To me, science is the nature of prediction. How well do your predictions match reality? Predictions are made on the basis of some kind of model (a set of equations is an example of one such model). The quality of science then, is predicated upon how closely predictions made via a model match reality.

In this sense, physics is the "best" science currently (12 decimal places of accuracy in predicting the gyromagnetic ratio of an isolated electron), followed probably by chemistry, then biology, then medicine, then psychology, etc. The only thing I mean by this ranking is that it is harder to come up with models that give accurate predictions in some fields relative to others.

A few people on this page have stated "Computer models are not science."

I disagree with this. My work is in molecular dynamics simulations and quantum chemistry.

Consider an experiment: you test nature and try to derive some sort of model that allows you to make future predictions. However, your model is marred by the concept of experimental error and system complexity (for instance, we can't currently observe all the neural activity in the human brain because of how difficult it is to image a brain without being too invasive).

Now consider a simulation: you take pre-existing models and use them to formulate predictions.

Both experiment and simulation allow you to make predictions that can be tested experimentally. But the quality of your predictions depends only on how accurate your model is, not the mere fact that you are running a simulation!

Let me elaborate: quantum mechanics is almost perfectly accurate in describing all phenomena that occur in everyday life (Peter Gill has said this, and I believe Dirac said it as well). It only falls apart with things like quantum gravity.

So we have a very accurate model. If you plug the wavefunction of a particular human brain into the Schrodinger equation, you'll get an almost perfect evolution of the brain through time (as compared experimentally to the real brain). The problem is that despite having a very accurate model of reality, it is not easy at all to turn this model into a testable prediction. We can really only use this model to its fullest capability for a couple of particles.

And this is where computational modeling comes into play. You can take this highly accurate model of reality called quantum mechanics and intentionally introduce error into it in order to speed up the rate at which you can formulate a prediction from it, e.g., you make an approximation to the Schrodinger equation that you can solve quickly, and while you know that this approximation is not an exact solution, you can still develop predictions from it. And when you take these predictions and then test them experimentally, you find that the experimental results match up pretty well. In fact, in some cases the error in your approximation to the Schrodinger equation is small enough that you can do better than experiment, because your numerical error is smaller than the systematic error that an experimentalist must deal with in the lab.

So to me, it doesn't matter where the prediction comes from, or how it was formed. If that prediction can be tested -- and if once tested it is found to match reality to some degree -- then you have some form of science (of varying levels of quality).

String theory does in fact make physical predictions. But those predictions can't be tested yet. So it's still a form of science, although maybe not a very useful form since it could be a long time (or never) before we are able to test it somehow. Many-world theory however is NOT a form of science, because it makes NO predictions whatsoever. It's just an interpretation. It says nothing different than any other interpretation of quantum mechanics. It is not science. (In a similar vein, I've always thought people who try to "use" science to argue for or against the existence of God are totally wasting their time since neither side can even come up with a testable prediction.)