Learn Physics with Functional Programming
summary
Claims a working Haskell pipeline that turns physics formulas into runnable code and live plots, encoding Haskell types for position velocity acceleration, using numerical integration via the midpoint rule and differentiation as higher‑order functions, solving ODEs with the Euler method and Runge Kutta 2, building a one‑body force solver over vectors, reproducing parabolic freefall, terminal velocity and a cyclist step‑force profile, and comparing Newtonian growth to a relativistic asymptote at c.
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chapters (13)
- 0:00Introduction
- 1:05Why functional programming
- 3:11Physics with Haskell types
- 5:20Derivatives as higher-order functions
- 8:11Numerical integration in Haskell
- 10:21Antiderivatives and fundamental theorem
- 12:28Kinematic physics problems
- 13:54Newton’s second law and forces
- 16:24Differential equations with Euler’s method
- 18:32Extending to vectors
- 19:38Newton’s law solver
- 20:45Newtonian vs relativistic physics
- 21:54Closing thoughts
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