Title :
SDP Integrality Gaps with Local ell_1-Embeddability
Author :
Khot, Subhash ; Saket, Rishi
Author_Institution :
Comput. Sci. Dept., New York Univ., New York, NY, USA
Abstract :
We construct integrality gap instances for SDP relaxation of the MAXIMUM CUT and the SPARSEST CUT problems. If the triangle inequality constraints are added to the SDP, then the SDP vectors naturally define an n-point negative type metric where n is the number of vertices in the problem instance. Our gap-instances satisfy a stronger constraint that every sub-metric on t = O((log log log n)1/6) points is isometrically embeddable into l1. The local l1-embeddability constraints are implied when the basic SDP relaxation is augmented with t rounds of the Sherali-Adams LP-relaxation. For the MAXIMUM CUT problem, we obtain an optimal gap of αGW -1 - ϵ, where αGW is the Goemans-Williamson constant [11] and ϵ ≫ 0 is an arbitrarily small constant. For the SPARSEST CUT problem, we obtain a gap of Ω((log log log n)1/13). The latter result can be rephrased as a construction of an npoint negative type metric such that every t-point sub-metric is isometrically l1-embeddable, but embedding the whole metric into l1 incurs distortion Ω((log log log n)1/13).
Keywords :
approximation theory; computational complexity; Goemans-Williamson constant; SDP integrality gaps; Sherali-Adams LP-relaxation; embeddability constraints; maximum cut problems; sparsest cut problems; triangle inequality constraints; Approximation algorithms; Computer science; Educational institutions; Engineering profession; Polynomials; Programming profession; USA Councils; SDP; embedding; integrality; metric;
Conference_Titel :
Foundations of Computer Science, 2009. FOCS '09. 50th Annual IEEE Symposium on
Conference_Location :
Atlanta, GA
Print_ISBN :
978-1-4244-5116-6
DOI :
10.1109/FOCS.2009.37