Implementation and study of the Lorenz 1980 model in Python 🌪️
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Updated
Jan 10, 2026 - Python
Implementation and study of the Lorenz 1980 model in Python 🌪️
Lorenz system - Repository for the project for Software and Computing for Applied Physics
🌀 Illustration of the Lorenz System
Plain Convolution Encryption as an Alternative to Overcoming the Limitations of Synchronization-Based Methods
This repository contains the code for the blog post on Solving the Lorenz system using Runge-Kutta methods. For further details, please refer to this post.
Computation of Unstable Periodic Orbits for the Lorenz system
Code for the paper "System Identification with Copula Entropy"
Lorenz Attractor
Hybrid Physics-AI for forecasting the Lorenz-63 chaotic system with Explainable AI (gradient saliency). Compares Physics Baseline, MLP, and Hybrid (RK4 + residual NN) on short-term MSE, divergence time, and attractor similarity.
Python project evaluating multi-process parallelism for numerical simulation of the Lorenz system using RK4 and multiprocessing
A high-fidelity Physics-Informed Neural Network (PINN) research platform for solving the 1D convection-diffusion equation with enforced conservation of mass. Neural ODE · PINN · NODE-ONet · Real-time inference · Interactive dashboard.
A Python framework for chaotic/hyperchaotic synchronization, control, disturbance analysis, and nonlinear dynamical systems simulation.
This project features two dynamic simulations: bungee jumping and atmospheric convection models, using Runge-Kutta methods to capture their behavior. Dive into chaotic Lorenz attractor visuals, track variable evolution via time series charts, and compare cord lengths between these intriguing simulations. Explore dynamic modeling and chaotic systems
MATLAB benchmark suite for comparing numerical integrators on classical differential-equation problems, including linear decay, harmonic oscillator, Van der Pol, Lorenz, Robertson kinetics, and Kepler two-body dynamics. The repository includes performance plots, accuracy metrics, conservation analysis, and a simulation video available on YouTube.
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