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Quantum Field Theory-Based Computational Complexity Research

Jincheng Zhang

Published Sep 7, 2026• 0 citations
Publisher

Abstract

This research investigates computational complexity problems through the lens of quantum field theory (QFT). Traditional approaches to complexity theory often rely on algorithmic and logical arguments, while QFT provides a powerful framework for analyzing systems with high dimensionality and entanglement. This paper explores how QFT concepts – such as renormalization, path integrals, and the representation of states as quantum fields – can be applied to understand and potentially mitigate the challenges inherent in certain computational problems. Specifically, we examine how the inherent probabilistic nature of QFT, combined with its ability to handle complex, high-dimensional spaces, might offer new perspectives on problems like NP-completeness and the limits of computation. We propose a framework for translating complexity problems into QFT-inspired models and discuss potential avenues for leveraging these models to explore the landscape of computational complexity. The core contribution of this work lies in establishing a novel methodology for tackling complexity questions by drawing upon the established tools and techniques of QFT. We investigate the potential for utilizing QFT's inherent parallelism and its ability to represent exponentially large state spaces to overcome limitations faced by classical algorithms.

DOI
10.5281/zenodo.22574534

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