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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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Principais autores: Jasmin Frkatovic, Akash Malemath, Ivan Kankeu, Yannick Werner, Matthias Tschöpe, Vitor Fortes Rey, Sungho Suh, Paul Lukowicz, Nikolaos Palaiodimopoulos, Maximilian Kiefer-Emmanouilidis
Formato: Artigo
Idioma:Inglês
Publicado em: Nature Portfolio 2026-06-01
coleção:Scientific Reports
Assuntos:
Quantum generative adversarial networks
Quantum machine learning
Image processing
Quantum generative models
Acesso em linha:https://doi.org/10.1038/s41598-026-54900-7
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