Eigenvalue distribution of bipartite large weighted random graphs. Resolvent approach

We study eigenvalue distribution of the adjacency matrix $A^{(N,p,\alpha )}$ of weighted random bipartite graphs $\mathrm{\Gamma }={\mathrm{\Gamma }}_{N,p}$. We assume that the graphs have $N$ vertices, the ratio of parts is $\frac{\alpha }{1-\alpha }$ and the average number of edges attached to one vertex is $\alpha \cdot p$ or $(1-\alpha )\cdot p$. To each edge of the graph $e_{ij}$ we assign a weight given by a random variable $a_{ij}$ with the finite second moment. We consider the resolvents $G^{(N,p,\alpha )}(z)$ of $A^{(N,p,\alpha )}$ and study the functions $f_{1,N}(u,z)=\frac{1}{[\alpha N]}\sum_{k=1}^{[\alpha N]}e^{-ua_k^2G_{kk}^{(N,p,\alpha)}(z)}$and$f_{2,N}(u,z)=\frac{1}{N-[\alpha N]}\sum_{k=[\alpha N]+1}^Ne^{-ua_k^2G_{kk}^{(N,p,\alpha)}(z)}$inthelimit$N\to \infty$. We derive closed system of equations that uniquely determine the limiting functions $f_1(u,z)$ and $f_2(u,z)$. This system of equations allow us to prove the existence of the limiting measure ${\sigma }_{p,\alpha }$ . The weak convergence in probability of normalized eigenvalue counting measures is proved.