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We propose a novel coarse graining tensor renormalization group method based on the higher-order singular value decomposition. This method provides an accurate but low computational cost technique for studying both classical and quantum…

Statistical Mechanics · Physics 2015-03-19 Z. Y. Xie , J. Chen , M. P. Qin , J. W. Zhu , L. P. Yang , T. Xiang

The Time Renormalization Group (TRG) is an effective method for accurate calculations of the matter power spectrum at the scale of the first baryonic acoustic oscillations. By using a particular variable transformation in the TRG formalism,…

Cosmology and Nongalactic Astrophysics · Physics 2016-02-24 Adrian Vollmer , Luca Amendola , Riccardo Catena

The truncation scheme dependence of the exact renormalization group equations is investigated for scalar field theories in three dimensions. The exponents are numerically estimated to the next-to-leading order of the derivative expansion.…

High Energy Physics - Theory · Physics 2009-10-31 Ken-Ichi Aoki , Keiichi Morikawa , Wataru Souma , Jun-Ichi Sumi , Haruhiko Terao

We study the $SU(2)$ gauge-Higgs model in two Euclidean dimensions using the tensor renormalization group (TRG) approach. We derive a tensor formulation for this model in the unitary gauge and compare the expectation values of different…

High Energy Physics - Lattice · Physics 2019-06-27 Alexei Bazavov , Simon Catterall , Raghav G. Jha , Judah Unmuth-Yockey

We present a hybrid lattice Hamiltonian truncation method that integrates the numerical renormalization group (NRG) with a truncated lattice integrable spectrum. The technique is tailored for generic deformations of integrable lattice…

Strongly Correlated Electrons · Physics 2025-11-18 Xiaodong He , Xiao Wang , Jianda Wu

We propose a second renormalization group method to handle the tensor-network states or models. This method reduces dramatically the truncation error of the tensor renormalization group. It allows physical quantities of classical…

Strongly Correlated Electrons · Physics 2024-06-26 Z. Y. Xie , H. C. Jiang , Q. N. Chen , Z. Y. Weng , T. Xiang

Tensor-network renormalization group (TNRG) is an efficient real-space renormalization group method for studying the criticality in both classical and quantum lattice systems. Exploiting symmetries of a system in a TNRG algorithm can…

Statistical Mechanics · Physics 2026-04-17 Xinliang Lyu , Naoki Kawashima

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 propose a multi-impurity method for the bond-weighted tensor renormalization group (BWTRG) to compute the higher-order moment of physical quantities in a two-dimensional system. The replacement of the bond weight with an impurity matrix…

Statistical Mechanics · Physics 2025-02-26 Satoshi Morita , Naoki Kawashima

We propose a family of renormalization group transformations characterized by free parameters that may be tuned in order to reduce the truncation effects. As a check we test them in the three dimensional XY model. The Schwinger--Dyson…

High Energy Physics - Lattice · Physics 2009-10-28 L. A. Fernandez , A. Munoz Sudupe , J. J. Ruiz-Lorenzo , A. Tarancon

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 apply the real space Renormalisation Group (RNG) technique to a variety of one-dimensional Ising chains. We begin by recapitulating the work of Nauenberg for an ordered Ising chain, namely the decimation approach. We extend this work to…

Statistical Mechanics · Physics 2024-08-05 Shraddha singh , Vijay Singh

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

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

We propose a forward-mode automatic differentiation (AD) framework for tensor renormalization group (TRG) methods. In this approach, evaluating the derivatives of the partition function up to order $k$ increases the matrix-multiplication…

High Energy Physics - Lattice · Physics 2026-02-12 Yuto Sugimoto

We present our progress on a study of the $O(3)$ model in two-dimensions using the Tensor Renormalization Group method. We first construct the theory in terms of tensors, and show how to construct $n$-point correlation functions. We then…

High Energy Physics - Lattice · Physics 2014-11-18 Judah Unmuth-Yockey , Yannick Meurice , James Osborn , Haiyuan Zou

The tensor-network renormalization group (TNRG) is an accurate numerical real-space renormalization group method for studying phase transitions in both quantum and classical systems. Continuous phase transitions, as an important class of…

Statistical Mechanics · Physics 2026-03-27 Xinliang Lyu

We present real--space renormalization group (RG) calculations of the critical properties of the random--field Ising model on a cubic lattice in three dimensions. We calculate the RG flows in a two--parameter truncation of the Hamiltonian…

Condensed Matter · Physics 2009-10-22 M. E. J. Newman , B. W. Roberts , G. T. Barkema , J. P. Sethna

We develop the tensor renormalization group (TRG) algorithm for statistical systems with open boundaries, which allows us to investigate not only the bulk but also the boundary property, such as the surface magnetization. We demonstrate…

Statistical Mechanics · Physics 2019-08-02 Shumpei Iino , Satoshi Morita , Naoki Kawashima

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