Python编程探索光学原理

需积分: 0 148 浏览量更新于2024-06-26 1 收藏 62.95MB PDF 举报

"Understanding Optics with Python" 本书"Understanding Optics with Python"是CRC Series on MULTIDISCIPLINARY AND APPLIED OPTICS系列中的一本，由Vasudevan Lakshminarayanan、Hassen Ghalila、Ahmed Ammar和L. Srinivasa Varadharajan共同撰写。它旨在通过Python编程来解释和理解光学原理，适合对光学和编程感兴趣的读者。书中的章节结构如下： 1. **第一章：Python入门** - 这一章将介绍Python编程的基础，包括语法、数据类型、控制流和函数，为后续的光学计算和模拟打下基础。 2. **第二章：Python与Qt图形用户界面编程** - 讲解如何使用Python结合Qt库创建图形用户界面（GUI），以便实现交互式的光学模拟应用。 3. **第三章：电磁波** - 阐述光作为电磁波的基本性质，如波长、频率、传播和偏振。 4. **第四章：辐射度学与光度学** - 介绍测量和量化光的强度和分布的科学，包括辐射通量、光通量、亮度等概念。 5. **第五章：费马原理、反射与折射** - 解释费马原理如何用于确定光线传播路径，以及光线在不同介质中反射和折射的规则。 6. **第六章：透镜与镜子** - 研究透镜和镜子的成像原理，包括基本的光学仪器设计，如凸透镜和凹透镜。 7. **第七章：厚透镜与透镜系统** - 深入探讨多个透镜组合在一起的系统，讨论焦距、物距、像距的计算以及光学系统的优化。 8. **第八章：偏振** - 探讨光的偏振现象，包括自然光、线性偏振光和圆偏振光，以及偏振片和偏振滤镜的应用。 9. **第九章：干涉** - 分析光的干涉现象，如双缝干涉、薄膜干涉等，以及干涉图样如何揭示波的特性。 10. **第十章：相干性** - 讨论光的相干性，包括光源的相干长度、激光的相干性和干涉实验中的相干条件。 11. **第十一章：衍射** - 介绍光的衍射现象，包括单缝衍射、菲涅尔衍射和夫琅禾费衍射，以及衍射光栅和光学分辨率的概念。 12. **附录A：菲涅尔积分** - 提供关于菲涅尔积分的详细数学背景，这些积分在解决光学问题，特别是衍射问题时非常重要。此书利用Python编程语言为工具，通过实例和代码演示，使读者能够更直观地理解和应用光学原理。对于学习光学和计算机科学的学生，或是需要在科研或工程领域使用光学模拟的专业人士来说，这是一份宝贵的资源。

xii Contents

11.2 Fresnel Diﬀraction...................................................... 317

11.2.1 Fresnel Integrals ............................................. 317

11.2.1.1 Diﬀracted Intensity.......................... 317

11.2.1.2 Fresnel Integrals Properties ............. 320

11.2.2 Clothoid.......................................................... 323

11.2.2.1 Clothoid Properties.......................... 323

11.2.2.2 Diﬀraction by a Single Slit .............. 327

11.2.2.3 Diﬀraction by an Edge..................... 333

11.2.3 Diﬀraction by a Single Slit ............................. 337

11.2.4 Diﬀraction by an Edge ................................... 340

Appendix A Fresnel Integrals................................................................. 347

Index.......................................................................................... 353

Preface

“You will see light in the darkness

You will make some sense of this.”[1]

Optics, an “enabling science” has myriad applications. “Optics and photonics

technologies are ubiquitous: they are responsible for the displays on smart

phones and computing devices, optical ﬁber[s] that [carry] the information in

the [Internet], advanced precision manufacturing, enhanced defense capabil-

ities, and a plethora of [bio]medical [applications such as] diagnostics tools.

The opportunities arising from optics and photonics oﬀer the potential for

even greater societal impact in the next few decades, including solar power

generation and new eﬃcient lighting that could transform the [world]’s energy

landscape and new optical capabilities that will be essential to support the

continued exponential growth of the Internet” [2]. In fact, if the twentieth

century was the century of the electron, the twenty-ﬁrst is the century of the

photon. Therefore, an understanding of optics is essential for every student

of physics and engineering.

This book had its origin in the year 2013, when one of us (VL), working

with an undergraduate summer intern, Mr. Ritambhar Burman (now a grad-

uate student in the Department of Biomedical Engineering at the University

of Miami), developed a set of computational modules on various aspects of

optics using the open source programming language Python [3]. In parallel,

we decided to further expand the initial foray into a more complete set of

programs and simulations. The ﬁrst report on this project was presented at

the Education and Training in Optics and Photonics meeting held in Bor-

deaux, France in 2015, the International Year of Light. This has been further

expanded and some of the results are provided in the present book.

Why simulations? As educators, we are concerned with students under-

standing that physics in general and optics in particular are more than a set

of equations and that the mathematical equations are only shorthand for de-

scribing the physical phenomena. It is essential for the student to learn the

concepts behind the equations. The concepts can be learned in laboratories.

Consider the case where laboratory facilities are not available (a situation

found in many developing countries) or when there are time constraints and

laboratory exercises are not possible. Then, the obvious recourse is to do sim-

ulations on a computer in order for the student to see the eﬀect of changing

various variables in a given situation. This is discussed in detail in the paper

by Lakshminarayanan et al. [4]. It can be argued that simulations are an

essential part of active-learning pedagogical methods; there is considerable

evidence that active learning pedagogical methods are superior to traditional

educational methods [5].

xiii

xiv Preface

A second aim is to make the student comfortable with the task of writing

and analyzing computer codes and hence be computer literate. It is a de

facto requirement that the student in the physical sciences or engineering

have some knowledge of programming. Given the plethora of languages, the

obvious question is “Which one?” We have chosen Python for a number of

reasons.

Python (https://www.python.org/) is an interpreted, interactive, object-

oriented programming language that is open source and easy to learn. Fur-

thermore, it has a remarkably simple and elegant syntax. Beginners would

ﬁnd the clean syntax and indentation structure easy to learn. Like many

other scripting languages it is free, even for commercial purposes, and it can

be run on practically any modern computer. A Python program is compiled

automatically by the interpreter into a platform independent code which is

then interpreted. Exactly the same source code is understood in the same way

by diﬀerent operating systems ensuring perfect cross-platform compatibility.

A large number of specialized modules or applications are written in Python.

Additional advantages of using Python are discussed elsewhere [4, 6].

We encourage the student to modify the codes and “play” with them

and see what results. In this sense, the reader is conducting numerical

experiments. All the programs in the b ook are available at the website:

https://www.crcpress.com/9781498755047. We welcome comments and criti-

cism from the users of this book.

Finally, we would like to thank the publishers, CRC Press/Taylor and

Francis for their enthusiastic support for this book. Special thanks go to

the initial eﬀorts of Ms. Ashley Gasque (now at the Institute of Physics

Publishers), and subsequently by Mr. Marc Gutierrez. Ms. Nora Konopka,

the acquisitions editor of the series on Multi-Disciplinary and Applied Optics

also deserves acknowledgment. It has been a great pleasure to work with these

individuals.

Vasudevan Lakshminarayanan, Ann Arbor, MI

Hassen Ghalila and Ahmed Ammar, Tunis, Tunisia

Srinivasa Varadharajan, Hyderabad, India

1. The Police. “Secret Journey” in The Ghost in the Machine, Track 10. A&M

Records, 1981.

2. National Research Council. Optics and Photonics Essential Technologies for

our Nation. National Academies Press, Washington, DC, 2013.

3. Vasudevan Lakshminarayanan and Ritambhar Burman. Optics tutorials with

Python. Technical report, University of Waterloo, Canada, 2015. Technical

Rep ort. DOI: 10.13140/RG.2.1.2940.2325

4. Vasudevan Lakshminarayanan, Hassen Ghalila, Ahmed Ammar, and Srinivasa

Varadharajan. Role of simulations in optics education. Proc. SPIE 9946, Optics

Education and Outreach IV, doi: 10.1117/12.2236159.

剩余379页未读，继续阅读

光学码农

粉丝: 8807
资源: 38

Python编程探索光学原理

Understanding Optical communications

optics

understanding optics with python

资源下载understanding optics with python下载

聚类分析OPTICS算法python实现

optics算法python实现

传输矩阵计算薄膜系.rar_optics_python_transfer matrix_传输矩阵_薄膜传输矩阵

Engineering Optics With Matlab

crystal nonlinear optics with SNLO examples.pdf

英文原版-Geoprocessing with Python 1st Edition

最新资源