arXiv subjects

S. V. Buldyrev

Publications and source records attributed to S. V. Buldyrev.

At least 19 recordsLinked to original sources

arXiv2024

Hamiltonian limited valence model for liquid polyamorphism

Liquid-liquid phase transitions have been found experimentally or by computer simulations in many compounds such as water, hydrogen, sulfur, phosphorus, carbon, silica, and silicon. Limited valence model implemented via event-driven molecular dynamics algorithm provides a simple generic mechanism for the liquid-liquid phase transitions in all these diverse cases. Here, we introduce a variant of the limited valence model with a well defined Hamiltonian, i.e., a unique algorithm by which the potential energy of the system of particles can be computed solely from the coordinates of the particles and is thus equivalent to a complex multi-body potential. We present several examples of the model which can be used to reproduce liquid-liquid phase transition in systems with maximum valence $z=1$ (hydrogen), $z=2$ (sulfur) and $z=4$ (water), where $z$ is the maximum number of bonds an atom is allowed to have. For $z=1$, we find a set of parameters for which the system has a liquid-liquid and an isostructural solid--solid critical points. For $z=4$, we find a set of parameters for which the phase diagram resembles that of water with a wide region of negative thermal expansion coefficient (density anomaly) extending into the metastable region of negative pressures. The limited valence model can be modified to forbid not only too large valences but also too low valences. In the case of sulfur, we forbid the formation of monomers, thus restricting the valence $v$ of an atom to be within an interval $1=v_{\rm min}\leqslant v\leqslant v_{\rm max}\equiv z=2$.

cond-mat.soft↗

arXiv2022

Cascading failures in isotropic and anisotropic spatial networks induced by localized attacks and overloads

In this paper we study the Motter-Lai model of cascading failures induced by overloads in both isotropic and anisotropic spatial networks, generated by placing nodes in a square lattice and using various distributions of link lengths and angles. Anisotropy has not been earlier considered in the Motter-Lai model and is a real feature that may affect the cascading failures. This could reflect the existence of a preferred direction in which a given attribute of the system manifests, such as power lines that follow a city built parallel to the coast. We show that the anisotropy causes a greater spread of damage along the preferential direction of links. We also identify the critical linear size, $l_c$, for a square shaped localized attack, which satisfies with high probability that above $l_c$ the cascading disrupts the giant component of functional nodes, while below $l_c$ the damage does not spread. We find that, for networks with any characteristic link length, their robustness decreases with the strength of the anisotropy. We show that the value of $l_c$ is finite and independent of the system size (for large systems), both for isotropic and anisotropic networks. Thus, in contrast to random attacks, where the critical fraction of nodes that survive the initial attack, $p_c$, is usually below 1, here $p_c = 1$. Note that the analogy to $p_c = 1$ is also found for localized attacks in interdependent spatial networks. Finally, we measure the final distribution of functional cluster sizes and find a power-law behavior, with exponents similar to regular percolation. This indicates that, after the cascade which destroys the giant component, the system is at a percolation critical point. Additionally, we observe a crossover in the value of the distribution exponent, from critical percolation in a two-dimensional lattice for strong spatial embedding, to mean-field percolation for weak embedding.

physics.soc-ph↗

arXiv2021

Comment on "Inverse Square Lévy Walks are not Optimal Search Strategies for d $\geq$ 2" [Phys. Rev. Lett. 124, 080601 (2020)]

It is widely accepted that inverse square Lévy walks are optimal search strategies because they maximize the encounter rate with sparse, randomly distributed, replenishable targets when the search restarts in the vicinity of the previously visited target, which becomes revisitable again with high probability, i.e., non-destructive foraging [Nature 401, 911 (1999)]. The precise conditions for the validity of this Lévy flight foraging hypothesis (LFH) have been widely described in the literature [Phys. Life Rev. 14, 94 (2015)]. Nevertheless, three objecting claims to the LFH have been raised recently for $d \geq 2$: (i) the capture rate $η$ has linear dependence on the target density $ρ$ for all values of the Lévy index $α$; (ii) "the gain $η_{max}/η$ achieved by varying $α$ is bounded even in the limit $ρ\to 0 $" so that "tuning $α$ can only yield a marginal gain"; (iii) depending on the values of the radius of detection $a$, the restarting distance $l_c$ and the scale parameter $s$, the optimum is realized for a range of $α$ [Phys. Rev. Lett. 124, 080601 (2020)]. Here we answer each of these three criticisms in detail and show that claims (i)-(iii) do not actually invalidate the LFH. Our results and analyses restore the original result of the LFH for non-destructive foraging.

cond-mat.stat-mech↗

arXiv2020

Reversible bootstrap percolation: Fake news and fact checking

Bootstrap percolation has been used to describe opinion formation in society and other social and natural phenomena. The formal equation of the bootstrap percolation may have more than one solution, corresponding to several stable fixed points of the corresponding iteration process. We construct a reversible bootstrap percolation process, which converges to these extra solutions displaying a hysteresis typical of discontinuous phase transitions. This process provides a reasonable model for fake news spreading and the effectiveness of fact checking. We show that sometimes it is not sufficient to discard all the sources of fake news in order to reverse the belief of a population that formed under the influence of these sources.

physics.soc-ph↗

arXiv2019

Insights into bootstrap percolation: Its equivalence with k-core percolation and the giant component

K-core and bootstrap percolation are widely studied models that have been used to represent and understand diverse deactivation and activation processes in natural and social systems. Since these models are considerably similar, it has been suggested in recent years that they could be complementary. In this manuscript we provide a rigorous analysis that shows that for any degree and threshold distributions heterogeneous bootstrap percolation can be mapped into heterogeneous k-core percolation and vice versa, if the functionality thresholds in both processes satisfy a complementary relation. Another interesting problem in bootstrap and k-core percolation is the fraction of nodes belonging to their giant connected components $P_{\infty b}$ and $P_{\infty c}$, respectively. We solve this problem analytically for arbitrary randomly connected graphs and arbitrary threshold distributions, and we show that $P_{\infty b}$ and $P_{\infty c}$ are not complementary. Our theoretical results coincide with computer simulations in the limit of very large graphs. In bootstrap percolation, we show that when using the branching theory to compute the size of the giant component, we must consider two different types of links, which are related to distinct spanning branches of active nodes.

physics.soc-ph↗

arXiv2018

Comparison of the roughness scaling of the surface topography of Earth and Venus

We report the scaling behavior of the Earth and Venus over a wider range of length scales than reported by previous researchers. All landscapes (not only mountains) together follow a consistent scaling behavior, demonstrating a crossover between highly correlated (smooth) behavior at short length scales (with a scaling exponent $α$=1) and self-affine behavior at long length scales ($α$=0.4). The self-affine behavior at long scales is achieved on Earth above 10 km and on Venus above 50 km.

cond-mat.stat-mech↗

arXiv2017

Cascading Failures in Interdependent Networks with Multiple Supply-Demand Links and Functionality Thresholds

Various social, financial, biological and technological systems can be modeled by interdependent networks. It has been assumed that in order to remain functional, nodes in one network must receive the support from nodes belonging to different networks. So far these models have been limited to the case in which the failure propagates across networks only if the nodes lose all their supply nodes. In this paper we develop a more realistic model for two interdependent networks in which each node has its own supply threshold, i.e., they need the support of a minimum number of supply nodes to remain functional. In addition, we analyze different conditions of internal node failure due to disconnection from nodes within its own network. We show that several local internal failure conditions lead to similar nontrivial results. When there are no internal failures the model is equivalent to a bipartite system, which can be useful to model a financial market. We explore the rich behaviors of these models that include discontinuous and continuous phase transitions. Using the generating functions formalism, we analytically solve all the models in the limit of infinitely large networks and find an excellent agreement with the stochastic simulations.

physics.soc-ph↗

arXiv2016

Cascading failures in interdependent networks with finite functional components

We present a cascading failure model of two interdependent networks in which functional nodes belong to components of size greater than or equal to $s$. We find theoretically and via simulation that in complex networks with random dependency links the transition is first-order for $s\geq 3$ and second-order for $s=2$. We find for two square lattices with a distance constraint $r$ in the dependency links that increasing $r$ moves the system from a regime without a phase transition to one with a second-order transition. As $r$ continues to increase the system collapses in a first-order transition. Each regime is associated with a different structure of domain formation of functional nodes.

physics.soc-ph↗

arXiv2012

Fragile to strong crossover coupled to liquid-liquid transition in hydrophobic solutions

Using discrete molecular dynamics simulations we study the relation between the thermodynamic and diffusive behaviors of a primitive model of aqueous solutions of hydrophobic solutes consisting of hard spheres in the Jagla particles solvent, close to the liquid-liquid critical point of the solvent. We find that the fragile-to-strong dynamic transition in the diffusive behavior is always coupled to the low-density/high-density liquid transition. Above the liquid-liquid critical pressure, the diffusivity crossover occurs at the Widom line, the line along which the thermodynamic response functions show maxima. Below the liquid-liquid critical pressure, the diffusivity crossover occurs when the limit of mechanical stability lines are crossed, as indicated by the hysteresis observed when going from high to low temperature and vice versa. These findings show that the strong connection between dynamics and thermodynamics found in bulk water persists in hydrophobic solutions for concentrations from low to moderate, indicating that experiments measuring the relaxation time in aqueous solutions represent a viable route for solving the open questions in the field of supercooled water.

cond-mat.soft↗

arXiv2011

Robustness of a Tree-like Network of Interdependent Networks

In reality, many real-world networks interact with and depend on other networks. We develop an analytical framework for studying interacting networks and present an exact percolation law for a network of $n$ interdependent networks (NON). We present a general framework to study the dynamics of the cascading failures process at each step caused by an initial failure occurring in the NON system. We study and compare both $n$ coupled Erdős-Rényi (ER) graphs and $n$ coupled random regular (RR) graphs. We found recently [Gao et. al. arXive:1010.5829] that for an NON composed of $n$ ER networks each of average degree $k$, the giant component, $P_{\infty}$, is given by $P_{\infty}=p[1-\exp(-kP_{\infty})]^n$ where $1-p$ is the initial fraction of removed nodes. Our general result coincides for $n=1$ with the known Erdős-Rényi second-order phase transition at a threshold, $p=p_c$, for a single network. For $n=2$ the general result for $P_{\infty}$ corresponds to the $n=2$ result [Buldyrev et. al., Nature, 464, (2010)]. Similar to the ER NON, for $n=1$ the percolation transition at $p_c$, is of second order while for any $n>1$ it is of first order. The first order percolation transition in both ER and RR (for $n>1$) is accompanied by cascading failures between the networks due to their interdependencies. However, we find that the robustness of $n$ coupled RR networks of degree $k$ is dramatically higher compared to the $n$ coupled ER networks of average degree $k$. While for ER NON there exists a critical minimum average degree $k=k_{\min}$, that increases with $n$, below which the system collapses, there is no such analogous $k_{\min}$ for RR NON system.

physics.data-an↗

arXiv2010

Catastrophic Cascade of Failures in Interdependent Networks

Modern network-like systems are usually coupled in such a way that failures in one network can affect the entire system. In infrastructures, biology, sociology, and economy, systems are interconnected and events taking place in one system can propagate to any other coupled system. Recent studies on such coupled systems show that the coupling increases their vulnerability to random failure. Properties for interdependent networks differ significantly from those of single-network systems. In this article, these results are reviewed and the main properties discussed.

physics.data-an↗

arXiv2007

A transactional theory of fluctuations in company size

Detailed empirical studies of publicly traded business firms have established that the standard deviation of annual sales growth rates decreases with increasing firm sales as a power law, and that the sales growth distribution is non-Gaussian with slowly decaying tails. To explain these empirical facts, a theory is developed that incorporates both the fluctuations of a single firm's sales and the statistical differences among many firms. The theory reproduces both the scaling in the standard deviation and the non-Gaussian distribution of growth rates. Earlier models reproduce the same empirical features by splitting firms into somewhat ambiguous subunits; by decomposing total sales into individual transactions, this ambiguity is removed. The theory yields verifiable predictions and accommodates any form of business organization within a firm. Furthermore, because transactions are fundamental to economic activity at all scales, the theory can be extended to all levels of the economy, from individual products to multinational corporations.

physics.soc-ph↗

arXiv2007

Breakdown of the Stokes-Einstein Relation in Supercooled Water

Supercooled water exhibits a breakdown of the Stokes-Einstein relation between the diffusion constant $D$ and the alpha relaxation time $τ_α$. For water simulated with the TIP5P and ST2 potentials, we find that the temperature of the decoupling of diffusion and alpha relaxation correlates with the temperature of the maximum in specific heat that corresponds to crossing the Widom line $T_W(P)$. Specifically, we find that our results for $Dτ_α/T$ collapse onto a single master curve if temperature is replaced by $T-T_W(P)$, where $T_W(P)$ is the temperature where the constant-pressure specific heat achieves a maximum. Also, we find agreement between our ST2 simulations and experimental values of $Dτ_α/T$. We further find that the size of the mobile molecule clusters (dynamical heterogeneities) increases sharply near $T_W(P)$. Moreover, our calculations of mobile particle cluster size $ _w$ for different pressures, where $t^*$ is the time for which the mobile particle cluster size is largest, also collapse onto a single master curve if $T$ is replaced by $T-T_W(P)$. The crossover to a more locally structured low density liquid (LDL) environment as $T\to T_W(P)$ appears to be well correlated with both the breakdown of the Stokes-Einstein relation and the growth of dynamic heterogeneities.

cond-mat.soft↗

arXiv2006

Optimal Path and Minimal Spanning Trees in Random Weighted Networks

We review results on the scaling of the optimal path length in random networks with weighted links or nodes. In strong disorder we find that the length of the optimal path increases dramatically compared to the known small world result for the minimum distance. For Erdős-Rényi (ER) and scale free networks (SF), with parameter $λ$ ($λ>3$), we find that the small-world nature is destroyed. We also find numerically that for weak disorder the length of the optimal path scales logaritmically with the size of the networks studied. We also review the transition between the strong and weak disorder regimes in the scaling properties of the length of the optimal path for ER and SF networks and for a general distribution of weights, and suggest that for any distribution of weigths, the distribution of optimal path lengths has a universal form which is controlled by the scaling parameter $Z=\ell_{\infty}/A$ where $A$ plays the role of the disorder strength, and $\ell_{\infty}$ is the length of the optimal path in strong disorder. The relation for $A$ is derived analytically and supported by numerical simulations. We then study the minimum spanning tree (MST) and show that it is composed of percolation clusters, which we regard as "super-nodes", connected by a scale-free tree. We furthermore show that the MST can be partitioned into two distinct components. One component the {\it superhighways}, for which the nodes with high centrality dominate, corresponds to the largest cluster at the percolation threshold which is a subset of the MST. In the other component, {\it roads}, low centrality nodes dominate. We demonstrate the significance identifying the superhighways by showing that one can improve significantly the global transport by improving a very small fraction of the network.

cond-mat.dis-nn↗

arXiv2006

A Generalized Preferential Attachment Model for Business Firms Growth Rates: II. Mathematical Treatment

We present a preferential attachment growth model to obtain the distribution $P(K)$ of number of units $K$ in the classes which may represent business firms or other socio-economic entities. We found that $P(K)$ is described in its central part by a power law with an exponent $ϕ=2+b/(1-b)$ which depends on the probability of entry of new classes, $b$. In a particular problem of city population this distribution is equivalent to the well known Zipf law. In the absence of the new classes entry, the distribution $P(K)$ is exponential. Using analytical form of $P(K)$ and assuming proportional growth for units, we derive $P(g)$, the distribution of business firm growth rates. The model predicts that $P(g)$ has a Laplacian cusp in the central part and asymptotic power-law tails with an exponent $ζ=3$. We test the analytical expressions derived using heuristic arguments by simulations. The model might also explain the size-variance relationship of the firm growth rates.

physics.soc-ph↗

arXiv2006

A Generalized Preferential Attachment Model for Business Firms Growth Rates: I. Empirical Evidence

We introduce a model of proportional growth to explain the distribution $P(g)$ of business firm growth rates. The model predicts that $P(g)$ is Laplace in the central part and depicts an asymptotic power-law behavior in the tails with an exponent $ζ=3$. Because of data limitations, previous studies in this field have been focusing exclusively on the Laplace shape of the body of the distribution. We test the model at different levels of aggregation in the economy, from products, to firms, to countries, and we find that the its predictions are in good agreement with empirical evidence on both growth distributions and size-variance relationships.

physics.data-an↗

arXiv2006

Glass transition in biomolecules and the liquid-liquid critical point of water

Using molecular dynamics simulations, we investigate the relation between the dynamic transitions of biomolecules (lysozyme and DNA) and the dynamic and thermodynamic properties of hydration water. We find that the dynamic transition of the macromolecules, sometimes called a ``protein glass transition'', occurs at the temperature of dynamic crossover in the diffusivity of hydration water, and also coincides with the maxima of the isobaric specific heat $C_P$ and the temperature derivative of the orientational order parameter. We relate these findings to the hypothesis of a liquid-liquid critical point in water. Our simulations are consistent with the possibility that the protein glass transition results from crossing the Widom line, which is defined as the locus of correlation length maxima emanating from the hypothesized second critical point of water.

cond-mat.soft↗

arXiv2006

Non-Gaussian energy landscape of a simple model for strong network-forming liquids: accurate evaluation of the configurational entropy

We present a numerical study of the statistical properties of the potential energy landscape of a simple model for strong network-forming liquids. The model is a system of spherical particles interacting through a square well potential, with an additional constraint that limits the maximum number of bonds, $N_{\rm max}$, per particle. Extensive simulations have been carried out as a function of temperature, packing fraction, and $N_{\rm max}$. The dynamics of this model are characterized by Arrhenius temperature dependence of the transport coefficients and by nearly exponential relaxation of dynamic correlators, i.e. features defining strong glass-forming liquids. This model has two important features: (i) landscape basins can be associated with bonding patterns; (ii) the configurational volume of the basin can be evaluated in a formally exact way, and numerically with arbitrary precision. These features allow us to evaluate the number of different topologies the bonding pattern can adopt. We find that the number of fully bonded configurations, i.e. configurations in which all particles are bonded to $N_{\rm max}$ neighbors, is extensive, suggesting that the configurational entropy of the low temperature fluid is finite. We also evaluate the energy dependence of the configurational entropy close to the fully bonded state, and show that it follows a logarithmic functional form, differently from the quadratic dependence characterizing fragile liquids. We suggest that the presence of a discrete energy scale, provided by the particle bonds, and the intrinsic degeneracy of fully bonded disordered networks differentiates strong from fragile behavior.

cond-mat.soft↗