【ニュース】新刊など - fortran66のブログ

Computational Quantum Mechanics

Kindle 対応？

Computational Quantum Mechanics (Undergraduate Lecture Notes in Physics)

作者: Joshua Izaac,Jingbo Wang
出版社/メーカー: Springer
発売日: 2019/03/01
メディア: ハードカバー
この商品を含むブログを見る

www.springer.com
第一章が浮動小数点数等数値の話で、第二章が Fortran、第三章が Python で、ここまでで第一部の計算機の説明がおわり、以下具体的問題に移ります。

プレヴュー出来るところに、Fortran と Python それぞれの利点がまとめられています。

Fortran and Python. Feel free to learn either or both; throughout the book, examples are presented using both programming languages.
Fortran 90/95 is recommended for this book for the following reasons:
• Its history: designed specifically for scientific computation, Fortran is focused on array and matrix computations, and many highly optimised mathematical and scientific libraries are still written in Fortran.
• Its speed: as a result, array and matrix computations are much faster than other programming languages such as Java, MATLAB, and Mathematica, even faster than C in most situations.
• It can be easily parallelised for use in high-performance computing environments, an increasingly important resource in the twenty-first century.
While Fortran remains pervasive in scientific computation, the field is slowly moving towards more modern programming languages such as Python, which are being extensively developed with the scientific community in mind. This increase in popularity is well justified, as can be seen from the following:
• It is easy to learn: Python has a relatively simple syntax; as such, it is reasonably straightforward to read and learn.
• Its ecosystem: more and more scientific libraries are being written in Python, making for a rich ecosystem, even for niche fields. Some of these libraries are even written in Fortran, providing speeds in Python almost comparable to native Fortran.
• It makes problem-solving faster: Python does not need to be compiled and can be used in a web-based notebook interface.