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Equivariant QAOA and the Duel of the Mixers

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arxiv 2405.07211 v1 pith:QYZM5HRJ submitted 2024-05-12 quant-ph

classification quant-ph
keywords qaoamixerhamiltonianoptimizationgroupperformanceproblemsproposed
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abstract

Constructing an optimal mixer for Quantum Approximate Optimization Algorithm (QAOA) Hamiltonian is crucial for enhancing the performance of QAOA in solving combinatorial optimization problems. We present a systematic methodology for constructing the QAOA tailored mixer Hamiltonian, ensuring alignment with the inherent symmetries of classical optimization problem objectives. The key to our approach is to identify an operator that commutes with the action of the group of symmetries on the QAOA underlying Hilbert space and meets the essential technical criteria for effective mixer Hamiltonian functionality. We offer a construction method specifically tailored to the symmetric group $S_d$, prevalent in a variety of combinatorial optimization problems. By rigorously validating the required properties, providing a concrete formula and corresponding quantum circuit for implementation, we establish the viability of the proposed mixer Hamiltonian. Furthermore, we demonstrate that the classical mixer $B$ commutes only with a subgroup of $S_d$ of significantly smaller order than the group itself, enhancing the efficiency of the proposed approach. To evaluate the effectiveness of our methodology, we compare two QAOA variants utilizing different mixer Hamiltonians: conventional $B=\sum X_i$ and the newly proposed $H_M$ in edge coloring and graph partitioning problems across various graphs. We observe statistically significant differences in mean values, with the new variant consistently demonstrating superior performance across multiple independent simulations. Additionally, we analyze the phenomenon of poor performance in alternative warm-start QAOA variants, providing a conceptual explanation supported by recent literature findings.

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Cited by 2 Pith papers

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

  1. Fundamental Limitations of QAOA on Constrained Problems and a Route to Exponential Enhancement

    quant-ph 2025-11 reject novelty 8.0 of 10

    Standard QAOA faces an intrinsic feasibility bottleneck on permutation problems that CE QAOA overcomes with an exponential gain in feasible probability for sublinear-to-linear depths under mild hypergraph growth.

  2. QAOA-GPT: Efficient Generation of Adaptive and Regular Quantum Approximate Optimization Algorithm Circuits

    quant-ph 2025-04 conditional novelty 6.0 of 10

    A transformer trained on ADAPT-QAOA solutions can generate valid QAOA circuits for unseen MaxCut instances, matching ADAPT-QAOA approximation ratios within about 0.005 while avoiding iterative parameter optimization.

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