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We develop a method to obtain the large N renormalization group flows for matrix models of 2 dimensional gravity plus branched polymers. This method gives precise results for the critical points and exponents for one matrix models. We show…

High Energy Physics - Theory · Physics 2009-10-31 Gabrielle Bonnet , Francois David

Tensor renormalization group, originally devised as a numerical technique, is emerging as a rigorous analytical framework for studying lattice models in statistical physics. Here we introduce a new renormalization map - the 2x1 map - which…

Statistical Mechanics · Physics 2025-06-05 Nikolay Ebel , Tom Kennedy , Slava Rychkov

We have discussed the tensor-network representation of classical statistical or interacting quantum lattice models, and given a comprehensive introduction to the numerical methods we recently proposed for studying the tensor-network…

Strongly Correlated Electrons · Physics 2013-05-29 H. H. Zhao , Z. Y. Xie , Q. N. Chen , Z. C. Wei , J. W. Cai , T. Xiang

We introduce canonical weight normalization for convolutional neural networks. Inspired by the canonical tensor decomposition, we express the weight tensors in so-called canonical networks as scaled sums of outer vector products. In…

Machine Learning · Computer Science 2022-06-06 Lokesh Veeramacheneni , Moritz Wolter , Reinhard Klein , Jochen Garcke

The recently developed tensor renormalization-group (TRG) method provides a highly precise technique for deriving thermodynamic and critical properties of lattice Hamiltonians. The TRG is a local coarse-graining transformation, with the…

Statistical Mechanics · Physics 2008-02-18 Michael Hinczewski , A. Nihat Berker

The quantum critical behavior and the Griffiths-McCoy singularities of random quantum Ising ferromagnets are studied by applying a numerical implementation of the Ma-Dasgupta-Hu renormalization group scheme. We check the procedure for the…

Disordered Systems and Neural Networks · Physics 2009-10-31 Y. -C. Lin , N. Kawashima , F. Igloi , H. Rieger

We introduce an efficient algorithm for reducing bond dimensions in an arbitrary tensor network without changing its geometry. The method is based on a novel, quantitative understanding of local correlations in a network. Together with a…

Strongly Correlated Electrons · Physics 2018-08-23 Markus Hauru , Clement Delcamp , Sebastian Mizera

We consider the double-scaling limit in matrix models for two-dimensional quantum gravity, and establish the nonperturbative functional Renormalization Group as a novel technique to compute the corresponding interacting fixed point of the…

General Relativity and Quantum Cosmology · Physics 2013-10-30 Astrid Eichhorn , Tim Koslowski

We develop coarse-graining tensor renormalization group algorithms to compute physical properties of two-dimensional lattice models on finite periodic lattices. Two different coarse-graining strategies, one based on the tensor…

Strongly Correlated Electrons · Physics 2016-07-12 Hui-Hai Zhao , Zhi-Yuan Xie , Tao Xiang , Masatoshi Imada

We summarize our renormalization group approach for the vector model as well as the matrix model which are the discretized quantum gravity in one- and two-dimensional spacetime. A difference equation is obtained which relates free energies…

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

We review recent developments in tensor network approaches, focusing on renormalization group methods. Since they are free from the negative sign and complex action problems, there is growing interest in their application to lattice field…

High Energy Physics - Lattice · Physics 2026-03-04 Shinichiro Akiyama

Iterative Gaussianization is a fixed-point iteration procedure that can transform any continuous random vector into a Gaussian one. Based on iterative Gaussianization, we propose a new type of normalizing flow model that enables both…

Machine Learning · Computer Science 2020-03-05 Chenlin Meng , Yang Song , Jiaming Song , Stefano Ermon

We study the stability and breakup of invariant tori in Hamiltonian flows using a combination of Kolmogorov-Arnold-Moser (KAM) theory and renormalization-group techniques. We implement the scheme numerically for a family of Hamiltonians…

chao-dyn · Physics 2009-10-31 M. Govin , C. Chandre , H. R. Jauslin

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

Functional renormalisation group approach is applied to a system of kaons with finite chemical potential. A set of approximate flow equations for the effective couplings is derived and solved. At high scale the system is found to be at the…

Nuclear Theory · Physics 2017-06-07 Boris Krippa

We present a unified framework for the renormalisation of the Hamiltonian and eigenbasis of a system of correlated electrons, unveiling thereby the interplay between electronic correlations and many-particle entanglement. For this, we…

Strongly Correlated Electrons · Physics 2021-10-25 Anirban Mukherjee , Siddhartha Lal

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

We develop a renormalization group for weak Harris-marginal disorder in otherwise strongly interacting quantum critical theories, focusing on systems which have emergent conformal invariance. Using conformal perturbation theory, we argue…

High Energy Physics - Theory · Physics 2022-03-30 Koushik Ganesan , Andrew Lucas , Leo Radzihovsky

We provide a brief overview of tensor models and group field theories, focusing on their main common features. Both frameworks arose in the context of quantum gravity research, and can be understood as higher-dimensional generalizations of…

Mathematical Physics · Physics 2024-04-12 Sylvain Carrozza

We study the renormalization group flow of higher derivative gravity, utilizing the functional renormalization group equation for the average action. Employing a recently proposed algorithm, termed the universal renormalization group…

High Energy Physics - Theory · Physics 2012-02-29 F. Saueressig , K. Groh , S. Rechenberger , O. Zanusso