On the generalization limits of quantum generative adversarial networks with pure state generators

Abstract We investigate the capabilities of quantum generative adversarial networks (QGANs) in image generations tasks. Our analysis centers on fully quantum implementations of both the generator and discriminator. Through extensive numerical testing of current main architectures, we find that QGANs...

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Auteurs principaux:	Jasmin Frkatovic, Akash Malemath, Ivan Kankeu, Yannick Werner, Matthias Tschöpe, Vitor Fortes Rey, Sungho Suh, Paul Lukowicz, Nikolaos Palaiodimopoulos, Maximilian Kiefer-Emmanouilidis
Format:	Artigo
Langue:	Inglês
Publié:	Nature Portfolio 2026-06-01
Collection:	Scientific Reports
Sujets:	Quantum generative adversarial networks Quantum machine learning Image processing Quantum generative models
Accès en ligne:	https://doi.org/10.1038/s41598-026-54900-7
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