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The purpose of this paper is (i) to present a generic and fully functional implementation of the density-matrix renormalization group (DMRG) algorithm, and (ii) to describe how to write additional strongly-correlated electron models and…

Strongly Correlated Electrons · Physics 2015-05-13 G. Alvarez

We review recent results concerning the renormalization group (RG) transformation of Dyson's hierarchical model (HM). This model can be seen as an approximation of a scalar field theory on a lattice. We introduce the HM and show that its…

High Energy Physics - Theory · Physics 2008-11-26 Y. Meurice

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

Exploiting symmetries in the numerical renormalization group (NRG) method significantly enhances performance by improving accuracy, increasing computational speed, and optimizing memory efficiency. Published codes focus on continuous…

Strongly Correlated Electrons · Physics 2024-09-19 Aitor Calvo-Fernández , María Blanco-Rey , Asier Eiguren

We develop renormalization group methods for solving partial and stochastic differential equations on coarse meshes. Renormalization group transformations are used to calculate the precise effect of small scale dynamics on the dynamics at…

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

In this article we apply a recently invented analytical real-space renormalization group formulation which is based on numerical concepts of the density matrix renormalization group. Within a rigorous mathematical framework we construct…

Statistical Mechanics · Physics 2009-10-31 Andreas Degenhard

We consider the sign problem for classical spin models at complex $\beta =1/g_0^2$ on $L\times L$ lattices. We show that the tensor renormalization group method allows reliable calculations for larger Im$\beta$ than the reweighting Monte…

High Energy Physics - Lattice · Physics 2014-01-15 Alan Denbleyker , Yuzhi Liu , Y. Meurice , M. P. Qin , T. Xiang , Z. Y. Xie , J. F. Yu , Haiyuan Zou

A numerical real-space version of the Inverse Renormalization Group proposed by Gawedzky et al is developed. It has been tested to obtain the scaling behaviour of the random-forced heat equation in the short scales limit. Prospectives are…

Statistical Mechanics · Physics 2007-05-23 Javier Rodriguez-Laguna

We study constraint effective potentials for various strongly interacting $\phi^4$ theories. Renormalization group (RG) equations for these quantities are discussed and a heuristic development of a commonly used RG approximation is…

High Energy Physics - Lattice · Physics 2009-09-25 J. R. Shepard , V. Dmitrašinović , J. A. McNeil

We report a Monte Carlo simulation of the $2D$ Edwards-Anderson spin glass model within the recently introduced multicanonical ensemble. Replica on lattices of size $L^2$ up to $L=48$ are investigated. Once a true groundstate is found, we…

High Energy Physics - Lattice · Physics 2015-06-25 B. A. Berg , T. Celik

We develop a Renormalization Group (RG) approach to the study of existence and uniqueness of solutions to stochastic partial differential equations driven by space-time white noise. As an example we prove well-posedness and independence of…

Probability · Mathematics 2015-02-20 Antti Kupiainen

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) constitutes a fundamental framework in modern theoretical physics. It allows the study of many systems showing states with large-scale correlations and their classification in a relatively small set of…

Statistical Mechanics · Physics 2024-09-04 Guido Caldarelli , Andrea Gabrielli , Tommaso Gili , Pablo Villegas

The numerical renormalization group (NRG) is rephrased as a variational method with the cost function given by the sum of all the energies of the effective low-energy Hamiltonian. This allows to systematically improve the spectrum obtained…

Quantum Physics · Physics 2013-05-23 Iztok Pizorn , Frank Verstraete

We develop the exact renormalization group approach as a way to evaluate the effective speed of propagation of a scalar wave in a medium with random inhomogeneities. We use the Martin-Siggia-Rose formalism to translate the problem into a…

Disordered Systems and Neural Networks · Physics 2017-08-02 Federico Lamagna , Esteban Calzetta

We use the numerical renormalization group method (NRG) to investigate a single-impurity Anderson model with a coupling of the impurity to a superconducting host. Analysis of the energy flow shows, in contrast to previous belief, that NRG…

Strongly Correlated Electrons · Physics 2015-05-13 Theresa Hecht , Andreas Weichselbaum , Jan von Delft , Ralf Bulla

Multi-scale renormalization group (RG) methods are reviewed and applied to the analysis of the effective potential for radiative symmetry breaking with multiple scalar fields, allowing an extension of the Gildener & Weinberg (GW) method…

High Energy Physics - Phenomenology · Physics 2014-11-19 T. G. Steele , Zhi-Wei Wang , D. G. C. McKeon

We explore the implications of recent work by Br\'ezin and Zinn-Justin, applying the renormalization group techniques from critical phenomena to the scaling limit of matrix models in two-dimensional quantum gravity. They endeavor to get the…

High Energy Physics - Theory · Physics 2009-10-22 Carles Ayala

We summarize our recent results on the large N renormalization group (RG) approach to matrix models for discretized two-dimensional quantum gravity. We derive exact RG equations by solving the reparametrization identities, which reduce…

High Energy Physics - Theory · Physics 2007-05-23 S. Higuchi , C. Itoi , S. Nishigaki , N. Sakai

We propose a real-space renormalization group algorithm for accurately coarse-graining two-dimensional tensor networks. The central innovation of our method lies in utilizing variational boundary tensors as a globally optimized environment…

Statistical Mechanics · Physics 2026-03-03 Feng-Feng Song , Naoki Kawashima