As someone else said, not really. The link is linear algebra which is perhaps the best computational tool we have. In many areas of applied math, as soon as thi

As someone else said, not really. The link is linear algebra which is perhaps the best computational tool we have. In many areas of applied math, as soon as things get nonlinear (or non-quadratic if we’re taking derivatives since those derivatives become linear), it is impossible to find closed-form solutions (I.e., solutions you can write in a simple form). A big reason for this is that solving Ax = b might require a matrix (pseudo)inverse, but once you have that inverse, you have the solution for any pair (x, b), whereas if you had to solve f(x) = b, a new pair requires a fresh computation. Put in other terms, for linear problems, local properties are often global properties when studying linear problems. A lot of the numerical methods we use to solve hard problems are based on solutions to linear problems (or quadratic problems if we’re taking derivatives) that predate computer graphics because those problems are simple to solve. We can just solve them a lot faster now so approximating nonlinear things with linear things iteratively becomes a lot more computationally tractable.