Today was our last inverse theory class. We didn’t have time to cover the conjugate gradient method, which was too bad, I was really hoping we would get to that stuff. One of our lab group’s weekly readings was on the double-differencing technique for earthquake location. In it, they described using a conjugate gradient-type method called LSQR. It’s supposed to allow you to avoid inverting a giant matrix when solving inverse problems. From my very basic understanding, it finds the answer in a sort of iterative way, by making successive guesses to find the minimum in some objective surface. The good news is that Matlab has a canned lsqr function, so I could just try it out and see for myself. Although the canned function can be a bad thing, because then you can just treat it like a black box.