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Physics with Excel and Python

Physics with Excel and Python
Author: Dieter Mergel
Publisher: Springer Nature
Total Pages: 493
Release: 2023-01-01
Genre: Science
ISBN: 3030823253

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This book is intended to serve as a basic introduction to scientific computing by treating problems from various areas of physics - mechanics, optics, acoustics, and statistical reasoning in the context of the evaluation of measurements. After working through these examples, students are able to independently work on physical problems that they encounter during their studies. For every exercise, the author introduces the physical problem together with a data structure that serves as an interface to programming in Excel and Python. When a solution is achieved in one application, it can easily be translated into the other one and presumably any other platform for scientific computing. This is possible because the basic techniques of vector and matrix calculation and array broadcasting are also achieved with spreadsheet techniques, and logical queries and for-loops operate on spreadsheets from simple Visual Basic macros. So, starting to learn scientific calculation with Excel, e.g., at High School, is a targeted road to scientific computing. The primary target groups of this book are students with a major or minor subject in physics, who have interest in computational techniques and at the same time want to deepen their knowledge of physics. Math, physics and computer science teachers and Teacher Education students will also find a companion in this book to help them integrate computer techniques into their lessons. Even professional physicists who want to venture into Scientific Computing may appreciate this book.


Python for Scientists

Python for Scientists
Author: John M. Stewart
Publisher: Cambridge University Press
Total Pages: 272
Release: 2017-07-20
Genre: Computers
ISBN: 1316641236

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Scientific Python is taught from scratch in this book via copious, downloadable, useful and adaptable code snippets. Everything the working scientist needs to know is covered, quickly providing researchers and research students with the skills to start using Python effectively.


Effective Computation in Physics

Effective Computation in Physics
Author: Anthony Scopatz
Publisher: "O'Reilly Media, Inc."
Total Pages: 567
Release: 2015-06-25
Genre: Science
ISBN: 1491901586

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More physicists today are taking on the role of software developer as part of their research, but software development isnâ??t always easy or obvious, even for physicists. This practical book teaches essential software development skills to help you automate and accomplish nearly any aspect of research in a physics-based field. Written by two PhDs in nuclear engineering, this book includes practical examples drawn from a working knowledge of physics concepts. Youâ??ll learn how to use the Python programming language to perform everything from collecting and analyzing data to building software and publishing your results. In four parts, this book includes: Getting Started: Jump into Python, the command line, data containers, functions, flow control and logic, and classes and objects Getting It Done: Learn about regular expressions, analysis and visualization, NumPy, storing data in files and HDF5, important data structures in physics, computing in parallel, and deploying software Getting It Right: Build pipelines and software, learn to use local and remote version control, and debug and test your code Getting It Out There: Document your code, process and publish your findings, and collaborate efficiently; dive into software licenses, ownership, and copyright procedures


Computational Physics

Computational Physics
Author: Mark E. J. Newman
Publisher: Createspace Independent Publishing Platform
Total Pages: 0
Release: 2013
Genre: Computational physics
ISBN: 9781480145511

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This book explains the fundamentals of computational physics and describes the techniques that every physicist should know, such as finite difference methods, numerical quadrature, and the fast Fourier transform. The book offers a complete introduction to the topic at the undergraduate level, and is also suitable for the advanced student or researcher. The book begins with an introduction to Python, then moves on to a step-by-step description of the techniques of computational physics, with examples ranging from simple mechanics problems to complex calculations in quantum mechanics, electromagnetism, statistical mechanics, and more.


Numerical Calculation for Physics Laboratory Projects Using Microsoft EXCEL®

Numerical Calculation for Physics Laboratory Projects Using Microsoft EXCEL®
Author: Shinil Cho
Publisher: Morgan & Claypool Publishers
Total Pages: 162
Release: 2019-10-31
Genre: Science
ISBN: 164327726X

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This book covers essential Microsoft EXCEL®'s computational skills while analyzing introductory physics projects. Topics of numerical analysis include; multiple graphs on the same sheet, calculation of descriptive statistical parameters, a 3-point interpolation, the Euler and the Runge-Kutter methods to solve equations of motion, the Fourier transform to calculate the normal modes of a double pendulum, matrix calculations to solve coupled linear equations of a DC circuit, animation of waves and Lissajous figures, electric and magnetic field calculations from the Poisson equation and its 3D surface graphs, variational calculus such as Fermat's least traveling time principle and the least action principle. Nelson's stochastic quantum dynamics is also introduced to draw quantum particle trajectories.


Visualizing Quantum Mechanics with Python

Visualizing Quantum Mechanics with Python
Author: Steve Spicklemire
Publisher: CRC Press
Total Pages: 79
Release: 2024-06-05
Genre: Science
ISBN: 1040030092

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Quantum Mechanics can be an abstract and complex subject. Students often complain of confusion, struggle, and frustration as they try to master the topic. The goal of this book is to reduce the complexity and clarify the abstractions with concrete visual examples driven by simple python programs. It is assumed that the reader is concurrently taking a course in quantum mechanics, or self-studying quantum mechanics, but is looking for supplementary material to help with understanding and visualizing how quantum mechanics works. The focus of this book is writing python programs to visualize the underlying behavior of the mathematical theory. The background needed to understand quantum mechanics is differential equations, linear algebra and modern physics. We need a strong foundation in differential equations and linear algebra because the behavior of quantum systems is governed by equations that are written in terms of these concepts. Modern physics includes concepts such as special relativity and quantum phenomena like the photoelectric effect and energy quantization that the theory of quantum mechanics seeks to explain. This book is also not an introduction to the python programming language, or to numpy, or even to VPython. However its programming examples start simply and grow more complex as the chapters progress, so deep expertise in any of these is not a pre-requisite. Key features: · Provides an accessible and practical guide to the abstractions in quantum mechanics with concrete visual examples driven by simple python programs. · Contains few derivations, equations, and proofs. · For complete beginners of python programming, appendix B serves as a very brief introduction to the main concepts needed to understand the code in this book. Dr. Stephen Spicklemire is Associate Professor of Physics at the University of Indianapolis, USA. He has been teaching physics at the University of Indianapolis for more than 30 years. From the implementation of "flipped" physics class to the modernization of scientific computing and laboratory instrumentation courses, he has brought the strengths of his background in physics, engineering and computer science into the classroom. Dr. Spicklemire also does IT and engineering consulting. He is an active participant in several national research initiatives relating to improving physics education. These range from improving materials to help students prepare for class, to supporting students success through standards based grading. He is an active developer of the VPython and WebVPython projects and a contributor to the Matter and Interactions textbook.


Introduction to Python in Earth Science Data Analysis

Introduction to Python in Earth Science Data Analysis
Author: Maurizio Petrelli
Publisher: Springer Nature
Total Pages: 229
Release: 2021-09-16
Genre: Science
ISBN: 3030780554

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This textbook introduces the use of Python programming for exploring and modelling data in the field of Earth Sciences. It drives the reader from his very first steps with Python, like setting up the environment and starting writing the first lines of codes, to proficient use in visualizing, analyzing, and modelling data in the field of Earth Science. Each chapter contains explicative examples of code, and each script is commented in detail. The book is minded for very beginners in Python programming, and it can be used in teaching courses at master or PhD levels. Also, Early careers and experienced researchers who would like to start learning Python programming for the solution of geological problems will benefit the reading of the book.


Introduction to Python for Science and Engineering

Introduction to Python for Science and Engineering
Author: David J. Pine
Publisher: CRC Press
Total Pages: 444
Release: 2024-09-23
Genre: Computers
ISBN: 1040119573

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Introduction to Python for Science and Engineering offers a quick and incisive introduction to the Python programming language for use in any science or engineering discipline. The approach is pedagogical and “bottom up,” which means starting with examples and extracting more general principles from that experience. No prior programming experience is assumed. Readers will learn the basics of Python syntax, data structures, input and output, conditionals and loops, user-defined functions, plotting, animation, and visualization. They will also learn how to use Python for numerical analysis, including curve fitting, random numbers, linear algebra, solutions to nonlinear equations, numerical integration, solutions to differential equations, and fast Fourier transforms. Readers learn how to interact and program with Python using JupyterLab and Spyder, two simple and widely used integrated development environments. All the major Python libraries for science and engineering are covered, including NumPy, SciPy, Matplotlib, and Pandas. Other packages are also introduced, including Numba, which can render Python numerical calculations as fast as compiled computer languages such as C but without their complex overhead.


Python Data Science Handbook

Python Data Science Handbook
Author: Jake VanderPlas
Publisher: "O'Reilly Media, Inc."
Total Pages: 743
Release: 2016-11-21
Genre: Computers
ISBN: 1491912138

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For many researchers, Python is a first-class tool mainly because of its libraries for storing, manipulating, and gaining insight from data. Several resources exist for individual pieces of this data science stack, but only with the Python Data Science Handbook do you get them all—IPython, NumPy, Pandas, Matplotlib, Scikit-Learn, and other related tools. Working scientists and data crunchers familiar with reading and writing Python code will find this comprehensive desk reference ideal for tackling day-to-day issues: manipulating, transforming, and cleaning data; visualizing different types of data; and using data to build statistical or machine learning models. Quite simply, this is the must-have reference for scientific computing in Python. With this handbook, you’ll learn how to use: IPython and Jupyter: provide computational environments for data scientists using Python NumPy: includes the ndarray for efficient storage and manipulation of dense data arrays in Python Pandas: features the DataFrame for efficient storage and manipulation of labeled/columnar data in Python Matplotlib: includes capabilities for a flexible range of data visualizations in Python Scikit-Learn: for efficient and clean Python implementations of the most important and established machine learning algorithms


Python for Mechanical and Aerospace Engineering

Python for Mechanical and Aerospace Engineering
Author: Alex Kenan
Publisher: Alex Kenan
Total Pages: 210
Release: 2021-01-01
Genre: Computers
ISBN: 1736060600

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The traditional computer science courses for engineering focus on the fundamentals of programming without demonstrating the wide array of practical applications for fields outside of computer science. Thus, the mindset of “Java/Python is for computer science people or programmers, and MATLAB is for engineering” develops. MATLAB tends to dominate the engineering space because it is viewed as a batteries-included software kit that is focused on functional programming. Everything in MATLAB is some sort of array, and it lends itself to engineering integration with its toolkits like Simulink and other add-ins. The downside of MATLAB is that it is proprietary software, the license is expensive to purchase, and it is more limited than Python for doing tasks besides calculating or data capturing. This book is about the Python programming language. Specifically, it is about Python in the context of mechanical and aerospace engineering. Did you know that Python can be used to model a satellite orbiting the Earth? You can find the completed programs and a very helpful 595 page NSA Python tutorial at the book’s GitHub page at https://www.github.com/alexkenan/pymae. Read more about the book, including a sample part of Chapter 5, at https://pymae.github.io