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We provide a theoretical analysis by means of the nonperturbative functional renormalization group (NP-FRG) of the corrections to scaling in the critical behavior of the random-field Ising model (RFIM) near the dimension $d_{DR}\approx 5.1$…

Disordered Systems and Neural Networks · Physics 2021-01-04 Ivan Balog , Gilles Tarjus , Matthieu Tissier

We propose a new picture of the renormalization group (RG) approach in the presence of disorder, which considers the RG trajectories of each random sample (realization) separately instead of the usual renormalization of the averaged free…

Statistical Mechanics · Physics 2009-10-31 Karim Bernardet , Ferenc Pazmandi , G. G. Batrouni

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

Non-equilibrium dynamics of classical random Ising spin chains are studied using asymptotically exact real space renormalization group. Specifically the random field Ising model with and without an applied field (and the Ising spin glass…

Condensed Matter · Physics 2009-10-31 Daniel S. Fisher , Pierre Le Doussal , Cecile Monthus

We study in detail the active Ising model, a stochastic lattice gas where collective motion emerges from the spontaneous breaking of a discrete symmetry. On a 2d lattice, active particles undergo a diffusion biased in one of two possible…

Statistical Mechanics · Physics 2015-10-12 A. P. Solon , J. Tailleur

Random intersection graphs containing an underlying community structure are a popular choice for modelling real-world networks. Given the group memberships, the classical random intersection graph is obtained by connecting individuals when…

Probability · Mathematics 2023-08-31 Marta Milewska , Remco van der Hofstad , Bert Zwart

We study a zero-temperature phase transition in the random field Ising model on scale-free networks with the degree exponent $\gamma$. Using an analytic mean-field theory, we find that the spins are always in the ordered phase for…

Statistical Mechanics · Physics 2007-05-23 Sang Hoon Lee , Hawoong Jeong , Jae Dong Noh

The random-field Ising model is one of the few disordered systems where the perturbative renormalization group can be carried out to all orders of perturbation theory. This analysis predicts dimensional reduction, i.e., that the critical…

Disordered Systems and Neural Networks · Physics 2017-04-12 Nikolaos G. Fytas , Victor Martin-Mayor , Marco Picco , Nicolas Sourlas

The recently developed tensor renormalization-group (TRG) method provides a highly precise technique for deriving thermodynamic and critical properties of lattice Hamiltonians. The TRG is a local coarse-graining transformation, with the…

Statistical Mechanics · Physics 2008-02-18 Michael Hinczewski , A. Nihat Berker

We show that an interaction decaying as a stretched exponential function of the distance, $J(l)\sim e^{-cl^a}$, is able to alter the universality class of short-range systems having an infinite-disorder critical point. To do so, we study…

Disordered Systems and Neural Networks · Physics 2015-06-19 Róbert Juhász

The stationary distributions of sums of positions of trajectories generated by the logistic map have been found to follow a basic renormalization group (RG) structure: a nontrivial fixed-point multi-scale distribution at the period-doubling…

Chaotic Dynamics · Physics 2015-06-23 Alvaro Diaz-Ruelas , Miguel Angel Fuentes , Alberto Robledo

We discuss a two-point particle irreducible (2PPI) approach to many-body physics which relies on a renormalization group (RG) flow equation for the associated effective action. In particular, the general structure and properties of this RG…

Nuclear Theory · Physics 2015-06-15 Sandra Kemler , Jens Braun

It is demonstrated that the renormalization group (RG) flows of depinning transitions do not depend on whether the driving force or the system velocity is kept constant. This allows for a comparison between RG results and corresponding…

Condensed Matter · Physics 2009-10-31 Onuttom Narayan

Haros graphs have been recently introduced as a set of graphs bijectively related to real numbers in the unit interval. Here we consider the iterated dynamics of a graph operator $\cal R$ over the set of Haros graphs. This operator was…

Statistical Mechanics · Physics 2023-05-10 Jorge Calero-Sanz , Bartolo Luque , Lucas Lacasa

The class of random-cluster models is a unification of a variety of stochastic processes of significance for probability and statistical physics, including percolation, Ising, and Potts models; in addition, their study has impact on the…

Probability · Mathematics 2007-05-23 Geoffrey Grimmett

We consider m two-dimensional semi-infinite planes of Ising spins joined together through surface spins and study the critical behaviour near to the junction. The m=0 limit of the model - according to the replica trick - corresponds to the…

Statistical Mechanics · Physics 2007-05-23 F. Igloi , L. Turban , B. Berche

We develop a renormalization group (RG) description of the localization properties of onedimensional (1D) quasiperiodic lattice models. The RG flow is induced by increasing the unit cell of subsequent commensurate approximants. Phases of…

Disordered Systems and Neural Networks · Physics 2023-10-10 Miguel Gonçalves , Bruno Amorim , Eduardo V. Castro , Pedro Ribeiro

The critical behavior of the two-dimensional N-vector cubic model is studied within the field-theoretical renormalization-group (RG) approach. The beta-functions and critical exponents are calculated in the five-loop approximation, RG…

Statistical Mechanics · Physics 2016-08-31 P. Calabrese , E. V. Orlov , D. V. Pakhnin , A. I. Sokolov

Randomly coupled Ising spins constitute the classical model of collective phenomena in disordered systems, with applications covering ferromagnetism, combinatorial optimization, protein folding, stock market dynamics, and social dynamics.…

Disordered Systems and Neural Networks · Physics 2016-08-24 David Dahmen , Hannah Bos , Moritz Helias

When studying networks using random graph models, one is sometimes faced with situations where the notion of adjacency between nodes reflects multiple constraints. Traditional random graph models are insufficient to handle such situations.…

Information Theory · Computer Science 2008-09-10 N. Prasanth Anthapadmanabhan , Armand M. Makowski