Hi everyone! 
I’m excited to share the Logistic Map Simulator, an interactive application I developed to visualize the limits of predictability in chaotic systems both for initial and model error scenarios. Please see all relevant links at the bottom.
This app serves as the frontend interface for my recent research paper published in Chaos: “A Monte Carlo approach to understanding the impacts of initial-condition uncertainty…” (Aksoy, 2024).
What the app does: It allows users to explore how tiny errors in initial conditions grow exponentially over time (the Butterfly Effect). You can use it to:
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Generate Bifurcation Diagrams: Visualize the transition from order to chaos with density plots.
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Run Ensemble Simulations: See how a “cloud” of initial conditions spreads out over time.
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Analyze Predictability: Calculate the exact time step where a forecast becomes useless based on model error.
Tech Stack:
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Streamlit
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Matplotlib (for the static visualizations)
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Numpy & Scipy (for the heavy computation)
Links:
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Live App: https://logistic-map.streamlit.app/
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Original Paper: https://doi.org/10.1063/5.0181705
I’d love to hear your feedback on the UI or the visualization tools!
Cheers, Altug