Conference paper
Quantum Kernel Alignment with Stochastic Gradient Descent
Gian Gentinetta, David Sutter, et al.
QCE 2023
Quantum computing is advancing rapidly, and quantum optimization is a promising area of application. Quantum optimization algorithms — whether provably exact, provably approximate or heuristic — offer opportunities to demonstrate quantum advantage. Systematic benchmarking is crucial to guide research, track progress and further advance understanding of quantum optimization. Theoretical research and empirical research using real hardware can complement each other, in the move towards demonstrating quantum advantage.
Gian Gentinetta, David Sutter, et al.
QCE 2023
Ritajit Majumdar, Dhiraj Madan, et al.
VLSID 2024
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Quantum
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ACS Fall 2024