With the work of Khot and Vishnoi as a starting point, we obtain integrality gaps for certain strong SDP relaxations of Unique Games. Specifically, we exhibit a Unique Games gap instance for the basic semidefinite program strengthened by all valid linear inequalities on the inner products of up to exp(¿(log log n) 1/4 ) vectors. For a stronger relaxation obtained from the basic semidefinite program by R rounds of Sherali-Adams liftand-project, we prove a Unique Games integrality gap for R = ¿(log log n) 1/4 . By composing these SDP gaps with UGC-hardness reductions, the above results imply corresponding integrality gaps for every problem for which a UGC-based hardness is known. Consequently, this work implies that including any valid constraints on up to exp(¿(log log n) 1/4 ) vectors to natural semidefinite program, does not improve the approximation ratio for any problem in the following classes: constraint satisfaction problems, ordering constraint satisfaction problems and metric labeling problems over constant-size metrics. We obtain similar SDP integrality gaps for Balanced Separator, building on. We also exhibit, for explicit constants ¿, ¿ > 0, an n-point negative-type metric which requires distortion ¿(log log n) ¿ to embed into ¿ 1 , although all its subsets of size exp(¿(log log n) ¿ ) embed isometrically into ¿ 1 .
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Raghavendra et al. (2009) studied this question.
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