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A Verified ODE Solver and the Lorenz Attractor

A rigorous numerical algorithm, formally verified with Isabelle/HOL, is used to certify the computations that Tucker used to prove chaos for the Lorenz attractor. The verification is based on a formalization of a diverse variety of mathematics and algorithms. Formalized mathematics include ordinary...

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Detalles Bibliográficos
Autor principal: Immler, Fabian
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer Netherlands 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6044317/
https://www.ncbi.nlm.nih.gov/pubmed/30069071
http://dx.doi.org/10.1007/s10817-017-9448-y
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author Immler, Fabian
author_facet Immler, Fabian
author_sort Immler, Fabian
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description A rigorous numerical algorithm, formally verified with Isabelle/HOL, is used to certify the computations that Tucker used to prove chaos for the Lorenz attractor. The verification is based on a formalization of a diverse variety of mathematics and algorithms. Formalized mathematics include ordinary differential equations and Poincaré maps. Algorithms include low level approximation schemes based on Runge–Kutta methods and affine arithmetic. On a high level, reachability analysis is guided by static hybridization and adaptive step-size control and splitting. The algorithms are systematically refined towards an implementation that can be executed on Tucker’s original input data.
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spelling pubmed-60443172018-07-30 A Verified ODE Solver and the Lorenz Attractor Immler, Fabian J Autom Reason Article A rigorous numerical algorithm, formally verified with Isabelle/HOL, is used to certify the computations that Tucker used to prove chaos for the Lorenz attractor. The verification is based on a formalization of a diverse variety of mathematics and algorithms. Formalized mathematics include ordinary differential equations and Poincaré maps. Algorithms include low level approximation schemes based on Runge–Kutta methods and affine arithmetic. On a high level, reachability analysis is guided by static hybridization and adaptive step-size control and splitting. The algorithms are systematically refined towards an implementation that can be executed on Tucker’s original input data. Springer Netherlands 2018-01-22 2018 /pmc/articles/PMC6044317/ /pubmed/30069071 http://dx.doi.org/10.1007/s10817-017-9448-y Text en © The Author(s) 2018 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.
spellingShingle Article
Immler, Fabian
A Verified ODE Solver and the Lorenz Attractor
title A Verified ODE Solver and the Lorenz Attractor
title_full A Verified ODE Solver and the Lorenz Attractor
title_fullStr A Verified ODE Solver and the Lorenz Attractor
title_full_unstemmed A Verified ODE Solver and the Lorenz Attractor
title_short A Verified ODE Solver and the Lorenz Attractor
title_sort verified ode solver and the lorenz attractor
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6044317/
https://www.ncbi.nlm.nih.gov/pubmed/30069071
http://dx.doi.org/10.1007/s10817-017-9448-y
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