Last year, at the start of my graduate education, I was given the assignment of describing my research (or what I thought it would be at that somewhat premature point) using only the thousand most commonly used words in the English language.
This assignment was inspired by a web comic that attempted to recreate a blueprint of the Saturn V rocket using this simplified language. Following the publication of that comic, the Up-Goer Five text editor was created and subsequently, the Ten Hundred Words of Science Challenge was born. The challenge led scientists from virtually all disciplines to create jargon-free descriptions of their projects.
While perusing some of these descriptions, I found one that really resonated with me. I’ve copied that entry below. It is by Matthew Hoyles on computer simulation:
“Some people learn by trying things out. Some people learn by thinking very hard. I make a world inside a computer the way people think the world works, and then try things out, to see if we are thinking right.”
In the first sentence, we are told that “some people learn by trying things out”. The people to which he is referring are experimentalists – or scientists who derive information by conducting physical experiments. This is the type of science you’ve probably tried your hand at during high school or undergraduate laboratory courses.
The second sentence tells us that “some people learn by thinking very hard”. These people are the theorists or those that develop abstract ideas about the universe. Albert Einstein is best known for his work constructing theories.
The two types are united when experimentalists design and conduct tests for the ideas proposed by theorists. There are, of course, people that do both as well as people that do science that is somewhere in between the two broad categories.
In the last sentence, the author states that he makes “a world inside a computer the way people think the world works”. In other words, he uses a computer to develop a model, or simplification of reality that can readily be constructed on that machine, based on what has already been observed and interpreted through other means. The model is used to “then try things out”. This is analogous to physical experimentation. The results of these simulations can either support or contradict a particular theory.
In my opinion, the power of computer simulation comes from this unique ability to simply “try things out”. Often, experimentalists are limited in their ability to observe physical phenomena and theorists in their ability to predict the outcome of scenarios that might involve many interacting factors. So by performing experiments via computer simulation greater opportunities are afforded.
For example, in my own work, I think about things that happen deep in the ground over millions of years. No human being has been around long enough to observe what happened 50 million years ago and we don’t have the ability to travel 100 km into the Earth to directly see what’s going on. Additionally, to accurately describe how a mountain forms, one must consider an entire complex system. For example, mountains grow when rocks get pushed together and thrust upward but that growth is limited by things like erosion at the surface. Also, the way the rock responds to these forces changes over time and isn’t the same everywhere in the Earth.
But by using computer simulations, I have the ability to construct models that account for those complexities based on what can be observed and then extrapolate (in both time and space) as well as vary how my unknowns are defined. I can then determine what works best and what makes the most sense. If all goes well, I hope that one day I might be able to “see if we are thinking right”.