We’re taught that science is split between theory and experiment. You either sweat away with pencil in hand, furiously scribbling equation after obscure equation, searching for answers. Or you sweat away in a laboratory or observatory, performing experiment after repetitive experiment, trying to wrangle some sort of clue from nature’s jealous grasp.
This view is…incomplete.
First, it completely ignores the fluid nature of scientific research - the lines between theory and experiment are very fuzzy. And secondly, it completely ignores a way of performing science that is relatively new: the rise of the machine.
The physical sciences use mathematics to understand nature. That is our stock-in-trade: we model systems with math, we analyze experiments with math, we discuss results with math.
But some (heck, most) math problems are too hard (heck, impossible) to solve with pencil and paper. Enter the computer, a machine specifically designed to…well, compute.
All modern-day scientists are basically amateur computer programmers. Computers are used to evolve predictions from initial conditions, to perform numerical experiments in situations where we can’t perform real ones, for data analysis, for…understanding nature. For doing science.
If you’re interested in science, I hope you like computers.