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An introduction to variational quantum algorithms for combinatorial optimization problems

Author

Listed:
  • Camille Grange

    (University of Montpellier, CNRS
    SNCF, Technology, Innovation and Group Projects Department)

  • Michael Poss

    (University of Montpellier, CNRS)

  • Eric Bourreau

    (University of Montpellier, CNRS)

Abstract

Noisy intermediate-scale quantum computers are now readily available, motivating many researchers to experiment with Variational Quantum Algorithms. Among them, the Quantum Approximate Optimization Algorithm is one of the most popular one studied by the combinatorial optimization community. In this tutorial, we provide a mathematical description of the class of Variational Quantum Algorithms, assuming no previous knowledge of quantum physics from the readers. We introduce precisely the key aspects of these hybrid algorithms on the quantum side (parametrized quantum circuit) and the classical side (guiding function, optimizer). We devote a particular attention to QAOA, detailing the quantum circuits involved in that algorithm, as well as the properties satisfied by its possible guiding functions. Finally, we discuss the recent literature on QAOA, highlighting several research trends.

Suggested Citation

  • Camille Grange & Michael Poss & Eric Bourreau, 2024. "An introduction to variational quantum algorithms for combinatorial optimization problems," Annals of Operations Research, Springer, vol. 343(2), pages 847-884, December.
    • Handle: RePEc:spr:annopr:v:343:y:2024:i:2:d:10.1007_s10479-024-06253-5
    DOI: 10.1007/s10479-024-06253-5
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