努梅罗夫 python脚本，用于解一维时间独立的Schrodinger方程的束缚态。 该脚本使用Numerov方法来求解微分方程，并显示所需的能级和带有这些能级中每一个的近似波动函数的图形。 跑步 要运行此代码，只需克隆此存储库并使用python运行Numerov.py脚本（需要numpy和matplotlib模块）： $ git clone https://github.com/FelixDesrochers/Numerov/ $ cd Numerov $ python Numerov.py 然后程序将要求您输入要显示的能级数和所需的电势（确保电势大约位于x = 0的中心）： $ >> Which first energy levels do you want (enter an integer) : 4 $ >> Potential (as a fonction of x):

MIT计算科学与工程 18.085-Gilbert Strang

计算流体力学经典教材，英文版 John.D.Anderson

介绍 使用numpy和scipy库用Python3编写的基本量子化学程序。 当前，该程序完全支持RHF，UHF，CIS，TDHF，DFT，CCSD和CCSD（T）。 我的下一个计划是在程序中实现DFT。 我使用Attlia Szabo和Neil S. Ostlunds的《现代量子化学：高级电子结构理论入门》和《计算量子化学手册》的David B. Cooks作为我对电子结构计算背后的理论和方法的主要参考。 的开发人员资源对于项目的成功也是非常宝贵的，并且拥有许多出色的教程和编程示例。 指示 要运行此程序，请将所需的molfiles和basisset文件添加到molfiles和basisset目录中。 接下来，编辑src/main/main.py menu()函数，以便进行所需的计算，例如， def menu (): start ( 'H2O.mol' , 'STO-3G.g

Computational fluid dynamics. The basics with applications (Anderson J.D) 比较适合入门级的，中文版也不错，买了一本。请支持正版吧！

COMPUTATIONAL METHODS FOR INVERSE PROBLEMS，反问题的计算方法，国外艾斯维尔出版的关于反问题求解的重要书籍，JPG版本

Computational neuroscience is the theoretical study of the brain to uncover the principles and mechanisms that guide the development, organization, information processing, and mental functions of the nervous system. Although not a new area, it is only recently that enough knowledge has been gathered to establish computational neuroscience as a scientific discipline in its own right. Given the complexity of the field, and its increasing importance in progressing our understanding of how the brain works, there has long been a need for an introductory text on what is often assumed to be an impenetrable topic. The new edition of Fundamentals of Computational Neuroscience build on the success and strengths of the first edition. It introduces the theoretical foundations of neuroscience with a focus on the nature of information processing in the brain. The book covers the introduction and motivation of simplified models of neurons that are suitable for exploring information processing in large brain-like networks. Additionally, it introduces several fundamental network architectures and discusses their relevance for information processing in the brain, giving some examples of models of higher-order cognitive functions to demonstrate the advanced insight that can be gained with such studies. Each chapter starts by introducing its topic with experimental facts and conceptual questions related to the study of brain function. An additional feature is the inclusion of simple Matlab programs that can be used to explore many of the mechanisms explained in the book. An accompanying webpage includes programs for download. The book will be the essential text for anyone in the brain sciences who wants to get to grips with this topic.

Computational Thinking (CT) involves fundamental concepts and reasoning, distilled from computer science and other computational sciences, which become powerful general mental tools for solving problems, increasing efficiency, reducing complexity, designing procedures, or interacting with humans and machines. An easy-to-understand guidebook, From Computing to Computational Thinking gives you the tools for understanding and using CT. It does not assume experience or knowledge of programming or of a programming language, but explains concepts and methods for CT with clarity and depth.Successful applications in diverse disciplines have shown the power of CT in problem solving. The book uses puzzles, games, and everyday examples as starting points for discussion and for connecting abstract thinking patterns to real-life situations. It provides an interesting and thought-provoking way to gain general knowledge about modern computing and the concepts and thinking processes underlying modern digital technologies.,解压密码 share.weimo.info

该问题取自 Ramesh Garg 的《电磁学分析计算方法》。 该代码使用矩量法求解积分方程。 脉冲函数用作基函数，点匹配（delta 函数）用作加权函数。 计算矩阵是针对所有行和列计算的。

是JOHN CANNY大师在1986年写的关于边检测论文，该论文是起始文件． 有兴趣的同学自己下载哈