These high resolution wallpapers were created quickly, in about 30 minutes each.

Please note that each was created at a specific resolution, and was simply scaled to fit the other resolutions. You may want to download the wallpaper at the specific resolution that it was created in and let your Operating System automatically resize it to fit others. Most of the new Operating Systems (at least Windows ME and later) have good resizing capabilities. Note that some older Operating Systems (at least Windows 98 and prior) do not have this capability, and allowing it to resize your background will result in very blocky images (if resized larger), or missing scan lines (if resized smaller).

My brother, Matthew Doucette, has more wallpapers / desktops available on his personal website located here: http://www.matthewdoucette.com/wallpapers/. Check it out.

But, that's boring. We can create astonishing pictures by coloring all points that are outside the Mandelbrot set according to their proximity to the Mandelbrot set. In other words, we color points outside of the Mandelbrot set according to how close to the Mandelbrot set they are. Besides, if we just colored it black and white, a lot of beautiful images would be all white, since often only a minute, indistinguishable percentage of the image's area is within the set (any of the images below that have an absence of black areas are examples of this). If we color the areas outside of the set, we are able to distinguish which portions are closer to the set than others, and it creates breathtaking patterns. Here is what the same image looks like with colors:

How can you tell how close to the Mandelbrot set a point is?

We can find this out by looking how quickly each point is divergent. If it takes a lot of iterations to notice a point is divergent, it means the point is almost in the Mandelbrot set, but not quite. We color this a different color than points that are really far away from being inside the Mandelbrot set - those that are divergent right away. The result is a smooth palette of colors that signifies how close to the set each point is.

Why are the colors different in each picture?

The colors chosen for 'painting' these pictures are arbitrary - they were just made up, and have no real significance other than two similar colors represent places that are the same distance away from the Mandelbrot set. By creating a smooth flowing palette of colors, we can visualize portions of the image that are all relatively the same distance away from the Mandelbrot Set.

Why does every picture look different?

Perhaps the most amazing thing about the Mandelbrot set is that it has infinite detail. You can zoom in on any point with detail forever and get more detail. The images below are places I personally zoomed in on. Some of the images are zoomed in sections of others - if you look close enough, you will notice.

Why are there two links for each picture?

The first link ([Normal]) is the normal way Mandelbrot set images are created - without any anti-aliasing. You will see lots of graphic artifacts in these. This is not how the image would look in real life, if it existed.

The second link ([Better]) is my method of creating Mandelbrot images, which removes aliasing. I do this by supersampling. I sample each pixel thousands of times to ensure that it is the right color. These images are the way you would see the Mandelbrot set with your own eyes, if this were possible.

By comparing the two, you will notice a significant amount of greater detail and clarity with my version.

The image files are huge! Why?
I can see some fuzziness when looking really close. Why?

I use the web standard .JPG image format to store these images. Unfortunately, the .JPG format is lossy, meaning that data is lost during the compression of the data. While this is okay with most real life images, you can notice unclear portions of this images if you look close enough (when dealing with images of infinite detail, one tends to look very closely at the detail of a single snapshot to find more detail). I have avoided data loss as much as possible by saving the images in a high quality setting, but these images still do not match the perfect image data of the originals.

The original (perfect data) images stored in .TGA image format range from over 550 KB to almost 2,000 KB in size. In comparison, these .JPGs only range from 100 KB to almost 500 KB.