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Large-scale interactive numerical experiments of chaos, solitons and fractals in real time via GPU in a web browser

Author

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  • Kaboudian, Abouzar
  • Cherry, Elizabeth M.
  • Fenton, Flavio H.

Abstract

The study of complex systems has emerged as an important field with many discoveries still to be made. Computer simulation and visualization provide important tools for studying complex dynamics including chaos, solitons, and fractals, but available computing power has been a limiting factor. In this work, we describe a novel and highly efficient computing and visualization paradigm using a Web Graphics Library (WebGL 2.0) methodology along with our newly developed library (Abubu.js). Our approach harnesses the power of widely available and highly parallel graphics cards while maintaining ease of use by simplifying programming through hiding implementation details, running in a web browser without the need for compilation, and avoiding the use of plugins. At the same time, it allows for interactivity, such as changing parameter values on the fly, and its computing is so fast that zooming in on a region of a fractal like the Mandelbrot set can incur no delay despite having to recalculate values for the entire plane. We demonstrate our approach using a wide range of complex systems that display dynamics from fractals to standing and propagating waves in 1, 2 and 3 dimensions. We also include some models with instabilities that can lead to chaotic dynamics. For all the examples shown here we provide links to the codes for anyone to use, modify and further develop with other models. Overall, the enhanced visualization and computation capabilities provided by WebGL together with Abubu.js have great potential to facilitate new discoveries about complex systems.

Suggested Citation

  • Kaboudian, Abouzar & Cherry, Elizabeth M. & Fenton, Flavio H., 2019. "Large-scale interactive numerical experiments of chaos, solitons and fractals in real time via GPU in a web browser," Chaos, Solitons & Fractals, Elsevier, vol. 121(C), pages 6-29.
    • Handle: RePEc:eee:chsofr:v:121:y:2019:i:c:p:6-29
    DOI: 10.1016/j.chaos.2019.01.005
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    Cited by:

    1. Kumari, Sudesh & Gdawiec, Krzysztof & Nandal, Ashish & Postolache, Mihai & Chugh, Renu, 2022. "A novel approach to generate Mandelbrot sets, Julia sets and biomorphs via viscosity approximation method," Chaos, Solitons & Fractals, Elsevier, vol. 163(C).
    2. Aguirre, J. & Almendral, J.A. & Buldú, J.M. & Criado, R. & Gutiérrez, R. & Leyva, I. & Romance, M. & Sendiña-Nadal, I., 2019. "Experimental complexity in physical, social and biological systems," Chaos, Solitons & Fractals, Elsevier, vol. 120(C), pages 200-202.
    3. Wang, Guancheng & Li, Qinrou & Liu, Shaoqing & Xiao, Hua & Zhang, Bob, 2022. "New zeroing neural network with finite-time convergence for dynamic complex-value linear equation and its applications," Chaos, Solitons & Fractals, Elsevier, vol. 164(C).

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