Author

Bao Gia Bach

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Preprint Sep 2026

The Expressive Power of Constrained QAOA: What You Might Have MISsed

Feasibility-preserving mixer Hamiltonians offer an attractive alternative to penalty encodings for constrained quantum optimization, yet how enforcing constraints alters the state space reachable by the Quantum Approximate Optimization Algorithm (QAOA) remains largely unexplored. We address this question within the con...

Boris Tsvelikhovskiy, Bao Gia Bach, Ilya Safro · 1 citation

Preprint Sep 2026

Efficient Estimation of Reduced QAOA Expressibility on Acyclic Graphs

The theoretical and experimental results show how classical graph structure can be used to diagnose and potentially guide the quantum dynamics of variational algorithms before running them on quantum hardware.

Bao Gia Bach, Boris Tsvelikhovskiy, Jose Falla et al. · 0 citations

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