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Quantum impurity problems can be solved using the numerical renormalization group (NRG), which involves discretizing the free conduction electron system and mapping to a `Wilson chain'. It was shown recently that Wilson chains for different…

Strongly Correlated Electrons · Physics 2016-06-08 K. M. Stadler , A. K. Mitchell , J. von Delft , A. Weichselbaum

We make Kadanoff's block idea into a reliable three-dimensional (3D) real space renormalization group (RG) method. Kadanoff's idea, expressed in spin representation, offers a qualitative intuition for clarifying scaling behavior in…

Statistical Mechanics · Physics 2025-05-30 Xinliang Lyu , Naoki Kawashima

We develop a renormalization group method to investigate synchronization clusters in a one-dimensional chain of nearest-neighbor coupled phase oscillators. The method is best suited for chains with strong disorder in the intrinsic…

Pattern Formation and Solitons · Physics 2016-11-28 Oleg Kogan , Jeffrey L. Rogers , M. C. Cross , G. Refael

Sharp two- and three-dimensional phase transitional magnetization curves are obtained by an iterative renormalization-group coupling of Ising chains, which are solved exactly. The chains by themselves do not have a phase transition or…

Statistical Mechanics · Physics 2021-06-02 Ibrahim Kecoglu , A. Nihat Berker

We develop a novel real-space renormalization group (RG) scheme which accurately estimates correlation length exponent $\nu$ near criticality of higher-dimensional quantum Ising and Potts models in a transverse field. Our method is…

Statistical Mechanics · Physics 2014-02-05 Aleksander Kubica , Beni Yoshida

We aim at an explicit characterization of the renormalized Hamiltonian after decimation transformation of a one-dimensional Ising-type Hamiltonian with a nearest-neighbor interaction and a magnetic field term. To facilitate a deeper…

Statistical Mechanics · Physics 2015-06-05 Mei Yin

We propose a real-space renormalization group algorithm for accurately coarse-graining two-dimensional tensor networks. The central innovation of our method lies in utilizing variational boundary tensors as a globally optimized environment…

Statistical Mechanics · Physics 2026-03-03 Feng-Feng Song , Naoki Kawashima

The renormalization group (RG) is a class of theoretical techniques used to explain the collective physics of interacting, many-body systems. It has been suggested that the RG formalism may be useful in finding and interpreting emergent…

Statistical Mechanics · Physics 2022-03-23 Adam G. Kline , Stephanie E. Palmer

A real space Renormalization Group approach is presented for a non-mean field spin-glass. This approach has been conceived in the effort to develop an alternative method to the Renormalization Group approaches based on the replica method.…

Disordered Systems and Neural Networks · Physics 2014-09-09 Michele Castellana

We analyze the renormalization-group (RG) flows of two effective Lagrangians, one for measurement induced transitions of monitored quantum systems and one for entanglement transitions in random tensor networks. These Lagrangians, previously…

Statistical Mechanics · Physics 2024-09-20 Adam Nahum , Kay Joerg Wiese

The random-field Ising model is one of the few disordered systems where the perturbative renormalization group can be carried out to all orders of perturbation theory. This analysis predicts dimensional reduction, i.e., that the critical…

Disordered Systems and Neural Networks · Physics 2017-04-12 Nikolaos G. Fytas , Victor Martin-Mayor , Marco Picco , Nicolas Sourlas

Expanding and improving the repertoire of numerical methods for studying quantum lattice models is an ongoing focus in many-body physics. While the density matrix renormalization group (DMRG) has been established as a practically useful…

Strongly Correlated Electrons · Physics 2021-09-28 Maxwell Block , Johannes Motruk , Snir Gazit , Michael P. Zaletel , Zeph Landau , Umesh Vazirani , Norman Y. Yao

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 introduce a general method for optimizing real-space renormalization-group transformations to study the critical properties of a classical system. The scheme is based on minimizing the Kullback-Leibler divergence between the distribution…

Statistical Mechanics · Physics 2019-12-20 Jui-Hui Chung , Ying-Jer Kao

In this paper, we focus on the interpretability of deep neural network. Our work is motivated by the renormalization group (RG) in statistical mechanics. RG plays the role of a bridge connecting microscopical properties and macroscopic…

Disordered Systems and Neural Networks · Physics 2022-12-02 Fuzhou Gong , Zigeng Xia

We propose a new concept upon the renormalization group (RG) procedure for an interacting many-electron correlated system in the framework of natural orbitals, and formulate an algorithm for this RG approach. To demonstrate its…

Strongly Correlated Electrons · Physics 2014-02-17 Rong-Qiang He , Zhong-Yi Lu

A tensor network renormalization algorithm with global optimization based on the corner transfer matrix is proposed. Since the environment is updated by the corner transfer matrix renormalization group method, the forward-backward iteration…

Statistical Mechanics · Physics 2021-01-26 Satoshi Morita , Naoki Kawashima

We use a real-space renormalization group (RSRG) to study the low temperature dynamics of kinetically constrained Ising chains (KCICs). We consider the cases of the Fredrickson-Andersen (FA) model, the East model, and the partially…

Statistical Mechanics · Physics 2009-11-10 Stephen Whitelam , Juan P. Garrahan

We present a method for computing resonant inelastic x-ray scattering (RIXS) spectra in one-dimensional systems using the density matrix renormalization group (DMRG) method. By using DMRG to address the problem, we shift the computational…

Strongly Correlated Electrons · Physics 2018-09-20 A. Nocera , U. Kumar , N. Kaushal , G. Alvarez , E. Dagotto , S. Johnston

We apply the projective truncation technique to the tensor renormalization group (TRG) algorithm in order to reduce the computational cost from $O(\chi^6)$ to $O(\chi^5)$, where $\chi$ is the bond dimension, and propose three kinds of…

Statistical Mechanics · Physics 2019-04-03 Yoshifumi Nakamura , Hideaki Oba , Shinji Takeda