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To describe the non-equilibrium dynamics of random systems, we have recently introduced (C. Monthus and T. Garel, arxiv:0802.2502) a 'strong disorder renormalization' (RG) procedure in configuration space that can be defined for any master…

Disordered Systems and Neural Networks · Physics 2008-10-08 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

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

Disordered systems are an important class of models in statistical mechanics, having the defining characteristic that the energy landscape is a fixed realization of a random field. Examples include various models of glasses and polymers.…

Probability · Mathematics 2008-12-16 Sourav Chatterjee

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

The renormalization group (RG) is a powerful theoretical framework developed to consistently transform the description of configurations of systems with many degrees of freedom, along with the associated model parameters and coupling…

Statistical Mechanics · Physics 2026-04-20 Andrea Gabrielli , Diego Garlaschelli , Subodh P. Patil , M. Ángeles Serrano

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

We propose a tensor network method for investigating strongly disordered systems that is based on an adaptation of entanglement renormalization [G. Vidal, Phys. Rev. Lett. 99, 220405 (2007)]. This method makes use of the strong disorder…

Strongly Correlated Electrons · Physics 2017-10-26 Andrew M. Goldsborough , Glen Evenbly

We formulate a real-space renormalization group (RG) approach for efficient numerical analysis of the low-temperature hopping dynamics in energy-disordered lattices. The approach explicitly relies on the time-scale separation of the…

Mesoscale and Nanoscale Physics · Physics 2013-09-16 Kirill A. Velizhanin , Andrei Piryatinski , Vladimir Y. Chernyak

We develop a scaling theory and a renormalization technique in the context of the modern theory of polarization. The central idea is to use the characteristic function (also known as the polarization amplitude) in place of the free energy…

Disordered Systems and Neural Networks · Physics 2021-12-17 Balázs Hetényi , Selçuk Parlak , Mohammad Yahyavi

In these proceedings, we discuss why functional renormalization is an essential tool to treat strongly disordered systems. More specifically, we treat elastic manifolds in a disordered environment. These are governed by a disorder…

Disordered Systems and Neural Networks · Physics 2007-05-23 Kay Joerg Wiese

Guided by critical systems found in nature we develop a novel mechanism consisting of inhomogeneous polynomial regularisation via which we can induce scale invariance in deep learning systems. Technically, we map our deep learning (DL)…

Statistical Mechanics · Physics 2017-06-01 Dan Oprisa , Peter Toth

Many numerical schemes for hyperbolic systems require a piecewise polynomial reconstruction of the cell averaged values, and to simulate perturbed steady states accurately we require a so called 'well balanced' reconstruction scheme. For…

Numerical Analysis · Mathematics 2021-06-22 Edward W. G. Skevington

Renormalization Group (RG) techniques have been successfully employed in quantum field theory and statistical physics. Here we apply RG methods to study the non-linear stages of structure formation in the Universe. Exact equations for the…

Astrophysics · Physics 2010-10-27 Sabino Matarrese , Massimo Pietroni

The interplay of disorder and interactions is a challenging topic of condensed matter physics, where correlations are crucial and exotic phases develop. In one spatial dimension, a particularly successful method to analyze such problems is…

Strongly Correlated Electrons · Physics 2019-12-10 V. L. Quito , Pedro L. S. Lopes , José A. Hoyos , E. Miranda

Finite volume schemes for hyperbolic balance laws require a piecewise polynomial reconstruction of the cell averaged values, and a reconstruction is termed `well-balanced' if it is able to simulate steady states at higher order than time…

Numerical Analysis · Mathematics 2021-06-22 Edward W. G. Skevington

A recently proposed renormalization group technique, based on the hierarchical structures present in theories with fluctuating geometry, is implemented in the model of branched polymers. The renormalization group equations can be solved…

High Energy Physics - Lattice · Physics 2009-10-28 Jan Ambjorn , Piotr Bialas , Jerzy Jurkiewicz

We studied the correlated quasi-one-dimensional systems by one-loop renormalization group techniques in weak coupling. In contrast to conventional g-ology approach, we formulate the theory in terms of bilinear currents and obtain all…

Strongly Correlated Electrons · Physics 2009-11-11 Ming-Shyang Chang , Wei Chen , Hsiu-Hau Lin

The physics of strongly correlated systems offers some of the most intriguing physics challenges such as competing orders or the emergence of dynamical composite degrees of freedom. Often, the resolution of these physics challenges is…

High Energy Physics - Theory · Physics 2025-08-29 Friederike Ihssen , Jan M. Pawlowski

The main aim of this work is to present two different methodologies for configuration averaging in disordered systems. The Recursion method is suitable for the calculation of spatial or self-averaging, while the Augmented space formalism…

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