Hi All,
I am completely new to python/cvxopt, and convex optimization in general. I am lucky to work in a field of physics where I really only ever have to solve one problem:
minimize (Trace(A*B_i)-v_i)^2
subject to Trace(A)=1,A>0 (matrix inequality)
The B_i's are hermitian matrices (user defined) and the v_i's are real scalars (also user defined).
I have been browsing the cvxopt website for a few days (and also browsing the docs for cvxpy, which have largely been of no help), so I thought I would ask here.
I'm sure there is a way to formulate this as a standard problem, but not really knowing much about convex optimization, I can't figure it out.
-dylan