INCREASING THE PERFORMANCE OF COMMUNICATION SYSTEMS USING THE SPIN DYNAMICS EQUATION

The continuous expansion of communication networks and computing systems has created stringent requirements for higher data rates, lower latency, improved reliability, and enhanced energy efficiency. Classical algorithmic and signal-processing approaches, although highly optimized, face increasing challenges when dealing with large-scale, non-linear, and dynamically changing systems. In recent years, physics-inspired computational models have emerged as promising alternatives for addressing these challenges. Among them, spin dynamics equations—originating from statistical physics and magnetism—offer a powerful mathematical framework for modeling collective behavior, non-linear interactions, and distributed optimization. This article presents a comprehensive study of how spin dynamics equations can be employed to increase the performance of communication systems, including communication networks and computer systems. We examine the theoretical foundations of spin dynamics, establish mappings between spin-based models and communication problems, and analyze their impact on routing, signal detection, synchronization, and resource allocation. The results demonstrate that spin-dynamics-based approaches can significantly improve scalability, robustness, and energy efficiency, making them attractive for next-generation communication systems.