English

Linear Shannon Capacity of Cayley Graphs

Information Theory 2021-09-02 v3 Computational Complexity Combinatorics math.IT

Abstract

The Shannon capacity of a graph is a fundamental quantity in zero-error information theory measuring the rate of growth of independent sets in graph powers. Despite being well-studied, this quantity continues to hold several mysteries. Lov\'asz famously proved that the Shannon capacity of C5C_5 (the 5-cycle) is at most 5\sqrt{5} via his theta function. This bound is achieved by a simple linear code over F5\mathbb{F}_5 mapping x2xx \mapsto 2x. This motivates the notion of linear Shannon capacity of graphs, which is the largest rate achievable when restricting oneself to linear codes. We give a simple proof based on the polynomial method that the linear Shannon capacity of C5C_5 is 5\sqrt{5}. Our method applies more generally to Cayley graphs over the additive group of finite fields Fq\mathbb{F}_q, giving an upper bound on the linear Shannon capacity. We compare this bound to the Lov\'asz theta function, showing that they match for self-complementary Cayley graphs (such as C5C_5), and that the bound is smaller in some cases. We also exhibit a quadratic gap between linear and general Shannon capacity for some graphs.

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Cite

@article{arxiv.2009.05685,
  title  = {Linear Shannon Capacity of Cayley Graphs},
  author = {Venkatesan Guruswami and Andrii Riazanov},
  journal= {arXiv preprint arXiv:2009.05685},
  year   = {2021}
}