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We develop an algorithmic, system-specific renormalization group (RG) procedure that is adapted from model reductions techniques from engineering control theory. The resulting "generalized" RG is a consistent generalization of the Wilsonian…

Statistical Mechanics · Physics 2007-05-23 David E. Reynolds

We introduce an RG-inspired coarse-graining for extracting the collective features of data. The key to successful coarse-graining lies in finding appropriate pairs of data sets. We coarse-grain the two closest data in a regular real-space…

Data Analysis, Statistics and Probability · Physics 2023-07-19 Jonathan Landy , Tsvi Tlusty , YeongKyu Lee , YongSeok Jho

Although there has been a rapid development of practical applications, theoretical explanations of deep learning are in their infancy. Deep learning performs a sophisticated coarse graining. Since coarse graining is a key ingredient of the…

Machine Learning · Computer Science 2020-06-11 Ellen de Mello Koch , Robert de Mello Koch , Ling Cheng

Separating relevant and irrelevant information is key to any modeling process or scientific inquiry. Theoretical physics offers a powerful tool for achieving this in the form of the renormalization group (RG). Here we demonstrate a…

Machine Learning · Computer Science 2025-05-14 Jessica N. Howard , Ro Jefferson , Anindita Maiti , Zohar Ringel

The so-called renormalization group (RG) method is applied to derive kinetic and transport equations from the respective microscopic equations. The derived equations include Boltzmann equation in classical mechanics, Fokker-Planck equation,…

High Energy Physics - Theory · Physics 2009-11-07 Y. Hatta , T. Kunihiro

The key idea behind the renormalization group (RG) transformation is that properties of physical systems with very different microscopic makeups can be characterized by a few universal parameters. However, finding the optimal RG…

Disordered Systems and Neural Networks · Physics 2021-06-30 Jui-Hui Chung , Ying-Jer Kao

Sampling equilibrium molecular configurations from the Boltzmann distribution is a longstanding challenge. Boltzmann Generators (BGs) address this by combining exact-likelihood generative models with importance sampling, but practical…

Machine Learning · Computer Science 2026-05-29 Weilong Chen , Bojun Zhao , Jan Eckwert , Julija Zavadlav

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

We present a variational renormalization group (RG) approach using a deep generative model based on normalizing flows. The model performs hierarchical change-of-variables transformations from the physical space to a latent space with…

Statistical Mechanics · Physics 2018-12-31 Shuo-Hui Li , Lei Wang

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

Complex networks can model a range of different systems, from the human brain to social connections. Some of those networks have a large number of nodes and links, making it impractical to analyze them directly. One strategy to simplify…

Disordered Systems and Neural Networks · Physics 2023-04-06 Matheus de C. Loures , Alan Albert Piovesana , José Antônio Brum

We develop a variational scheme called "Gutzwiller renormalization group" (GRG), which enables us to calculate the ground state of Anderson impurity models (AIM) with arbitrary numerical precision. Our method can exploit the…

Strongly Correlated Electrons · Physics 2017-02-15 Nicola Lanatà , Yong-Xin Yao , Xiaoyu Deng , Cai-Zhuang Wang , Kai-Ming Ho , Gabriel Kotliar

We derive generic relativistic hydrodynamical equations with dissipative effects from the underlying Boltzmann equation in a mechanical and systematic way on the basis of so called the renormalization-group (RG) method. A macroscopic frame…

High Energy Physics - Phenomenology · Physics 2008-11-26 K. Tsumura , T. Kunihiro , K. Ohnishi

We review our study of the Wilsonian renormalization group (WRG) analysis for nuclear current operators. We apply WRG method to axial-current operators derived from various approaches and obtain the unique effective low-energy operator.

Nuclear Theory · Physics 2017-08-23 Satoshi X. Nakamura , Shung-ichi Ando

The Numerical Renormalization Group method (NRG) has been developed by Wilson in the 1970's to investigate the Kondo problem. The NRG allows the non-perturbative calculation of static and dynamic properties for a variety of impurity models.…

Strongly Correlated Electrons · Physics 2009-10-31 R. Bulla

We investigate the renormalization group approach to nonequilibrium field theory. We show that it is possible to derive nontrivial renormalization group flow from iterative coarse graining of a closed-time-path action. This renormalization…

Condensed Matter · Physics 2009-11-07 Juan Zanella , Esteban Calzetta

The Wilsonian renormalization group (RG) method is applied to finite temperature systems for the study of non-perturbative methods in the field theory. We choose the O(N) linear sigma model as the first step. Under the local potential…

High Energy Physics - Phenomenology · Physics 2007-05-23 T. Umekawa , K. Naito , M. Oka

We are interested in the consistency between the cutoff, chiral symmetry, and the power counting. For this purpose, we apply the Wilsonian renormalization group (RG) to an operator and then decrease the Wilsonian cutoff. As an example, we…

Nuclear Theory · Physics 2008-11-26 Satoshi X. Nakamura , Anders Gardestig

The renormalization group plays an essential role in many areas of physics, both conceptually and as a practical tool to determine the long-distance low-energy properties of many systems on the one hand and on the other hand search for…

Statistical Mechanics · Physics 2021-05-10 N. Dupuis , L. Canet , A. Eichhorn , W. Metzner , J. M. Pawlowski , M. Tissier , N. Wschebor

The operator-theoretic renormalization group (RG) methods are powerful analytic tools to explore spectral properties of field-theoretical models such as quantum electrodynamics (QED) with non-relativistic matter. In this paper these methods…

Mathematical Physics · Physics 2009-07-17 Juerg Froehlich , Marcel Griesemer , Israel Michael Sigal
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