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Trainability barriers and opportunities in quantum generative modeling / Rudolph, Manuel S. (Ecole Polytechnique, Lausanne) ; Lerch, Sacha (Ecole Polytechnique, Lausanne) ; Thanasilp, Supanut (Ecole Polytechnique, Lausanne ; Chulalongkorn U.) ; Kiss, Oriel (CERN ; Geneva U.) ; Shaya, Oxana (LPHE, Lausanne) ; Vallecorsa, Sofia (CERN) ; Grossi, Michele (CERN) ; Holmes, Zoë (Ecole Polytechnique, Lausanne)
Quantum generative models, in providing inherently efficient sampling strategies, show promise for achieving a near-term advantage on quantum hardware. Nonetheless, important questions remain regarding their scalability. [...]
arXiv:2305.02881.- 2024-11-13 - 52 p. - Published in : npj Quantum Inf. 10 (2024) 116 Fulltext: 2305.02881 - PDF; document - PDF;

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