Improving the Performance of Deep Quantum Optimization Algorithms with Continuous Gate Sets

Improving the Performance of Deep Quantum Optimization Algorithms with Continuous Gate Sets

Variational quantum algorithms are believed to be promising for solving computationally hard problems on noisy intermediate-scale quantum (NISQ) systems. Gaining computational power from these algorithms critically relies on the mitigation of errors during their execution, which for coherence-limite...

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Bibliographic Details
Main Authors: Nathan Lacroix, Christoph Hellings, Christian Kraglund Andersen, Agustin Di Paolo, Ants Remm, Stefania Lazar, Sebastian Krinner, Graham J. Norris, Mihai Gabureac, Johannes Heinsoo, Alexandre Blais, Christopher Eichler, Andreas Wallraff
Format: Article
Language:English
Published: American Physical Society 2020-10-01
Series:PRX Quantum
Online Access:http://doi.org/10.1103/PRXQuantum.1.020304

Internet

http://doi.org/10.1103/PRXQuantum.1.020304

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