Partial Differential Equations book for self-study

In summary, the book "Applied Partial Differential Equations by Richard Haberman" is used in PDE course. It is a decent book for learning techniques, but it has some problems with its writing style. The book by Strauss is also very good, but requires a lot more work on the part of the reader than does the Haberman book. The book "Partial Differential Equations for Scientists and Engineers" by Stephenson is a very short book, which covers the fundamentals of each topic. It is a well written book that is just an outline.
  • #1
rubrix
136
0
I want to self-study partial differential equations.

i have done some pure math course but I wish to keep proofs to minimal. If possible I don't want to be bothered with PDE proofs in my self study. Instead, I want to learn how to apply and solve PDEs.

the ultimate goal is to prepare myself my quantum mechanics course and Applied PDE course. It seems I'll be doing Applied PDE course after QM.

"Applied Partial Differential Equations by Richard Haberman" is used in PDE course.

https://www.amazon.com/dp/0130652431/?tag=pfamazon01-20

any feedback and suggestions will be highly appreciated.

rubrix.
 
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  • #2
I have used the Haberman book and it's decent... for learning techniques.

His style of writing bugs me to no end though. He uses a lot of words to say very little. Furthermore, there are some paragraphs in which the phrase "(non)-homogeneous linear partial differential equation" appears at least once per sentence, which gets very annoying. He also exclusively uses Leibniz notation. In fact, I think the book would be half its current size if he switched to subscripts to indicate partial derivatives, and started sections with a disclaimer like "in this section we will be discussing (non)-homogeneous linear partial differential equations". These are nit-picky points, obviously. All things considered, it's a decent book.

The book by Strauss is also very good, but requires a lot more work on the part of the reader than does the Haberman book.

Edit: I also suggest looking into the PDE book by Farlow as a sort of prelude to other more comprehensive books. Also the book "An Introduction to the Mathematical Theory of Waves" by Knobel is good, it covers a lot of material but not very deeply, and has accessible sections on interesting things like solitons and shocks which are completely avoided or glossed over in other introductory PDE texts.
 
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  • #3
  • #4
I'm not going to buy Haberman until few months before i take the course. Who knows they might just change the text for the course or a newer edition of the book might come out. This book is expensive afterall.

I'll skip over Strauss as it does not seem to be suitable for self-study.

I've heard positive things about Farlow's PDE book before. It is also cheap. So can i get more words on it? Is it suitable for first time PDE learner? I hear it has lots of mistakes.

Also what about Applied PDE by Paul DuChateau?

https://www.amazon.com/dp/0486419762/?tag=pfamazon01-20thnx for the info and online resource both of u :)
 
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  • #5
All You Wanted to Know About Mathematics but Were Afraid to Ask by Lyons is a two-volume set written for physics students. About 3/4 of volume 2 is devoted to PDE stuff. A lot of motivation, examples and intuition is from physics. A lot of emphasis is placed on understanding methods and results, rather than formal proofs. He even has a section on estimating Fourier coefficients simply from the graph of the function!

Partial Differential Equations for Scientists and Engineers by Stephenson is a very short book, which covers the fundamentals of each topic. Few examples and excercises. To-the-point and only 161 pages long. Just an outline. Well written though.
 
  • #6
For beginning pde Hans Weinberger´s book Int. to PDE, is quite good, because it introduces the usual heat-wave eqns. at a beginner´s level. The text is elementary without being needlessly verbose, and makes use of complex numbers as well as some complex analysis. The mathematical sophistication needed is perhaps more than Haberman, but certainly not that of Evan´s PDE, where you would learn hilbert space methods or and prove difficult inequalities in the exercises.
 
  • #7
unfortunately, i have not done a course on complex analysis yet.
 

1. What are partial differential equations (PDEs) and why are they important?

Partial differential equations are mathematical equations that involve multiple variables and their partial derivatives. They are used to model many physical phenomena in fields such as physics, engineering, and economics. PDEs are important because they provide a powerful tool for understanding and predicting behavior in complex systems.

2. Is it necessary to have a strong background in mathematics to study PDEs?

While a strong foundation in mathematics is helpful, it is not always necessary to have a deep understanding of advanced concepts such as real analysis or functional analysis to study PDEs. However, a good understanding of calculus and linear algebra is essential.

3. How can I use a PDE book for self-study?

Self-studying PDEs can be challenging, but with a good textbook and determination, it is definitely possible. Start by familiarizing yourself with the basics of PDEs, such as classification, boundary conditions, and solution techniques. Then, work through example problems and practice exercises to solidify your understanding.

4. Can you recommend a good PDE book for self-study?

There are many great PDE books for self-study, but some popular choices include "Partial Differential Equations: An Introduction" by Walter Strauss, "Partial Differential Equations: Methods and Applications" by J. David Logan, and "A First Course in Partial Differential Equations with Complex Variables and Transform Methods" by H. F. Weinberger.

5. How can I apply my knowledge of PDEs in real-world situations?

PDEs have a wide range of applications in fields such as physics, engineering, and finance. By studying PDEs, you will gain valuable problem-solving skills that can be applied to real-world situations. Some examples include modeling heat transfer in engineering, predicting stock market fluctuations, and understanding the behavior of waves in physics.

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