![]() In this work, we propose and experimentally implement a photonic computational platform capable of simulating complex phenomena using CA. Notable previous attempts to implement physical systems tailored to perform CA include self-assembling DNA molecules 22, arrays of nanomagnets 23, memristor networks 24, and living slime molds 25. Therefore, it is desirable to seek out physical hardware that better encapsulates the computational principles of CA to enable more efficient simulation. On the other hand, most CA are only implemented as high-level software on conventional computers, resulting in unnecessary overhead. Owing to their simple formulations, certain CA of interest are computationally irreducible 21, i.e., there are no analytical shortcuts to evaluate their state after an arbitrary time without resorting to executing the sequential simulation in its entirety. Furthermore, CA have important applications in real-world computational problems such as cryptography 16, data compression 17, error-correction 18, simulating traffic flow 19, and developing more robust artificial intelligence 20. Consequently, CA have found utility in modeling a wide range of natural phenomena in physics 10, 11, chemistry 12, 13, 14, and biology 15. Subsequent landmark studies revealed that CA are also capable of replicating other complex behavior such as fractals 5, chaos 6, self-organized criticality 7, synchronization 8, and universal computation 9. CA were introduced in the 1940s to study how self-replication and evolution can emerge in artificial life 3 and was later popularized in Conway’s Game of Life 4, which exhibits self-organizing patterns reminiscent of biological systems. One class of computational models that can benefit from simple and decentralized physical hardware is cellular automata (CA), which exhibits complex behavior emerging from the local interactions of cells arranged on a regular lattice 2. ![]() This suggests that an alternative and potentially more efficient way to simulate such phenomena is to harness simple and decentralized physical hardware that directly emulates the underlying rules of a complex system. For example, social insects like ants with only limited local information can collectively self-organize to form global structures 1. Unlike the von Neumann architecture, nature is abound with emergent phenomena and complex systems containing many interacting components following simple rules with no hierarchical control. ![]() Modern digital electronic computers, which are based on the von Neumann architecture, exhibit extreme hardware complexity in their construction and are composed of billions of transistors engineered in a hierarchical and highly structured manner.
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