quantum computers to prepare quantum states and generate samples from complex probability distributions that are otherwise intractable for classical computers.
- Quantum algorithms for data analysis: leveraging quantum machine learning and quantum generative models to identify patterns, finding correlations in data, and process large collider datasets.
- Quantum phenomena at high-energy: a quantum approach to quantum effects that occurs only at particle experiments such as entanglement in top quark pair production and flavour transitions.
Keywords: Quantum Field Theory, Quantum Sampling, Quantum Optimization, Quantum Machine Learning, Entanglement in Particle Physics
Publishing Model: Open Access
Deadline: Jul 01, 2026