Probabilistic algorithms for Ising machines from optimization to generative AI
Ising machines could accelerate hard optimization and sampling tasks, but their impact depends on algorithm–hardware co-design. This Review surveys portable probabilistic methods, from annealing and tempering to Probabilistic Approximate Optimization Algorithm and generative AI hybrids, arguing that principled algorithms and specialized hardware should evolve together to expand capability, scalability and practical adoption.
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