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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Classical kernelisation fully reduces many small and sparse unit-disk graphs for MIS and MWIS native to Rydberg arrays, but dense graphs retain finite irreducible kernels, with vertex weights increasing reducibility and extended interaction ranges suppressing it.
Physics-informed quantum neural networks trained on noisy measurements can construct nontrivial decision boundaries to classify quantum states via order parameters and are suited for NISQ hardware due to links with Markovian open many-body systems.
citing papers explorer
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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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Reducibility of native weighted graphs on Rydberg Arrays
Classical kernelisation fully reduces many small and sparse unit-disk graphs for MIS and MWIS native to Rydberg arrays, but dense graphs retain finite irreducible kernels, with vertex weights increasing reducibility and extended interaction ranges suppressing it.
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Getting large-scale quantum neural networks ready for quantum hardware
Physics-informed quantum neural networks trained on noisy measurements can construct nontrivial decision boundaries to classify quantum states via order parameters and are suited for NISQ hardware due to links with Markovian open many-body systems.