Local minima in nonconvex sum-of-square optimization via syzygies
- Shixuan Zhang
Abstract
We study spurious local minima in a nonconvex low-rank formulation of sum-of-squares optimization on a real variety $X$. We reformulate the problem of finding a spurious local minimum in terms of syzygies of the underlying linear series, and also bring in topological tools to study this problem. When the variety $X$ is of minimal degree, there exist spurious local minima if and only if both the dimension and the codimension of the variety are greater than one and $X$ is not the Veronese surface, answering a question by Legat, Yuan, and Parrilo. Moreover, for surfaces of minimal degree, we provide sufficient conditions to exclude points from being spurious local minima. In particular, all spurious local minima on the Veronese surface, corresponding to ternary quartics, lie on the boundary and can be written as a binary quartic, up to a linear change of coordinates, complementing work by Scheiderer on decompositions of ternary quartics as a sum of three squares. For general varieties of higher degree, we give examples and characterizations of spurious local minima in the interior, which can potentially lead to efficient low-rank sum-of-squares algorithms.