The paper *Approximations to the Normal Distribution Function and An Extended Table for the Mean Range of the Normal Variables by Kiani, M and Panaretos, J and Psarakis, S and Saleem, M (2008)* reviews algorithms for computing the CDF of the univariate Normal distribution. Then they develop some new approximations.

From use of their new approximations, we learn that:

Φ(−600) = 6.54658820580769285210592771388810878211941283185317721116943e − 78177

This required them to compute 1080 terms of their series approximation.

Now Julia:

```
julia> sn=Normal(BigFloat("0.0"),BigFloat("1.0"))
Normal{BigFloat}(μ=0.0, σ=1.0)
julia> cdf(sn,-600)
6.546588205807692852105927713888108782119412831853177211169430430310177386453905e-78177
```

How did Julia do it?

Best I can figure out, the univariate Normal CDF is computed using the error function from the GNU MFPR library. Apparently it just keeps going until all the bits of BigFloat accurate.