Adversarial quantum circuit learning for pure state approximation

Adversarial learning is one of the most successful approaches to modeling high-dimensional probability distributions from data. The quantum computing community has recently begun to generalize this idea and to look for potential applications. In this work, we derive an adversarial algorithm for the...

Πλήρης περιγραφή

Λεπτομέρειες βιβλιογραφικής εγγραφής

Κύριοι συγγραφείς:	Marcello Benedetti, Edward Grant, Leonard Wossnig, Simone Severini
Μορφή:	Artigo
Γλώσσα:	Inglês
Έκδοση:	IOP Publishing 2019-01-01
Σειρά:	New Journal of Physics
Θέματα:	quantum circuit learning generative models unsupervised learning
Διαθέσιμο Online:	https://doi.org/10.1088/1367-2630/ab14b5
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