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Item #:
87866601
Numerical Methods in Physics with Python
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Item #:
87866601
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This is an ideal standalone textbook for courses on computational physics.
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What Stands Out
Comprehensive Coverage
This edition offers an in-depth exploration of numerical methods specifically tailored for physics applications, ensuring that users grasp complex concepts effectively.
Python Integration
Seamless integration of Python throughout the text allows readers to apply numerical methods practically, enhancing both learning and software skills relevant in modern scientific computing.
Updated Examples
The second edition features revised examples and exercises that reflect current trends in physics, providing students with relevant, hands-on experience to solve real-world problems.
Product Details
| Publisher | Cambridge University Press |
| Publication date | July 20, 2023 |
| Edition | 2nd |
| Language | English |
| Print length | 706 pages |
| ISBN-10 | 1009303864 |
| ISBN-13 | 978-1009303866 |
| Item Weight | 2.9 pounds (1.32 kg) |
| Dimensions | 7 x 1.59 x 10 inches (17.8 x 4 x 25.4 cm) |
Who Should Buy?
-
Physics Students
Ideal for undergraduate physics students seeking to understand numerical methods and computational tools in their studies.
-
Python Programmers
Beneficial for programmers wanting to apply Python in solving complex physics problems through numerical methods.
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Researchers
Useful for researchers in physics who require numerical techniques for simulations and modeling in their projects.
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Complete Beginners
Not suitable for those without prior knowledge of Python or numerical methods, as it requires foundational understanding.
Product Description
Numerical Methods in Physics with Python
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Customer Questions & Answers
-
Question:
What is the focus of the Numerical Methods in Physics with Python 2nd Edition?
Answer: The focus of this edition is on applying numerical methods to solve physics problems using Python. It caters to both beginners and experienced programmers by providing practical examples and applications of numerical techniques, such as solving differential equations, performing integration, and simulating physical situations. This makes it an excellent resource for students and professionals who want to enhance their computational skills in physics. -
Question:
Who is the target audience for this book?
Answer: The target audience includes undergraduate and graduate students in physics, engineering, and computational science programs, as well as professionals working in research who need to apply numerical methods in their work. Additionally, educators looking for a comprehensive guide to teaching computational physics will find it valuable. -
Question:
What programming languages are used in this book?
Answer: This book predominantly uses Python for implementing numerical methods, making it accessible and relevant given Python's popularity in scientific computing. The code examples provided are well-commented, allowing readers to understand the implementation of methods without needing deep programming expertise. -
Question:
Can beginners understand the content in this book?
Answer: Yes, beginners can understand the content as the book starts with foundational concepts before progressing to more complex topics. Each chapter includes clear explanations and step-by-step examples, allowing readers to build their understanding gradually and gain confidence in using numerical methods for solving physics problems. -
Question:
What kind of problems does the book address?
Answer: The book addresses a variety of problems in physics, including classical mechanics, electromagnetism, quantum mechanics, and statistical mechanics. It provides a practical approach to solving these problems through numerical methods, making theoretical concepts more tangible and applicable. -
Question:
Does the book include resources for further learning?
Answer: Yes, it includes a host of resources for further learning, such as references to other books, online tutorials, and access to Python libraries that are essential for numerical computing. These resources enhance the learning experience by providing pathways for deeper exploration into numerical methods and their applications. -
Question:
Is there an accompanying code repository for this book?
Answer: Yes, there is an accompanying code repository that provides access to all the code examples used in the book. This can be particularly helpful for readers who want to run the code and experiment with the examples directly, allowing for a hands-on learning experience. -
Question:
How does the second edition differ from the first edition?
Answer: The second edition is updated with new content, additional examples, and enhanced explanations that reflect the latest advancements in numerical methods and Python programming. Readers can expect improved clarity, more practical applications, and additional exercises that facilitate a deeper understanding of the material. -
Question:
Are there practical exercises included in the book?
Answer: Yes, the book includes practical exercises at the end of each chapter that challenge readers to apply what they've learned. These exercises range from straightforward programming tasks to complex problem-solving scenarios, enhancing the practical skills necessary for tackling real-world physics problems. -
Question:
Where can I buy Numerical Methods in Physics with Python 2nd Edition?
Answer: You can buy Numerical Methods in Physics with Python 2nd Edition from Ubuy available in Mayotte. Ubuy is a trusted online platform that stocks a variety of educational books with convenient browsing and purchasing options, ensuring an accessible buying experience for readers.
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€ 65
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Features & Benefits
- Combines idiomatic Python programming with foundational numerical methods.
- Covers a comprehensive range of numerical methods used in physics.
- Includes 140 new problems and several new codes for enhanced learning.
- Features new sections on advanced topics like neural networks and Bayesian regression.
- Each chapter concludes with an in-depth project addressing complex physics problems.
- Perfect for students new to computational physics, facilitating quick mastery of Python.
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