Mathematical question: procedural generation of a galaxy

Question

I\'m going to make a space/trading/combat game that is completely procedurally generated. But, I know that storing all of the details of the whole galaxy in memory is unfeas

Answer 1

I think it is worth noting, that

1. a generator that produces the same random-looking output for the same input is called a pseudo random number generator, "PRNG". Typically you give it one "seed" input number at the very beginning and then just pull random numbers from it, calling it without further input. Note: you cannot "go back" to an earlier number, at least not without starting at the beginning.

2. a PRNG-like function that is called with coordinates as input of each call is typically a "noise" function. Here you do NOT have the "cannot go back" problem - just call with the "earlier" input again. A noise function uses a PRNG (as a backend; or at least it could) which still can be seeded at the very start, so you do not lose your "universe out of one number" feature.

3. While you could just use a PRNG and combine the galaxy coordinates to a "seed" each time, you would only get "white noise" at best, with no further attributes. A noise function is a much better fit for the job, as it can be chosen or even adjusted to give you tileable/smoothed/spiral-like looking/etc. results. For examples search texture images that were made using perlin noise. I expect you to see that with the same noise function you may create e.g. thousands of random clouds, but by adjusting the noise function to your needs (not just the seed or coordinates), you may get lava or galaxies instead. Adjusting it may not be trivial though.

4. The number of input coordinates for each call determines the number of dimensions of the noise function, so for a two dimensional map (or texture etc.) you could use a 2-dimensional noise function. Then you call it like noise2d(x,y) each time.

In your situation I would try a 3-dimensional simplex noise function (simplex is from the author of perlin noise, recommended as being better).

Each star system coordinate-triplet then gives you one result number. Next decision would be: what does the number represent? To put the smoothing feature of the simplex noise to good use, I would map lower numbers to emptier solar systems and higher numbers to systems with more mass. Or, maybe better, for each system call simplex noise multiple times with sub-coordinates. Medium sized result numbers then are planets, small numbers are vacuum or asteroids. Big numbers stars, etc.

The topic is not active and it is old but searches may end up here, as mine did.