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By combining the Grassmann algebra with multi-scale entanglement renormalization ansatz (MERA), we introduce a new unbiased and effective numerical method for simulating 2D strongly correlated electronic systems. The new GMERA method…

Strongly Correlated Electrons · Physics 2015-06-12 Jie Lou , Yan Chen

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

The quasi-2D electrostatic systems, characterized by periodicity in two dimensions with a free third dimension, have garnered significant interest in many fields. We apply the sum-of-Gaussians (SOG) approximation to the Laplace kernel,…

Numerical Analysis · Mathematics 2024-12-09 Xuanzhao Gao , Shidong Jiang , Jiuyang Liang , Zhenli Xu , Qi Zhou

We investigate the QCD chiral phase transition at finite temperature and finite baryon density using the functional Renormalization Group (fRG). While conventional fRG studies often employ techniques such as dynamical bosonization to…

High Energy Physics - Phenomenology · Physics 2025-12-22 Yuepeng Guan , Masatoshi Yamada

Tensor decompositions are promising tools for big data analytics as they bring multiple modes and aspects of data to a unified framework, which allows us to discover complex internal structures and correlations of data. Unfortunately most…

Numerical Analysis · Computer Science 2014-12-30 Guoxu Zhou , Andrzej Cichocki , Shengli Xie

A new implementation of the canonical polyadic decomposition (CPD) is presented. It features lower computational complexity and memory usage than the available state of art implementations available. The CPD of tensors is a challenging…

Numerical Analysis · Mathematics 2019-12-09 Felipe Bottega Diniz

I apply a two-step density-matrix renormalization group method to the anisotropic two-dimensional Hubbard model. As a prelude to this study, I compare the numerical results to the exact one for the tight-binding model. I find a ground-state…

Strongly Correlated Electrons · Physics 2009-11-13 S. Moukouri

The Taylor expansion of thermodynamic observables at a finite baryon chemical potential $\mu_B$ is an oft-used method to circumvent the well-known sign problem of Lattice QCD. Owing to the associated difficulty and limitations of precision…

High Energy Physics - Phenomenology · Physics 2023-02-14 Sabarnya Mitra , Prasad Hegde , Christian Schmidt

Due to the explosive growth of large-scale data sets, tensors have been a vital tool to analyze and process high-dimensional data. Different from the matrix case, tensor decomposition has been defined in various formats, which can be…

Optimization and Control · Mathematics 2023-12-27 Rachel Grotheer , Shuang Li , Anna Ma , Deanna Needell , Jing Qin

In this study, the higher-order tensor renormalization group (HOTRG) method is applied to a lattice glass model that has local constraints on the occupation number of neighboring particles represented by many-body interactions. This model…

Statistical Mechanics · Physics 2020-09-16 Kota Yoshiyama , Koji Hukushima

We extend our previous formulation of low-energy QCD in terms of an effective lagrangian containing operators of dimensionality $d\le 6$ constructed with pseudoscalars and quark fields, describing physics below the scale of chiral symmetry…

High Energy Physics - Phenomenology · Physics 2009-10-31 A. A. Andrianov , D. Espriu

We compute the imaginary part of the heavy quark contribution to the photon polarization tensor, i.e. the quarkonium spectral function in the vector channel, at next-to-leading order in thermal QCD. Matching our result, which is valid…

High Energy Physics - Phenomenology · Physics 2009-02-09 Y. Burnier , M. Laine , M. Vepsalainen

Low-rank tensor completion aims to recover a tensor from partially observed entries, and it is widely applicable in fields such as quantum computing and image processing. Due to the significant advantages of the tensor train (TT) format in…

Machine Learning · Computer Science 2025-01-24 Fengmiao Bian , Jian-Feng Cai , Xiaoqun Zhang , Yuanwei Zhang

A nonperturbative approach to 2D covariant gauge QCD is presented in the context of the Schwinger-Dyson equations for quark and ghost propagators and the corresponding Slavnov-Taylor identities. The distribution theory, complemented by the…

High Energy Physics - Phenomenology · Physics 2007-05-23 V. Gogohia , Gy. Kluge

This study presents novel strategies for improving the node-level performance of matrix-free evaluation of continuous and discontinuous Galerkin spatial discretizations on unstructured tetrahedral grids. In our approach the underlying…

Numerical Analysis · Mathematics 2025-09-15 Dominik Still , Niklas Fehn , Wolfgang A. Wall , Martin Kronbichler

Graph condensation reduces the size of large graphs while preserving performance, addressing the scalability challenges of Graph Neural Networks caused by computational inefficiencies on large datasets. Existing methods often rely on…

Machine Learning · Computer Science 2025-10-10 Lin Wang , Qing Li

Fluctuations are included in a chiral nucleon-meson model within the framework of the functional renormalization group. The model, with parameters fitted to reproduce the nuclear liquid-gas phase transition, is used to study the phase…

Nuclear Theory · Physics 2015-06-16 Matthias Drews , Thomas Hell , Bertram Klein , Wolfram Weise

We review recent developments in tensor network approaches, focusing on renormalization group methods. Since they are free from the negative sign and complex action problems, there is growing interest in their application to lattice field…

High Energy Physics - Lattice · Physics 2026-03-04 Shinichiro Akiyama

We perform threshold resummation of soft gluon corrections to the total cross sections and the invariant mass distributions for production of a top-antitop quark pair associated with a heavy electroweak boson $V = W^+$, $W^-$ or $Z$ in $pp$…

High Energy Physics - Phenomenology · Physics 2019-03-27 Anna Kulesza , Leszek Motyka , Daniel Schwartländer , Tomasz Stebel , Vincent Theeuwes

In order to develop fast inversion algorithms we have used overlap solvers in two dimensions. Lattice QED theory with U(1) group symmetry in two dimensional space-times dimensions has always been a testing ground for algorithms. By the…

High Energy Physics - Lattice · Physics 2014-06-25 Dafina Xhako , Artan Boriçi