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Related papers: Non-equilibrium dynamics of finite-dimensional dis…

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To describe the equilibrium properties of disordered systems and the possible emergence of various 'phases' at low temperature, we adopt here the 'broken ergodicity' point of view advocated in particular by Palmer [Adv. Phys. 31, 669…

Disordered Systems and Neural Networks · Physics 2008-08-18 Cecile Monthus , Thomas Garel

We show that an appropriate description of the non-equilibrium dynamics of disordered systems is obtained through a strong disorder renormalization procedure in {\it configuration space}, that we define for any master equation with…

Disordered Systems and Neural Networks · Physics 2008-10-08 Cecile Monthus , Thomas Garel

Exploring and understanding topological phases in systems with strong distributed disorder requires developing fundamentally new approaches to replace traditional tools such as topological band theory. Here, we present a general real-space…

Disordered Systems and Neural Networks · Physics 2024-04-25 Zhe Zhang , Yifei Guan , Junda Wang , Benjamin Apffel , Aleksi Bossart , Haoye Qin , Oleg V. Yazyev , Romain Fleury

Strong Disorder Renormalization is an energy-based renormalization that leads to a complicated renormalized topology for the surviving clusters as soon as $d>1$. In this paper, we propose to include Strong Disorder Renormalization ideas…

Disordered Systems and Neural Networks · Physics 2012-05-04 Cecile Monthus , Thomas Garel

We study the low-energy physics of the critical (2+1)-dimensional random transverse-field Ising model. The one-dimensional version of the model is a paradigmatic example of a system governed by an infinite-randomness fixed point, for which…

Statistical Mechanics · Physics 2023-11-21 Akshat Pandey , Aditya Mahadevan , Aditya Cowsik

There is a large variety of quantum and classical systems in which the quenched disorder plays a dominant r\^ole over quantum, thermal, or stochastic fluctuations : these systems display strong spatial heterogeneities, and many averaged…

Disordered Systems and Neural Networks · Physics 2009-11-11 Ferenc Igloi , Cecile Monthus

The Strong Disorder RG approach for random systems has been extended in many new directions since our previous review of 2005 [Phys. Rep. 412, 277]. The aim of the present colloquium paper is thus to give an overview of these various recent…

Disordered Systems and Neural Networks · Physics 2018-11-26 Ferenc Iglói , Cécile Monthus

For arbitrary networks of random masses connected by random springs, we define a general strong disorder real-space renormalization (RG) approach that generalizes the procedures introduced previously by Hastings [Phys. Rev. Lett. 90, 148702…

Disordered Systems and Neural Networks · Physics 2011-02-03 Cecile Monthus , Thomas Garel

The Renormalization Group (RG) is a set of methods that have been instrumental in tackling problems involving an infinite number of degrees of freedom. What all these methods have in common -- which is what explains their success -- is that…

Statistical Mechanics · Physics 2020-04-30 Pedro Pessoa , Ariel Caticha

Renormalisation group (RG) methods provide one of the most important techniques for analysing the physics of many-body systems, both analytically and numerically. By iterating an RG map, which "course-grains" the description of a many-body…

Quantum Physics · Physics 2022-12-26 James D. Watson , Emilio Onorati , Toby S. Cubitt

We consider the continuous-time random walk of a particle in a two-dimensional self-affine quenched random potential of Hurst exponent $H>0$. The corresponding master equation is studied via the strong disorder renormalization procedure…

Disordered Systems and Neural Networks · Physics 2010-02-01 Cecile Monthus , Thomas Garel

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

We present a renormalization group (RG) approach to explain universal features of extreme statistics, applied here to independent, identically distributed variables. The outlines of the theory have been described in a previous Letter, the…

Statistical Mechanics · Physics 2015-05-18 G. Gyorgyi , N. R. Moloney , K. Ozogany , Z. Racz , M. Droz

Complex systems with many degrees of freedom are typically intractable, but some of their behaviors may admit simpler effective descriptions. The question of when such effective descriptions are possible remains open. The paradigmatic…

Statistical Mechanics · Physics 2020-11-26 Charlotte Strandkvist , Pavel Chvykov , Mikhail Tikhonov

We study flow of renormalization group (RG) transformations for the massless Gross-Neveu model in a non-perturbative formulation. The model is defined on a d=2 dimensional Euclidean space with a finite volume. The quadratic approximation to…

Mathematical Physics · Physics 2024-03-15 J. Dimock , Cheng Yuan

We suggest a new, renormalization group (RG) based, nonperturbative method for treating the intermittency problem of fully developed turbulence which also includes the effects of a finite boundary of the turbulent flow. The key idea is not…

chao-dyn · Physics 2007-05-23 Alexander Esser , Siegfried Grossmann

We describe in detail and extend a recently introduced nonperturbative renormalization group (RG) method for surface growth. The scale invariant dynamics which is the key ingredient of the calculation is obtained as the fixed point of a RG…

Statistical Mechanics · Physics 2009-10-31 C. Castellano , M. Marsili , M. A. Munoz , L. Pietronero

The renormalization group (RG) in statistical physics focuses on ground-state properties of equilibrium systems. However, it is unclear how it should be generalized to nonunitary quantum dynamics caused by dissipation and measurement…

Statistical Mechanics · Physics 2026-05-12 Atsushi Oyaizu , Hongchao Li , Masaya Nakagawa , Masahito Ueda

Self-similarity, where observables at different length scales exhibit similar behavior, is ubiquitous in natural systems. Such systems are typically characterized by power-law correlations and universality, and are studied using the…

Disordered Systems and Neural Networks · Physics 2026-01-05 Gorka Peraza Coppola , Moritz Helias , Zohar Ringel

We present a numerical implementation of the renormalization group (RG) for partial differential equations, constructing similarity solutions and travelling waves. We show that for a large class of well-localized initial conditions,…

chao-dyn · Physics 2009-10-22 Lin-Yuan Chen , Nigel Goldenfeld
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