Title: Quantum Simulation of Cellular Automata with Variable Thresholds

Jincheng Zhang

Published Aug 29, 2026• 0 citations

Abstract

Quantum simulation has the potential to revolutionize our understanding of complex systems, and cellular automata (CA) models offer a particularly attractive platform for exploring emergent behavior. This paper investigates a novel quantum simulation approach to CA, focusing on dynamically adjusting the threshold of the simulation based on the system's internal state. We propose a quantum algorithm that iteratively evolves the threshold, driven by a feedback loop between the system's dynamics and the threshold itself. This dynamic threshold adjustment enables a level of responsiveness and adaptability rarely achieved in traditional CA simulations, potentially leading to novel emergent patterns and behaviors. We demonstrate the algorithm's efficacy through a series of simulations exploring complex CA models with varying threshold configurations. The resulting simulations exhibit qualitatively and quantitatively distinct emergent properties compared to existing approaches.

DOI: 10.5281/zenodo.22158929

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