Learn Fourier Transforms: Books & Applications for QM

  • Context: Graduate 
  • Thread starter Thread starter kashokjayaram
  • Start date Start date
  • Tags Tags
    Fourier
Click For Summary

Discussion Overview

The discussion centers around the exploration of Fourier transforms, their applications, particularly in quantum mechanics, and recommendations for books that can aid in understanding these concepts. Participants share their insights on the mathematical foundations and physical interpretations of Fourier transforms and related topics.

Discussion Character

  • Exploratory
  • Technical explanation
  • Conceptual clarification
  • Debate/contested
  • Mathematical reasoning

Main Points Raised

  • One participant seeks book recommendations on Fourier transforms, emphasizing their relevance in quantum mechanics and expressing difficulty in visualizing the concepts.
  • Another participant reflects on their past struggles with understanding transforms and highlights the importance of the correlation between functions and harmonic components, suggesting that this perspective aids visualization.
  • A recommendation is made for the book "Applied Analysis" by Lanczos, which contains a chapter on harmonic analysis.
  • One participant connects the Fourier Transform to linear algebra, suggesting it can be viewed as an expansion in terms of plane waves, with orthogonality playing a role in understanding the process.
  • Another participant proposes starting with Fourier series as a more intuitive introduction, explaining how periodic functions can be represented as sums of cosines and sines, and how this leads to the Fourier transform as a generalization for non-periodic functions.
  • A participant shares their preference for a physical interpretation of Fourier transforms, likening the process to scanning a time domain signal with a frequency probe, which they believe aligns with the original poster's desire for tangible understanding.
  • One participant challenges a mathematical statement regarding the integral of cosine functions, providing a more rigorous formulation and noting the importance of keeping the integral finite.
  • A later reply acknowledges the need for rigor in the previous mathematical discussion, relating it to hardware concepts like synchronous detectors and spectrum analyzers.
  • Another participant emphasizes the significance of linear algebra and differential equations in understanding Fourier transforms.

Areas of Agreement / Disagreement

Participants express a range of views on the best approach to understanding Fourier transforms, with some advocating for starting with Fourier series while others emphasize the importance of mathematical rigor. There is no consensus on a single method or resource, indicating multiple competing perspectives remain.

Contextual Notes

Some discussions involve assumptions about mathematical rigor and physical interpretations that may not be universally accepted. The conversation reflects varying levels of familiarity with the concepts and the need for clarity in mathematical expressions.

Who May Find This Useful

This discussion may be useful for students and enthusiasts of physics and mathematics, particularly those interested in Fourier transforms, their applications in quantum mechanics, and the underlying mathematical principles.

kashokjayaram
Messages
15
Reaction score
0
Can anybody helps in suggesting books on Fourier transforms and applications. I have seen many applications of Fourier transforms. But, I'm not able to visualize what's going on. Fourier transformations are there in Quantum mechanics also. It will be helpful in learning quantum mechanics.

Thanks
 
Physics news on Phys.org
Many years ago I was really stumped for an understanding of the idea of transforms, convolution, correlation, modulation etc etc.
The thing that tipped the balance for me (to allow me to visualise the process) was when I looked again at the identity:

∫(-∞ to +∞) A Cos(ax) Cos(bx) dx is zero except for a = b, when it equals A

(If you avoid using the exponential notation, it is easier to explain.)
If you accept that any function f(t) can actually be represented by an infinite sum of simple harmonic functions then putting f(t) in the above gives you

∫(-∞ to +∞) f(t)Cos(bt) dt, which is the amplitude of the Cos(bx) component of f(x). That is what the Fourier transform does - it shows the correlation between your function (as a function of time) and the harmonic function with a particular angular frequency b over the whole range of b values - which shows it as a function of frequency.
I really must get to grips with writing equations better! but I think the above says what I mean. You need to tart it up a bit, with exponential notation but the basic idea is the correlation between the time function and what is, effectively, a swept frequency - to give the frequency function.
 
The book by Lanczos, Applied Analysis, has a nice chapter on harmonic analysis.
 
If you've taken any Linear Algebra, you can think of the Fourier Transform of a function as an expansion in terms of plane waves.
Sophiecentaur's observation of can then be understood as a result of orthogonality.
 
I think maybe it is easiest to start with Fourier series. Because then you can clearly see that you are really just writing out some periodic function as a sum of cosines and sines. Which is fairly intuitive in my opinion. Also, you can directly calculate the partial Fourier series (i.e. only use the first few terms), and you will see that the partial Fourier series will already approximately look like the periodic function you are trying to represent. And the more terms you add to your series, the more it will look like the function you are trying to represent.

And then, the Fourier transform can be seen as a generalization of the Fourier series. The Fourier transform can be used on non-periodic functions. So, roughly speaking, as the period of our function tends to infinity, we must use a continuum of frequencies, rather than discretely spaced frequencies. So we must use an integral, instead of a series.
 
I have no problem with the Maths but I like the almost physical process of 'scanning' the time domain test signal with a swept probe frequency and working out what!s there at each frequency step. It is a direct equivalent to the old spectrum analyser. The OP seemed to be after something tangible and my approach is along those lines.
 
sophiecentaur said:
∫(-∞ to +∞) A Cos(ax) Cos(bx) dx is zero except for a = b, when it equals A


That's not quite right, as you can see in the case [itex]a=b=0[/itex]. Then that integral gives infinity, rather than [itex].<br /> <br /> The correct statement is this:<br /> <br /> <div style="margin-left: 20px">For [itex]a > 0, b > 0[/itex], the limit as [itex]L \rightarrow \infty[/itex] of<br /> <br /> [itex]\dfrac{1}{L} \int_{-L}^{+L} A cos(a x) cos(b x) dx[/itex]<br /> <br /> is equal to [itex]A[/itex] if [itex]a=b[/itex]<br /> is equal to [itex]0[/itex] if [itex]a \neq b[/itex].<br />​</div>[/itex]
 
Thanks for adding the rigour. I had a feeling that it needed something to keep the integral finite. It's been a long time . . . . .
The hardware equivalent is a synchronous detector / homodyne receiver followed by an integrator with a period that relates to L in your expression - really not very different from a spectrum analyser (which looks at an intermediate frequency just above zero)
 
Linear algebra and Diffs Eq. is the key here!
 

Similar threads

  • · Replies 4 ·
Replies
4
Views
4K
  • · Replies 14 ·
Replies
14
Views
5K
  • · Replies 5 ·
Replies
5
Views
2K
  • · Replies 4 ·
Replies
4
Views
3K
  • · Replies 6 ·
Replies
6
Views
14K
  • · Replies 4 ·
Replies
4
Views
3K
  • · Replies 7 ·
Replies
7
Views
789
  • · Replies 1 ·
Replies
1
Views
2K
  • · Replies 4 ·
Replies
4
Views
4K
  • · Replies 2 ·
Replies
2
Views
1K