arXiv subjects

Sergey Buldyrev

Publications and source records attributed to Sergey Buldyrev.

7 recordsLinked to original sources

arXiv2026

Two phase transitions in modular multiplex networks

Modular networks, such as critical infrastructures, are often built from distinct, densely connected modules (e.g., cities) that are sparsely interconnected. When such networks are gradually and randomly disrupted under a percolation process, they undergo two critical phase transitions. The first transition occurs when modules become isolated from one another, while the second corresponds to the collapse of the entire network, including the internal connectivity of the modules. Here, we study these phase transitions in modular multiplex networks and compare them with those observed in single-layer modular networks. We focus on models in which the modules are arranged and connected either as a Random Regular network or as a two-dimensional square lattice. We show here that these systems exhibit diverse transition behaviors, with some transitions occurring continuously and others abruptly; notably, one realistic model could display two distinct first-order transitions in the same system. For the modular Random Regular multiplex, we further characterize the spatial transition through its scaling behavior, revealing signatures of a mixed-order phase transitions. In addition, we analytically determine the critical threshold at which modules become disconnected. Our results highlight the crucial role of modular organization and the critical role of interdependence in shaping network vulnerabilities under failures.

physics.soc-ph↗

arXiv2017

Critical field-exponents for secure message-passing in modular networks

We study secure message-passing in the presence of multiple adversaries in modular networks. We assume a dominant fraction of nodes in each module have the same vulnerability, i.e., the same entity spying on them. We find both analytically and via simulations that the links between the modules (interlinks) have effects analogous to a magnetic field in a spin system in that for any amount of interlinks the system no longer undergoes a phase transition. We then define the exponents $δ$, which relates the order parameter (the size of the giant secure component) at the critical point to the field strength (average number of interlinks per node), and $γ$, which describes the susceptibility near criticality. These are found to be $δ=2$ and $γ=1$ (with the scaling of the order parameter near the critical point given by $β=1$). When two or more vulnerabilities are equally present in a module we find $δ=1$ and $γ=0$ (with $β\geq2$). Apart from defining a previously unidentified universality class, these exponents show that increasing connections between modules is more beneficial for security than increasing connections within modules. We also measure the correlation critical exponent $ν$, and the upper critical dimension $d_c$, finding that $νd_c=3$ as for ordinary percolation, suggesting that for secure message-passing $d_c =6$. These results provide an interesting analogy between secure message-passing in modular networks and the physics of magnetic spin-systems.

physics.soc-ph↗

arXiv2016

Crises and Physical Phases of a Bipartite Market Model

We analyze the linear response of a market network to shocks based on the bipartite market model we introduced in an earlier paper, which we claimed to be able to identify the time-line of the 2009-2011 Eurozone crisis correctly. We show that this model has three distinct phases that can broadly be categorized as "stable" and "unstable". Based on the interpretation of our behavioral parameters, the stable phase describes periods where investors and traders have confidence in the market (e.g. predict that the market rebounds from a loss). We show that the unstable phase happens when there is a lack of confidence and seems to describe "boom-bust" periods in which changes in prices are exponential. We analytically derive these phases and where the phase transition happens using a mean field approximation of the model. We show that the condition for stability is $αβ<1$ with $α$ being the inverse of the "price elasticity" and $β$ the "income elasticity of demand", which measures how rash the investors make decisions. We also show that in the mean-field limit this model reduces to the Langevin model by Bouchaud et al. for price returns.

q-fin.RM↗

arXiv2012

Nanoscale Dynamics of Phase Flipping in Water near its Hypothesized Liquid-Liquid Critical Point

Achieving a coherent understanding of the many thermodynamic and dynamic anomalies of water is among the most important unsolved puzzles in physics, chemistry, and biology. One hypothesized explanation imagines the existence of a line of first order phase transitions separating two liquid phases and terminating at a novel "liquid-liquid" critical point in a region of low temperature ($T \approx 250 \rm{K}$) and high pressure ($P \approx 200 \rm{MPa}$). Here we analyze a common model of water, the ST2 model, and find that the entire system flips between liquid states of high and low density. Further, we find that in the critical region crystallites melt on a time scale of nanoseconds. We perform a finite-size scaling analysis that accurately locates both the liquid-liquid coexistence line and its associated liquid-liquid critical point.

cond-mat.stat-mech↗

arXiv2008

Asperity contacts at the nanoscale: comparison of Ru and Au

We develop and validate an interatomic potential for ruthenium based on the embedded atom method framework with the Finnis/Sinclair representation. We confirm that the new potential yields a stable hcp lattice with reasonable lattice and elastic constants and surface and stacking fault energies. We employ molecular dynamics simulations to bring two surfaces together; one flat and the other with a single asperity. We compare the process of asperity contact formation and breaking in Au and Ru, two materials currently in use in micro electro mechanical system switches. While Au is very ductile at 150 and 300 K, Ru shows considerably less plasticity at 300 and 600 K (approximately the same homologous temperature). In Au, the asperity necks down to a single atom thick bridge at separation. While similar necking occurs in Ru at 600 K, it is much more limited than in Au. On the other hand, at 300 K, Ru breaks by a much more brittle process of fracture/decohesion with limited plastic deformation.

cond-mat.mtrl-sci↗

arXiv2006

Thermodynamic and Dynamic Anomalies for Dumbbell Molecules Interacting with a Repulsive Ramp-Like Potential

Using collision driven discrete molecular dynamics (DMD), we investigate the thermodynamics and dynamics of systems of 500 dumbbell molecules interacting by a purely repulsive ramp-like discretized potential, consisting of $n$ steps of equal size. We compare the behavior of the two systems, with $n = 18$ and $n = 144$ steps. Each system exhibits both thermodynamic and dynamic anomalies, a density maximum and the translational and rotational mobilities show anomalous behavior. Starting with very dense systems and decreasing the density, both mobilities first increase, reache a maximum, then decrease, reache a minimum, and finally increase; this behavior is similar to the behavior of SPC/E water. The regions in the pressure-temperature plane of translational and rotational mobility anomalies depend strongly on $n$. The product of the translational diffusion coefficient and the orientational correlation time increases with temperature, in contrast with the behavior of most liquids.

cond-mat.soft↗

arXiv1996

The Pinning Paths of an Elastic Interface

We introduce a model describing the paths that pin an elastic interface moving in a disordered medium. We find that the scaling properties of these ``elastic pinning paths'' (EPP) are different from paths embedded on a directed percolation cluster, which are known to pin the interface of the ``directed percolation depinning'' class of surface growth models. The EPP are characterized by a roughness exponent $α=1.25$, intermediate between that of the free inertial process ($α=3/2$) and the diode-resistor problem on a Cayley tree ($α=1$). We also calculate numerically the mean cluster size and the cluster size distribution for the EPP.

cond-mat↗