Monte-Carlo Simulation

Klaus Werner

  1. Possible applications
  2. Purpose of this lecture
  3. Further reading
  1. Definition
  2. Chaotic RN generator
  3. Congruential generator   (Exercise 1)
  4. Shift register generator    (Exercise 2)
  5. A realistic RN generator   (Exercise 3) (Exercise 4) (Exercise 5)
  1. Definition
  2. Inversion method      (Exercise 1)  (Exercise 2)
  3. Change of scale         (Exercise 3)
  4. Rejection method       (Exercise 4)
  5. Discrete distributions     (Exercise 5)
  6. Superposition method     (Exercise 6)
  7. Combining different methods
  8. Combining random numbers  (Exercise 7)
  9. The normal distribution     (Exercise 8)
  1. Introduction
  2. Diffusion equation
  3. Solution of the diffusion equation
  4. Solution via Monte Carlo    (Exercise 1)
  5. Exact Solution         (Exercise 2)
  6. Possibility of decay      (Exercise 3)
  7. Drift and FP equation     (Exercise 4)
  8. Time evolution         (Exercise 5)
  1. Diffusion equation
  2. Solution of the diffusion equation
  3. Solution via Monte Carlo    (Exercise 1)
  4. Random direction       (Exercise 2)
  5. Reflecting wall        (Exercise 3)