Cell design and dynamics of quantum cellular automata

Gerhard Grössing, Anton Zeilinger

Jincheng Zhang

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.

Jincheng Zhang

This paper explores the potential of Quantum Cellular Automata (QCA) for simulating complex systems with enhanced efficiency compared to their classical counterparts. Classical Cellular Automata (CCA) face limitations when modeling systems exhibiting quantum phenomena or requiring computational power for intricate simulations. QCA, leveraging the principles of quantum mechanics, offers a fundamentally different approach. This work details the design of a QCA where cells are represented by qubits, and the governing rules are defined by quantum gates. The core argument presented is that QCA's inherent parallelism and superposition capabilities can lead to significant speedups in simulating complex systems. This research proposes a novel methodology for applying QCA to various complex systems, highlighting its potential advantages and exploring the theoretical foundations underpinning this approach. The investigation focuses on the theoretical aspects of QCA design and simulation, without the need for experimental validation.

Peter J. Love

Massimo Macucci

Thiago L. M. Guedes, D. Winter, Markus Müller

Quantum cellular automata are alternative quantum-computing paradigms to quantum Turing machines and quantum circuits. Their working mechanisms are inherently automated, therefore measurement free, and they act in a translation invariant manner on all cells or qudits of a register, generating a global rule that updates cell states locally, i.e., based solely on the states of their neighbors. Although desirable features in many applications, it is generally not clear to which extent these fully automated discrete-time local updates can generate and sustain long-range order in the (noisy) systems they act upon. In particular, whether and how quantum cellular automata can perform quantum error correction remain open questions. We close this conceptual gap by proposing quantum cellular automata with quantum-error-correction capabilities. We design and investigate two (quasi)one dimensional quantum cellular automata based on known classical cellular-automata rules with density-classification capabilities, namely the local majority voting and the two-line voting. We investigate the performances of those quantum cellular automata as quantum-memory components by simulating the number of update steps required for the logical information they act upon to be afflicted by a logical bit flip. The proposed designs pave a way to further explore the potential of new types of quantum cellular automata with built-in quantum-error-correction capabilities.