  Since diffusion processes arise in so many different fields, efficient
tech-nics for the simulation of sample paths, like discretization schemes,
represent crucial tools in applied probability. Such methods permit to obtain
approximations of the first-passage times as a by-product. For efficiency
reasons, it is particularly challenging to simulate directly this hitting time
by avoiding to construct the whole paths. In the Brownian case, the
distribution of the first-passage time is explicitly known and can be easily
used for simulation purposes. The authors introduce a new rejection sampling
algorithm which permits to perform an exact simulation of the first-passage
time for general one-dimensional diffusion processes. The efficiency of the
method, which is essentially based on Girsanov's transformation , is described
through theoretical results and numerical examples.
