arXiv subjects

Hernan Makse

Publications and source records attributed to Hernan Makse.

7 recordsLinked to original sources

arXiv2026

Extreme vulnerability to intruder attacks destabilizes network dynamics

Consensus, synchronization, formation control, and power grid balance are examples of desirable dynamical states that arise in networks. Here we investigate how such states can be destabilized by an intruder agent within an otherwise functioning network. We see that a single adversarial node, coupled through adversarial connections to one or more other nodes, is sufficient to destabilize the entire network. We further show that concentrating the attack on a single low-indegree node induces the greatest instability, challenging the common assumption that hubs are the most critical nodes. This leads to a new characterization of network vulnerability, identifying low-indegree nodes as the most vulnerable components. Although derived for linear systems, our results extend to nonlinear networks, including the Kuramoto model. These findings reveal an intrinsic vulnerability of technological, social, and biological networks.

nlin.AO↗

arXiv2024

The Role of Fibration Symmetries in Geometric Deep Learning

Geometric Deep Learning (GDL) unifies a broad class of machine learning techniques from the perspectives of symmetries, offering a framework for introducing problem-specific inductive biases like Graph Neural Networks (GNNs). However, the current formulation of GDL is limited to global symmetries that are not often found in real-world problems. We propose to relax GDL to allow for local symmetries, specifically fibration symmetries in graphs, to leverage regularities of realistic instances. We show that GNNs apply the inductive bias of fibration symmetries and derive a tighter upper bound for their expressive power. Additionally, by identifying symmetries in networks, we collapse network nodes, thereby increasing their computational efficiency during both inference and training of deep neural networks. The mathematical extension introduced here applies beyond graphs to manifolds, bundles, and grids for the development of models with inductive biases induced by local symmetries that can lead to better generalization.

cs.LG↗

arXiv2024

Visiting Distant Neighbors in Graph Convolutional Networks

We extend the graph convolutional network method for deep learning on graph data to higher order in terms of neighboring nodes. In order to construct representations for a node in a graph, in addition to the features of the node and its immediate neighboring nodes, we also include more distant nodes in the calculations. In experimenting with a number of publicly available citation graph datasets, we show that this higher order neighbor visiting pays off by outperforming the original model especially when we have a limited number of available labeled data points for the training of the model.

cs.LG↗

arXiv2023

Scale-up of Dry Impregnation Processes for Porous Spherical Catalyst Particles in a Rotating Drum: Experiments and Simulations

Catalyst impregnation is one of the most crucial steps for preparing industrial catalysts. The inter-particle variability of the impregnated liquid inside the particles significantly affects the activity and selectivity of the catalyst. Current scale-up practices lead to poor fluid distribution and inhomogeneity in the liquid content. This work aims to understand the dynamic behavior of the particles under the spray nozzle and to develop a scale-up model for dry impregnation processes. We considered five dimensionless numbers in the scaling analysis. We performed Discrete Element Method simulations and experiments of dry impregnation inside porous particles for different vessel sizes. The water content of the particles was compared for other times locations, and the relative standard deviation (RSD) was calculated from the axial water content. Simulation and experimental results show excellent agreement, confirming that the scale-up rules apply to all vessel sizes.

physics.flu-dyn↗

arXiv2022

Matryoshka and Disjoint Cluster Synchronization of Networks

The main motivation for this paper is to present a definition of network synchronizability for the case of cluster synchronization (CS), in an analogous fashion to Barahona and Pecora for the case of complete synchronization. We find this problem to be substantially more complex than the original one. We distinguish between the two cases of networks with intertwined clusters and no intertwined clusters and between {the two cases that the master stability function is negative either in a bounded range or in an unbounded range of its argument. We first obtain a definition of synchronizability that applies to each individual cluster within a network and then attempt to generalize this definition to the entire network. For CS, the synchronous solution of each cluster may be stable independent of the stability of the other clusters, which results in possibly different ranges in which each cluster synchronizes (isolated CS.) For each pair of clusters, we distinguish between three different cases: Matryoshka Cluster Synchronization (when the range of the stability of the synchronous solution for one cluster is included in that of the other cluster), Partially Disjoint Cluster Synchronization (when the ranges of stability of the synchronous solutions partially overlap), and Complete Disjoint Cluster Synchronization (when the ranges of stability of the synchronous solutions do not overlap.)

eess.SY↗

arXiv2019

Dynamics of racial segregation and gentrification in New York City

Racial residential segregation is interconnected with several other phenomena such as income inequalities, property values inequalities, and racial disparities in health and in education. Furthermore, recent literature suggests the phenomena of gentrification as a cause of perpetuation or increase of racial residential segregation in some American cities. In this paper, we analyze the dynamics of racial residential segregation for white, black, Asian, and Hispanic citizens in New York City in the years of 1990, 2000, and 2010. It was possible to observe that segregation between white and Hispanic citizens, and discrimination between white and Asian ones has grown, while segregation between white and black is quite stable. Furthermore, we analyzed the per capita income and the Gini coefficient in each segregated zone, showing that the highest inequalities occur in the zones where there is overlap of high-density zones of pair of races. Focusing on census tracts that have changed density of population during these twenty years, and, particularly, by analyzing white and black people's segregation, our analysis reveals that a positive flux of white (black) people is associated to a substantial increase (decrease) of the property values, as compared with the city mean. Furthermore, by clustering the region of high density of black citizens, we measured the variation of area and displacement of the four biggest clusters in the period from 1990 to 2010. The large displacements (~ 1.6 Km) observed for two of these clusters, namely, one in the neighborhood of Harlem and the other inside the borough of Brooklyn, led to the emergence of typically gentrified regions.

physics.soc-ph↗

arXiv1995

Singularities and Avalanches in Interface Growth with Quenched Disorder

A simple model for an interface moving in a disordered medium is presented. The model exhibits a transition between the two universality classes of interface growth phenomena. Using this model, it is shown that the application of constraints to the local slopes of the interface produces avalanches of growth, that become relevant in the vicinity of the depinning transition. The study of these avalanches reveals a singular behavior that explains a recently observed singularity in the equation of motion of the interface.

cond-mat↗