Newton Polytopes and Relative Entropy Optimization
Riley Murray, Venkat Chandrasekaran, Adam Wierman

TL;DR
This paper introduces new structural insights into SAGE certificates for certifying signomial nonnegativity, enabling efficient convex relaxation methods for a broad class of nonconvex optimization problems, including polynomial cases.
Contribution
It characterizes the extreme rays of SAGE cones, links Newton polytope structure to nonnegativity certification, and broadens the class of problems solvable via convex relaxation.
Findings
SAGE certificates can be characterized by extreme rays and sparsity.
Signomial nonnegativity is equivalent to SAGE decomposition under certain conditions.
Polynomial nonnegativity certification can be achieved efficiently, independent of degree.
Abstract
Certifying function nonnegativity is a ubiquitous problem in computational mathematics, with especially notable applications in optimization. We study the question of certifying nonnegativity of signomials based on the recently proposed approach of Sums-of-AM/GM-Exponentials (SAGE) decomposition due to the second author and Shah. The existence of a SAGE decomposition is a sufficient condition for nonnegativity of a signomial, and it can be verified by solving a tractable convex relative entropy program. We present new structural properties of SAGE certificates such as a characterization of the extreme rays of the cones associated to these decompositions as well as an appealing form of sparsity preservation. These lead to a number of important consequences such as conditions under which signomial nonnegativity is equivalent to the existence of a SAGE decomposition; our results represent…
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