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Periodic orbits in chaotic systems simulated at low precision

Non-periodic solutions are an essential property of chaotic dynamical systems. Simulations with deterministic finite-precision numbers, however, always yield orbits that are eventually periodic. With 64-bit double-precision floating-point numbers such periodic orbits are typically negligible due to...

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Autores principales: Klöwer, Milan, Coveney, Peter V., Paxton, E. Adam, Palmer, Tim N.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10349059/
https://www.ncbi.nlm.nih.gov/pubmed/37452044
http://dx.doi.org/10.1038/s41598-023-37004-4
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author Klöwer, Milan
Coveney, Peter V.
Paxton, E. Adam
Palmer, Tim N.
author_facet Klöwer, Milan
Coveney, Peter V.
Paxton, E. Adam
Palmer, Tim N.
author_sort Klöwer, Milan
collection PubMed
description Non-periodic solutions are an essential property of chaotic dynamical systems. Simulations with deterministic finite-precision numbers, however, always yield orbits that are eventually periodic. With 64-bit double-precision floating-point numbers such periodic orbits are typically negligible due to very long periods. The emerging trend to accelerate simulations with low-precision numbers, such as 16-bit half-precision floats, raises questions on the fidelity of such simulations of chaotic systems. Here, we revisit the 1-variable logistic map and the generalised Bernoulli map with various number formats and precisions: floats, posits and logarithmic fixed-point. Simulations are improved with higher precision but stochastic rounding prevents periodic orbits even at low precision. For larger systems the performance gain from low-precision simulations is often reinvested in higher resolution or complexity, increasing the number of variables. In the Lorenz 1996 system, the period lengths of orbits increase exponentially with the number of variables. Moreover, invariant measures are better approximated with an increased number of variables than with increased precision. Extrapolating to large simulations of natural systems, such as million-variable climate models, periodic orbit lengths are far beyond reach of present-day computers. Such orbits are therefore not expected to be problematic compared to high-precision simulations but the deviation of both from the continuum solution remains unclear.
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spelling pubmed-103490592023-07-16 Periodic orbits in chaotic systems simulated at low precision Klöwer, Milan Coveney, Peter V. Paxton, E. Adam Palmer, Tim N. Sci Rep Article Non-periodic solutions are an essential property of chaotic dynamical systems. Simulations with deterministic finite-precision numbers, however, always yield orbits that are eventually periodic. With 64-bit double-precision floating-point numbers such periodic orbits are typically negligible due to very long periods. The emerging trend to accelerate simulations with low-precision numbers, such as 16-bit half-precision floats, raises questions on the fidelity of such simulations of chaotic systems. Here, we revisit the 1-variable logistic map and the generalised Bernoulli map with various number formats and precisions: floats, posits and logarithmic fixed-point. Simulations are improved with higher precision but stochastic rounding prevents periodic orbits even at low precision. For larger systems the performance gain from low-precision simulations is often reinvested in higher resolution or complexity, increasing the number of variables. In the Lorenz 1996 system, the period lengths of orbits increase exponentially with the number of variables. Moreover, invariant measures are better approximated with an increased number of variables than with increased precision. Extrapolating to large simulations of natural systems, such as million-variable climate models, periodic orbit lengths are far beyond reach of present-day computers. Such orbits are therefore not expected to be problematic compared to high-precision simulations but the deviation of both from the continuum solution remains unclear. Nature Publishing Group UK 2023-07-14 /pmc/articles/PMC10349059/ /pubmed/37452044 http://dx.doi.org/10.1038/s41598-023-37004-4 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Article
Klöwer, Milan
Coveney, Peter V.
Paxton, E. Adam
Palmer, Tim N.
Periodic orbits in chaotic systems simulated at low precision
title Periodic orbits in chaotic systems simulated at low precision
title_full Periodic orbits in chaotic systems simulated at low precision
title_fullStr Periodic orbits in chaotic systems simulated at low precision
title_full_unstemmed Periodic orbits in chaotic systems simulated at low precision
title_short Periodic orbits in chaotic systems simulated at low precision
title_sort periodic orbits in chaotic systems simulated at low precision
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10349059/
https://www.ncbi.nlm.nih.gov/pubmed/37452044
http://dx.doi.org/10.1038/s41598-023-37004-4
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