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We derive the Lagrangian for a new model of a massive rank-4 tensor field with generalized spin (2,1,1) in Minkowski spacetime of any dimension d>5, by using dimensional reduction applied to a reducible gauge model of a massless rank-4…

High Energy Physics - Theory · Physics 2015-06-15 A. A. Reshetnyak , P. Yu. Moshin

A universal model for D=4 spinning particle is constructed with the configuration space chosen as ${\bf R}^{3,1}\times S^2$, where the sphere corresponds to the spinning degrees of freedom. The Lagrangian includes all the possible…

High Energy Physics - Theory · Physics 2008-11-26 S. L. Lyakhovich , A. Yu. Segal , A. A. Sharapov

A tensor network is a diagram that specifies a way to "multiply" a collection of tensors together to produce another tensor (or matrix). Many existing algorithms for tensor problems (such as tensor decomposition and tensor PCA), although…

Data Structures and Algorithms · Computer Science 2018-11-05 Ankur Moitra , Alexander S. Wein

The computation of light scattering by the superposition T-matrix scheme has been so far restricted to systems made of particles that are either sparsely distributed or of near-spherical shape. In this work, we extend the range of…

Optics · Physics 2017-09-20 Dominik Theobald , Amos Egel , Guillaume Gomard , Uli Lemmer

The demand for precision predictions in the field of high energy physics has dramatically increased over recent years. Experiments conducted at the LHC, as well as precision measurements at the intensity frontier such as Belle II require…

High Energy Physics - Phenomenology · Physics 2022-09-28 Marvin Gerlach , Florian Herren , Martin Lang

This paper presents a tensor-recovery method to solve probabilistic power flow problems. Our approach generates a high-dimensional and sparse generalized polynomial-chaos expansion that provides useful statistical information. The result…

Computational Engineering, Finance, and Science · Computer Science 2015-08-12 Zheng Zhang , Hung Dinh Nguyen , Konstantin Turitsyn , Luca Daniel

The Lagrangian formalism for tensor fields over differentiable manifolds with contravariant and covariant affine connections (whose components differ not only by sign) and metrics [$(\bar{L}_n,g)$-spaces] is considered. The functional…

General Relativity and Quantum Cosmology · Physics 2007-05-23 S. Manoff

We consider scalar and spinor particles in the spacetime of a domain wall in the context of low energy effective string theories, such as the generalized scalar-tensor gravity theories. This class of theories allows for an arbitrary…

General Relativity and Quantum Cosmology · Physics 2009-11-07 V. B. Bezerra , L. P. Colatto , M. E. X. Guimaraes , e R. M. Teixeira Filho

The wavefunction for the multiparticle Schr\"odinger equation is a function of many variables and satisfies an antisymmetry condition, so it is natural to approximate it as a sum of Slater determinants. Many current methods do so, but they…

Mathematical Physics · Physics 2009-11-13 Gregory Beylkin , Martin J. Mohlenkamp , Fernando Pérez

In a four-dimensional space, I shall construct all of the conformally invariant scalar-tensor field theories, which are flat space compatible; i.e., well-defined and differentiable when evaluated for a flat metric tensor and constant scalar…

General Relativity and Quantum Cosmology · Physics 2017-06-16 Gregory W. Horndeski

We study the scattering of low-energy tensor multiplet particles against a BPS saturated cosmic string. We show that the corresponding S-matrix is largely determined by symmetry considerations. We then apply a specific supersymmetric model…

High Energy Physics - Theory · Physics 2016-09-06 Erik Flink

We make use of O(2r+1) spinning particle models to construct linearized higher-spin curvatures in (A)dS spaces for fields of arbitrary half-integer spin propagating in a space of arbitrary (even) dimension: the field potentials, whose…

High Energy Physics - Theory · Physics 2014-11-21 Olindo Corradini

This paper describes a flexible framework for generalized low-rank tensor estimation problems that includes many important instances arising from applications in computational imaging, genomics, and network analysis. The proposed estimator…

Statistics Theory · Mathematics 2021-02-08 Rungang Han , Rebecca Willett , Anru R. Zhang

Because tensor data appear more and more frequently in various scientific researches and real-world applications, analyzing the relationship between tensor features and the univariate outcome becomes an elementary task in many fields. To…

Machine Learning · Computer Science 2019-12-04 Jiaqi Zhang , Beilun Wang

Boolean tensor decomposition approximates data of multi-way binary relationships as product of interpretable low-rank binary factors, following the rules of Boolean algebra. Here, we present its first probabilistic treatment. We facilitate…

Machine Learning · Statistics 2018-05-15 Tammo Rukat , Chris C. Holmes , Christopher Yau

We analyze algebraic structure of a relativistic semi-classical Wigner function of particles with spin 1/2 and show that it consistently includes information about the spin density matrix both in two-dimensional spin and four-dimensional…

Nuclear Theory · Physics 2020-06-24 Wojciech Florkowski , Avdhesh Kumar , Radoslaw Ryblewski

In this paper I shall show how the notions of Finsler geometry can be used to construct a similar geometry using a scalar field, f, on the cotangent bundle of a differentiable manifold M. This will enable me to use the second vertical…

General Relativity and Quantum Cosmology · Physics 2022-03-23 Gregory W. Horndeski

To model a realistic situation for the beginning we consider massive real scalar $\phi^4$ theory in a (1+1)-dimensional asymptotically static Minkowski spacetime with an intermediate stage of expansion. To have an analytic headway we assume…

High Energy Physics - Theory · Physics 2018-02-28 Emil T. Akhmedov , Francesco Bascone

Spectral densities encode non-perturbative information that enters the calculation of a plethora of physical observables in strongly coupled field theories. Phenomenological applications encompass aspects of standard-model hadronic physics,…

Super-symmetric tensors - a higher-order extension of scatter matrices - are becoming increasingly popular in machine learning and computer vision for modelling data statistics, co-occurrences, or even as visual descriptors. However, the…

Computer Vision and Pattern Recognition · Computer Science 2015-09-11 Piotr Koniusz , Anoop Cherian
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