• Properties and generation of Random Numbers with different distributions.
  • Monte Carlo simulation of Random Walks.
  • Numerical integration in 1 dimension: deterministic and stochastic algorithms;
  • Monte Carlo algorithms.
  • Error estimate and reduction of the variance methods.
  • Metropolis algorithm for arbitrary random number generation.
  • Metropolis method in the canonical ensamble.
  • Ising model and Metropolis-Monte Carlo simulation.
  • Classical fluids: Monte Carlo and Molecular Dynamics simulation of hard spheres and Lennard-Jones fluids.
  • Microstates and macrostates: efficient algorithm for the numerical calculation of entropy.
  • Variational Monte Carlo in quantum mechanics (basics).
  • Lattice gas: vacancy diffusion in a solid.
  • Fractals: diffusion and aggregation, models for surface growth simulation. Percolation.
  • Chaos and determinism: classical billiards and chaotic billiards, logistic maps; Lyapunov exponents.

Ultime modifiche: lunedì, 2 marzo 2020, 13:24