Status: Fully Deployed
This visualization tool is fully deployed on Streamlit. I'm open to expanding it according to community input.
This visualization tool is fully deployed on Streamlit. I'm open to expanding it according to community input.
Interactive Logistic Map Simulator: Exploring the Boundaries of Chaos and Predictability
This tool allows you to explore the transitions from order to chaos in the logistic map equation:
\(x_{i+1} = r x_i (1 - x_i)\)
🚀 Access the Simulator
- Launch the Live App: Run the interactive ensemble simulations directly in your web browser.
💻 Source Code & Citation
The complete, modular source code (v1.0.0) for this application is open-source. If you use this tool in your research, please cite both the paper and the software archive:
- Software Archive (Zenodo):
- GitHub Repository: aaksoy-umiami/logistic_map
📄 Research Publication
- Aksoy, A. (2024). A Monte Carlo approach to understanding the impacts of initial-condition uncertainty, model uncertainty, and simulation variability on the predictability of chaotic systems. Chaos, 34, 011102. Read the Paper (DOI)