Journal of Modern Classical Physics & Quantum Neuroscience

Open Access • Peer Reviewed • Bi-Monthly Publication

Foundations and Synthesis of Quantum Electrodynamics within the Ali-Bodmer Folding Model: Applications for Quantum Computing

Authors: Anis Rahman
Published: 2026-08-05
Pages: 1-21
DOI: 10.63721/26JPQN0170
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Abstract

This paper presents a unified theoretical framework that synthesizes Quantum Electrodynamics (QED) with the Ali-Bodmer (AB) folding model, bridging microscopic gauge field dynamics and many-body nuclear phenomenology. By embedding QED Lagrangian equations for fermionic matter and photon fields into the AB potential's structure, this framework robustly describes clustered nuclei and hypernuclei. Key results include the first-principles calculation of interaction potentials for the Xi-Nucleon (Ξ-N) system, revealing it as a lightly bound state with a binding energy of 1.56 MeV and a potential well-depth of -7.0 MeV. The model employs a Mass-Energy Compensation (MEC) effect and a scalar formalism for Pauli spinors to simulate relativistic shifts in cluster-model Hamiltonians. The research shows that incoherent cluster processes in dilepton production exceed coherent nuclear motion by a factor of 10–100, establishing a foundation for simulating relativistic dynamics. This synthesis enables three quantum computing applications: (a) high fidelity ab initio simulations using effective QED (eQED); (b) strong-field QED (SFQED) analysis in extreme environments; and (c) optimization of heuristic quantum algorithms via nuclear folding problems. A novel Slater Determinant (SD) qubit mapping strategy with linear circuit depth and constant gate overhead, combined with Zero-Noise Extrapolation (ZNE), achieves computational accuracy within 4% of theoretical predictions for 100-plus qubit systems.

Copyright & License

© 2026 The Author(s). Published by WM Journals.

This is an open access article distributed under the terms of the Creative Commons Attribution 4.0 International License (CC BY 4.0), which permits unrestricted use, distribution and reproduction in any medium, provided the original author and source are credited.

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