QADR decomposes n-qubit VQCs into local sub-circuits to reduce memory from O(2^n) to O(n * 2^{2d+1}) and mitigate barren plateaus, scaling to 2000 features on MNIST and wind turbine diagnostics while matching classical models.
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quant-ph 2years
2026 2verdicts
UNVERDICTED 2representative citing papers
Hybrid classical adiabatic annealing yields marginal improvements on limited MaxCut instances but offers no substantial practical benefit over existing techniques for Ising machines.
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Quantum Algorithm for Distributed Reduction of Entanglements (QADR): A Trainable and Simulation-Efficient QML Framework
QADR decomposes n-qubit VQCs into local sub-circuits to reduce memory from O(2^n) to O(n * 2^{2d+1}) and mitigate barren plateaus, scaling to 2000 features on MNIST and wind turbine diagnostics while matching classical models.
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Performance analysis of classical adiabatic annealing on Ising machines
Hybrid classical adiabatic annealing yields marginal improvements on limited MaxCut instances but offers no substantial practical benefit over existing techniques for Ising machines.