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Contraction coefficients give a quantitative strengthening of the data processing inequality. As such, they have many natural applications whenever closer analysis of information processing is required. However, it is often challenging to…

Quantum Physics · Physics 2024-05-24 Christoph Hirche

We present a subtraction scheme for eliminating the ultraviolet, soft, and collinear divergences in the numerical calculation of an arbitrary one-loop QCD amplitude with an arbitrary number of external legs. The subtractions consist of…

High Energy Physics - Phenomenology · Physics 2009-11-10 Zoltan Nagy , Davison E. Soper

Electron repulsion integral tensor has ubiquitous applications in quantum chemistry calculations. In this work, we propose an algorithm which compresses the electron repulsion tensor into the tensor hypercontraction format with…

Numerical Analysis · Mathematics 2015-06-18 Jianfeng Lu , Lexing Ying

In this paper, we propose a new unified optimization algorithm for general tensor decomposition which is formulated as an inverse problem for low-rank tensors in the general linear observation models. The proposed algorithm supports three…

Computer Vision and Pattern Recognition · Computer Science 2023-12-20 Manabu Mukai , Hidekata Hontani , Tatsuya Yokota

Projected gradient descent and its Riemannian variant belong to a typical class of methods for low-rank matrix estimation. This paper proposes a new Nesterov's Accelerated Riemannian Gradient algorithm by efficient orthographic retraction…

Optimization and Control · Mathematics 2023-06-05 Hongyi Li , Zhen Peng , Chengwei Pan , Di Zhao

We consider the problem of decomposing a real-valued symmetric tensor as the sum of outer products of real-valued vectors. Algebraic methods exist for computing complex-valued decompositions of symmetric tensors, but here we focus on…

Numerical Analysis · Mathematics 2018-08-23 Tamara G. Kolda

In this paper, we provide local and global convergence guarantees for recovering CP (Candecomp/Parafac) tensor decomposition. The main step of the proposed algorithm is a simple alternating rank-$1$ update which is the alternating version…

Machine Learning · Computer Science 2015-03-05 Animashree Anandkumar , Rong Ge , Majid Janzamin

Large tensors are frequently encountered in various fields such as computer vision, scientific simulations, sensor networks, and data mining. However, these tensors are often too large for convenient processing, transfer, or storage.…

Optimization and Control · Mathematics 2024-09-26 Zhiguang Cheng , Gaohang Yu , Xiaohao Cai , Liqun Qi

The evaluation of partition functions is a central problem in statistical physics. For lattice systems and other discrete models the partition function may be expressed as the contraction of a tensor network. Unfortunately computing such…

Computational Physics · Physics 2020-01-15 Adam S. Jermyn

We describe methods for evaluating one-loop integrals in $4-2\e$ dimensions. We give a recursion relation that expresses the scalar $n$-point integral as a cyclicly symmetric combination of $(n-1)$-point integrals. The computation of such…

High Energy Physics - Phenomenology · Physics 2008-11-26 Z. Bern , L. Dixon , D. A. Kosower

Nonsmooth composite optimization with orthogonality constraints has a wide range of applications in statistical learning and data science. However, this problem is challenging due to its nonsmooth objective and computationally expensive…

Optimization and Control · Mathematics 2026-05-15 Ganzhao Yuan

In this talk we review the GOLEM approach to one-loop calculations and present an automated implementation of this technique. This method is based on Feynman diagrams and an advanced reduction of one-loop tensor integrals which avoids…

An algorithm, based on the OPP reduction method, to automatically compute any one-loop amplitude, for all momentum, color and helicity configurations of the external particles, is presented. It has been implemented using the tree-order…

High Energy Physics - Phenomenology · Physics 2010-11-19 A. van Hameren , C. G. Papadopoulos , R. Pittau

This chapter studies the problem of decomposing a tensor into a sum of constituent rank one tensors. While tensor decompositions are very useful in designing learning algorithms and data analysis, they are NP-hard in the worst-case. We will…

Data Structures and Algorithms · Computer Science 2020-07-31 Aravindan Vijayaraghavan

We introduce $\mathcal{V}$-polyhedral disjunctive cuts (VPCs) for generating valid inequalities from general disjunctions. Cuts are critical to integer programming solvers, but the benefit from many families is only realized when the cuts…

Optimization and Control · Mathematics 2024-02-20 Egon Balas , Aleksandr M. Kazachkov

We demonstrate for the specific case of $C_{3v}$ how the direct-product decomposition scheme for the treatment of symmetry in coupled-cluster (CC) calculations can be extended to non-Abelian point groups. We show that for the two-electron…

Chemical Physics · Physics 2026-01-16 Malte Hellmann , Jürgen Gauss

For loop integrals, the reduction is the standard method. Having an efficient way to find reduction coefficients is an important topic in scattering amplitudes. In this paper, we present the generation functions of reduction coefficients…

High Energy Physics - Phenomenology · Physics 2025-03-26 Bo Feng

The method for functional reduction of Feynman integrals, proposed by the author, is used to calculate one-loop integrals corresponding to diagrams with four external lines. The integrals that emerge from amplitudes for the scattering of…

High Energy Physics - Phenomenology · Physics 2023-07-12 O. V. Tarasov

An efficient numerical algorithm to evaluate one-loop amplitudes using tensor integrals is presented. In particular, it is shown by explicit calculations that for ordered QCD amplitudes with a number of external legs up to 10, its…

High Energy Physics - Phenomenology · Physics 2009-08-11 A. van Hameren

We present an algorithm for low rank decomposition of tensors of any symmetry type, from fully asymmetric to fully symmetric. It recovers the decomposition one summand at a time via the higher-order power method. This approach is known to…

Numerical Analysis · Mathematics 2026-05-22 Kexin Wang , João M. Pereira , Joe Kileel , Anna Seigal