Quantum algorithms for topological and geometric analysis of data

Persistent homology allows identification of topological features in data sets, allowing the efficient extraction of useful information. Here, the authors propose a quantum machine learning algorithm that provides an exponential speed up over known algorithms for topological data analysis.

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Autores principales: Seth Lloyd, Silvano Garnerone, Paolo Zanardi
Formato: article
Lenguaje:EN
Publicado: Nature Portfolio 2016
Materias:
Q
Acceso en línea:https://doaj.org/article/70f1e67b437a4e34a6db16ebd4c0eb3d
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