I am recently self-learning random matrix theory and made some simulations about the spectrum of Erdős-Rényi random graph $G(n,p)$ when $np\to\infty$,
and $np\to c=2,3$.
Plots above is already normalized such that the y-axis is about the frenquency and the x-axis is the eigenvalues divided by $\sqrt{np(1-p)}$.
Now it turns out that, although the spectrum itself is not symmetric(like the largest eigenvalue is far away from the bulk), the limiting shape is asymptotically symmetric. I wonder whether we can read this property out from the ER graph or its adjacency matrix directly, before we show that eg. in the dense case the limiting distribution is the semi-circle law.
And when I try to answer this myself, I ran into another question: what does symmetric spectrum mean in graph theory?
Edit:
I kind of get why the atoms in sparse case are symmetric, because they come from small components of the graph which are trees, thus bipartite and bipartite graphs have symmetric spectrum.
But why does the continuous part in the sparse case, as well as the dense one, still symmetric?
For the sparse one I probably can explain it like, the contiuous part should be the contribution of the giant component which is also locally tree-like, but still not very promising(like, why locally tree-like is enough to guarantee symmetry?). And for the dense case I have no clue--the graph does not seem like bipartite to me.