Random numbers

• Introduction
  • Main concepts

Uniformly distributed integer random numbers with boost

• Linear congruential generators
  • Short cycle length
  • Sensitivity to algorithm parameters
• Mersenne Twister Generators
  • Seeding the generator
  • Saving and restoring the state of the generator
• Uniform integer random numbers on a user-defined range

Floating point number distributions

• Uniform floating point numbers in the interval 0 to 1
  • Introduction
  • Generation using boost
  • Relationship with the underlying integer generator
• Normally distributed random numbers
  • Introduction
  • Algorithms for generating normally distributed numbers
  • Generation using boost
• Trivial example: Monte Carlo integration of the normal distribution
  • The Monte-Carlo algorithm
  • The program

References

[Bauke09.7]

“Tina’s Random Number Generator Library” (user manual), Heiko Bauke