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Binary mixtures growing on small-world networks under far-from-equilibrium conditions are studied by means of extensive Monte Carlo simulations. For any positive value of the shortcut fraction of the network ($p>0$), the system undergoes a…

Statistical Mechanics · Physics 2009-11-11 Julián Candia

It has long been argued that neural networks have to establish and maintain a certain intermediate level of activity in order to keep away from the regimes of chaos and silence. Strong evidence for criticality has been observed in terms of…

Disordered Systems and Neural Networks · Physics 2012-12-14 Matthias Rybarsch , Stefan Bornholdt

Understanding the impact of network clustering and small-world properties on epidemic spread can be crucial in developing effective strategies for managing and controlling infectious diseases. Particularly in this work, we study the impact…

Social and Information Networks · Computer Science 2023-10-20 Mohammadreza Doostmohammadian , Houman Zarrabi , Azam Doustmohammadian , Hamid R. Rabiee

The critical behavior of the XY model on small-world network is investigated by means of dynamic Monte Carlo simulations. We use the short-time relaxation scheme, i.e., the critical behavior is studied from the nonequilibrium relaxation to…

Disordered Systems and Neural Networks · Physics 2009-11-10 Kateryna Medvedyeva , Petter Holme , Petter Minnhagen , Beom Jun Kim

We present high-accuracy quasi-stationary (QS) simulations of the contact process in quenched networks, built using the configuration model with both structural and natural cutoffs. The critical behavior is analyzed in the framework of the…

Statistical Mechanics · Physics 2011-12-09 Silvio C. Ferreira , Ronan S. Ferreira , Claudio Castellano , Romualdo Pastor-Satorras

Two different models exhibiting self-organized criticality are analyzed by means of the dynamic renormalization group. Although the two models differ by their behavior under a parity transformation of the order parameter, it is shown that…

Condensed Matter · Physics 2009-10-22 Albert Diaz-Guilera

We investigate the effects of quenched randomness on topological quantum phase transitions in strongly interacting two-dimensional systems. We focus first on transitions driven by the condensation of a subset of fractionalized…

Strongly Correlated Electrons · Physics 2021-03-03 Byungmin Kang , S. A. Parameswaran , Andrew C. Potter , Romain Vasseur , Snir Gazit

A nonlinear small-world network model has been presented to investigate the effect of nonlinear interaction and time delay on the dynamic properties of small-world networks. Both numerical simulations and analytical analysis for networks…

Disordered Systems and Neural Networks · Physics 2015-05-18 Xin-She Yang

In spiking neural networks an action potential could in principle trigger subsequent spikes in the neighbourhood of the initial neuron. A successful spike is that which trigger subsequent spikes giving rise to cascading behaviour within the…

Adaptation and Self-Organizing Systems · Physics 2015-08-03 Victor Hernandez-Urbina , Tom L. Underwood , J. Michael Herrmann

We employ an adaptation of a strong-disorder renormalization-group technique in order to analyze the ferro-paramagnetic quantum phase transition of Ising chains with aperiodic but deterministic couplings under the action of a transverse…

Statistical Mechanics · Physics 2012-03-16 Fleury J. Oliveira Filho , Maicon S. Faria , André P. Vieira

We use a simple real-space renormalization group approach to investigate the critical behavior of the quantum Ashkin-Teller model, a one-dimensional quantum spin chain possessing a line of criticality along which critical exponents vary…

Strongly Correlated Electrons · Physics 2015-11-02 Aroon O'Brien , Stephen D. Bartlett , Andrew C. Doherty , Steven T. Flammia

We develop a renormalization group for weak Harris-marginal disorder in otherwise strongly interacting quantum critical theories, focusing on systems which have emergent conformal invariance. Using conformal perturbation theory, we argue…

High Energy Physics - Theory · Physics 2022-03-30 Koushik Ganesan , Andrew Lucas , Leo Radzihovsky

We propose a renormalization group treatment of stochastically growing networks. As an example, we study percolation on growing scale-free networks in the framework of a real-space renormalization group approach. As a result, we find that…

Statistical Mechanics · Physics 2009-11-10 S. N. Dorogovtsev

The "edge of chaos" phase transition in artificial neural networks is of renewed interest in light of recent evidence for criticality in brain dynamics. Statistical mechanics traditionally studied this transition with connectivity $k$ as…

Disordered Systems and Neural Networks · Physics 2019-07-17 Lorenz Baumgarten , Stefan Bornholdt

The small-world phenomenon has been already the subject of a huge variety of papers, showing its appeareance in a variety of systems. However, some big holes still remain to be filled, as the commonly adopted mathematical formulation…

Statistical Mechanics · Physics 2009-11-07 Vito Latora , Massimo Marchiori

Perturbation theory for the random-field Ising model (RFIM) has the infamous attribute that it predicts at all orders a dimensional-reduction property for the critical behavior that turns out to be wrong in low dimension. Guided by our…

Disordered Systems and Neural Networks · Physics 2015-10-07 Gilles Tarjus , Matthieu Tissier

An anomalous mean-field solution is known to capture the non trivial phase diagram of the Ising model in annealed complex networks. Nevertheless the critical fluctuations in random complex networks remain mean-field. Here we show that a…

Statistical Mechanics · Physics 2015-05-14 Serena Bradde , Fabio Caccioli , Luca Dall'Asta , Ginestra Bianconi

The critical behaviour of the randomly spin-diluted Ising model in two space dimensions is investigated by a new method which combines a grand ensemble approach to disordered systems proposed by Morita with the phenomenological…

Condensed Matter · Physics 2009-10-22 R. Kühn

We consider a two-dimensional Ising model with random i.i.d. nearest-neighbor ferromagnetic couplings and no external magnetic field. We show that, if the probability of supercritical couplings is small enough, the system admits a…

Disordered Systems and Neural Networks · Physics 2015-05-30 L. Bertini , Emilio N. M. Cirillo , E. Olivieri

As more connectome data become available, the question of how to best analyse the structure of biological neural networks becomes increasingly pertinent. In brain networks, knowing that two areas are connected is often not sufficient, as…

Neurons and Cognition · Quantitative Biology 2024-01-30 Tanguy Fardet , Emmanouil Giannakakis , Lukas Paulun , Anna Levina
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