181 citations · 333 across the 18 of their papers we have counts for
6 papers · 1 filter
Efficient Circuit Transpilation of Commuting Gates on 2D Grids
Sabina Drăgoi, Daniel J. Egger
Combinatorial optimization problems are central to many applications but can be challenging to solve. Quantum approaches such as the Quantum Approximate Optimization Algorithm (QAO…
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…
Optimizing Symmetry Informed Probabilistic Error Cancellation
Tom O'Leary, Daniel J. Egger, Dieter Jaksch
We show that combining quantum error detection (QED) with probabilistic error cancellation (PEC) gives more accurate and lower-variance estimates than PEC alone, provided that the…
Setting angles in quantum approximate optimization at utility-scale
Maosheng Guo, Joel Jurado Diaz, Anurag Ramesh +16
The quantum approximate optimization algorithm (QAOA) is a powerful heuristic that seeks to solve combinatorial optimization problems using quantum hardware and classical optimizat…
Efficient Fourier-Based Linear Combination of Unitaries and Applications in Quantum Optimization
Almudena Carrera Vazquez, Daniel J. Egger, Stefan Woerner
We investigate ancilla-free linear combination of unitaries (LCU) as a framework for approximating complex quantum circuits. This is particularly effective for quantum optimization…
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…