How do exponential size solutions arise in semidefinite programming?
Abstract
A striking pathology of semidefinite programs (SDPs) is illustrated by a classical example of Khachiyan: feasible solutions in SDPs may need exponential space even to write down. Such exponential size solutions are the main obstacle to solve a long standing, fundamental open problem: can we decide feasibility of SDPs in polynomial time? The consensus seems that SDPs with large size solutions are rare. However, here we prove that they are actually quite common: a linear change of variables transforms every strictly feasible SDP into a Khachiyan type SDP, in which the leading variables are large. As to ``how large", that depends on the singularity degree of a dual problem. Further, we present some SDPs coming from sum-of-squares proofs, in which large solutions appear naturally, without any change of variables. We also partially answer the question: how do we represent such large solutions in polynomial space?
Cite
@article{arxiv.2103.00041,
title = {How do exponential size solutions arise in semidefinite programming?},
author = {Gábor Pataki and Aleksandr Touzov},
journal= {arXiv preprint arXiv:2103.00041},
year = {2023}
}
Comments
To appear, SIAM Journal on Optimization. Many minor points were clarified compared to v1. We also added a lot more detail to the proof of the most technical lemma, Lemma 5