17 citations · 32 across the 13 of their papers we have counts for
6 papers · 1 filter
Complexity Amplification from Compression in Quantum Random Access Optimization
Stuart Hadfield
Compressed quantum encodings aim to overcome hardware limitations towards tackling challenging problems at scale, with many classical variables mapped onto noncommuting observables…
No Free Compression in Quantum Relaxations for Optimization
Stuart Hadfield
Qubit-efficient quantum relaxations compress classical decision variables into expectation values on substantially fewer qubits. We ask what resource tradeoffs this compression ent…
Separating Geometry From Interference in Constrained Quantum Optimization
Chinonso Onah, Stuart Hadfield, Kristel Michielsen
We study the separation of geometric effects from quantum interference in quantum optimization algorithms. Constrained optimization problems such as routing, assignment, and schedu…
Evaluating QAOA expectation values can be as hard as counting optimal solutions
Stuart Hadfield
Evaluating expectation values is a critical task for variational quantum eigensolvers, and for parameterized quantum circuits and other quantum algorithms more generally. We consid…
Quantum Approximate Optimization via Noise-Directed Adaptive Warm-Starting
Filip B. Maciejewski, Stuart Hadfield, Oscar Wallis +5
Progress towards a quantum advantage using known heuristic methods for combinatorial optimization is impeded by hardware noise and limited qubit count. Here, we propose a noise-awa…
Noise-Directed Adaptive Remapping for Integer Optimization: from qubits to (encoded) qudits
Stuart Hadfield, Filip B. Maciejewski, Davide Venturelli
We extend Noise-Directed Adaptive Remapping (NDAR), a recently proposed heuristic meta-algorithm that leverages device noise as a computational resource, to optimization problems o…