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Related papers: Programming matrix optics into Mathematica

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We present a general class of machine learning algorithms called parametric matrix models. In contrast with most existing machine learning models that imitate the biology of neurons, parametric matrix models use matrix equations that…

Machine Learning · Computer Science 2025-01-07 Patrick Cook , Danny Jammooa , Morten Hjorth-Jensen , Daniel D. Lee , Dean Lee

Monte Carlo simulations are based on the manipulation of random numbers to evaluate probable outcomes, with applicability in a variety of different fields. By assigning probabilities, which can be determined a priori, to various events, it…

Physics Education · Physics 2022-01-03 Parasuraman Swaminathan

In this paper, we introduce methods of encoding propositional logic programs in vector spaces. Interpretations are represented by vectors and programs are represented by matrices. The least model of a definite program is computed by…

Artificial Intelligence · Computer Science 2018-11-29 Chiaki Sakama , Hien D. Nguyen , Taisuke Sato , Katsumi Inoue

Linear exact modeling is a problem coming from system identification: Given a set of observed trajectories, the goal is find a model (usually, a system of partial differential and/or difference equations) that explains the data as precisely…

Optimization and Control · Mathematics 2011-10-26 Kristina Schindelar , Viktor Levandovskyy , Eva Zerz

Conceptual studies and numerical simulations are performed for imaging devices that transform a near-field pattern into magnified far-zone images and are based on high-order spatial transformation in cylindrical domains. A lens translating…

Optics · Physics 2009-11-13 Alexander V. Kildishev , Vladimir M. Shalaev

A Monte Carlo simulation has been performed to track light rays in cylindrical multimode fibres by ray optics. The trapping efficiencies for skew and meridional rays in active fibres and distributions of characteristic quantities for all…

Nuclear Experiment · Physics 2015-06-26 Patrick Achenbach , John H Cobb

Numerical Simulation is an essential part of the design and optimisation of astronomical adaptive optics systems. Simulations of adaptive optics are computationally expensive and the problem scales rapidly with telescope aperture size, as…

Astrophysics · Physics 2009-11-13 A. G. Basden , F. Assemat , T. Butterley , D. Geng , C. D. Saunter , R. W. Wilson

In this paper we present an algorithm for computing a matrix representation for a surface in P^3 parametrized over a 2-dimensional toric variety T. This algorithm follows the ideas of [Botbol-Dickenstein-Dohm-09] and it was implemented in…

Algebraic Geometry · Mathematics 2010-01-08 Nicolas Botbol Marc Dohm

We examine implicit representations of parametric or point cloud models, based on interpolation matrices, which are not sensitive to base points. We show how interpolation matrices can be used for ray shooting of a parametric ray with a…

Algebraic Geometry · Mathematics 2017-06-09 Ioannis Z. Emiris , Christos Konaxis , Ilias S. Kotsireas , Clement Laroche

We introduce the \prog{Mathematica} package \prog{MT} which can be used to compute, both analytically and numerically, convolutions involving harmonic polylogarithms, polynomials or generalized functions. As applications contributions to…

High Energy Physics - Phenomenology · Physics 2015-06-16 Maik Hoeschele , Jens Hoff , Alexey Pak , Matthias Steinhauser , Takahiro Ueda

Probabilistic programming has emerged as a powerful paradigm in statistics, applied science, and machine learning: by decoupling modelling from inference, it promises to allow modellers to directly reason about the processes generating…

Machine Learning · Statistics 2019-06-10 Maria I. Gorinova , Dave Moore , Matthew D. Hoffman

A Monte Carlo simulation has been performed to track light rays in cylindrical fibres by ray optics. The trapping efficiencies for skew and meridional rays in active fibres and distributions of characteristic quantities for all trapped…

Optics · Physics 2009-11-07 C. P. Achenbach , J. H. Cobb

End-to-end optimization, which simultaneously optimizes optics and algorithms, has emerged as a powerful data-driven method for computational imaging system design. This method achieves joint optimization through backpropagation by…

Computer Vision and Pattern Recognition · Computer Science 2025-08-08 Chi-Jui Ho , Yash Belhe , Steve Rotenberg , Ravi Ramamoorthi , Tzu-Mao Li , Nicholas Antipa

It is shown that the one-lens system in para-axial optics can serve as an optical computer for contraction of Wigner's little groups and an analogue computer which transforms analytically computations on a spherical surface to those on a…

Mathematical Physics · Physics 2009-11-07 S. Baskal , Y. S. Kim

The Mathieu functions are used to solve analytically some problems in elliptical cylinder coordinates. A computational toolbox was implemented in Matlab. Since the notation and normalization for Mathieu functions vary in the literature, we…

Mathematical Physics · Physics 2008-11-13 E. Cojocaru

We study the problem of approximating orthogonal matrices so that their application is numerically fast and yet accurate. We find an approximation by solving an optimization problem over a set of structured matrices, that we call extended…

Numerical Analysis · Mathematics 2021-03-24 Cristian Rusu , Lorenzo Rosasco

Computational modelling has made many useful contributions to the field of optical tweezers. One aspect in which it can be applied is the simulation of the dynamics of particles in optical tweezers. This can be useful for systems with many…

Materials of which the optical response is determined by their structure are of much interest both for their fundamental properties and applications. Examples range from simple gratings to photonic crystals. Obtaining control over the…

Since the early twentieth century, it has been understood that mathematical definitions and proofs can be represented in formal systems systems with precise grammars and rules of use. Building on such foundations, computational proof…

History and Overview · Mathematics 2023-11-07 Jeremy Avigad

The paper covers a formulation of the inverse quadratic programming problem in terms of unconstrained optimization where it is required to find the unknown parameters (the matrix of the quadratic form and the vector of the quasi-linear part…

Numerical Analysis · Computer Science 2017-01-09 E. G. Abramov