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Communications in Mathematical Physics

, Volume 369, Issue 2, pp 523–636 | Cite as

Local Kesten–McKay Law for Random Regular Graphs

  • Roland BauerschmidtEmail author
  • Jiaoyang Huang
  • Horng-Tzer Yau
Open Access
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Abstract

We study the adjacency matrices of random d-regular graphs with large but fixed degree d. In the bulk of the spectrum \({[-2\sqrt{d-1}+\varepsilon, 2\sqrt{d-1}-\varepsilon]}\) down to the optimal spectral scale, we prove that the Green’s functions can be approximated by those of certain infinite tree-like (few cycles) graphs that depend only on the local structure of the original graphs. This result implies that the Kesten–McKay law holds for the spectral density down to the smallest scale and the complete delocalization of bulk eigenvectors. Our method is based on estimating the Green’s function of the adjacency matrices and a resampling of the boundary edges of large balls in the graphs.

Notes

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Authors and Affiliations

  1. 1.Statistical Laboratory, DPMMSUniversity of CambridgeCambridgeUK
  2. 2.Department of MathematicsHarvard UniversityCambridgeUSA

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