Low-Depth Gradient Measurements Can Improve Convergence in Variational Hybrid Quantum-Classical Algorithms

Within a natural black-box setting, we exhibit a simple optimization problem for which a quantum variational algorithm that measures analytic gradients of the objective function with a low-depth circuit and performs stochastic gradient descent provably converges to an optimum faster than any algorit...

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Veröffentlicht in:	Physical review letters 2021-04, Vol.126 (14), p.140502-140502, Article 140502
Hauptverfasser:	Harrow, Aram W, Napp, John C
Format:	Artikel
Sprache:	eng
Schlagworte:	Algorithms Circuits Convergence Optimization Upper bounds
Online-Zugang:	Volltext
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