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Numerical Methods for Physics (Python)
85% من المشترين سيوصون بهذا المنتج لصديق
IQD 34410
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Covers a broad spectrum of the most important, basic numerical and analytical techniques used in physics, including ordinary and partial differential equations, linear algebra, Fourier transforms, integration, and probability.
شحن
سريع
استرجاع
مجاني*
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منتجات أصلية %100
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تفاصيل المنتج
| Publisher | CreateSpace Independent Publishing Platform |
| Publication date | July 12, 2017 |
| Edition | Second, Revised (Python) |
| Language | English |
| Print length | 350 pages |
| ISBN-10 | 1548865494 |
| ISBN-13 | 978-1548865498 |
| Item Weight | 1.72 pounds (780 grams) |
| Dimensions | 8 x 0.79 x 10 inches (20.3 x 2 x 25.4 cm) |
من يجب أن يشتري؟
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Physics Students
Ideal for undergraduate or graduate students studying physics, as it covers essential numerical methods using Python.
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Self-learners
Great resource for individuals looking to independently learn numerical methods and Python for practical applications.
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Educators
Useful for professors and teachers seeking comprehensive teaching materials on numerical methods in physics with hands-on coding.
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Complete Beginners
Not suitable for users with no prior programming or mathematical background, as it assumes some knowledge.
وصف المنتج
Numerical Methods for Physics (Python)
أسئلة العملاء & الإجابات
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سؤال:
What are the main topics covered in 'Numerical Methods for Physics Python Second, Revised Python Edition'?
إجابه: This book covers a wide range of topics essential for solving various problems in physics using numerical methods. Key areas include root finding, interpolation, numerical integration, and solving ordinary differential equations. Detailed explanations and Python implementations accompany each method, making it suitable for both beginners and advanced learners. For instance, students may apply these techniques to model physical systems or analyze experimental data, enhancing their understanding and practical skills in computational physics. -
سؤال:
Who is the intended audience for this book?
إجابه: The intended audience for 'Numerical Methods for Physics Python Second, Revised Python Edition' includes undergraduate and graduate students in physics or related fields, as well as researchers looking to enhance their computational skills. The text is tailored to those who wish to apply Python programming to solve real-world physics problems. Regardless of whether readers are new to numerical methods or seeking to deepen their knowledge, this book provides a comprehensive resource for practical learning. -
سؤال:
What programming skills are required to understand this book?
إجابه: While 'Numerical Methods for Physics Python Second, Revised Python Edition' is designed for a range of skill levels, a foundational understanding of Python programming is beneficial. Readers should be familiar with basic programming concepts such as variables, loops, and functions. However, the book includes explanations and code snippets that guide learners through each numerical method. This makes it a great resource for those looking to introduce programming into their physics studies, bridging the gap between theory and computational practice. -
سؤال:
Does the book include practical examples or exercises?
إجابه: Yes, the book is rich in practical examples and exercises that encourage hands-on learning. Each chapter typically concludes with problems that challenge readers to apply the numerical methods discussed. These exercises help solidify concepts and are particularly useful for students working on projects or those who wish to practice their coding skills. For instance, a student might solve a complex physics simulation project by applying the learned numerical techniques, reinforcing their understanding through real applications. -
سؤال:
Is this book suitable for self-study?
إجابه: Absolutely! 'Numerical Methods for Physics Python Second, Revised Python Edition' is well-structured for self-study, featuring clear explanations and examples that allow learners to progress at their own pace. Each chapter builds upon the previous one, providing a cohesive learning experience. Self-learners can easily follow along with the Python programming exercises, making it an excellent choice for independent study or supplementary material for academic courses. -
سؤال:
How does this book compare to other numerical methods texts?
إجابه: Compared to other numerical methods texts, 'Numerical Methods for Physics Python Second, Revised Python Edition' stands out due to its focus on Python as a programming tool. While many texts cover similar mathematical concepts, this book emphasizes practical application through coding. The integration of Python makes it accessible for modern learners who value computational approaches in physics. Additionally, its clear explanations and thorough examples set it apart, making it both informative and user-friendly. -
سؤال:
Can this book help with computational physics research?
إجابه: Yes, it can significantly aid in computational physics research by providing essential numerical techniques used in modeling and simulation. Researchers can use the methods discussed to analyze experiments, perform simulations, and develop models of physical phenomena. The Python codes serve as a practical reference, allowing researchers to adapt the examples to their specific needs. This book equips researchers with the tools necessary to tackle advanced problems in computational physics effectively. -
سؤال:
What edition is this book, and what are the improvements from previous editions?
إجابه: This is the second, revised edition of 'Numerical Methods for Physics Python'. The updates include enhanced explanations, new examples, and improved clarity in presenting complex concepts. Feedback from users of the first edition informed revisions, making this edition more accessible and easier to follow. New topics may also be incorporated, addressing advancements in Python as a programming language, ensuring that readers learn the most current approaches in computational physics. -
سؤال:
What is the level of mathematical background needed for this book?
إجابه: A solid understanding of calculus and basic linear algebra is recommended for readers of 'Numerical Methods for Physics Python Second, Revised Python Edition'. Familiarity with these mathematical concepts is crucial as the numerical methods often rely on them for formulation and understanding. However, the book offers explanations that bridge the gap, making it approachable for a wide range of readers. Advanced students can benefit from refreshing their mathematical knowledge in the context of computational applications. -
سؤال:
Where can I buy 'Numerical Methods for Physics Python Second, Revised Python Edition' in Iraq?
إجابه: You can purchase 'Numerical Methods for Physics Python Second, Revised Python Edition' on Ubuy, a reliable online retailer that offers various products, including books. Ubuy provides a user-friendly platform to find your desired title with multiple purchasing options in Iraq. They ensure a seamless shopping experience, making it easy for you to access this valuable resource for your studies.
Mathematical Physics Editorial Review
Python texts for web development, artificial intelligence, and machine learning are ubiquitous. There are few, however, developed specifically as treatments for solving physical problems using computational numerical methods. This text does that. The treatments of the techniques are useful, with many real-world applications. However, the book is not updated for newer versions of Python and the code structures leave something to be desired.
مراجعات العملاء وتقييماتهم
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أضف تقييم لهذا المنتج
شارك أفكارك مع عملاء آخرين
إيجابيات
- Provides treatments for solving physical problems using computational numerical methods
- Useful techniques with real-world applications
سلبيات
- Not updated for newer versions of Python
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IQD 34410
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المميزات والفوائد
- Comprehensive coverage of essential numerical and analytical techniques in physics
- Utilizes Python with additional Matlab, C++, and FORTRAN versions available online
- Includes topics such as ordinary and partial differential equations, linear algebra, Fourier transforms, integration, and probability
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