A [Very] Rough Approximation to "White Noise" with Sine Waves This might be a silly question, but I'm pretty rusty on my signals. The problem is the following:
I'm using a program which does not have a random signal generator, but I can sum up sines; and I need to have a "white noise" signal.

What would be a good way to "approximate" a white noise signal with sines?

I know that I'll need an infinite amount of sines... but understand that I can't do that, I'm limited to the program limitations. So my specific questions are the following:

1) Should the frequencies of the sine waves be below or(and?) above the Nyquist frequency?

2) Say I've chosen I want "white noise" in frequencies 10Hz-100Hz, and I can only use 10 sines. Should I equally space the frequencies inside this range? Or choose them at random?

3) Now that I have my frequencies, what magnitudes should I assign these sines if I want to have a specific "Gaussian" distribution of my "white noise" signal values?

Hope this question doesn't cringe upon anybody that likes "pure" white noise!
Phase and amplitude of this sinusoids should be random, so you need Gaussian random number generator. If you don't have the random number  generator then might want to think about implementing one, here is, I believe, the most popular algorithm: Box-Muller transform.

Depending on your application and device, you might also want to use other noise source (i.e. Online generators, highly amplified signal from a probe).