Optimization using Bose-Einstein condensation and measurement-feedback circuits

We investigate a computational device that harnesses the effects of Bose-Einstein condensation (BEC) to accelerate the speed of finding the solution of a given optimization problem. Many computationally difficult problems, including NP-complete problems, can be formulated as a ground state search problem. In a BEC, below the critical temperature, bosonic particles have a natural tendency to accumulate in the ground state. Furthermore, the speed of attaining this configuration is enhanced as a result of final state stimulation. We propose a physical device that incorporates these basic properties of bosons into the optimization problem, such that an optimized solution is found by a simple cooling of the physical temperature of the device. We find that the speed of convergence to the ground state can be sped up by a factor of $N$ at a given error, where N is the boson number per site.

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