Part of what I do is study typical behavior of large combinatorial structures by looking at pseudorandom instances.  But many commercially available pseudorandom number generators have known defects, which makes me wonder whether I should just use the digits (or bits) of $\pi$.

A colleague of mine says he "read somewhere" that the digits of $\pi$ don't make a good random number generator.  Perhaps he's thinking of the article "A study on the randomness of the digits of $\pi$" by Shu-Ju Tu and Ephraim Fischbach.  Does anyone know this article?  Some of the press it got (see e.g. http://news.uns.purdue.edu/html4ever/2005/050426.Fischbach.pi.html ) made it sound like $\pi$ wasn't such a good source of randomness, but the abstract for the article itself (see http://adsabs.harvard.edu/abs/2005IJMPC..16..281T ) suggests the opposite.

Does anyone know of problems with using $\pi$ in this way?  Of course if you use the digits of $\pi$ you should be careful not to re-use digits you've already used elsewhere in your experiment.

My feeling is, you should use the digits of $\pi$ for Monte Carlo simulations.  If you use a commercial RNG and it leads you to publish false conclusions, you've wasted time and misled colleagues.  If you use $\pi$ and it leads you to publish false conclusions, you've still wasted time and misled colleagues, but you've also found a pattern in the digits of $\pi$!

Strictly speaking, there are some known patterns in the digits of $\pi$.  There are some known results on how well $\pi$ can be approximated by rationals, which imply (for example) that we know a priori that the next $n$ as-yet-uncomputed digits of $\pi$ can't all be zero (for some explicit value of $n$ that I'm too lazy to compute right now).  In practice, though, these "patterns" are so weak that they will not affect any Monte Carlo experiments.

The main limitation of using the digits of $\pi$ may be the computational speed.  Depending on how many random digits you need, computing fresh digits of $\pi$ might become a computational bottleneck.  The further out you go, the harder it becomes to compute more digits of $\pi$.

If you are worried about the quality of random digits that you're getting, then you may want to use cryptographic random number generators.  For example, finding a pattern in the Blum-Blum-Shub random number generator would probably yield a new algorithm for factoring large integers!  Cryptographic random number generators will run more slowly than the "commercial" random number generators you're talking about but you can certainly find some that will generate digits faster than algorithms for computing $\pi$ will.
