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Quantum State Collapse as a Cellular Automata Algorithm

Jincheng Zhang

Published Aug 31, 2026• 0 citations
Publisher

Abstract

This paper explores the concept of quantum state collapse as a cellular automata algorithm, providing a novel framework for understanding and modeling this fundamental phenomenon. We propose a model where the evolution of a quantum state is governed by a set of differential equations, driven by a series of rules and feedback loops, mimicking the collapse of a quantum state. The core claim is that this approach offers a mathematically rigorous and potentially insightful way to simulate and analyze the collapse process, providing a bridge between quantum mechanics and cellular automata. The paper details the mathematical formulation, explores its implications for understanding quantum information processing, and discusses potential applications within the context of quantum simulation and early-stage quantum computing.

DOI
10.5281/zenodo.22186671

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This paper explores the concept of quantum state collapse as a cellular automata algorithm, providing a novel framework for understanding and modeling this fundamental phenomenon. We propose a model where the evolution of a quantum state is governed by a set of differential equations, driven by a series of rules and feedback loops, mimicking the collapse of a quantum state. The core claim is that this approach offers a mathematically rigorous and potentially insightful way to simulate and analyze the collapse process, providing a bridge between quantum mechanics and cellular automata. The paper details the mathematical formulation, explores its implications for understanding quantum information processing, and discusses potential applications within the context of quantum simulation and early-stage quantum computing.
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This paper proposes a novel model utilizing Quantum Cellular Automata (QCA) to simulate complex system evolution. The core idea involves transforming classical Cellular Automata (CA) into QCA, incorporating quantum phenomena such as superposition and entanglement to model intricate dynamics. This approach offers a fresh perspective on complex system modeling by leveraging the principles of quantum mechanics. The model's design incorporates key QCA mechanisms, including the Bloch sphere representation of states and the application of unitary transformations to govern cell interactions. We present a foundational framework for QCA simulation and discuss potential applications in areas such as pattern formation, reaction-diffusion processes, and emergent behavior. The focus is on demonstrating the theoretical feasibility and outlining a methodology for future research, rather than presenting empirical experimental results. This work emphasizes the conceptual shift and potential computational advantages offered by QCA in understanding complex systems.
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