A genetic-algorithm-based method to find the unitary transformations for any de- sired quantum computation and application to a one-bit oracle decision problem

Abstract

We propose a genetic-algorithm-based method to find the unitary transformations for any desired quantum computation. We formulate a simple genetic algorithm by introducing the "genetic parameter vector" of the unitary transformations to be found. In the genetic algorithm process, all components of the genetic parameter vectors are supposed to evolve to the solution parameters of the unitary transformations. We apply our method to find the optimal unitary transformations and to generalize the corresponding quantum algorithms for a realistic problem, the one-bit oracle decision problem, or the often-called Deutsch problem. By numerical simulations, we can faithfully find the appropriate unitary transformations to solve the problem by using our method. We analyze the quantum algorithms identified by the found unitary transformations and generalize the variant models of the original Deutsch's algorithm.

Published version

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Cited by in corpus (4)

• Noisy intermediate-scale quantum (NISQ) algorithms
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• Efficient experimental design of high-fidelity three-qubit quantum gates via genetic programming
• Multi-objective evolutionary algorithms for quantum circuit discovery