An evolutionary strategy for finding effective quantum 2-body Hamiltonians of p-body interacting systems

Abstract

Embedding p-body interacting models onto the 2-body networks implemented on commercial quantum annealers is a relevant issue. For highly interacting models, requiring a number of ancilla qubits, that can be sizable and make unfeasible (if not impossible) to simulate such systems. In this manuscript, we propose an alternative to minor embedding, developing a new approximate procedure based on genetic algorithms, allowing to decouple the p-body in terms of 2-body interactions. A set of preliminary numerical experiments demonstrates the feasibility of our approach for the ferromagnetic p-spin model and paves the way towards the application of evolutionary strategies to more complex quantum models.

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Correspondence to G. Passarelli.

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Authors’ contribution

G. A. and A. V. supervised the research activities related to evolutionary computation. P. R. H. and G. P. designed and implemented the genetic algorithm, and performed numerical simulations and data analysis. P. L. and V. C. supervised the project. All authors contributed to the preparation of the present manuscript.

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Acampora, G., Cataudella, V., Hegde, P.R. et al. An evolutionary strategy for finding effective quantum 2-body Hamiltonians of p-body interacting systems. Quantum Mach. Intell. 1, 113–122 (2019). https://doi.org/10.1007/s42484-019-00011-8

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Keywords

  • Adiabatic quantum computation
  • Quantum annealing
  • p-spin model
  • Genetic algorithms
  • Graph embedding