Tom Van Baak tvb at LeapSecond.com
Fri Oct 26 15:00:42 EDT 2018

```Ole,

> I'm simulating some noise to try to improve my somewhat sketchy
> understanding of what goes on with the various noise types as shown on an
> ADEV plot. Nothing fancy, ~3600 points of gaussian random numbers between 0
> and 1 in excel, imported into Timelab as phase data, scaled to ns.

I forgot to mention this page where I use Stable32 and TimeLab to look at all 5 noise types:

> You are correct, my statement was imprecise - I generate numbers between 0
> and 1, but then multiply that with a function in Excel that yields a normal
> distribution with a standard distribution of 1.

If you suspect problems with Excel, perhaps try something in Python or C instead.
That also will make it possible to work with millions of points when necessary.
For random numbers I use ancient code by George Marsaglia, and also Mersenne Twister 19937.
To convert uniform [0-1] random to Gaussian I use:

// Get normal (Gaussian) random sample with mean 0 and standard deviation 1
// See https://en.wikipedia.org/wiki/Marsaglia_polar_method
double normal (void)
{
// Use Box-Muller algorithm
double u1 = genrand1();
double u2 = genrand1();
double r = sqrt(-2.0 * log(u1));
double pi = 4 * atan(1);
double theta = 2.0 * pi * u2;
return r * sin(theta);
}

/tvb

```