QRAC design is recast as a spectral problem for noncommuting measurements, yielding elementary proofs and refinements of the Nayak bound plus MUPVM constructions that attain conjectured optimal N-scaling.
Quantum- Relaxation Based Optimization Algorithms: Theoretical Extensions
3 Pith papers cite this work. Polarity classification is still indexing.
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Complete MUB ensembles are optimal for isotropic Gaussian random-Hamiltonian width among d+1 basis unions, and adaptive MUB-XRot QAOA is non-worse than standard QAOA in 80% of 1500 benchmark cases across MaxCut, MIS, and knapsack.
Decoder-consistent Hamiltonians are defined via POVM pullback, revealing inconsistencies in standard QRAO for mixed-degree quadratics and yielding new MaxCut approximation guarantees.
citing papers explorer
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Measurement Geometry for Quantum Random Access Codes: Beyond Nayak Bound and Toward Optimality
QRAC design is recast as a spectral problem for noncommuting measurements, yielding elementary proofs and refinements of the Nayak bound plus MUPVM constructions that attain conjectured optimal N-scaling.
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Mutually Unbiased Bases for Variational Quantum Initialization: Basis-Union Optimality and Adaptive Family Search
Complete MUB ensembles are optimal for isotropic Gaussian random-Hamiltonian width among d+1 basis unions, and adaptive MUB-XRot QAOA is non-worse than standard QAOA in 80% of 1500 benchmark cases across MaxCut, MIS, and knapsack.
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Decoder-Consistent Hamiltonians for POVM-Based Quantum Relaxations
Decoder-consistent Hamiltonians are defined via POVM pullback, revealing inconsistencies in standard QRAO for mixed-degree quadratics and yielding new MaxCut approximation guarantees.