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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

The infrared behaviour of a non-mean field spin-glass system is analysed, and the critical exponent related to the divergence of the correlation length is computed at two loops within the epsilon-expansion technique with two independent…

Disordered Systems and Neural Networks · Physics 2014-09-12 Michele Castellana , Giorgio Parisi

With the help of a smooth scaling and coarse-graining approach of observables, developed recently by us in the context of so-called fluctuation operators (inspired by prior work of Verbeure et al) we perform a rigorous renormalisation group…

Mathematical Physics · Physics 2007-05-23 Manfred Requardt

The "critical brain hypothesis" posits that neural circuitry may be tuned close to a "critical point" or "phase transition" -- a boundary between different operating regimes of the circuit. The renormalization group and theory of critical…

Neurons and Cognition · Quantitative Biology 2025-10-30 Braden A. W. Brinkman

We study in a rigorous way the XYZ spin model by Renormalization Group methods.

Strongly Correlated Electrons · Physics 2007-05-23 V. Mastropietro

We analyze the critical behavior of isotropic systems with dipole-dipole interaction by renormalization-group methods in fixed space-time dimensions. Working in three-dimensional theory we analytically find three-loop expressions for…

Statistical Mechanics · Physics 2022-11-09 A. Kudlis , A. Pikelner

We discuss universal and non-universal critical exponents of a three dimensional Ising system in the presence of weak quenched disorder. Both experimental, computational, and theoretical results are reviewed. Special attention is paid to…

Disordered Systems and Neural Networks · Physics 2016-08-31 R. Folk , Yu. Holovatch , T. Yavors'kii

Dynamic critical behavior in superfluid systems is considered in a presence of external stirring and advecting processes. The latter are generated by means of the Gaussian random velocity ensemble with white-noise character in time variable…

Statistical Mechanics · Physics 2020-08-19 Michal Dančo , Michal Hnatič , Tomáš Lučivjanský , Lukáš Mižišin

Different perturbation theory treatments of the Ginzburg-Landau phase transition model are discussed. This includes a criticism of the perturbative renormalization group (RG) approach and a proposal of a novel method providing critical…

Statistical Mechanics · Physics 2017-09-27 J. Kaupuzs

We study the critical behavior and phase diagram of the $d$-dimensional random field O(N) model by means of the nonperturbative functional renormalization group approach presented in the preceding paper. We show that the dimensional…

Statistical Mechanics · Physics 2011-07-20 Matthieu Tissier , Gilles Tarjus

For certain hierarchical structures, one can study the percolation problem using the renormalization-group method in a very precise way. We show that the idea can be also applied to two-dimensional planar lattices by regarding them as…

Statistical Mechanics · Physics 2011-05-06 Seung Ki Baek , Petter Minnhagen

We establish a renormalization group approach which is implemented on the degrees of freedom defined by the overlap of two replicas to determine the critical fixed point and to extract four critical exponents for the phase transition of the…

Statistical Mechanics · Physics 2024-05-17 Dimitrios Bachtis

General aspects of fundamental physics are considered. We comment the Wigner's logical scheme and modify it to adjust to modern theoretical physics. Then, we discuss the role and indicate the place of renormalization group in the logic of…

High Energy Physics - Theory · Physics 2011-04-15 Dmitri V. Shirkov

In this thesis we investigate the Renormalization Group (RG) approach in finite-dimensional glassy systems, whose critical features are still not well-established, or simply unknown. We focus on spin and structural-glass models built on…

Disordered Systems and Neural Networks · Physics 2015-04-02 Michele Castellana

We introduce a Renormalization scheme for the one and two dimensional Forest-Fire models in order to characterize the nature of the critical state and its scale invariant dynamics. We show the existence of a relevant scaling field…

Condensed Matter · Physics 2009-10-28 V. Loreto , L. Pietronero , A. Vespignani , S. Zapperi

We review recent results concerning the renormalization group (RG) transformation of Dyson's hierarchical model (HM). This model can be seen as an approximation of a scalar field theory on a lattice. We introduce the HM and show that its…

High Energy Physics - Theory · Physics 2008-11-26 Y. Meurice

An elementary introduction to perturbative renormalization and renormalization group is presented. No prior knowledge of field theory is necessary because we do not refer to a particular physical theory. We are thus able to disentangle what…

High Energy Physics - Theory · Physics 2015-06-26 B. Delamotte

We point out some limits of the perturbative renormalization group used in statistical mechanics both at and out of equilibrium. We argue that the non perturbative renormalization group formalism is a promising candidate to overcome some of…

Statistical Mechanics · Physics 2007-05-23 B. Delamotte , L. Canet

We introduce the general formulation of a renormalization method suitable to study the critical properties of non-equilibrium systems with steady-states: the Dynamically Driven Renormalization Group. We renormalize the time evolution…

Statistical Mechanics · Physics 2008-02-03 Alessandro Vespignani , Stefano Zapperi , Vittorio Loreto

In the past two decades or so, we have learned how to understand crackling noise in a wide variety of systems. We review here the basic ideas and methods we use to understand crackling noise - critical phenomena, universality, the…

Disordered Systems and Neural Networks · Physics 2007-05-23 James P. Sethna