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When a wave, such as sound or light, scatters within a densely packed particulate, it can be rescattered many times between the particles, which is called multiple scattering. Multiple scattering can be unavoidable when: trying to use sound…

Classical Physics · Physics 2023-08-28 K. K. Napal , P. S. Piva , A. L. Gower

We investigate the wave-optical light scattering properties of deformed thin circular films of constant thickness using the discrete-dipole approximation. Effects on the intensity distribution of the scattered light due to different…

Optics · Physics 2020-10-09 Hannu Parviainen , Kari Lumme

We propose a new method for low-rank approximation of Moore-Penrose pseudoinverses (MPPs) of large-scale matrices using tensor networks. The computed pseudoinverses can be useful for solving or preconditioning of large-scale overdetermined…

Numerical Analysis · Mathematics 2016-07-06 Namgil Lee , Andrzej Cichocki

Large-area metasurfaces composed of discrete wavelength-scale scatterers present an extremely large number of degrees of freedom to engineer an optical element. These degrees of freedom provide tremendous design flexibility, and a central…

Optics · Physics 2019-08-29 Maksym V. Zhelyeznyakov , Alan Zhan , Arka Majumdar

We discuss how Dokken's methods of approximate implicitization can be applied to triangular B\'ezier surfaces in both the original and weak forms. The matrices $\mathbf{D}$ and $\mathbf{M}$ that are fundamental to the respective forms of…

Numerical Analysis · Mathematics 2017-07-06 Oliver J. D. Barrowclough , Tor Dokken

We consider a new splitting based on the Sherman-Morrison-Woodbury formula, which is particularly effective with iterative methods for the numerical solution of large linear systems. These systems involve matrices that are perturbations of…

Numerical Analysis · Mathematics 2023-10-17 Dimitrios Mitsotakis

How can we design neural networks that allow for stable universal approximation of maps between topologically interesting manifolds? The answer is with a coordinate projection. Neural networks based on topological data analysis (TDA) use…

Machine Learning · Computer Science 2022-10-04 Michael Puthawala , Matti Lassas , Ivan Dokmanic , Pekka Pankka , Maarten de Hoop

We introduce a robust optimization method for flip-free distortion energies used, for example, in parametrization, deformation, and volume correspondence. This method can minimize a variety of distortion energies, such as the symmetric…

Graphics · Computer Science 2022-11-17 Oded Stein , Jiajin Li , Justin Solomon

In this paper, we extend the Discrete Empirical Interpolation Method (DEIM) to the third-order tensor case based on the t-product and use it to select important/ significant lateral and horizontal slices/features. The proposed Tubal DEIM…

Numerical Analysis · Mathematics 2023-05-09 Salman Ahmadi-Asl , Anh-Huy Phan , Cesar F. Caiafa , Andrzej Cichocki

Estimates of the approximate factor model are increasingly used in empirical work. Their theoretical properties, studied some twenty years ago, also laid the ground work for analysis on large dimensional panel data models with cross-section…

Econometrics · Economics 2020-08-04 Jushan Bai , Serena Ng

We extend the geometrical inverse approximation approach for solving linear least-squares problems. For that we focus on the minimization of $1-\cos(X(A^TA),I)$, where $A$ is a given rectangular coefficient matrix and $X$ is the approximate…

Numerical Analysis · Mathematics 2019-02-25 Jean-Paul Chehab , Marcos Raydan

We consider discretizations of the hyper-singular integral operator on closed surfaces and show that the inverses of the corresponding system matrices can be approximated by blockwise low-rank matrices at an exponential rate in the block…

Numerical Analysis · Mathematics 2017-12-04 Markus Faustmann , Jens Markus Melenk , Dirk Praetorius

Dynamical low-rank approximation in the Tucker tensor format of given large time-dependent tensors and of tensor differential equations is the subject of this paper. In particular, a discrete time integration method for rank-constrained…

Numerical Analysis · Mathematics 2017-09-11 Christian Lubich , Bart Vandereycken , Hanna Walach

We develop fixed-point algorithms for the approximation of structured matrices with rank penalties. In particular we use these fixed-point algorithms for making approximations by sums of exponentials, or frequency estimation. For the basic…

Numerical Analysis · Mathematics 2016-01-07 Fredrik Andersson , Marcus Carlsson

The computation of a matrix function $f(A)$ is an important task in scientific computing appearing in machine learning, network analysis and the solution of partial differential equations. In this work, we use only matrix-vector products…

Numerical Analysis · Mathematics 2026-03-03 Taejun Park , Yuji Nakatsukasa

This paper introduces a new fast algorithm for the 8-point discrete cosine transform (DCT) based on the summation-by-parts formula. The proposed method converts the DCT matrix into an alternative transformation matrix that can be decomposed…

Data Structures and Algorithms · Computer Science 2018-03-30 D. F. G. Coelho , R. J. Cintra , V. S. Dimitrov

DDSCAT 7.2 is a freely available open-source Fortran-90 software package applying the discrete dipole approximation (DDA) to calculate scattering and absorption of electromagnetic waves by targets with arbitrary geometries and complex…

Computational Physics · Physics 2012-05-16 Bruce T. Draine , Piotr J. Flatau

A matrix balanced version of the Recursive Centered T Matrix Algorithm (RCTMA) applicable to systems possessing resonant inter-particle couplings is presented. Possible domains of application include systems containing interacting localized…

Optics · Physics 2009-05-21 Brian Stout , Jean-Claude Auger , Alexis Devilez

We consider an optimization problem related to semi-active damping of vibrating systems. The main problem is to determine the best damping matrix able to minimize influence of the input on the output of the system. We use a minimization…

Dynamical Systems · Mathematics 2017-07-07 Zoran Tomljanović , Christopher Beattie , Serkan Gugercin

Digital nets are among the most successful methods to construct low-discrepancy point sets for quasi-Monte Carlo integration. Their quality is traditionally assessed by a measure called the $t$-value. A refinement computes the $t$-value of…

Computation · Statistics 2020-01-08 Pierre Marion , Maxime Godin , Pierre L'Ecuyer
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