PCAfold: Python software to generate, analyze and improve PCA-derived low-dimensional manifolds
Sign Up to like & getrecommendations! Published in 2020 at "SoftwareX"
DOI: 10.1016/j.softx.2020.100630
Abstract: Abstract Many scientific disciplines rely on dimensionality reduction techniques for computationally less expensive handling of multivariate data sets. In particular, Principal Component Analysis (PCA) is a popular method that can be used to discover the… read more here.
Keywords: pcafold python; low dimensional; dimensional manifolds; python software ... See more keywords
Low dimensional manifolds in reservoir computers.
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DOI: 10.1063/5.0047006
Abstract: A reservoir computer is a complex dynamical system, often created by coupling nonlinear nodes in a network. The nodes are all driven by a common driving signal. Reservoir computers can contain hundreds to thousands of… read more here.
Keywords: low dimensional; reservoir computer; reservoir computers; dimensional manifolds ... See more keywords
Low dimensional manifolds for exact representation of open quantum systems
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DOI: 10.1103/physreva.96.062113
Abstract: Weakly nonlinear degrees of freedom in dissipative quantum systems tend to localize near manifolds of quasiclassical states. We present a family of analytical and computational methods for deriving optimal unitary model transformations that reduce the… read more here.
Keywords: state; quantum; quantum systems; low dimensional ... See more keywords
New Cases of Homogeneous Integrable Systems with Dissipation on Tangent Bundles of Two-Dimensional Manifolds
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DOI: 10.1134/s1064562420050403
Abstract: The integrability of certain classes of homogeneous dynamical systems on the tangent bundles of two-dimensional manifolds is shown. The force fields involved in the systems lead to dissipation of variable sign and generalize previously considered… read more here.
Keywords: new cases; dissipation; dimensional manifolds; bundles two ... See more keywords