3 papers
quant-ph2026
Efficient re-sampling in quasi-probability decompositions
Sara Santos, Stefan Woerner, Vincenzo Savona +1
Near-term quantum devices are limited by noise and hardware constraints, motivating algorithmic approaches that trade circuit complexity for increased sampling overhead. Quasi-prob…
quant-ph2026
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…
quant-ph2026
Quantum-enhanced Markov Chain Monte Carlo for Combinatorial Optimization
Kate V. Marshall, Daniel J. Egger, Michael Garn +4
Quantum computing offers an alternative paradigm for addressing combinatorial optimization problems compared to classical computing. Despite recent hardware improvements, the execu…