At the heart of physics lies the idea that anything can be fully described by its most fundamental parts. A snowflake, for example, is simply a collection of water molecules arranged in a shape. This idea, rooted in reductionist philosophy, is so intuitive that defining it seems pedantic. However, philosophers of science have been questioning this viewpoint since the late 19th century, introducing a counterview known as "emergence." Emergence is said to occur when something depends on, yet is completely different from, its parts. A snowflake is still made of water, but it has properties which a water molecule simply cannot have on its own. At the heart of my project lies emergence. In particular, emergent computation is especially interesting to me. Simple rules can be said to give rise to emergent systems that have the novel capacity to process information. The computer scientist Christopher Langton found that in order for computation to emerge, a delicate balance of order and chaos must exist—order being needed to store information, and chaos being needed to transmit it. A system placed on this tipping point (known in statistical mechanics as a "phase transition") would then have the same computational limits as a home computer. In my project, I will explore emergent computation through the framework of statistical mechanics by building computer simulations of simple systems, including cellular automata and Boolean networks.