Failure-guided local fuzzing around non-convergent seeds improves detection of faulty HQC configurations over random testing, with concolic seeding adding workload-dependent benefits on VQE versus QAOA.
Noisy intermediate-scale quantum algorithms
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Diagonal ANOs are mathematically equivalent to full ANOs modulo unitary similarity, reducing k-local observable complexity from O(4^k) to O(2^k) and lowering measurement-side classical computation while including conventional VQCs as a special case.
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Failure-Guided Fuzzing for Hybrid Quantum-Classical Programs
Failure-guided local fuzzing around non-convergent seeds improves detection of faulty HQC configurations over random testing, with concolic seeding adding workload-dependent benefits on VQE versus QAOA.
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Diagonal Adaptive Non-local Observables on Quantum Neural Networks
Diagonal ANOs are mathematically equivalent to full ANOs modulo unitary similarity, reducing k-local observable complexity from O(4^k) to O(2^k) and lowering measurement-side classical computation while including conventional VQCs as a special case.