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相关论文: Loop-TNR analysis of CP(1) model with theta term

200 篇论文

Dimension reduction techniques are often used when the high-dimensional tensor has relatively low intrinsic rank compared to the ambient dimension of the tensor. The CANDECOMP/PARAFAC (CP) tensor completion is a widely used approach to find…

数值分析 · 数学 2021-04-01 Jiahua Jiang , Fatoumata Sanogo , Carmeliza Navasca

We theoretically and experimentally investigate tensor-based regression and classification. Our focus is regularization with various tensor norms, including the overlapped trace norm, the latent trace norm, and the scaled latent trace norm.…

机器学习 · 计算机科学 2015-09-08 Kishan Wimalawarne , Ryota Tomioka , Masashi Sugiyama

We apply a recently developed numerical renormalization group, the corner-transfer-matrix renormalization group (CTMRG), to 2D classical lattice models at their critical temperatures. It is shown that the combination of CTMRG and the…

凝聚态物理 · 物理学 2009-10-28 T. Nishino , K. Okunishi , M. Kikuchi

Loop torsors over Laurent polynomial rings in characteristic 0 were originally introduced in relation to infinite dimensional Lie theory. Applications to other areas require a theory that can yields results in positive characteristic, and…

代数几何 · 数学 2024-12-11 Philippe Gille , Vladimir Chernousov , Arturo Pianzola

In this paper, we study the problem of low-rank tensor learning, where only a few of training samples are observed and the underlying tensor has a low-rank structure. The existing methods are based on the sum of nuclear norms of unfolding…

机器学习 · 计算机科学 2024-10-25 Sijia Xia , Michael K. Ng , Xiongjun Zhang

In this work we use cMERA, a continuous tensor network, to find a Gaussian approximation to the ground state of a $T\bar{T}$-deformed scalar CFT on the line, to first order in the deformation parameter. The result is used to find the…

高能物理 - 理论 · 物理学 2022-07-18 Biel Cardona , Javier Molina-Vilaplana

We compute, both explicitly up to next-to-leading order and in a proof by induction for all loop levels, the critical exponents for thermal Lorentz-violating O($N$) self-interacting scalar field theory. They are evaluated in a massless…

高能物理 - 理论 · 物理学 2019-10-03 William C. Vieira , Paulo R. S. Carvalho

This paper studies tensor-based Robust Principal Component Analysis (RPCA) using atomic-norm regularization. Given the superposition of a sparse and a low-rank tensor, we present conditions under which it is possible to exactly recover the…

最优化与控制 · 数学 2019-01-31 Derek Driggs , Stephen Becker , Jordan Boyd-Graber

In this paper, we propose a novel model to recover a low-rank tensor by simultaneously performing double nuclear norm regularized low-rank matrix factorizations to the all-mode matricizations of the underlying tensor. An block successive…

计算机视觉与模式识别 · 计算机科学 2020-05-07 Haijin Zeng , Xiaozhen Xie , Jifeng Ning

One of the popular approaches for low-rank tensor completion is to use the latent trace norm regularization. However, most existing works in this direction learn a sparse combination of tensors. In this work, we fill this gap by proposing a…

机器学习 · 计算机科学 2018-11-13 Madhav Nimishakavi , Pratik Jawanpuria , Bamdev Mishra

One may argue that QCD solves the strong CP problem by itself, without having to introduce new symmetries and particles. To test this idea, a lattice simulation is performed. The problem is investigated in the CP$^3$ model first. It is…

高能物理 - 格点 · 物理学 2007-05-23 G. Schierholz

In this work, we study the tensor ring decomposition and its associated numerical algorithms. We establish a sharp transition of algorithmic difficulty of the optimization problem as the bond dimension increases: On one hand, we show the…

数值分析 · 数学 2020-06-17 Ziang Chen , Yingzhou Li , Jianfeng Lu

We develop a new methodology to contract tensor networks within the corner transfer matrix renormalization group approach for a wide range of two-dimensional lattice geometries. We discuss contraction algorithms on the example of…

统计力学 · 物理学 2024-04-19 I. V. Lukin , A. G. Sotnikov

Tensor currents are the only quark bilinear operators lacking a non-perturbative determination of their renormalisation group (RG) running between hadronic and electroweak scales. We develop the setup to carry out the computation in lattice…

高能物理 - 格点 · 物理学 2018-08-15 Carlos Pena , David Preti

The fully-connected tensor network (FCTN) decomposition has gained prominence in the field of tensor completion owing to its powerful capacity to capture the low-rank characteristics of tensors. Nevertheless, the recovery of local details…

数值分析 · 数学 2025-10-28 Wenchao Xie , Qingsong Wang , Chengcheng Yan , Zheng Peng

Non-perturbative renormalization of lattice composite operators plays a crucial role in many applications of lattice field theory. We sketch the general problems involved in this task and the methods which are currently used to cope with…

高能物理 - 格点 · 物理学 2007-05-23 Andrea Montanari

We perform a tensor network simulation of the (1+1)-dimensional $O(3)$ nonlinear $\sigma$-model with $\theta=\pi$ term. Within the Hamiltonian formulation, this field theory emerges as the finite-temperature partition function of a modified…

高能物理 - 格点 · 物理学 2021-12-28 Wei Tang , X. C. Xie , Lei Wang , Hong-Hao Tu

The fields of entanglement theory and tensor networks have recently emerged as central tools for characterising quantum phases of matter. In this article, we determine the entanglement structure of ground states of gapped symmetric quantum…

量子物理 · 物理学 2025-10-16 Laurens Lootens , Clement Delcamp , Frank Verstraete

Real-space renormalization-group techniques for quantum systems can be divided into two basic categories - those capable of representing correlations following a simple boundary (or area) law, and those which are not. I discuss the scaling…

强关联电子 · 物理学 2013-04-03 Andrew J. Ferris

D-theory provides an alternative lattice regularization of the (1+1)-d CP(N-1) quantum field theory. In this formulation the continuous classical CP(N-1) fields emerge from the dimensional reduction of discrete SU(N) quantum spins. In…

高能物理 - 格点 · 物理学 2009-11-10 B. B. Beard , M. Pepe , S. Riederer , U. J. Wiese