arXiv subjects

Giacomo Passuello

Publications and source records attributed to Giacomo Passuello.

5 recordsLinked to original sources

arXiv2026

Spectrum of Directed Inhomogeneous Random Graphs

We study the spectrum of the adjacency matrix $A_n$ of directed inhomogeneous random graphs on $n$ vertices. We assume that $A_n$ has independent entries and diverging average degree scale $s_n$. This framework includes, as special cases, the directed Chung--Lu random graph and directed stochastic block models. Assuming boundedness of the variance profile and that $s_n$ diverges faster than a suitable logarithmic function of $n$, we show that the rank-one Chung--Lu model satisfies a non-homogeneous version of the circular law, which in some situations allows for an explicit expression. Moreover, under mild conditions, we identify the asymptotic singular value distribution using tools from free probability. Finally, for finite-rank directed models, we prove the existence of eigenvalues outside the bulk and establish their joint Gaussian fluctuations at the scale $\sqrt{s_n/n}$, with an explicit covariance matrix. These results extend the theory of spectral outliers and their fluctuations to directed inhomogeneous random graphs.

math.PR↗

arXiv2026

Mixing trichotomy for random walks on directed stochastic block models

We consider a directed version of the classical Stochastic Block Model with $m\ge 2$ communities and a parameter $α$ controlling the inter-community connectivity. We show that, depending on the scaling of $α$, the mixing time of the random walk on this graph can exhibit three different behaviors, which we refer to as subcritical, critical and supercritical. In the subcritical regime, the total variation distance to equilibrium decays abruptly, providing the occurrence of the so-called cutoff phenomenon. In the supercritical regime, the mixing is governed by the inter-community jumps, and the random walk exhibits a metastable behavior: at first it collapses to a local equilibrium, then, on a larger timescale, it can be effectively described as a mean-field process on the $m$ communities, with a decay to equilibrium which is asymptotically smooth and exponential. Finally, for the critical regime, we show a sort of interpolation of the two above-mentioned behaviors. Although the metastable behavior shown in the supercritical regime appears natural from a heuristic standpoint, a substantial part of our analysis can be read as a control on the homogenization of the underlying random environment.

math.PR↗

arXiv2025

A standard CLT for triangles in a class of ERGs

We prove a standard Central Limit Theorem for the (normalized) number of triangles in a class of Exponential Random Graphs derived from a slight modification of the edge-triangle model. Our main theorem covers the whole analyticity region of the free energy, and is based on a polynomial representation of the partition function.

math.PR↗

arXiv2024

Mixing cutoff for simple random walks on the Chung-Lu digraph

In this paper, we are interested in the mixing behaviour of simple random walks on inhomogeneous directed graphs. We focus our study on the Chung-Lu digraph, which is an inhomogeneous network that generalizes the Erdős-Rényi digraph. In particular, under the Chung-Lu model, edges are included in the graph independently and according to given Bernoulli laws, so that the average degrees are fixed. To guarantee the a.s. existence of a unique reversible measure, which is implied by the strong connectivity of the graph, we assume that the average degree grows logarithmically in the size $n$ of the graph. In this weakly dense regime, we prove that the total variation distance to equilibrium displays a cutoff behaviour at the entropic time of order $\log(n)/\log\log(n)$. Moreover, we prove that on a precise window, the cutoff profile converges to the Gaussian tail function. This is qualitatively similar to what was proved in [6,7,8] for the directed configuration model, where degrees are deterministically fixed. In terms of statistical ensembles, our analysis provides an extension of these cutoff results from a hard to a soft-constrained model.

math.PR↗

arXiv2024

Statistics for the triangle density in ERGM and its mean-field approximation

We consider the edge-triangle model (or Strauss model), and focus on the asymptotic behavior of the triangle density when the size of the graph increases to infinity. This random graph belongs to the class of exponential random graphs, which follows the statistical mechanics approach of introducing a Hamiltonian to weigh the probability measure on the state space of graphs. In the analyticity region of the free energy, we prove a law of large numbers for the triangle density. Along the critical curve, where analyticity breaks down, we show that the triangle density concentrates with high probability in a neighborhood of its typical value. A predominant part of our work is devoted to the study of a mean-field approximation of the edge-triangle model, where explicit computations are possible. In this setting we can go further, and additionally prove a standard and non-standard central limit theorem at the critical point, together with many concentration results obtained via large deviations and statistical mechanics techniques. Despite a rigorous comparison between these two models is still lacking, we believe that they are asymptotically equivalent in many respects, therefore we formulate conjectures on the edge-triangle model, partially supported by simulations, based on the mean-field investigation.

math.PR↗