Expand function as series of eigenfunctions

In summary: Read moreand 1 + \cot^2 \beta = \dfrac{4 + \beta^2}{\beta^2} = \dfrac{1}{\sin^2 ... Read more. Then, you have \dfrac{1}{1 + \tan^2 \beta} = 1 - \tan^2 \beta = 1 - \sin^2 \beta = \cos^2 \beta, \quad \text{and} \quad \dfrac{1}{1 + \cot^2 \beta} = 1 - \cot^2 \beta = 1 - \cos^2 \beta = \sin^2 \beta. As a result,
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Incand
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Homework Statement


Determine all eigenvalues and eigenfunctions for the Sturm-Liouville problem
\begin{cases}
-e^{-4x}\frac{d}{dx} \left(e^{4x}\frac{d}{dx}\right) = \lambda u, \; \; 0 < x <1\\
u(0)=0, \; \; u'(1)=0
\end{cases}
Expand the function ##e^{-2x}## as a series of eigenfunctions.

Homework Equations


Orthonormal series expansion
##f(x) = \sum_1^\infty \langle f, \phi_n \rangle \phi_n##
where ##\phi_n## is the orthonormal eigenfunctions.

The Attempt at a Solution


I managed to find the eigenvalues and eigenfunctions (correct according to the answer to the exercise) but I'm having trouble expanding the function as a series.
We have from the first part of the exercise (##\lambda## is eigenvalues and ##u## eigenfunctions)
##\lambda_1 = 4-\beta_1^2## where ##\beta_1## is the positive root of ##\tanh \beta = \frac{\beta}{2}##, ##u_1(x) = e^{-2x}\sinh (\beta_1 x)##
##\lambda_n = 4+\beta_n^2## where ##\beta_n##, ##n=2,3,\dots## are the positive roots of ##\tan \beta = \frac{\beta}{2}##, ##u_n(x) = e^{-2x}\sin (\beta_n x)##.

Starting with the part I'm having trouble with. Normalize the eigenfunctions. We have the weight function ##w = e^{4x}## so the norm is given by
##\int_0^1 |f(x)|^2w(x)dx##. We get
##c_1^2\int_0^1 \sinh^2 \beta x dx = c^2 \frac{\sinh (2\beta) -2\beta}{4\beta}## so we have ##c_1^2 = \frac{4\beta}{\sinh (2\beta) -2\beta}##
##c_2^2 \int_0^1 sin^2 \beta x dx = c_1^2 \frac{(2\beta-sin(2\beta))}{4\beta}## so we have
##c_2^2 = \frac{4\beta}{(2\beta-sin(2\beta))}##.

Calculating the coefficients we get
##\int_0^1 \sin (\beta x)dx = \frac{1-\cos \beta}{\beta}## and
##\int_0^1 \sinh (\beta x)dx = \frac{\cosh \beta -1}{\beta}##.
So our series should be given by
##f(x) = \frac{1}{c_1^2} \frac{\cosh \beta -1}{\beta} u_1(x) +\frac{1}{c_2^2}\sum_2^\infty \frac{1-\cos \beta}{\beta}u_n(x) = \frac{(sinh(2b)-2\beta)(\cosh \beta -1)}{4\beta^2}u_1(x)+\sum_2^\infty \frac{2\beta-(\sin (2\beta) )(1-\cos \beta)}{4\beta^2 }u_n(x) ## (Note how we get ##c_1^2## and ##c_2^2## since ##u_n## refers to the old non normalized eigenfunctions and we also get one from the coefficient calculations before.)

I'm pretty sure I made a mistake here already but I keep ending up at the same thing when I redo the exercise. The answer should be
##e^{-2x}=\sum_1^\infty \frac{2\sqrt{\lambda_n}\left[ \sqrt{\lambda_n}+2(-1)^n\right]}{\beta_n(\lambda_n-2)}u_n(x)## which I can't get close to however much algebra I apply.
I suspect I made some conceptual misunderstanding since I can't even get close to the expression in the answer.

Sorry for a rather lenghty post. Thanks a lot to anyone with the patience to take a look at it.
 
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  • #2
First of all, there are several typos for the expression of f(x), the coefficients have to be inverse of them.

You mostly well done, so, I will show an example for [itex] n=2 [/itex]. In this case, [itex] c_2^2 = \frac{4\beta_2}{(2\beta_2 - \sin(2\beta_2))} [/itex] and
[tex] < f, \phi_2 > = c_2 \left( \dfrac{1-\cos\beta_2}{\beta_2} \right). [/tex]
Then,
[tex] < f, \phi_2 > \phi_2 = c_2^2 \left( \dfrac{1-\cos\beta_2}{\beta_2} \right) u_2(x) = \left(\dfrac{4\beta_2}{2\beta_2 - \sin 2\beta_2} \right) \left( \dfrac{1-\cos\beta_2}{\beta_2} \right) u_2(x). [/tex]
From the fact that
[tex] \tan \beta_n = \dfrac{\beta_n}{2}, [/tex]
the sine and cosine function can be obtained by
[tex] \sin \beta_n = (-1)^n \dfrac{\beta_n}{\sqrt{\lambda_n}}, \quad \text{and} \quad \cos\beta_n = (-1)^n \dfrac{2}{\sqrt{\lambda_n}}. [/tex]

By using these things,
[tex]
\begin{array}{rl}
\left(\dfrac{4\beta_2}{2\beta_2 - \sin 2\beta_2} \right) \left( \dfrac{1-\cos\beta_2}{\beta_2} \right) &= \left(\dfrac{4\beta_2}{2\beta_2 - 2 \frac{\beta_2}{\sqrt{\lambda_2}}\frac{2}{\sqrt{\lambda_2}} } \right) \left( \dfrac{1-\frac{2}{\sqrt{\lambda_2}}}{\beta_2} \right) \\
& = \left( \dfrac{4\beta_2 \lambda_2}{2\beta_2 \lambda_2 - 4\beta_2} \right) \left(\dfrac{1-\frac{2}{\sqrt{\lambda_2}}}{\beta_2} \right) \\
& = \dfrac{2 \sqrt{\lambda_2} ( \sqrt{\lambda_2} - 2 )}{(\lambda_2 - 2)\beta_2}.
\end{array}
[/tex]

Therefore,
[tex] < f, \phi_2 > \phi_2 = \dfrac{2 \sqrt{\lambda_2} ( \sqrt{\lambda_2} - 2 )}{(\lambda_2 - 2)\beta_2} u_2(x). [/tex]
 
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  • #3
Thanks a lot! Don't know why I inverted the coefficients again when I already inverted to get them in the first place.
Daeho Ro said:
From the fact that
[tex] \tan \beta_n = \dfrac{\beta_n}{2}, [/tex]
the sine and cosine function can be obtained by
[tex] \sin \beta_n = (-1)^n \dfrac{\beta_n}{\sqrt{\lambda_n}}, \quad \text{and} \quad \cos\beta_n = (-1)^n \dfrac{2}{\sqrt{\lambda_n}}. [/tex]
I'm a little unsure how you get the ##\sin## and ##\cos## functions. I guess you set ##\sin \beta = A\beta_n## and ##\cos \beta = B\beta_n## and then set ##A,B## so that ##\sin^2\beta + \cos^2\beta = 1##.
The ##(-1)^n## (Actually I think it should be ##(-1)^{n+1}##) you get from ##\tan \beta = \frac{\beta}{2}## only having a solution each in intervals of length ##\pi## the first would be ##(\pi/2,3\pi/2), (3\pi/2, 5\pi/5), \dots)##. Is this correct or is there something I'm missing here?For the case with ##n=1## i get from
##\tanh \beta_1= \frac{\beta_1}{2}## that
##\sinh \beta_1 = \frac{\beta_1}{\sqrt{\lambda_1}}## and ##\cosh \beta_1 = \frac{2i}{\sqrt{\lambda_1}}##.
Again I'm not entirely sure about determining these. I just made them satisfy the hyperbolic one, but I got the feeling If I'm not careful here I may get the expressions (luckily it works out in this case).

Edit: Think I got them wrong, edited the post a bit.

So the coefficient is given by
##\frac{4\beta_1}{\sinh 2\beta_1 -2\beta_1}\frac{\cosh \beta_1-1}{\beta_1} = \frac{2(\cosh \beta_1 -1)}{\sinh \beta_1 \cosh b_2 - \beta_1} = \frac{2(2i-\sqrt{\lambda_1})}{\beta_1(2i-\sqrt{\lambda_1)}}## which doesn't look to good.

So I think I mess up when I calculate ##\sinh## and ##\cosh##.
 
Last edited:
  • #4
The sign problem, you are correct. It should start from the negative sign first.

The [itex] \sin \beta [/itex] and [itex] \cos \beta [/itex] just obtained by the properties of trigonometric functions. Let us consider the right angled triangle with width [itex] 2 [/itex] and height [itex] \beta [/itex]. Then, the length of incline is [itex] \sqrt{4 + \beta^2} = \sqrt{\lambda} [/itex]. It gives the result what I used.

If you are still not comfortable, then you might get the same result from
[tex] 1 + \tan^2 \beta = \dfrac{4 + \beta^2}{4} = \dfrac{1}{\cos^2 \beta}. [/tex]
 
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  • #5
Daeho Ro said:
The sign problem, you are correct. It should start from the negative sign first.

The [itex] \sin \beta [/itex] and [itex] \cos \beta [/itex] just obtained by the properties of trigonometric functions. Let us consider the right angled triangle with width [itex] 2 [/itex] and height [itex] \beta [/itex]. Then, the length of incline is [itex] \sqrt{4 + \beta^2} = \sqrt{\lambda} [/itex]. It gives the result what I used.
Thanks!
I also see where I messed up, last part of my post is all wrong. I had forgotten the hyperbolic one and used an incorrect version.

Going to post the rest of the solution incase anyone comes upon this thread in the future
##\sinh \beta = \frac{\beta_1 }{\sqrt{\lambda_1}}## and ##\cosh \beta = \frac{2}{\sqrt{\lambda_1}}##
Then we have
##\frac{4\beta_1}{\sinh 2\beta_1 - 2\beta_1}\frac{\cosh \beta-1}{\beta_1} = \frac{2(\cosh \beta_1-1)}{\sinh \beta_1 \cosh b_1 -\beta_1} = \frac{2(\frac{2}{\sqrt{\lambda}}-1)}{\beta_1(\frac{2}{\lambda_1}-1)} = \frac{2\sqrt\lambda_1(\sqrt{\lambda_1}-2)}{\beta_1(\lambda_1-2)}##
 
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Related to Expand function as series of eigenfunctions

1. What is the "expand function as series of eigenfunctions" concept?

The "expand function as series of eigenfunctions" concept is a mathematical technique used in the field of linear algebra to represent a function as a sum of eigenfunctions, also known as eigenvectors. This allows for a more simplified representation of a function and facilitates the analysis and manipulation of complex systems.

2. How is this concept applied in scientific research?

The "expand function as series of eigenfunctions" concept is often used in scientific research to analyze and understand systems that exhibit complex behavior. It is commonly used in fields such as quantum mechanics, signal processing, and fluid dynamics to model and analyze the behavior of systems and make predictions about their future behavior.

3. What are some advantages of using this technique?

One of the main advantages of using the "expand function as series of eigenfunctions" technique is that it simplifies the representation of a function, making it easier to analyze and manipulate. Additionally, it allows for the study of complex systems through the use of a finite number of eigenfunctions, rather than trying to analyze the entire system at once.

4. Are there any limitations to this concept?

While the "expand function as series of eigenfunctions" concept is a powerful tool in mathematical analysis, it does have some limitations. It may not be applicable to all types of functions, and the accuracy of the results depends on the choice of eigenfunctions used to represent the function. Additionally, it may not always be possible to find a complete set of eigenfunctions for a given function.

5. How can the "expand function as series of eigenfunctions" concept be applied in real-world situations?

The "expand function as series of eigenfunctions" concept has a wide range of applications in real-world situations. It can be used to analyze and predict the behavior of complex systems such as weather patterns, electrical circuits, and financial markets. It is also used in image and sound processing to compress data and improve the efficiency of storage and transmission.

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