Introduces Λ-lr-QAOA and piecewise-ramp QAOA that promote penalty schedules to variational parameters and use a feasibility-driven loss on budget-constrained MWIS satellite planning instances.
Transferring linearly fixed qaoa angles: performance and real device results
4 Pith papers cite this work. Polarity classification is still indexing.
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quant-ph 4years
2026 4representative citing papers
Empirical evidence indicates QAOA entanglement scales like fermionic Gaussian states for MaxCut instances, unlike the annealing-schedule-dependent scaling in adiabatic quantum computation.
Combining a truncated classical surrogate, angle pruning, and exact fine-tuning cuts the number of active angles and estimated fine-tuning cost of ma-QAOA on small spin-glass and Max-Cut instances while preserving near-optimal approximation ratios.
The paper benchmarks approximation techniques and transfer learning for setting QAOA angles at utility scale and extracts operational guidance from hardware-validated results.
citing papers explorer
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Feasibility-driven QAOA with penalty scheduling
Introduces Λ-lr-QAOA and piecewise-ramp QAOA that promote penalty schedules to variational parameters and use a feasibility-driven loss on budget-constrained MWIS satellite planning instances.
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Entanglement Scaling and Problem Structure in Quantum Approximate and Adiabatic Optimization Algorithms
Empirical evidence indicates QAOA entanglement scales like fermionic Gaussian states for MaxCut instances, unlike the annealing-schedule-dependent scaling in adiabatic quantum computation.
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SAFE ma-QAOA: Surrogate-Assisted and Fine-Tuning Enhanced Multi-Angle QAOA with Parameter Distillation
Combining a truncated classical surrogate, angle pruning, and exact fine-tuning cuts the number of active angles and estimated fine-tuning cost of ma-QAOA on small spin-glass and Max-Cut instances while preserving near-optimal approximation ratios.
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Setting angles in quantum approximate optimization at utility-scale
The paper benchmarks approximation techniques and transfer learning for setting QAOA angles at utility scale and extracts operational guidance from hardware-validated results.