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Related papers: Renormalization group on tensor networks

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These lectures illustrate the key ideas of modern renormalization theory and effective field theories in the context of simple nonrelativistic quantum mechanics and the Schr\"odinger equation. They also discuss problems in QED, QCD and…

Nuclear Theory · Physics 2007-05-23 Peter Lepage

After a brief presentation of the exact renormalization group equation, we illustrate how the field theoretical (perturbative) approach to critical phenomena takes place in the more general Wilson (nonperturbative) approach. Notions such as…

High Energy Physics - Theory · Physics 2011-07-19 C. Bagnuls , C. Bervillier

Renormalization group methods are used to study the low-energy behavior of the unscreened Coulomb interaction in a one-dimensional electron system. By applying a GW approximation, a strong wavefunction renormalization is found in the model,…

Strongly Correlated Electrons · Physics 2007-05-23 S. Bellucci , J. Gonzalez

The renormalization group is the cornerstone of the modern theory of universality and phase transitions, a powerful tool to scrutinize symmetries and organizational scales in dynamical systems. However, its network counterpart is…

Statistical Mechanics · Physics 2023-01-11 Pablo Villegas , Tommaso Gili , Guido Caldarelli , Andrea Gabrielli

In this study, we propose a novel regularization/renormalization scheme that utilizes an auxiliary Feynman parameterization. This approach is employed to align a specified loop diagram with a designated unit of the form $1=\lambda/\lambda$.…

High Energy Physics - Phenomenology · Physics 2025-04-23 Vladimir Sauli

The development of tensor renormalization group (TRG) algorithm in higher dimensions is an important and urgent task, as the TRG is expected to provide a way to overcome the sign problem in lattice quantum chromodynamics (QCD) calculations…

High Energy Physics - Lattice · Physics 2025-11-27 Yuto Sugimoto , Shoichi Sasaki

We evaluate spectral zeta-functions of certain network Laplacians that can be treated exactly with the renormalization group. As specific examples we consider a class of Hanoi networks and those hierarchical networks obtained by the…

Mathematical Physics · Physics 2017-02-27 Stefan Boettcher , Shanshan Li

This review elaborates on the foundation, the advantages, and the prospects of tensor network representations for quantum states in vibrational spectroscopy. The focus is on the recently introduced matrix product state decomposition of…

Chemical Physics · Physics 2022-08-03 Nina Glaser , Alberto Baiardi , Markus Reiher

A nonperturbative approach is developed to analyze superconducting circuits coupled to quantized electromagnetic continuum within the framework of the functional renormalization group. The formalism allows us to determine complete physical…

Quantum Physics · Physics 2023-05-03 Takeru Yokota , Kanta Masuki , Yuto Ashida

Tensor currents are the only quark bilinear operators lacking a non-perturbative determination of their renormalisation group (RG) running between hadronic and electroweak scales. We develop the setup to carry out the computation in lattice…

High Energy Physics - Lattice · Physics 2018-08-15 Carlos Pena , David Preti

We discuss motivation and goals of renormalization analyses of group field theory models of simplicial 4d quantum gravity, and review briefly the status of this research area. We present some new computations of perturbative GFT (spin foam)…

High Energy Physics - Theory · Physics 2021-05-07 Marco Finocchiaro , Daniele Oriti

A recently introduced real space renormalization group technique, developed for the analysis of processes in the Kardar-Parisi-Zhang universality class, is generalized and tested by applying it to a different family of surface growth…

Condensed Matter · Physics 2016-08-31 G. Bianconi , M. A. Munoz , A. Gabrielli , L. Pietronero

The asymptotic high momentum behaviour of quantum field theories with cubic interactions is investigated using renormalization group techniques in the asymmetric limit x << 1. Particular emphasis is paid to theories with interactions…

High Energy Physics - Theory · Physics 2009-10-31 C. R. Stephens , A. Weber , J. C. Lopez Vieyra , P. O. Hess

The renormalization group is a tool that allows one to obtain a reduced description of systems with many degrees of freedom while preserving the relevant features. In the case of quantum systems, in particular, one-dimensional systems…

Quantum Physics · Physics 2009-11-13 Jose Gaite

Decompositions of tensors into factor matrices, which interact through a core tensor, have found numerous applications in signal processing and machine learning. A more general tensor model which represents data as an ordered network of…

Numerical Analysis · Computer Science 2016-09-30 Anh-Huy Phan , Andrzej Cichocki , Andre Uschmajew , Petr Tichavsky , George Luta , Danilo Mandic

Renormalization group methods are an essential ingredient in the study of nonperturbative problems of quantum field theory. This paper deal with the symmetry constraints on the renormalization group flow for quartic melonic tensorial group…

High Energy Physics - Theory · Physics 2019-08-14 Vincent Lahoche , Dine Ousmane Samary

Random graphs offer a useful mathematical representation of a variety of real world complex networks. Exponential random graphs, for example, are particularly suited towards generating random graphs constrained to have specified statistical…

Statistical Mechanics · Physics 2026-02-09 Alessio Catanzaro , Diego Garlaschelli , Subodh P. Patil

The persistent current in a lattice model of a one-dimensional interacting electron system is systematically studied using a complex version of the density matrix renormalization group algorithm and the functional renormalization group…

Strongly Correlated Electrons · Physics 2009-11-07 V. Meden , U. Schollwoeck

The possible usefulness of the renormalization group method in Nuclear Physics is pointed out in this talk in the context of the nuclear multifragmentation. The presentation is rather superficial and sketchy, to indicate the main lines…

Nuclear Theory · Physics 2007-05-23 J. Polonyi

We propose a new statistical model suitable for machine learning of systems with long distance correlations such as natural languages. The model is based on directed acyclic graph decorated by multi-linear tensor maps in the vertices and…

Computation and Language · Computer Science 2017-10-31 Vasily Pestun , Yiannis Vlassopoulos