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We consider renormalization group (RG) transformations for classical Ising-type lattice spin systems in the infinite volume limit. Formally, the RG maps a Hamiltonian H into a renormalized Hamiltonian H': exp(-H'(\sigma'))=\sum_\sigma…

Mathematical Physics · Physics 2012-05-04 Mei Yin

It is argued that cluster methods provide a viable alternative to Wilson's momentum shell integration technique at the early stage of renormalization in the field-theoretic models with strongly coupled fields because these methods allow for…

Statistical Mechanics · Physics 2016-06-23 V. I. Tokar

The renormalization group (RG) approach is largely responsible for the considerable success that has been achieved in developing a quantitative theory of phase transitions. Physical properties emerge from spectral properties of the…

Mathematical Physics · Physics 2015-05-14 Mei Yin

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 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

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

We show with several examples that renormalization group (RG) theory can be used to understand singular and reductive perturbation methods in a unified fashion. Amplitude equations describing slow motion dynamics in nonequilibrium phenomena…

Condensed Matter · Physics 2009-10-22 Lin-Yuan Chen , Nigel Goldenfeld , Y. Oono

We propose a new concept upon the renormalization group (RG) procedure for an interacting many-electron correlated system in the framework of natural orbitals, and formulate an algorithm for this RG approach. To demonstrate its…

Strongly Correlated Electrons · Physics 2014-02-17 Rong-Qiang He , Zhong-Yi Lu

In this paper we propose a novel method to study critical systems numerically by a combined collective-mode algorithm and Renormalization Group on the lattice. This method is an improved version of MCRG in the sense that it has all the…

Statistical Mechanics · Physics 2009-12-03 G. Palma , D. Zambrano

It is shown that the renormalization group (RG) method for global analysis can be formulated in the context of the classical theory of envelopes: Several examples from partial differential equations are analyzed. The amplitude equations…

patt-sol · Physics 2008-02-03 Teiji Kunihiro

Functional renormalization group (FRG) has become a diverse and powerful tool to derive effective low-energy scattering vertices of interacting many-body systems. Starting from a non-interacting expansion point of the action, the flow of…

Strongly Correlated Electrons · Physics 2014-01-22 Johannes Reuther , Ronny Thomale

We present a renormalization group (RG) procedure which works naturally on a wide class of interacting one-dimension models based on perturbed (possibly strongly) continuum conformal and integrable models. This procedure integrates Kenneth…

Strongly Correlated Electrons · Physics 2016-07-05 Robert M. Konik , Yury Adamov

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

Perturbative renormalization group theory is developed as a unified tool for global asymptotic analysis. With numerous examples, we illustrate its application to ordinary differential equation problems involving multiple scales, boundary…

High Energy Physics - Theory · Physics 2008-11-26 Lin-Yuan Chen , Nigel Goldenfeld , Y. Oono

These notes provide a concise introduction to important applications of the renormalization group (RG) in statistical physics. After reviewing the scaling approach and Ginzburg-Landau theory for critical phenomena, Wilson's momentum shell…

Statistical Mechanics · Physics 2015-03-19 Uwe C. Tauber

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

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

Analytic phenomenological scaling is carried out for the random field Ising model in general dimensions using a bar geometry. Domain wall configurations and their decorated profiles and associated wandering and other exponents…

Condensed Matter · Physics 2009-10-28 R. B. Stinchcombe , E. D. Moore , S. L. A. de Queiroz

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

We formally introduce a class of models inspired by renormalization group (RG) theory, built on additive hierarchical expansions analogous to those appearing in functional ANOVA and mixed-effects models. Like ReLU convolutional neural…

Methodology · Statistics 2026-05-08 Joshua C. Chang
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