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Lyapunov Controlled Counterdiabatic Quantum Optimization

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arxiv 2409.12525 v1 pith:QFPA4AP6 submitted 2024-09-19 quant-ph cond-mat.mes-hall

Pranav Chandarana , Koushik Paul , Kasturi Ranjan Swain , Xi Chen , Adolfo del Campo This is my paper · ORCID
classification quant-phcond-mat.mes-hall
keywords quantumalgorithmoptimizationapproachcomputingcontrolcounterdiabaticdigital
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We introduce a quantum algorithm integrating counterdiabatic (CD) protocols with quantum Lyapunov control (QLC) to tackle combinatorial optimization problems. This approach offers versatility, allowing implementation as either a digital-analog or purely digital algorithm based on selected control strategies. By examining spin-glass Hamiltonians, we illustrate how the algorithm can explore alternative paths to enhance solution outcomes compared to conventional CD techniques. This method reduces the dependence on extensive higher-order CD terms and classical optimization techniques, rendering it more suitable for existing quantum computing platforms. The combination of digital compression via CD protocols and the adaptable nature of QLC methods positions this approach as a promising candidate for near-term quantum computing.

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Cited by 3 Pith papers

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

  1. Tight bound for the total time in digital-analog quantum computation

    quant-ph 2025-12 reject novelty 7.0 of 10

    DAQC synthesis of any two-body Hamiltonian can be done in analog time at most √3·T·‖hP⊘hS‖₂, and the paper asserts this bound is tight.

  2. Improving Quantum Optimization to Achieve Quadratic Time Complexity

    quant-ph 2025-01 conditional novelty 6.0 of 10

    Penta-O sets QAOA parameters level by level using five energy measurements per level, cutting parameter-setting cost to O(p^2) circuit executions for depth p.

  3. Classical algorithm inspired by the feedback-based algorithm for quantum optimization and local counterdiabatic driving

    quant-ph 2025-06 conditional novelty 4.0 of 10

    CACAO is a classical spin-dynamics algorithm, derived from FALQON/CD-FQA, that outperforms the quantum versions on a 2-SAT-related benchmark and handles 10,000 spins.

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