Computational Physics: Problem Solving with Python
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Computational Physics: Problem Solving with Python
Computational Physics: Problem Solving with Python 3rd Edition is an upper-division text that provides an unusually broad survey of the topics of modern computational physics from a multidisciplinary, computational science point of view.
Computational Physics: Problem Solving with Python
Numéro d'article: 9859744

Computational Physics: Problem Solving with Python

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Numéro d'article: 9859744

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Computational Physics: Problem Solving with Python 3rd Edition is an upper-division text that provides an unusually broad survey of the topics of modern computational physics from a multidisciplinary, computational science point of view.
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Ce qui se démarque

Comprehensive Content
This edition covers a wide range of computational techniques, offering deep insights into both physics concepts and practical Python programming, making it suitable for students and professionals alike.
Hands-On Approach
The book promotes active learning with numerous examples and exercises, allowing readers to apply theoretical concepts through practical coding challenges in Python, enhancing their problem-solving skills.
Updated Resources
Including the latest advancements in computational physics and Python 3 features, this edition provides valuable updated tools and resources that support both learning and research applications in the field.

Détails du produit

Discover the best deals on Computational Physics: Problem Solving with Python 3rd Edition at Ubuy Réunion, your global online store for all your book needs. Shop now and enhance your problem-solving skills with Python.
Publisher Wiley-VCH
Publication date September 8, 2015
Edition 3rd
Language English
Print length 644 pages
ISBN-10 3527413154
ISBN-13 978-3527413157
Item Weight 3 pounds (1.36 kg)
Dimensions 6.7 x 1.3 x 9.4 inches (17 x 3.3 x 23.9 cm)

À qui est-ce destiné ?

Suitable For
  • Physics Students

    Ideal for undergraduate physics students seeking practical applications in programming and computational methods.

  • Research Scientists

    Useful for scientists looking to apply computational techniques in their research for data analysis and simulation.

  • Python Programmers

    Catering to Python programmers wanting to deepen their understanding of physics through coding problem-solving.

Not Suitable For
  • Absolute Beginners

    Not suitable for complete programming novices due to the technical nature and assumed knowledge of Python.

DESCRIPTION DU PRODUIT

Computational Physics: Problem Solving with Python

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Questions et réponses des clients

  • question: What is the focus of 'Computational Physics: Problem Solving with Python 3rd Edition'?

    répondre: The book primarily focuses on applying computational techniques to solve physical problems using Python programming. It encourages readers to develop strong problem-solving skills and computational thinking. By integrating theoretical physics concepts with practical programming skills, it is particularly suitable for students and professionals engaged in fields like physics, engineering, and data science, simulating complex systems, or analyzing experimental data.
  • question: What programming skills are required to effectively use this book?

    répondre: While the book caters to readers with varying levels of programming knowledge, a basic understanding of Python will be beneficial. The text guides readers through coding exercises and examples, building up complexity gradually. For those new to programming, starting with introductory Python resources alongside the book can enhance comprehension, allowing readers to engage with simulations and computations effectively.
  • question: How does this edition differ from previous versions?

    répondre: The 3rd edition includes updated examples, new algorithms, and refined problem sets that reflect recent advancements in computational physics. Additionally, it may feature enhanced explanations and usability improvements. This edition aims to provide a more engaging learning experience, making it even more relevant for current students and researchers looking to harness Python for solving complex physical problems.
  • question: Who is the target audience for this book?

    répondre: The target audience includes undergraduate and graduate students in physics and engineering as well as professionals working in computational science. It's ideal for those seeking to understand how to leverage Python in practical scenarios, such as developing simulations or analyzing experimental data. Hobbyists with a passion for physics and programming may also find the content engaging and informative.
  • question: Are there any prerequisites for understanding the material in this book?

    répondre: Having foundational knowledge in physics and an introductory understanding of Python programming is recommended for grasping the topics effectively. Familiarity with mathematics, particularly calculus and linear algebra, will also aid in comprehending the physical concepts discussed. If you're looking to strengthen your background, consider reviewing these subjects before diving into the book.
  • question: Does the book include practical exercises and examples?

    répondre: Yes, the book is rich with practical exercises and examples that encourage readers to apply what they learn immediately. Each chapter typically includes various problems that can be solved using Python, fostering interactive learning. This hands-on approach is crucial for reinforcing theoretical concepts while enhancing your programming skills, making it a valuable resource for both self-study and classroom settings.
  • question: Can this book help me in my research work?

    répondre: Absolutely! 'Computational Physics: Problem Solving with Python 3rd Edition' is designed to equip readers with computational tools that can be directly applied in research. Whether it's modeling physical phenomena or analyzing data from experiments, the techniques outlined in the book can enhance your analytical capabilities, making it a significant asset for researchers in various scientific fields.
  • question: What specific topics are covered in this book?

    répondre: The book covers a range of topics, including molecular dynamics, Monte Carlo simulations, wave propagation, and statistical methods in physics. Each chapter dives into different computational techniques and physical concepts, ensuring comprehensive coverage of key areas in computational physics. This variety allows readers to find relevant information aligned with their interests or projects they may be working on.
  • question: Is the book suitable for self-study?

    répondre: Yes, this book is well-structured for self-study. It provides clear explanations, progressive examples, and exercises that reinforce learning. Additionally, the logical flow aids readers in building their understanding incrementally. Many readers have found it helpful for independent learning, especially when supplemented with online resources or forums for additional support.
  • question: Where can I buy 'Computational Physics: Problem Solving with Python 3rd Edition' in Réunion?

    répondre: You can purchase 'Computational Physics: Problem Solving with Python 3rd Edition' on Ubuy. Ubuy offers a reliable platform for finding various books and educational materials. They provide a user-friendly experience for browsing and selecting your items, ensuring you get the resources you need for your studies.

Python Editorial Review

This book has received mixed reviews from customers. Some have found it to be poorly edited, with numerous typos and errors throughout. They also mention that there is no errata available for this edition. Due to these issues, they do not believe it is worth the high price. Others, however, have praised the book for its clear explanations and helpful code examples. They also appreciate the additional online lectures. Overall, if you are looking for a computational physics book, it may be best to consider other options.

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Avantages

  • Great explanations of challenging subjects
  • Helpful code examples
  • Additional online lectures

Les inconvénients

  • Poorly edited with numerous typos and errors

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Caractéristiques et avantages

  • Textbook provides broad survey of modern computational physics
  • Rooted in learning through hands-on experience and Python programming
  • Designed for upper-level undergraduate or beginning graduate courses
  • Encourages problem-based learning with sample problems at beginning of each chapter
  • Includes exercises and problems at end of each chapter
  • Model programs provided for exercises and problems

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