> What we need is a smoother, more organic randomness. That is what the noise function generates
Noise is really interpolated random numbers, and you can interpolate spatially and/or temporally. So noise definitely is smoother than a random number, but not exactly more organic.
> There are two flavours of noise—Perlin and Simplex.
There are lots more than two kinds of noise, just like there are a lot of different ways to interpolate data. This sentence should be corrected if possible.
> Vector fields are cool, but flow fields are an even more exciting visualization.
I don’t think this is standard terminology, flow field and vector field mean the same thing to me. If you google those two terms, you find images of what you’re calling vector fields for both, and also articles that say explicitly that they mean the same thing.
I usually think of the advected lines that are referred to as “flow” here called “streamlines”, or a “streamline visualization”.
BTW, the flow visualization rabbit hole is deep. The advection method in the article is a Newton integration, and there are many other ways push the particles around a vector field - and sometimes it really matters! It’s fun to figure out how to draw flow streamlines if the field is chaotic or divergent. Even more interesting & difficult is to compute and visualize the boundary (“separatrix”) between sections of the field that have different behavior.