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Simulating the flight gate assignment problem on a trapped ion quantum computer

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arxiv 2309.09686 v1 pith:UBQTYM6S submitted 2023-09-18 quant-ph

classification quant-ph
keywords quantumproblemtrappedassignmentcombinatorialcomputercurrenteigensolver
verification ladder T0 review T1 audit T2 compute T3 formal
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We study the flight gate assignment problem on IonQ's Aria trapped ion quantum computer using the variational quantum eigensolver. Utilizing the conditional value at risk as an aggregation function, we demonstrate that current trapped ion quantum hardware is able to obtain good solutions for this combinatorial optimization problem with high probability. In particular, we run the full variational quantum eigensolver for small instances and we perform inference runs for larger systems, demonstrating that current and near-future quantum hardware is suitable for addressing combinatorial optimization problems.

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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. Resource-Efficient Quantum Optimization via Higher-Order Encoding

    quant-ph 2025-11 conditional novelty 5.0 of 10

    HUBO encodings reduce qubit counts from n*m to n*ceil(log2 m) and cut CNOT counts by 89.6-100% in QAOA benchmarks on gate assignment, max k-colorable subgraph, and integer programming instances.

  2. Optimizing QUBO on a quantum computer by mimicking imaginary time evolution

    quant-ph 2025-05 conditional novelty 5.0 of 10

    ITEMC iteratively mimics imaginary time evolution to solve QUBO instances, achieving high CVaR-based approximation ratios in simulation and finding the best known solution on IBM hardware for up to 80 qubits.

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