The Fractal Noise Soup

In our investigation into fractal geometry, we ended up experimenting quite extensively with fractal noise. Noise has a multitude of different uses in the digital fields, and is commonly used to increase realism in computer graphics and motion effects, utilized for example in video games to create terrains such as mountains and oceans, but also to distribute things across a digital map that should not be completely randomly placed, such as, for example, trees in a forest. Compared to complete randomness, noise is more organic because it produces a naturally ordered (“smooth”) sequence of pseudo-random numbers that is possible to control, compared to the harshly ordered sequence of random numbers.

In 3D noise, which is what we used in the production of our structures, the noise can be thought of as a sort of soup of evenly spaced points in a 3D space, each with a force and a direction assigned to it. Furthermore, all of the points recieve their unique attributes (where they are pointing and with what force) from looking at the closest neighboring points. If one “dips” a geometrical shape into a noise soup, the points will transform the shape by tugging and pulling it in different directions. At the bottom of this page, a visual representation of a 3D noise known as Perlin noise can be seen.

As previously stated, the noise that we worked with is known as a fractal noise, meaning the same noise soup is applied over and over again at diminishing scales. This gives rise the same transformation of the input geometry across several scales, and the emergence of fractal geometry.