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We apply a functional implementation of the field-theoretical renormalization group (RG) method up to two loops to the single-impurity Anderson model. To achieve this, we follow a RG strategy similar to that proposed by Vojta \emph{et al.}…

Strongly Correlated Electrons · Physics 2012-01-11 Hermann Freire , Eberth Corrêa

Using continuous wavelet transform it is possible to construct a regularization procedure for scale-dependent quantum field theory models, which is complementary to functional renormalization group method in the sense that it sums up the…

High Energy Physics - Theory · Physics 2019-03-27 M. V. Altaisky

The gradient flow bears a close resemblance to the coarse graining, the guiding principle of the renormalization group (RG). In the case of scalar field theory, a precise connection has been made between the gradient flow and the RG flow of…

High Energy Physics - Theory · Physics 2021-03-10 Hidenori Sonoda , Hiroshi Suzuki

Renormalisation group approaches are tailor made for resolving the scale-dependence of quantum and statistical systems, and hence their phase structure and critical physics. Usually this advantage comes at the price of having to truncate…

High Energy Physics - Theory · Physics 2023-11-28 Friederike Ihssen , Jan M. Pawlowski

We show how to build a multi-scale entanglement renormalization ansatz (MERA) representation of the ground state of a many-body Hamiltonian $H$ by applying the recently proposed \textit{tensor network renormalization} (TNR) [G. Evenbly and…

Strongly Correlated Electrons · Physics 2015-11-18 Glen Evenbly , Guifre Vidal

According to the available publications, the field theoretical renormalization group (RG) approach in the two-dimensional case gives the critical exponents that differ from the known exact values. This fact was attempted to explain by the…

Statistical Mechanics · Physics 2009-11-13 A. A. Pogorelov , I. M. Suslov

We introduce the multi-scale entanglement renormalization ansatz (MERA), an efficient representation of certain quantum many-body states on a D-dimensional lattice. Equivalent to a quantum circuit with logarithmic depth and distinctive…

Quantum Physics · Physics 2009-11-13 G. Vidal

It is shown how to construct renormalization group flows of quantum field theories in real space, as opposed to the usual Wilsonian approach in momentum space. This is achieved by generalizing the multiscale entanglement renormalization…

High Energy Physics - Theory · Physics 2013-12-23 Jutho Haegeman , Tobias J. Osborne , Henri Verschelde , Frank Verstraete

The standard demand for the quantum partition function to be invariant under the renormalization group transformation results in a general class of exact renormalization group equations, different in the form of the kernel. Physical…

High Energy Physics - Theory · Physics 2007-05-23 Stefano Arnone , Antonio Gatti , Tim R. Morris

We holographically investigate the renormalization group flow in a two-dimensional conformal field theory deformed by a relevant operator. If the relevant operator allows another fixed point, the UV conformal field theory smoothly flows to…

High Energy Physics - Theory · Physics 2018-12-05 Chanyong Park , Daeho Ro , Jung Hun Lee

The multiscale entanglement renormalization ansatz (MERA) provides a constructive algorithm for realizing wavefunctions that are inherently scale invariant. Unlike conformally invariant partition functions however, the finite bond dimension…

Strongly Correlated Electrons · Physics 2020-10-21 Karel Van Acoleyen , Andrew Hallam , Matthias Bal , Markus Hauru , Jutho Haegeman , Frank Verstraete

Implementing the Wilsonian renormalization group (RG) transformation in a nonperturbative way, we construct an effective holographic dual description with an emergent extradimension identified with an RG scale. Taking the large$-N$ limit,…

High Energy Physics - Theory · Physics 2023-03-09 Ki-Seok Kim , Mitsuhiro Nishida , Yoonseok Choun

The density matrix renormalization group (DMRG) is a powerful numerical technique to solve strongly correlated quantum systems: it deals well with systems which are not dominated by a single configuration (unlike Coupled Cluster) and it…

Chemical Physics · Physics 2025-12-16 Martina Nibbi , Luca Frediani , Evgueni Dinvay , Christian B. Mendl

Exact Renormalization Group techniques are applied to supersymmetric models in order to get some insights into the low energy effective actions of such theories. Starting from the ultra-violet finite mass deformed N=4 supersymmetric…

High Energy Physics - Theory · Physics 2014-11-18 S. Arnone , S. Chiantese , K. Yoshida

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

At low energies, the microscopic characteristics and changes of physical systems as viewed at different distance scales are described by universal scale invariant properties investigated by the Renormalization Group (RG) apparatus, an…

General Physics · Physics 2018-04-03 Eric Howard

The gradient flow exact renormalization group (GFERG) is an exact renormalization group motivated by the Yang--Mills gradient flow and its salient feature is a manifest gauge invariance. We generalize this GFERG, originally formulated for…

High Energy Physics - Theory · Physics 2021-09-15 Yuki Miyakawa , Hiroshi Suzuki

In the paper [Angelini M C, Parisi G, and Ricci-Tersenghi F, Ensemble renormalization group for disordered systems, Phys. Rev. B 87 134201 (2013)] we introduced a real-space renormalization group called Ensemble Renormalization Group (ERG)…

Disordered Systems and Neural Networks · Physics 2020-09-04 Maria Chiara Angelini , Giorgio Parisi , Federico Ricci-Tersenghi

Tensor networks representations of many-body quantum systems can be described in terms of quantum channels. We focus on channels associated with the Multi-scale Entanglement Renormalization Ansatz (MERA) tensor network that has been…

Quantum Physics · Physics 2009-11-13 Vittorio Giovannetti , Simone Montangero , Rosario Fazio

Deep learning is a broad set of techniques that uses multiple layers of representation to automatically learn relevant features directly from structured data. Recently, such techniques have yielded record-breaking results on a diverse set…

Machine Learning · Statistics 2014-10-16 Pankaj Mehta , David J. Schwab