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We investigate an operator renormalization group method to extract and describe the relevant degrees of freedom in the evolution of partial differential equations. The proposed renormalization group approach is formulated as an analytical…

Statistical Mechanics · Physics 2007-05-23 Andreas Degenhard , Javier Rodriguez-Laguna

We investigate the use of renormalisation group methods to solve partial differential equations (PDEs) numerically. Our approach focuses on coarse-graining the underlying continuum process as opposed to the conventional numerical analysis…

Statistical Mechanics · Physics 2009-10-31 Nigel Goldenfeld , Alan McKane , Qing Hou

We combine histogram reweighting techniques with the two-lattice matching Monte Carlo renormalization group method to conduct computationally efficient calculations of critical exponents on systems with moderately small lattice sizes. The…

High Energy Physics - Lattice · Physics 2024-01-23 Dimitrios Bachtis

Renormalization group theory is a powerful and intriguing technique with a wide range of applications. One of the main successes of renormalization group theory is the description of continuous phase transitions and the development of…

Statistical Mechanics · Physics 2025-02-04 Luca Di Carlo

The partial success of the block renormalization group techniques is analysed in terms of a functional operator which formalizes the idea of self-replicability of a system in terms of smaller blocks which are similar to the original. The…

Mathematical Physics · Physics 2009-09-29 Javier Rodriguez-Laguna , German Sierra

Finite-size scaling at fixed renormalization-group invariant is a powerful and flexible technique to analyze Monte Carlo data at a critical point. It consists in fixing a given renormalization-group invariant quantity to a given value,…

Statistical Mechanics · Physics 2022-03-30 Francesco Parisen Toldin

The application of Renormalization Group (RG) methods to find perfect discretizations of partial differential equations is a promising but little investigated approach. We calculate the classically perfect fixed-point Laplace operator for…

High Energy Physics - Lattice · Physics 2009-10-31 S. Hauswirth

A class of exact infinitesimal renormalization group transformations is proposed and studied. These transformations are pure changes of variables (i.e., no integration or elimination of some degrees of freedom is required) such that a…

High Energy Physics - Theory · Physics 2017-11-08 Ariel Caticha

A finite-size scaling theory for the $\phi^4_4$ model is derived using renormalization group methods. Particular attention is paid to the partition function zeroes, in terms of which all thermodynamic observables can be expressed. While the…

High Energy Physics - Lattice · Physics 2009-10-22 R. Kenna , C. B. Lang

Renormalization group method is one of the most powerful tool to obtain approximate solutions to differential equations. We apply the renormalization group method to Hamiltonian systems whose integrable parts linearly depend on action…

chao-dyn · Physics 2007-05-23 Yoshiyuki Y. Yamaguchi , Yasusada Nambu

Renormalization group calculations are used to give exact solutions for rigidity percolation on hierarchical lattices. Algebraic scaling transformations for a simple example in two dimensions produce a transition of second order, with an…

Statistical Mechanics · Physics 2011-07-26 R. B. Stinchcombe , M. F Thorpe

A simple backreaction problem in quantum mechanics, the full quantum anharmonic oscillator, and quantum parametric resonance are studied using Renormalization Group techniques for global asymptotic analysis. In this short note this…

High Energy Physics - Theory · Physics 2017-02-16 I. L. Egusquiza , M. A. Valle-Basagoiti

We investigate an approach for the numerical solution of differential equations which is based on the perfect discretization of actions. Such perfect discretizations show up at the fixed points of renormalization group transformations. This…

High Energy Physics - Lattice · Physics 2007-05-23 S. Hauswirth

We introduce a numerical method to study critical properties near classical and quantum phase transitions. Our method applies ideas of the Tensor Renormalization Group to obtain an improved action which is used to extract critical…

Statistical Mechanics · Physics 2024-08-14 Guy Segall , Snir Gazit , Daniel Podolsky

In this paper we present an efficient numerical approach based on the Renormalization Group method for the computation of self-similar dynamics. The latter arise, for instance, as the long-time asymptotic behavior of solutions to nonlinear…

Analysis of PDEs · Mathematics 2016-09-06 Gastao A. Braga , Frederico Furtado , Jussara M. Moreira , Leonardo T. Rolla

The renormalization group method is applied in order to analyze models E and F of critical dynamics in the presence of velocity fluctuations generated by the stochastic Navier-Stokes equation. Results are given to the one-loop approximation…

Statistical Mechanics · Physics 2017-05-08 M. Dančo , M. Hnatič , M. V. Komarova , T. Lučivjanský , M. Yu. Nalimov

Renormalization group procedure for effective particles in the front form of Hamiltonian dynamics is applied to an elementary quantum field theory for two species of particles mixed through a mass-like interaction term. The model…

High Energy Physics - Theory · Physics 2015-06-04 Stanislaw D. Glazek

A new operator formalism for the reduction of degrees of freedom in the evolution of discrete partial differential equations (PDE) via real space Renormalization Group is introduced, in which cell-overlapping is the key concept.…

Statistical Mechanics · Physics 2009-11-07 Andreas Degenhard , Javier Rodriguez-Laguna

We study exact renormalization group equations in the framework of the effective average action. We present analytical solutions for the scale dependence of the potential in a variety of models. These solutions display a rich spectrum of…

High Energy Physics - Theory · Physics 2008-11-26 N. Tetradis , D. F. Litim

The renormalization group has proven to be a very powerful tool in physics for treating systems with many length scales. Here we show how it can be adapted to provide a new class of algorithms for discrete optimization. The heart of our…

Disordered Systems and Neural Networks · Physics 2009-10-31 J. Houdayer , O. C. Martin
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