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    A Note on the Reproducibility of Chaos Simulation


    Nazaré, Thalita E. and Nepomuceno, Erivelton and Martins, Samir A. M. and Butusov, Denis N. (2020) A Note on the Reproducibility of Chaos Simulation. Entropy, 22 (9). pp. 1-18. ISSN 1099-4300

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    Abstract

    An evergreen scientific feature is the ability for scientific works to be reproduced. Since chaotic systems are so hard to understand analytically, numerical simulations assume a key role in their investigation. Such simulations have been considered as reproducible in many works. However, few studies have focused on the effects of the finite precision of computers on the simulation reproducibility of chaotic systems; moreover, code sharing and details on how to reproduce simulation results are not present in many investigations. In this work, a case study of reproducibility is presented in the simulation of a chaotic jerk circuit, using the software LTspice. We also employ the OSF platform to share the project associated with this paper. Tests performed with LTspice XVII on four different computers show the difficulties of simulation reproducibility by this software. We compare these results with experimental data using a normalised root mean square error in order to identify the computer with the highest prediction horizon. We also calculate the entropy of the signals to check differences among computer simulations and the practical experiment. The methodology developed is efficient in identifying the computer with better performance, which allows applying it to other cases in the literature. This investigation is fully described and available on the OSF platform.

    Item Type: Article
    Keywords: reproducibility; computational chaos; computer arithmetic; OSF platform;
    Academic Unit: Faculty of Science and Engineering > Electronic Engineering
    Faculty of Science and Engineering > Research Institutes > Hamilton Institute
    Item ID: 16725
    Identification Number: https://doi.org/10.3390/e22090953
    Depositing User: Erivelton Nepomuceno
    Date Deposited: 21 Nov 2022 16:03
    Journal or Publication Title: Entropy
    Publisher: MDPI
    Refereed: Yes
    URI:
    Use Licence: This item is available under a Creative Commons Attribution Non Commercial Share Alike Licence (CC BY-NC-SA). Details of this licence are available here

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