A hybrid classical-quantum scheme compresses and disentangles bottleneck layers of pre-trained neural networks into MPO form for execution on quantum devices, validated via proof-of-concept on MNIST and CIFAR-10 image classification.
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Structure-aware approximate compilation for Hamiltonian dynamics on NISQ devices produces shallower circuits with higher observed fidelity than generic exact synthesis.
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.
A Transformer policy optimizes quantum circuit ansatzes for QSCI, yielding up to 98% reduction in two-qubit gates while reaching chemical accuracy on N2 and competitive compactness with classical methods.
QEVE on xTC transcorrelated Hamiltonians in STO-6G basis achieves T-gate counts between standard qubitization in cc-pVTZ and cc-pVQZ while delivering accuracy better than cc-pVQZ for Li and Be but worse than cc-pVDZ for O, F, and Ne.
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.
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.
citing papers explorer
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Classical Neural Networks on Quantum Devices via Tensor Network Disentanglers: A Case Study in Image Classification
A hybrid classical-quantum scheme compresses and disentangles bottleneck layers of pre-trained neural networks into MPO form for execution on quantum devices, validated via proof-of-concept on MNIST and CIFAR-10 image classification.
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Hardware-Efficient Hamiltonian Simulation via Trotter-Initialized Variational Optimization with Native Placement
Structure-aware approximate compilation for Hamiltonian dynamics on NISQ devices produces shallower circuits with higher observed fidelity than generic exact synthesis.
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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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Generative Circuit Design for Quantum-Selected Configuration Interaction
A Transformer policy optimizes quantum circuit ansatzes for QSCI, yielding up to 98% reduction in two-qubit gates while reaching chemical accuracy on N2 and competitive compactness with classical methods.
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Accuracy and resource advantages of quantum eigenvalue estimation with non-Hermitian transcorrelated electronic Hamiltonians
QEVE on xTC transcorrelated Hamiltonians in STO-6G basis achieves T-gate counts between standard qubitization in cc-pVTZ and cc-pVQZ while delivering accuracy better than cc-pVQZ for Li and Be but worse than cc-pVDZ for O, F, and Ne.
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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.