{ "id": "2212.06499", "version": "v1", "published": "2022-12-13T11:26:56.000Z", "updated": "2022-12-13T11:26:56.000Z", "title": "Random matrices with row constraints and eigenvalue distributions of graph Laplacians", "authors": [ "Pawat Akara-pipattana", "Oleg Evnin" ], "categories": [ "cond-mat.dis-nn", "math-ph", "math.MP", "math.PR" ], "abstract": "Symmetric matrices with zero row sums occur in many theoretical settings and in real-life applications. When the offdiagonal elements of such matrices are i.i.d. random variables and the matrices are large, the eigenvalue distributions converge to a peculiar universal curve $p_{\\mathrm{zrs}}(\\lambda)$ that looks like a cross between the Wigner semicircle and a Gaussian distribution. An analytic theory for this curve, originally due to Fyodorov, can be developed using supersymmetry-based techniques. We extend these derivations to the case of sparse matrices, including the important case of graph Laplacians for large random graphs with $N$ vertices of mean degree $c$. In the regime $1\\ll c\\ll N$, the eigenvalue distribution of the ordinary graph Laplacian (diffusion with a fixed transition rate per edge) tends to a shifted and scaled version of $p_{\\mathrm{zrs}}(\\lambda)$, centered at $c$ with width $\\sim\\sqrt{c}$. At smaller $c$, this curve receives corrections in powers of $1/\\sqrt{c}$ accurately captured by our theory. For the normalized graph Laplacian (diffusion with a fixed transition rate per vertex), the large $c$ limit is a shifted and scaled Wigner semicircle, again with corrections captured by our analysis.", "revisions": [ { "version": "v1", "updated": "2022-12-13T11:26:56.000Z" } ], "analyses": { "keywords": [ "random matrices", "row constraints", "fixed transition rate", "wigner semicircle", "zero row sums occur" ], "note": { "typesetting": "TeX", "pages": 0, "language": "en", "license": "arXiv", "status": "editable" } } }