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We present the $T$-flow renormalization group method, which computes the memory kernel for the density-operator evolution of an open quantum system by lowering the physical temperature $T$ of its environment. This has the key advantage that…

Quantum Physics · Physics 2022-04-20 K. Nestmann , M. R. Wegewijs

In this paper, a way of generalizing the tensor renormalization group(TRG) is proposed. Mathematically, the connection between patterns of tensor renormalization group and the concept of truncation sequence in polytope geometry is…

Statistical Mechanics · Physics 2017-06-12 Peiyuan Teng

We describe a simple real space renormalization group technique for two dimensional classical lattice models. The approach is similar in spirit to block spin methods, but at the same time it is fundamentally based on the theory of quantum…

Statistical Mechanics · Physics 2009-11-11 Michael Levin , Cody P. Nave

We apply real-space RG methods to study two quantum group invariant Hamiltonians, that of the XXZ model and the Ising model in a transverse field defined in an open chain with appropiate boundary terms. The quantum group symmetry is…

Condensed Matter · Physics 2008-11-26 Miguel A. Martin-Delgado , German Sierra

The renormalization group flow of an integrable two dimensional quantum field theory which contains unstable particles is investigated. The analysis is carried out for the Virasoro central charge and the conformal dimensions as a function…

High Energy Physics - Theory · Physics 2009-12-31 O. A. Castro-Alvaredo , A. Fring

Tensor networks (TNs) have become one of the most essential building blocks for various fields of theoretical physics such as condensed matter theory, statistical mechanics, quantum information, and quantum gravity. This review provides a…

Statistical Mechanics · Physics 2022-05-10 Kouichi Okunishi , Tomotoshi Nishino , Hiroshi Ueda

We have developed a very efficient numerical algorithm of the strong disorder renormalization group method to study the critical behaviour of the random transverse-field Ising model, which is a prototype of random quantum magnets. With this…

Disordered Systems and Neural Networks · Physics 2011-09-21 István A. Kovács , Ferenc Iglói

We present a variational renormalization group (RG) approach using a deep generative model based on normalizing flows. The model performs hierarchical change-of-variables transformations from the physical space to a latent space with…

Statistical Mechanics · Physics 2018-12-31 Shuo-Hui Li , Lei Wang

We present a renormalization group (RG) procedure which works naturally on a wide class of interacting one-dimension models based on perturbed (possibly strongly) continuum conformal and integrable models. This procedure integrates Kenneth…

Strongly Correlated Electrons · Physics 2016-07-05 Robert M. Konik , Yury Adamov

We review a formulation of a renormalization-group scheme for Hamiltonian systems with two degrees of freedom. We discuss the renormalization flow on the basis of the continued fraction expansion of the frequency. The goal of this approach…

chao-dyn · Physics 2007-05-23 C. Chandre , H. R. Jauslin

We develop a new methodology to contract tensor networks within the corner transfer matrix renormalization group approach for a wide range of two-dimensional lattice geometries. We discuss contraction algorithms on the example of…

Statistical Mechanics · Physics 2024-04-19 I. V. Lukin , A. G. Sotnikov

The renormalization group method has been adapted to the analysis of the long-time behavior of non-linear partial differential equation and has demonstrated its power in the study of critical phenomena of gravitational collapse. In the…

General Relativity and Quantum Cosmology · Physics 2008-11-26 Osamu Iguchi , Akio Hosoya , Tatsuhiko Koike

Recently, it has been claimed that some complex networks are self-similar under a convenient renormalization procedure. We present a general method to study renormalization flows in graphs. We find that the behavior of some variables under…

Physics and Society · Physics 2009-11-13 Filippo Radicchi , José Javier Ramasco , Alain Barrat , Santo Fortunato

We describe a renormalization group transformation that is related to the breakup of golden invariant tori in Hamiltonian systems with two degrees of freedom. This transformation applies to a large class of Hamiltonians, is conceptually…

chao-dyn · Physics 2009-10-31 Juan J. Abad , Hans Koch , Peter Wittwer

The spin-1/2 quantum Ising chain in a transverse random magnetic field is studied by means of the density-matrix renormalization group. The system evolves from an ordered to a paramagnetic state as the amplitude of the random field is…

Disordered Systems and Neural Networks · Physics 2009-10-30 A. Juozapavicius , S. Caprara , A. Rosengren

This paper is focused on the functional renormalization group applied to the $T_5^6$ tensor model on the Abelian group $U(1)$ with closure constraint. For the first time, we derive the flow equations for the couplings and mass parameters in…

High Energy Physics - Theory · Physics 2017-07-14 Vincent Lahoche , Dine Ousmane Samary

On the lattice, a renormalization group (RG) flow for two-dimensional partition functions expressed as a tensor network can be obtained using the tensor network renormalization (TNR) algorithm [G. Evenbly, G. Vidal, Phys. Rev. Lett. 115…

High Energy Physics - Theory · Physics 2018-09-17 Qi Hu , Adrian Franco-Rubio , Guifre Vidal

It is argued that renormalisation group flow can be interpreted as being a Hamiltonian vector flow on a phase space which consists of the couplings of the theory and their conjugate \lq\lq momenta", which are the vacuum expectation values…

High Energy Physics - Theory · Physics 2011-08-17 Brian P. Dolan

We investigate the phase transition of the four-dimensional Ising model with two types of tensor network scheme, one is the higher-order tensor renormalization group and the other is the anisotropic tensor renormalization group. The results…

High Energy Physics - Lattice · Physics 2020-09-28 Shinichiro Akiyama , Yoshinobu Kuramashi , Takumi Yamashita , Yusuke Yoshimura

We discuss the successes and limitations of statistical sampling for a sequence of models studied in the context of lattice QCD and emphasize the need for new methods to deal with finite-density and real-time evolution. We show that these…

High Energy Physics - Lattice · Physics 2022-09-21 Yannick Meurice , Ryo Sakai , Judah Unmuth-Yockey