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相关论文: Vertical Density Matrix Algorithm: A Higher-Dimens…

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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…

强关联电子 · 物理学 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…

统计力学 · 物理学 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…

统计力学 · 物理学 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…

统计力学 · 物理学 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…

强关联电子 · 物理学 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…

凝聚态物理 · 物理学 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…

高能物理 - 格点 · 物理学 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…

强关联电子 · 物理学 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…

数值分析 · 数学 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…

量子物理 · 物理学 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…

天体物理仪器与方法 · 物理学 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…

统计方法学 · 统计学 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…

凝聚态物理 · 物理学 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…

统计力学 · 物理学 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…

计算机视觉与模式识别 · 计算机科学 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…

数值分析 · 数学 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…

强关联电子 · 物理学 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…

量子物理 · 物理学 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…

统计力学 · 物理学 2026-03-06 Matej Mosko , Andrej Gendiar
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