@Article{Karney:2015:SEN,
  author =       "Charles F. F. Karney",
  title =        "Sampling Exactly from the Normal Distribution",
  journal =      "{ACM} Transactions on Mathematical Software",
  volume =       "42",
  number =       "1",
  accepted =     "22 December 2014",
  upcoming =     "true", 
  abstract =     "
                  An algorithm for sampling exactly from
                  the normal distribution is given. The
                  algorithm reads some number of uniformly
                  distributed random digits in a given
                  base and generates an initial portion of
                  the representation of a normal deviate
                  in the same base. Thereafter, uniform
                  random digits are copied directly
                  into the representation of the normal
                  deviate. Thus, in contrast to existing
                  methods, it is possible to generate
                  normal deviates exactly rounded to
                  any precision with a mean cost that
                  scales linearly in the precision. The
                  method performs no extended precision
                  arithmetic, calls no transcendental
                  functions, and, indeed, uses no floating
                  point arithmetic whatsoever; it uses
                  only simple integer operations. It can
                  easily be adapted to sample exactly from
                  the discrete normal distribution whose
                  parameters are rational numbers.",
}