Box Qubo

Quadratic Unconstrained Binary Optimization (QUBO) is a mathematical formulation used to represent complex optimization problems as quadratic functions of binary variables, making them suitable for solution via quantum annealing or classical approximation algorithms. Current research focuses on developing efficient algorithms for solving QUBOs, including adaptations of simulated annealing, variational quantum algorithms (VQAs), and hybrid classical-quantum approaches like the Frank-Wolfe method, often targeting specific hardware architectures like neuromorphic processors or quantum annealers. These advancements are improving the speed, energy efficiency, and scalability of solving QUBO problems, with applications ranging from computer vision and machine learning to traditional Chinese medicine and black-box optimization.