# Outliers in spectrum of sparse Wigner matrices

## TL;DR

This paper analyzes how sparsity affects outlier eigenvalues in sparse Wigner matrices and Erdős–Rényi graphs, revealing conditions under which outliers appear or vanish, and connecting these phenomena to phase transition behavior.

## Contribution

It provides new asymptotic formulas for eigenvalues of sparse matrices and graphs in regimes previously not well-understood, especially when $np_n=\Theta(\log n)$.

## Key findings

- Eigenvalue ratios converge to 1 under certain sparsity conditions.
- Outliers appear or disappear depending on the relation between $np_n$ and $\log n$.
- Results connect spectral outliers in sparse matrices to phase transition phenomena.

## Abstract

In this paper, we study the effect of sparsity on the appearance of outliers in the semi-circular law. Let $(W_n)_{n=1}^\infty$ be a sequence of random symmetric matrices such that each $W_n$ is $n\times n$ with i.i.d entries above and on the main diagonal equidistributed with the product $b_n\xi$, where $\xi$ is a real centered uniformly bounded random variable of unit variance and $b_n$ is an independent Bernoulli random variable with a probability of success $p_n$. Assuming that $\lim\limits_{n\to\infty}n p_n=\infty$, we show that for the random sequence $(\rho_n)_{n=1}^\infty$ given by $$\rho_n:=\theta_n+\frac{n p_n}{\theta_n},\quad \theta_n:=\sqrt{\max\big(\max\limits_{i\leq n}\|{\rm Row_i}(W_n)\|_2^2-np_n,n p_n\big)},$$ the ratio $\frac{\|W_n\|}{\rho_n}$ converges to one in probability. A non-centered counterpart of the theorem allows to obtain asymptotic expressions for eigenvalues of the Erd\H{o}s--Renyi graphs, which were unknown in the regime $n p_n=\Theta(\log n)$. In particular, denoting by $A_n$ the adjacency matrix of $\mathcal{G}(n,p_n)$ and by $\lambda_{|k|}(A_n)$ its $k$-th largest (by the absolute value) eigenvalue, under the assumptions $\lim\limits_{n\to\infty }n p_n=\infty$ and $\lim\limits_{n\to\infty}p_n=0$ we have: -(No non-trivial outliers) If $\liminf\frac{n p_n}{\log n}\geq\frac{1}{\log (4/e)}$ then for any fixed $k\geq2$, $\frac{|\lambda_{|k|}(A_n)|}{2\sqrt{n p_n}}$ converges to $1$ in probability. -(Outliers) If $\limsup\frac{n p_n}{\log n}<\frac{1}{\log (4/e)}$ then there is $\varepsilon>0$ such that for any $k\in\mathbb{N}$, we have $\lim\limits_{n\to\infty}\mathbb{P}\Big\{\frac{|\lambda_{|k|}(A_n)|}{2\sqrt{n p_n}}>1+\varepsilon\Big\}=1$. On a conceptual level, our result highlights similarities in appearance of outliers in spectrum of sparse matrices and the so-called BBP phase transition phenomenon in deformed Wigner matrices.