Quantum-inspired annealers as Boltzmann generators for machine learning and statistical physics

18 Dec 2019Alexander E. UlanovEgor S. TiunovA. I. Lvovsky

Quantum simulators and processors are rapidly improving nowadays, but they are still not able to solve complex and multidimensional tasks of practical value. However, certain numerical algorithms inspired by the physics of real quantum devices prove to be efficient in application to specific problems, related, for example, to combinatorial optimization... (read more)

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