Computational Physics

Numerical simulation of physical systems

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What I do

  • Implement numerical integration methods (Runge-Kutta, Verlet)
  • Solve partial differential equations (finite difference, FEM)
  • Monte Carlo simulations for statistical systems
  • Implement spectral methods (FFT-based solutions)
  • Optimize computational performance for physics problems
  • Validate simulations against analytical solutions

When to use me

When analytical solutions are intractable and numerical simulation is needed for physical systems.

Key Concepts

  • Finite Difference: Approximate derivatives as (f(x+h) - f(x))/h
  • Runge-Kutta 4th Order: y_{n+1} = y_n + (k₁ + 2k₂ + 2k₃ + k₄)/6 with staged evaluations
  • Verlet Integration: Symplectic method preserving energy for molecular dynamics
  • Fast Fourier Transform: O(N log N) for solving PDEs in spectral space
  • Monte Carlo: Random sampling for integration in high dimensions
  • Finite Element Method: Mesh-based solution for complex geometries

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