Parameter-Dependent Noise Resilience in the Quantum Approximate Optimization Algorithm

arXiv:2610.11710 · quant-ph · Submitted 2026-10-08 · Read on arXiv

quant-ph

Submitted: 2026-10-08

Updated: 2026-10-08

Terminology

• Adiabatic Evolution — 5× in this paper · explained in 2 episodes
• Robustness — 5× in this paper · explained in 5 episodes
• Trace — 4× in this paper · explained in 2 episodes
• Trace Distance — 4× in this paper · explained in 3 episodes
• Combinatorial Optimization — 3× in this paper · explained in 2 episodes
• Quantum Approximate Optimization Algorithm — 3× in this paper
• Objective Function — 2× in this paper · explained in 2 episodes
• Fidelity — 1× in this paper · explained in 2 episodes
• Physical Constraints — 1× in this paper · explained in 7 episodes
• Quantum Circuits — 1× in this paper · explained in 2 episodes
• Reinforcement Learning — 1× in this paper · explained in 4 episodes

Sources

• A Quantum Approximate Optimization Algorithm
• Quantum Computation by Adiabatic Evolution
• Variational Quantum Algorithms for Combinatorial Optimization
• Quantum Supremacy through the Quantum Approximate Optimization Algorithm
• Snapshot-QAOA: Extending QAOA to Quantum Hamiltonian Simulation
• Quantum-Enhanced Optimization by Warm Starts
• Noise Resilience and Robust Convergence Guarantees for the Variational Quantum Eigensolver
• Performance of the Quantum Approximate Optimization Algorithm on the Maximum Cut Problem
• Quantum Approximate Optimization via Noise-Directed Adaptive Warm-Starting

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