Title: Quantum Simulation of Cellular Automata with Adaptive Noise

Jincheng Zhang

Published Sep 3, 2026• 0 citations

Abstract

Quantum simulation has emerged as a powerful tool for modeling complex systems, particularly those exhibiting emergent behavior. Cellular automata (CA) provide a computationally tractable framework for exploring such systems, offering a rich landscape of patterns and dynamics. This paper investigates the application of quantum simulation to CA, specifically focusing on the development of a system that incorporates adaptive noise to enhance prediction accuracy. We present a novel quantum simulator architecture designed to efficiently model the evolution of CA, driven by a dynamically adjusted noise mechanism. The goal is to improve the fidelity of simulations by incorporating a level of complexity and realism not currently achievable through classical methods. This work explores the potential of quantum simulation to unlock new insights into the underlying mechanisms driving complex cellular automata patterns.

DOI: 10.5281/zenodo.22274398

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