Author

Filip B. Maciejewski

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Preprint Aug 2026

Warm-Starting MaxCut Relaxation via Low-Depth Quantum Approximate Optimization Algorithm

This work introduces a warm-start method based on local correlators obtained from the Quantum Approximate Optimization Algorithm (QAOA), and uses this information to initialize the Burer-Monteiro (BM) rank-two relaxation.

Bao Gia Bach, Ilya Safro, Filip B. Maciejewski · 0 citations

Preprint Jul 2026

Quantum Approximate Optimization via Noise-Directed Adaptive Warm-Starting

A noise-aware adaptive approach to quantum approximate optimization, Noise-Directed Adaptive Warm-Starting (ND-AWS), that builds on recent concepts such as Warm-Start QAOA and Noise-Directed Adaptive Remapping by leveraging bitflip gauge transformations, and exploits amplitude-damping-like noise components.

Filip B. Maciejewski, Stuart Hadfield, Oscar Wallis et al. · 4 citations