Quantum Annealing with Long-Range Interactions for Combinatorial Optimization

This paper explores the application of quantum annealing to combinatorial optimization problems, specifically focusing on systems with long-range interactions. We develop a theoretical framework that extends current quantum annealing models to efficiently handle non-local connectivity, which is crucial for solving complex real-world problems like drug discovery and logistics. Numerical simulations demonstrate a significant performance improvement over conventional annealing methods for certain classes of problems, suggesting a promising path toward practical quantum optimization devices.