ArticleScientific reports2023
Periodic orbits in chaotic systems simulated at low precision.
Article in Scientific reports, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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Who cites it
6 citing papers in PubMed, 17 citations in OpenAlex.
- Fast-forward prediction of lattice Boltzmann dynamics with physics-informed neural operators.Nature communications · 2026Article
- Quantum-informed machine learning for predicting spatiotemporal chaos with practical quantum advantage.Science advances · 2026Article
- Legendre based neural networks integrated with heuristic algorithms for the analysis of Lorenz chaotic model: an intelligent and comparative study.Scientific reports · 2025Article
- Artificial Intelligence Must Be Made More Scientific.Journal of chemical information and modeling · 2024Article
- Neuro-computing solution for Lorenz differential equations through artificial neural networks integrated with PSO-NNA hybrid meta-heuristic algorithms: a comparative study.Scientific reports · 2024Article
- Lessons for Theory from Scientific Domains Where Evidence is Sparse or Indirect.Computational brain & behavior · 2024Article
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Authors and funding
4 authors at 2 institutions in 2 countries.
Funding
Abstract
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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