For sparse non-Hermitian random matrices with constant average degree d<1, the paper claims spectral radius zero with probability (1-d)e^{d+d^2/2} and Theta_p(1) otherwise, but the zero probability and lower-bound proof have serious errors.
The sparse circular law, revisited
1 Pith paper cite this work. Polarity classification is still indexing.
abstract
Let $A_n$ be an $n\times n$ matrix with iid entries distributed as Bernoulli random variables with parameter $p = p_n$. Rudelson and Tikhomirov, in a beautiful and celebrated paper, show that the distribution of eigenvalues of $A_n \cdot (pn)^{-1/2}$ is approximately uniform on the unit disk as $n\rightarrow \infty$ as long as $pn \rightarrow \infty$, which is the natural necessary condition. In this paper we give a much simpler proof of this result, in its full generality, using a perspective we developed in our recent proof of the existence of the limiting spectral law when $pn$ is bounded. One feature of our proof is that it avoids the use of $\epsilon$-nets entirely and, instead, proceeds by studying the evolution of the singular values of the shifted matrices $A_n-zI$ as we incrementally expose the randomness in the matrix.
citation-role summary
citation-polarity summary
fields
math.PR 1years
2024 1verdicts
REJECT 1roles
background 1polarities
unclear 1representative citing papers
citing papers explorer
-
Spectral radii of sparse non-Hermitian random matrices
For sparse non-Hermitian random matrices with constant average degree d<1, the paper claims spectral radius zero with probability (1-d)e^{d+d^2/2} and Theta_p(1) otherwise, but the zero probability and lower-bound proof have serious errors.