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Quantum Program Synthesis: Swarm Algorithms and Benchmarks

Part of the Lecture Notes in Computer Science book series (LNTCS,volume 11451)

Abstract

In the two decades since Shor’s celebrated quantum algorithm for integer factorisation, manual design has failed to produce the anticipated growth in the number of quantum algorithms. Hence, there is a great deal of interest in the automatic synthesis of quantum circuits and algorithms. Here we present a set of experiments which use Ant Programming to automatically synthesise quantum circuits. In the proposed approach, ants choosing paths in high-dimensional Cartesian space are analogous to transformation of qubits in Hilbert space. In addition to the proposed algorithm, we introduce new evaluation criteria for searching the space of quantum circuits, both for classical simulation and simulation on a quantum computer. We demonstrate that the proposed approach significantly outperforms random search on a suite of benchmark problems based on these new measures.

Keywords

  • Quantum algorithms
  • Ant Programming

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Acknowledgements

T. Atkinson and J. Swan acknowledge the support of EPSRC grant EP/J017515/1.

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Atkinson, T., Karsa, A., Drake, J., Swan, J. (2019). Quantum Program Synthesis: Swarm Algorithms and Benchmarks. In: Sekanina, L., Hu, T., Lourenço, N., Richter, H., García-Sánchez, P. (eds) Genetic Programming. EuroGP 2019. Lecture Notes in Computer Science(), vol 11451. Springer, Cham. https://doi.org/10.1007/978-3-030-16670-0_2

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  • DOI: https://doi.org/10.1007/978-3-030-16670-0_2

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