English
Related papers

Related papers: Vertical Density Matrix Algorithm: A Higher-Dimens…

200 papers

The density-matrix renormalization group (DMRG) applied to transfer matrices allows it to calculate static as well as dynamical properties of one-dimensional quantum systems at finite temperature in the thermodynamic limit. To this end the…

Strongly Correlated Electrons · Physics 2007-12-20 S. Glocke , A. Klümper , J. Sirker

We propose a numerical variational method for three-dimensional (3D) classical lattice models. We construct the variational state as a product of local tensors, and improve it by use of the corner transfer matrix renormalization group…

Statistical Mechanics · Physics 2010-05-20 T. Nishino , K. Okunishi , Y. Hieida , N. Maeshima , Y. Akutsu

Variational tensor network optimization has become a powerful tool for studying classical statistical models in two dimensions. However, its application to three-dimensional systems remains limited, primarily due to the high computational…

Statistical Mechanics · Physics 2025-10-14 Xia-Ze Xu , Tong-Yu Lin , Guang-Ming Zhang

We generalize the corner transfer matrix renormalization group, which consists of White's density matrix algorithm and Baxter's method of the corner transfer matrix, to three dimensional (3D) classical models. The renormalization group…

Statistical Mechanics · Physics 2007-05-23 Tomotoshi Nishino , Kouichi Okunishi

We propose a numerical self-consistent method for 3D classical lattice models, which optimizes the variational state written as two-dimensional product of tensors. The variational partition function is calculated by the corner transfer…

Vertical density matrix algorithm (VDMA), a tensor product state formulation of the ``higher-dimensional'' density matrix renormalization group, is applied to the spin 1/2 antiferromagnetic XXZ model on the checkerboard lattice. The VDMA…

Strongly Correlated Electrons · Physics 2009-11-10 Nobuya Maeshima

The Density Matrix Renormalization Group (DMRG) has become a powerful numerical method that can be applied to low-dimensional strongly correlated fermionic and bosonic systems. It allows for a very precise calculation of static, dynamic and…

Condensed Matter · Physics 2007-05-23 Karen Hallberg

We investigate the multi-particle states of the (1+1)-dimensional Ising model using a spectroscopy scheme based on the tensor renormalization group method. We start by computing the finite-volume energy spectrum of the model from the…

High Energy Physics - Lattice · Physics 2026-02-17 Fathiyya Izzatun Az-zahra , Shinji Takeda , Takeshi Yamazaki

The density matrix renormalization group is one of the most powerful numerical methods for computing ground-state properties of two-dimensional (2D) quantum lattice systems. Here we show its finite-temperature extensions are also viable for…

Strongly Correlated Electrons · Physics 2017-08-24 Benedikt Bruognolo , Zhenyue Zhu , Steven R. White , E. Miles Stoudenmire

Dynamic mode decomposition (DMD) is a recently developed tool for the analysis of the behavior of complex dynamical systems. In this paper, we will propose an extension of DMD that exploits low-rank tensor decompositions of potentially…

Numerical Analysis · Mathematics 2019-08-14 Stefan Klus , Patrick Gelß , Sebastian Peitz , Christof Schütte

We combine the Density Matrix Renormalization Group (DMRG) with Matrix Product State tangent space concepts to construct a variational algorithm for finding ground states of one dimensional quantum lattices in the thermodynamic limit. A…

Quantum Physics · Physics 2019-04-22 V. Zauner-Stauber , L. Vanderstraeten , M. T. Fishman , F. Verstraete , J. Haegeman

The interstellar medium (ISM) exhibits complex, multi-scale structures that are challenging to study due to their projection into two-dimensional (2D) column density maps. We present the Volume Density Mapper, a novel algorithm based on…

Instrumentation and Methods for Astrophysics · Physics 2025-09-23 Guang-Xing Li , Mengke Zhao

The classical vector autoregressive model is a fundamental tool for multivariate time series analysis. However, it involves too many parameters when the number of time series and lag order are even moderately large. This paper proposes to…

Methodology · Statistics 2020-11-04 Di Wang , Yao Zheng , Heng Lian , Guodong Li

The Density Matrix Renormalization Group (DMRG) has become a powerful numerical method that can be applied to low-dimensional strongly correlated fermionic and bosonic systems. It allows for a very precise calculation of static, dynamical…

Condensed Matter · Physics 2007-05-23 Karen Hallberg

We have proposed an efficient algorithm to calculate physical quantities in the translational invariant three-dimensional tensor networks, which is particularly relevant to the study of the three-dimensional classical statistical models and…

Statistical Mechanics · Physics 2023-04-17 Li-Ping Yang , Y. F. Fu , Z. Y. Xie , T. Xiang

Score Distillation Sampling (SDS) has emerged as a prevalent technique for text-to-3D generation, enabling 3D content creation by distilling view-dependent information from text-to-2D guidance. However, they frequently exhibit shortcomings…

Computer Vision and Pattern Recognition · Computer Science 2024-09-20 Zeyu Cai , Duotun Wang , Yixun Liang , Zhijing Shao , Ying-Cong Chen , Xiaohang Zhan , Zeyu Wang

The density-equalizing map, a technique developed for cartogram creation, has been widely applied to data visualization but only for 2D applications. In this work, we propose a novel method called the volumetric density-equalizing reference…

Numerical Analysis · Mathematics 2021-04-06 Gary P. T. Choi , Chris H. Rycroft

The density-matrix renormalization group (DMRG) is a numerical algorithm for the efficient truncation of the Hilbert space of low-dimensional strongly correlated quantum systems based on a rather general decimation prescription. This…

Strongly Correlated Electrons · Physics 2009-11-10 Ulrich Schollwoeck

Tensor network states provide an efficient class of states that faithfully capture strongly correlated quantum models and systems in classical statistical mechanics. While tensor networks can now be seen as becoming standard tools in the…

Quantum Physics · Physics 2022-09-27 A. Nietner , B. Vanhecke , F. Verstraete , J. Eisert , L. Vanderstraeten

We propose a tensor-network-based algorithm to study the classical Ising model on an infinitely large hyperbolic lattice with a regular 3D tesselation of identical dodecahedra. We reformulate the corner transfer matrix renormalization group…

Statistical Mechanics · Physics 2026-03-06 Matej Mosko , Andrej Gendiar
‹ Prev 1 2 3 10 Next ›