Analytical reweighting rules for QAOA parameters on hypergraphs improve performance by adjusting mixing terms beyond previous graph-based methods.
From the quantum approximate optimization algorithm to a quantum alternating operator ansatz,
2 Pith papers cite this work. Polarity classification is still indexing.
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Pith papers citing it
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quant-ph 2years
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UNVERDICTED 2representative citing papers
A sandbox platform enables end-to-end hybrid workflows that reduce graph problems, run QAOA on IBM hardware up to 128 qubits, and refine outputs classically for problems including vertex cover and clique.
citing papers explorer
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QAOA Parameter Transfer for Hypergraphs
Analytical reweighting rules for QAOA parameters on hypergraphs improve performance by adjusting mixing terms beyond previous graph-based methods.
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Experimental Workflows for Combinatorial Optimization: Towards Quantum Advantage
A sandbox platform enables end-to-end hybrid workflows that reduce graph problems, run QAOA on IBM hardware up to 128 qubits, and refine outputs classically for problems including vertex cover and clique.