## Abstract

We introduce a new graph parameter, called the Grothendieck constant of a graph G = (V, E), which is defined as the least constant K such that for every A : E → ℝ, sup Σ A(u, v) · 〈f(u), f(v)〉 f:V → S^{|V|-1}{u, v} ∈ E ≤ K sup Σ A (u, v) · f(u) f (v). f:V → {-1,+1} {u, v} ∈ E The classical Grothendieck inequality corresponds to the case of bipartite graphs, but the case of general graphs is shown to have various algorithmic applications. Indeed, our work is motivated by the algorithmic problem of maximizing the quadratic form Σ{u, v}∈E A(u, v)f(u)f(v) over all f:V → {-1,1}, which arises in the study of correlation clustering and in the investigation of the spin glass model. We give upper and lower estimates for the integrality gap of this program. We show that the integrality gap is O(log ν(Ḡ)). where ν(Ḡ) is the Lovász Theta Function of the complement of G, which is always smaller than the chromatic number of G. This yields an efficient constant factor approximation algorithm for the above maximization problem for a wide range of graphs G. We also show that the maximum possible integrality gap is always at least ω(log ω)(G)), where ω(G) is the clique number of G. In particular it follows that the maximum possible integrality gap for the complete graph on n vertices with no loops is ⊖(log n). More generally, the maximum possible integrality gap for any perfect graph with chromatic number n is ⊖(log n). The lower bound for the complete graph improves a result of Kashin and Szarek on Gram matrices of uniformly bounded functions, and settles a problem of Megretski and of Charikar and Wirth.

Original language | English (US) |
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Pages (from-to) | 486-493 |

Number of pages | 8 |

Journal | Proceedings of the Annual ACM Symposium on Theory of Computing |

DOIs | |

State | Published - 2005 |

Externally published | Yes |

Event | 13th Color Imaging Conference: Color Science, Systems, Technologies, and Applications - Scottsdale, AZ, United States Duration: Nov 7 2005 → Nov 11 2005 |

## All Science Journal Classification (ASJC) codes

- Software

## Keywords

- Correlation Clustering
- Grothendieck's Inequaity
- Rounding Techniques
- Spin Glasses