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The spectra which occur in numerical density-matrix renormalization group (DMRG) calculations for quantum chains can be obtained analytically for integrable models via corner transfer matrices. This is shown in detail for the transverse…

Statistical Mechanics · Physics 2017-09-27 I. Peschel , M. Kaulke , Ö. Legeza

Polynomial time reductions between problems have long been used to delineate problem classes. Simulation reductions also exist, where an oracle for simulation from some probability distribution can be employed together with an oracle for…

Probability · Mathematics 2009-08-18 Mark L. Huber

The equilibrium transport properties of an elementary nanostructured device with side-coupled geometry are computed and related to universal functions. The computation relies on a real-space formulation of the numerical…

Strongly Correlated Electrons · Physics 2021-09-28 Ana Luiza Ferrari , Luiz N. Oliveira

We investigate the renormalization of ``nonlocal'' interactions in an effective field theory using dimensional regularization with minimal subtraction. In a scalar field theory, we write an integro-differential renormalization group…

High Energy Physics - Phenomenology · Physics 2007-05-23 V. Bhansali , H. Georgi

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 show with several examples that renormalization group (RG) theory can be used to understand singular and reductive perturbation methods in a unified fashion. Amplitude equations describing slow motion dynamics in nonequilibrium phenomena…

Condensed Matter · Physics 2009-10-22 Lin-Yuan Chen , Nigel Goldenfeld , Y. Oono

Complex networks have acquired a great popularity in recent years, since the graph representation of many natural, social and technological systems is often very helpful to characterize and model their phenomenology. Additionally, the…

Physics and Society · Physics 2009-02-06 Filippo Radicchi , Alain Barrat , Santo Fortunato , Jose J. Ramasco

The linear perturbation group transformation (LPRG) is used to study the thermodynamics of the axial next-nearest-neighbor Ising model with four spin interactions (extended ANNNI) in a field. The LPRG for weakly interacting Ising chains is…

Statistical Mechanics · Physics 2013-03-25 J. Sznajd

The Density Matrix Renormalization Group (DMRG) method with periodic boundary conditions is introduced for two dimensional classical spin models. It is shown that this method is more suitable for derivation of the properties of infinite 2D…

Statistical Mechanics · Physics 2009-10-31 Andrej Gendiar , Anton Surda

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

Using a recently proposed new renormalization group method (tensor renormalization group), we analyze the Ising model on the 2-dimensional square lattice. For the lowest order approximation with two domain wall states, it realizes the idea…

Statistical Mechanics · Physics 2015-05-30 Ken-Ichi Aoki , Tamao Kobayashi , Hiroshi Tomita

We present here various techniques to work with clean and disordered quantum Ising chains, for the benefit of students and non-experts. Starting from the Jordan-Wigner transformation, which maps spin-1/2 systems into fermionic ones, we…

Quantum Physics · Physics 2024-06-21 Glen Bigan Mbeng , Angelo Russomanno , Giuseppe E. Santoro

The relationship between mappings of sets and renormalization group transformations is established, and renormalization group invariants of such mappings are found. These results are valid both for continuous and discrete mappings and for…

Mathematical Physics · Physics 2007-05-23 Gennady N. Nikolaev

We introduce a tensor renormalization group scheme for coarse-graining a two-dimensional tensor network that can be successfully applied to both classical and quantum systems on and off criticality. The key innovation in our scheme is to…

Strongly Correlated Electrons · Physics 2017-03-17 Shuo Yang , Zheng-Cheng Gu , Xiao-Gang Wen

Perturbation theory is a crucial tool for many physical systems, when exact solutions are not available, or nonperturbative numerical solutions are intractable. Naive perturbation theory often fails on long timescales, leading to secularly…

High Energy Physics - Theory · Physics 2021-10-01 José T. Gálvez Ghersi , Leo C. Stein

I show how a renormalization group (RG) method can be used to incrementally integrate the information in cosmological large-scale structure data sets (including CMB, galaxy redshift surveys, etc.). I show numerical tests for Gaussian…

Cosmology and Nongalactic Astrophysics · Physics 2019-03-06 Patrick McDonald

Extending the parameter space of the three-dimensional (d=3) Ising model, we search for a regime of eliminated corrections to finite-size scaling. For that purpose, we consider a real-space renormalization group (RSRG) with respect to a…

Statistical Mechanics · Physics 2009-11-11 Yoshihiro Nishiyama

Tensor renormalization group method (TRG) is a real space renormalization group approach. It has been successfully applied to both classical and quantum systems. In this paper, we study a disordered and frustrated system, the…

Disordered Systems and Neural Networks · Physics 2014-10-27 Chuang Wang , Shao-Meng Qin , Hai-Jun Zhou

We present a pedagogical discussion of Similarity Renormalization Group (SRG) methods, in particular the In-Medium SRG (IMSRG) approach for solving the nuclear many-body problem. These methods use continuous unitary transformations to…

Nuclear Theory · Physics 2017-06-28 H. Hergert , S. K. Bogner , J. G. Lietz , T. D. Morris , S. J. Novario , N. M. Parzuchowski , F. Yuan

We propose a method to construct a tensor network representation of partition functions without singular value decompositions nor series expansions. The approach is demonstrated for one- and two-dimensional Ising models and we study the…

High Energy Physics - Lattice · Physics 2026-03-19 Katsumasa Nakayama , Manuel Schneider