Tensor network simulations act as effective surrogate models for training QAOA on large 2D lattices, overcoming limits of parameter transfer from small instances and remaining classically feasible with moderate bond dimensions.
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UNVERDICTED 4representative citing papers
Demonstrates a quantum wire encoding using Rydberg atom chains to solve MWIS and QUBO problems on neutral atom arrays with reduced ancilla overhead and experimental validation.
A divide-and-conquer heuristic enables solving MWIS instances from molecular docking with graphs of 225-585 vertices on neutral-atom quantum emulators, outperforming greedy baselines and recovering provably optimal solutions on some instances.
Classical solvers solve random Ising models on heavy-hex graphs efficiently, with Gurobi showing linear or weakly quadratic scaling up to 100k variables and simulated annealing showing exponential time-to-solution without cubic terms.
citing papers explorer
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Tensor network surrogate models for variational quantum computation
Tensor network simulations act as effective surrogate models for training QAOA on large 2D lattices, overcoming limits of parameter transfer from small instances and remaining classically feasible with moderate bond dimensions.
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A quantum wire approach to weighted combinatorial graph optimisation problems
Demonstrates a quantum wire encoding using Rydberg atom chains to solve MWIS and QUBO problems on neutral atom arrays with reduced ancilla overhead and experimental validation.
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A Scalable Heuristic for Molecular Docking on Neutral-Atom Quantum Processors
A divide-and-conquer heuristic enables solving MWIS instances from molecular docking with graphs of 225-585 vertices on neutral-atom quantum emulators, outperforming greedy baselines and recovering provably optimal solutions on some instances.
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Classical Combinatorial Optimization Scaling for Random Ising Models on 2D Heavy-Hex Graphs
Classical solvers solve random Ising models on heavy-hex graphs efficiently, with Gurobi showing linear or weakly quadratic scaling up to 100k variables and simulated annealing showing exponential time-to-solution without cubic terms.