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We solve the unstructured search problem in constant time by computing with a physically motivated nonlinearity of the Gross-Pitaevskii type. This speedup comes, however, at the novel expense of increasing the time-measurement precision. Jointly optimizing these resource requirements results in an overall scaling of . This is a significant, but not unreasonable, improvement over the scaling of Grover’s algorithm. Since the Gross-Pitaevskii equation approximates the multi-particle (linear) Schr"odinger equation, for which Grover’s algorithm is optimal, our result leads to a quantum information-theoretic lower bound on the number of particles needed for this approximation to hold, asymptotically.

生成讲解博客的中文版本

生成AI智能校验的中文版本