ﻻ يوجد ملخص باللغة العربية
Diffraction calculations, such as the angular spectrum method, and Fresnel diffractions, are used for calculating scalar light propagation. The calculations are used in wide-ranging optics fields: for example, computer generated holograms (CGHs), digital holography, diffractive optical elements, microscopy, image encryption and decryption, three-dimensional analysis for optical devices and so on. However, increasing demands made by large-scale diffraction calculations have rendered the computational power of recent computers insufficient. We have already developed a numerical library for diffraction calculations using a graphic processing unit (GPU), which was named the GWO library. However, this GWO library is not user-friendly, since it is based on C language and was also run only on a GPU. In this paper, we develop a new C++ class library for diffraction and CGH calculations, which is referred as to a CWO++ library, running on a CPU and GPU. We also describe the structure, performance, and usage examples of the CWO++ library.
ZKCM is a C++ library developed for the purpose of multiprecision matrix computation, on the basis of the GNU MP and MPFR libraries. It provides an easy-to-use syntax and convenient functions for matrix manipulations including those often used in num
Deep learning has achieved remarkable success in diverse applications; however, its use in solving partial differential equations (PDEs) has emerged only recently. Here, we present an overview of physics-informed neural networks (PINNs), which embed
HepLib is a C++ Library for computations in High Energy Physics, it works on top of GiNaC, a well-established C++ library used to perform symbolic computations. HepLib combines serval well-known packages to get high efficiency, including Qgraf to gen
MLPACK is a state-of-the-art, scalable, multi-platform C++ machine learning library released in late 2011 offering both a simple, consistent API accessible to novice users and high performance and flexibility to expert users by leveraging modern feat
We show how faceted search using a combination of traditional classification systems and mixed-membership topic models can go beyond keyword search to inform resource discovery, hypothesis formulation, and argument extraction for interdisciplinary re