Second Order Conditions to Decompose Smooth Functions as Sums of Squares

SIAM Journal on Optimization, Volume 34, Issue 1, Page 616-641, March 2024.
Abstract. We consider the problem of decomposing a regular nonnegative function as a sum of squares of functions which preserve some form of regularity. In the same way as decomposing nonnegative polynomials as sum of squares of polynomials allows one to derive methods in order to solve global optimization problems on polynomials, decomposing a regular function as a sum of squares allows one to derive methods to solve global optimization problems on more general functions. As the regularity of the functions in the sum of squares decomposition is a key indicator in analyzing the convergence and speed of convergence of optimization methods, it is important to have theoretical results guaranteeing such a regularity. In this work, we show second order sufficient conditions in order for a [math] times continuously differentiable nonnegative function to be a sum of squares of [math] differentiable functions. The main hypothesis is that, locally, the function grows quadratically in directions which are orthogonal to its set of zeros. The novelty of this result, compared to previous works is that it allows sets of zeros which are continuous as opposed to discrete, and also applies to manifolds as opposed to open sets of [math]. This has applications in problems where manifolds of minimizers or zeros typically appear, such as in optimal transport, and for minimizing functions defined on manifolds.