If you are willing to accept lookup tables or approximations, then yeah, arbitrary distributions are trivial. However for certain domains, you may want a more closed form solution for mapping uniform to your distribution, which may not be obvious. E.g. I would say generating pink noise is not "trivial" because there is no closed form solution (c.f. generating gaussian distribution via Box-Muller, that is trivial), so you need to pick a method which may have tradeoffs.
I guess I assumed the operative word was "good". The term "random number generator" almost always refers to a generator that intends to produce a uniform distribution.
Why do you need an arbitrary distribution? We are talking about breaking ties, just use uniform. You can probably just use RDRAND.
They are equivalent. Generating an arbitrary distribution from a uniform one is trivial.
If you are willing to accept lookup tables or approximations, then yeah, arbitrary distributions are trivial. However for certain domains, you may want a more closed form solution for mapping uniform to your distribution, which may not be obvious. E.g. I would say generating pink noise is not "trivial" because there is no closed form solution (c.f. generating gaussian distribution via Box-Muller, that is trivial), so you need to pick a method which may have tradeoffs.
i agree. to break ties uniform distribution should be sufficient
I guess I assumed the operative word was "good". The term "random number generator" almost always refers to a generator that intends to produce a uniform distribution.
If you can sample from a uniform distribution, it is trivial to turn that into any arbitrary distribution.