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Related papers: Tensor Calculus

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In this paper, we introduce a type of tensor neural network. For the first time, we propose its numerical integration scheme and prove the computational complexity to be the polynomial scale of the dimension. Based on the tensor product…

Numerical Analysis · Mathematics 2023-07-24 Yifan Wang , Pengzhan Jin , Hehu Xie

A theory of gravity with torsion is examined in which the torsion tensor is constructed from the exterior derivative of an antisymmetric rank two potential plus the dual of the gradient of a scalar field. Field equations for the theory are…

General Relativity and Quantum Cosmology · Physics 2009-11-07 Charro Gruver , Richard Hammond , P. F. Kelly

We present a simulation code which can solve broad ranges of partial differential equations in a full sphere. The code expands tensorial variables in a spectral series of spin-weighted spherical harmonics in the angular directions and a…

Instrumentation and Methods for Astrophysics · Physics 2018-04-26 Daniel Lecoanet , Geoffrey M. Vasil , Keaton J. Burns , Benjamin P. Brown , Jeffrey S. Oishi

Tensor completion is a problem of filling the missing or unobserved entries of partially observed tensors. Due to the multidimensional character of tensors in describing complex datasets, tensor completion algorithms and their applications…

Machine Learning · Statistics 2018-05-04 Qingquan Song , Hancheng Ge , James Caverlee , Xia Hu

It is argued that the partition of a quantum system into subsystems is dictated by the set of operationally accessible interactions and measurements. The emergence of a multi-partite tensor product structure of the state-space and the…

Quantum Physics · Physics 2011-04-29 Paolo Zanardi , Daniel Lidar , Seth Lloyd

We introduce a calculus for tuplices, which are expressions that generalize matrices and vectors. Tuplices have an underlying data type for quantities that are taken from a zero-totalized field. We start with the core tuplix calculus CTC…

Logic in Computer Science · Computer Science 2009-03-03 J. A. Bergstra , A. Ponse , M. B. van der Zwaag

Tensor decomposition methods are popular tools for learning latent variables given only lower-order moments of the data. However, the standard assumption is that we have sufficient data to estimate these moments to high accuracy. In this…

Machine Learning · Statistics 2019-03-13 Omer Gottesman , Weiwei Pan , Finale Doshi-Velez

This article presents the basis of a theory of entanglement. We begin with a classical theory of entangled discrete measures in Section~1. Section~2 treats quantum mechanics and discusses the statistics of bounded operators on a Hilbert…

Quantum Physics · Physics 2022-09-01 Stanley Gudder

Examples are worked out using a new equation proposed in the previous paper to show that it has new physical predictions for mesoscopic systems.

Quantum Physics · Physics 2015-02-16 Partha Ghose , Manoj K. Samal

A matrix approach to continuous iteration is proposed for general formal series. It leads, in particular, to an order{to{order iteration of the exponential function, and consequently to an algorithmic approach to tetration. Lower{order…

Mathematical Physics · Physics 2014-10-16 R. Aldrovandi

The tensor track approach to quantum gravity is based on a new class of quantum field theories, called tensor group field theories (TGFTs). We provide a brief review of recent progress and list some desirable properties of TGFTs. In order…

High Energy Physics - Theory · Physics 2012-09-28 Vincent Rivasseau

Tensors or {\em multi-way arrays} are functions of three or more indices $(i,j,k,\cdots)$ -- similar to matrices (two-way arrays), which are functions of two indices $(r,c)$ for (row,column). Tensors have a rich history, stretching over…

In the evolving domains of Machine Learning and Data Analytics, existing dataset characterization methods such as statistical, structural, and model-based analyses often fail to deliver the deep understanding and insights essential for…

Machine Learning · Computer Science 2025-10-17 Matthew D. Merris , Tim Andersen

We introduce a graphical calculus, consisting of a set of fermionic tensors with tensor-network equations, which can be used to perform various computations in fermionic many-body physics purely diagrammatically. The indices of our tensors…

Quantum Physics · Physics 2025-08-07 Yuanjie Ren , Kaifeng Bu , Andreas Bauer

We present a quantum algorithm that additively approximates the value of a tensor network to a certain scale. When combined with existing results, this provides a complete problem for quantum computation. The result is a simple new way of…

Quantum Physics · Physics 2010-02-09 Itai Arad , Zeph Landau

These lecture notes concern information-theoretic notions of entropy. They are intended for, and have been successfully taught to, undergraduate students interested inresearch careers. Besides basic notions of analysis related to…

Mathematical Physics · Physics 2018-06-20 Vojkan Jaksic

A number of topics in analysis are discussed, with emphasis on basic principles. There is some overlap with "Elements of linear and real analysis" (arXiv:math/0108030), with numerous changes in content and presentation since then.

Classical Analysis and ODEs · Mathematics 2011-11-22 Stephen Semmes

Tensors are fundamental in mathematics, computer science, and physics. Their study through algebraic geometry and representation theory has proved very fruitful in the context of algebraic complexity theory and quantum information. In…

Representation Theory · Mathematics 2025-10-10 Maxim van den Berg , Matthias Christandl , Vladimir Lysikov , Harold Nieuwboer , Michael Walter , Jeroen Zuiddam

In the present paper we take a step towards the generalization of the post-Newtonian formalism to tensor-multi-scalar theories. These are theories where we have more than one scalar field being mediators of the gravitational interaction in…

General Relativity and Quantum Cosmology · Physics 2022-03-24 Oliver Schön , Daniela D. Doneva

The current paper presents a new approach to multilinear dynamical systems analysis and control. The approach is based upon recent developments in tensor decompositions and a newly defined algebra of circulants. In particular, it is shown…

Machine Learning · Computer Science 2021-09-01 Randy C. Hoover , Kyle Caudle , Karen Braman