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The Computational Pendulum: From Classical Mechanics to Neural Networks

The Computational Pendulum: From Classical Mechanics to Neural Networks
This book is 50% completeLast updated on 2026-10-20

The ultimate bridge from high school AP Physics to modern AI. Start with the familiar physics you know, translate it into Python, and use it as a launchpad to build advanced Machine Learning models and neural networks. Includes 100% solved exercises and click-to-run Google Colab labs.

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About

About

About the Book

Most textbooks present math and physics as rigid formulas on flat paper. This book changes that by introducing Computational Physics—the exact blend of advanced mathematics, physics, and software engineering used by researchers at NASA, SpaceX, and top data science labs.

Designed explicitly for upper high school students (Grades 10-12), advanced middle schoolers, and tech-forward homeschool collectives, this workbook bridges the gap between theoretical calculations and practical software execution.

🗂️ How the Book is Structured: A 3-Stage Pipeline

  • Phase 1: The High School Runway (First 35% — Most of it Available Now): Perfect for AP Physics students and coding beginners. We start with standard AP-level mechanics, kinematics, and energy conservation. Instead of just solving these equations on paper, students learn how to convert them into foundational Python code.
  • Phase 2: The Numerical Leap (In Progress): Stepping into university-level computational physics. We strip away the over-simplified "small-angle approximations" found in standard textbooks. Students learn why standard math breaks down in the real world and how to solve complex dynamical systems using heavy numerical tools like 4th-order Runge-Kutta (RK4) integration and Fast Fourier Transforms (FFT).
  • Phase 3: The AI Destination (In Progress): Building a standout modern portfolio. We use our trusted pendulum model as a transparent baseline to explore modern artificial intelligence. Students will build and train Physics-Informed Neural Networks (PINNs) in JAX, discover physical laws directly from raw data, and explore cutting-edge concepts like Reservoir Computing.

💡 Why Buy the In-Progress Edition Today?

This is a living curriculum currently in active development. By purchasing the in-progress book today, you lock in the lowest possible price. As new chapters, calculus projects, and physics models are added, the minimum price of this book will scale upward. Buying today ensures you get all future updates entirely for free.

Author

About the Author

Horos Kyklos

HOROS KYKLOS holds advanced degrees in physics and computer science and has worked in both academia and the software industry. Having spent years navigating theoretical research and production software engineering, Kyklos writes with a focus on uniting mathematical rigor with modern computation. THE COMPUTATIONAL PENDULUM grew out of a desire to tear down the artificial walls between analytical physics, numerical simulation, and machine learning—showing students, educators, and developers how a single physical system can illuminate all three.

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