Title | Multi-Angle QAOA Does Not Always Need All Its Angles |

Publication Type | Journal Article |

Year of Publication | 2022 |

Authors | Shi, K, Herrman, R, Shaydulin, R, Chakrabarti, S, Pistoia, M, Larson, J |

Date Published | 9/23/2022 |

Keywords | FOS: Physical sciences, Quantum Physics (quant-ph) |

Abstract | Introducing additional tunable parameters to quantum circuits is a powerful way of improving performance without increasing hardware requirements. A recently introduced multi-angle extension of the quantum approximate optimization algorithm (ma-QAOA) significantly improves the solution from QAOA by allowing the parameters for each term in the Hamiltonian to vary independently. However, prior results suggest that there is considerable redundancy in parameters, the removal of which would reduce the cost of parameter optimization. In this work, we show numerically that problem symmetries can be used to reduce the number of parameters used by ma-QAOA without decreasing the solution quality. We study MaxCut on all 7,565 connected, non-isomorphic 8-node graphs with a non-trivial symmetry group and show numerically that in 67.4\% of these graphs, symmetry can be used to reduce the number of parameters with no decrease in the objective, with the average ratio of parameters reduced by 28.1\%. Moreover, we show that in 35.9\% of the graphs this can be achieved by simply using the largest symmetry. For the graphs where reducing the number of parameters leads to a decrease in the objective, the largest symmetry can be used to reduce the parameter count by 37.1\% at the cost of only a 6.1\% decrease in the objective. |

URL | https://arxiv.org/abs/2209.11839 |

DOI | 10.48550/ARXIV.2209.11839 |