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Machine learning quantum phases of matter beyond the fermion sign problem

State-of-the-art machine learning techniques promise to become a powerful tool in statistical mechanics via their capacity to distinguish different phases of matter in an automated way. Here we demonstrate that convolutional neural networks (CNN) can be optimized for quantum many-fermion systems suc...

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Detalles Bibliográficos
Autores principales: Broecker, Peter, Carrasquilla, Juan, Melko, Roger G., Trebst, Simon
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5562897/
https://www.ncbi.nlm.nih.gov/pubmed/28821785
http://dx.doi.org/10.1038/s41598-017-09098-0