Subscribe to the gold package and get unlimited access to Shamra Academy
Register a new userOGRe: An Object-Oriented General Relativity Package for Mathematica
345
0
0.0
(
0
)
Added by
Barak Shoshany
Publication date
2021
fields
Informatics Engineering
and research's language is
English
Authors
Barak Shoshany
Ask ChatGPT about the research
No Arabic abstract
We present OGRe, a modern Mathematica package for tensor calculus, designed to be both powerful and user-friendly. The package can be used in a variety of contexts where tensor calculations are needed, in both mathematics and physics, but it is especially suitable for general relativity. By implementing an object-oriented design paradigm, OGRe allows calculating arbitrarily complicated tensor formulas easily, and automatically transforms between index configurations and coordinate systems behind the scenes as needed, eliminating user errors by making it impossible for the user to combine tensors in inconsistent ways. Other features include displaying tensors in various forms, automatic calculation of curvature tensors and geodesic equations, easy importing and exporting of tensors between sessions, optimized algorithms and parallelization for improved performance, and more.
rate research
Read More
The computation of Feynman integrals often involves square roots. One way to obtain a solution in terms of multiple polylogarithms is to rationalize these square roots by a suitable variable change. We present a program that can be used to find such transformations. After an introduction to the theoretical background, we explain in detail how to use the program in practice.
The computation of first and second-order derivatives is a staple in many computing applications, ranging from machine learning to scientific computing. We propose an algorithm to automatically differentiate algorithms written in a subset of C99 code and its efficient implementation as a Python script. We demonstrate that our algorithm enables automatic, reliable, and efficient differentiation of common algorithms used in physical simulation and geometry processing.
This document describes the R package UBL that allows the use of several methods for handling utility-based learning problems. Classification and regression problems that assume non-uniform costs and/or benefits pose serious challenges to predictive analytic tasks. In the context of meteorology, finance, medicine, ecology, among many other, specific domain information concerning the preference bias of the users must be taken into account to enhance the models predictive performance. To deal with this problem, a large number of techniques was proposed by the research community for both classification and regression tasks. The main goal of UBL package is to facilitate the utility-based predictive analytic task by providing a set of methods to deal with this type of problems in the R environment. It is a versatile tool that provides mechanisms to handle both regression and classification (binary and multiclass) tasks. Moreover, UBL package allows the user to specify his domain preferences, but it also provides some automatic methods that try to infer those preference bias from the domain, considering some common known settings.
L1Packv2 is a Mathematica package that contains a number of algorithms that can be used for the minimization of an $ell_1$-penalized least squares functional. The algorithms can handle a mix of penalized and unpenalized variables. Several instructive examples are given. Also, an implementation that yields an exact output whenever exact data are given is provided.
MCViNE (Monte-Carlo VIrtual Neutron Experiment) is a versatile Monte Carlo (MC) neutron ray-tracing program that provides researchers with tools for performing computer modeling and simulations that mirror real neutron scattering experiments. By adopting modern software engineering practices such as using composite and visitor design patterns for representing and accessing neutron scatterers, and using recursive algorithms for multiple scattering, MCViNE is flexible enough to handle sophisticated neutron scattering problems including, for example, neutron detection by complex detector systems, and single and multiple scattering events in a variety of samples and sample environments. In addition, MCViNE can take advantage of simulation components in linear-chain-based MC ray tracing packages widely used in instrument design and optimization, as well as NumPy-based components that make prototypes useful and easy to develop. These developments have enabled us to carry out detailed simulations of neutron scattering experiments with non-trivial samples in time-of-flight inelastic instruments at the Spallation Neutron Source. Examples of such simulations for powder and single-crystal samples with various scattering kernels, including kernels for phonon and magnon scattering, are presented. With simulations that closely reproduce experimental results, scattering mechanisms can be turned on and off to determine how they contribute to the measured scattering intensities, improving our understanding of the underlying physics.
Log in to be able to interact and post comments
comments
Fetching comments
Sign in to be able to follow your search criteria
