This post is a work in progress

Science is great. It’s awesome to see the ways people use math to describe the world and how clever abstractions help us understand nature better.

This term, I’m in a couple physics courses and a chemistry course. As someone whose courseload has been dominated by computer science courses, it’s hard not to relate everything back to CS.

A few notable examples below.

Chemistry

Chemical Naming

Ever since I learned how to name molecules according to some basic IUPAC rules, I really have wanted to write a program to represent molecules as data and figure out how to name them according to the rules. This is one of those things where there is a well defined written algorithm for it, but it may or may not have been implemented yet. My professor indicated that a program called ChemDraw can do this, but sometimes/often gets the name wrong.

Chemical Structure Analysis

Using NMR and IR spectroscopy, we can determine a lot about a molecule’s structure. Each time I sit down with a problem set or an exam question, it’s easy to start applying the algorithm I’ve developed

I have some thoughts on how this could be automated. Perhaps if you had a sufficiently large training set, it would be possible to machine learn strucutres for compounds.

Physics

Visualization of equations

One of the things I really detest about the way physics is currently taught is that the student is just spoonfed a few equations, then told to solve some problems. I feel like that’s a doable way to learn, but it’s suboptimal because the student isn’t really invested in the problem. An alternate teaching style would be to give a student sufficient instrumentation such that they could come up with a solution to describe a phenomenon like simple harmonic oscillation on it’s own, but in practice this isn’t really feasible due to time constraints. That also seems like a suboptimal solution.

I wonder if there’s some middleground, where computer simulations (D3 + worrydream.com’s work) could help manipulate a system in real time to give a student intuition about what’s going on behind the scenes.

Side note: one thing I’ve found more and more is that people get really caught up in notation and it’s likely that use of better notation would lead to better understanding of a system. In my opinion, computer scientists are better at naming variables (even though, according to XKCD, it’s the hardest problem in comp sci). When I see an omega on the board, that doesn’t really symbolize angular velocity so much as the variable name angular_velocity would. Doing math in programming languages is easier and more clear despite the excess activiation energy required to type the variable name.