cppTPSA/pyTPSA:用于截断幂级数代数的 C++/Python 软件包

He Zhang
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引用次数: 0

摘要

截断幂级数代数(TPSA),也称为微分代数(DA),是粒子加速器物理学和天文学中一种成熟且广泛使用的方法。TPSA/DA 最直接的用法是计算给定函数在特定点的𝑛阶泰勒展开。近年来,随着 TPSA/TA 的应用扩展到其他领域,TPSA/DA 作为现代 C++ 库或其他高级编程语言(如 Python)的可重用实现已变得非常必要。cppTPSA 软件包在 C++11 中实现了 TPSA/DA,为开发人员提供了一个方便的库,用于构建基于 TPSA/DA 的高级方法。基于 C++ 库还开发了 Python 3 库 pyTPSA。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
cppTPSA/pyTPSA: a C++/Python package for truncated power series algebra
The truncated power series algebra (TPSA), also referred to as differential algebra (DA), is a well-established and widely used method in particle accelerator physics and astronomy. The most straightforward usage of TPSA/DA is to calculate the Taylor expansion of a given function at a specific point up to order 𝑛 . In recent years, as the application of TPSA/TA has been extended to other fields, a reusable implementation of TPSA/DA as a modern C++ library or other high level programming language like Python has become desirable. The cppTPSA package implements TPSA/DA in C++11 and provides developers a convenient library with which to build advanced TPSA/DA-based methods. A Python 3 library, pyTPSA, has also been developed based on the C++ lib.
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