Often in physics the equations are already known or can be derived. However, taking a formula, generally a PDE, and solving it efficiently is the real trick. Al

Often in physics the equations are already known or can be derived. However, taking a formula, generally a PDE, and solving it efficiently is the real trick. Also as you point out, formulating the equation in terms of core invariants you wish to hold, plays an important part. Finding simplified easy to solve solutions and using them to estimate solutions and using adjustments to get closer to the real solution is a baselime technique. That's the core of the pertubative approach in physics which uses : https://en.wikipedia.org/wiki/Perturbation_theory#:~:text=Perturbation%20theory%20develops%20an%20expression,%22first%2Dorder%22%20perturbative%20correction https://en.wikipedia.org/wiki/Perturbation_theory#:~:text=Pe... However, now it's possible to train AI models to learn much more complex approximations that allow them to run much quicker and more accurately. A prime example is DeepMinds AlphaFold, IMHO. I haven't read up on the research to much, but I'd place firm bets that AI models will be critical in controlling any viable fusion technology.