Fourier's Trick and calculation of Cn

In summary, the solutions to the time-independent Schrodinger equation are complete, meaning that a linear combination of the wavefunctions can describe any function (i.e. ##f(x) = \sum_{n = 1}^{\infty}c_n\psi_n(x) = \sqrt{\frac{2}{a}} \sum_{n=1}^{\infty} c_n\sin\left(\frac{n\pi}{a}x\right)## for the infinite well case). The Kronecker delta allows us to find the coefficients ##c_m## and ##c_n## through the dot product-like calculation of ##\sum_{n=1}^{\infty}c_n\delta_{
  • #1
I_laff
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I understand that the solutions to the time-independent Schrodinger equation are complete, so a linear combination of the wavefunctions can describe any function (i.e. ##f(x) = \sum_{n = 1}^{\infty}c_n\psi_n(x) = \sqrt{\frac{2}{a}} \sum_{n=1}^{\infty} c_n\sin\left(\frac{n\pi}{a}x\right)## for the infinite well case).

I don't understand how using Fourier's trick allows you to calculate ##c_n##. Also, I don't understand how ##\sum_{n=1}^{\infty}c_n\delta_{mn} = c_m##. I get that the Kronecker delta comes out of the fact that ##\psi_m^\ast(x)## and ##\psi_n(x)## are orthogonal. I understand that when ##m = n##, then the Kronecker delta equals 1, but how does this allow us to find ##c_m## and ##c_n## .
$$ \int_{0}^{a} \psi_m^\ast(x) f(x)\mathrm dx = \sum_{n=1}^{\infty}c_n \int_{0}^{a} \psi_m^\ast (x)\psi_n(x)\mathrm dx = \sum_{n=1}^{\infty}c_n\delta_{mn} = c_m $$
 
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  • #2
I_laff said:
I don't understand how using Fourier's trick allows you to calculate ##c_n##.
Read up on Fourier transforms in any textbook of your liking.

Also, I don't understand how ##\sum_{n=1}^{\infty}c_n\delta_{mn} = c_m##
That's because ##\delta=0## unless m = n; then it's 1. :rolleyes:

Fourier analysis is a bit more than just a 'trick' :mad:
 
  • #3
BvU said:
Fourier analysis is a bit more than just a 'trick'

I referred to it as a trick because that's what the material I was reading referred to it as. I'll take a look into Fourier transforms then.
 
  • #4
I_laff said:
I referred to it as a trick because that's what the material I was reading referred to it as. I'll take a look into Fourier transforms then.
What was that material? You'll generally get better answers if you identify your sources - chances are that someone here is already familiar with it.

(I remember that exact phrase "Fourier's trick" appearing in a thread here a while back)
 
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  • #5
It was from Griffiths, Introduction to quantum mechanics second edition chapter 2
 
  • #6
Found it on p 28. (and you are not responsible for his wording :smile:)
Now I'm puzzled about your question: you reproduce the line that works out ##c_m##, so that should answer it !?

(##c_n## does not come out, though! n is just a summation variable)
 
  • #7
I understand the properties of the Kronecker delta, what I didn't understand was why ##c_m## came out. So, let me get this right. When applying the Kronecker delta to ##\sum_{n = 1}^{\infty} c_n##, you will get a coefficient value that both ##\psi_n## and ##\psi_m## share (due to the properties of ##\delta_{mn}##)?

What I misunderstood previously, was that I thought ##\psi_m## consisted of multiple coefficients, and so ##\delta_{mn}## when applied would work out the mutual coefficients between ##\psi_n## and ##\psi_m##, however only one coefficient (##c_m##) was stated.
 
  • #8
Think of it like a dot product. If I have a 3D vector [itex] \overrightarrow{V} = V_x \overrightarrow{e_x} + V_y \overrightarrow{e_y} + V_z \overrightarrow{e_z}[/itex], and I take the dot product with a unit vector, I get [itex] \overrightarrow{V} \centerdot \overrightarrow{e_x} = V_x[/itex]. this is because the unit vectors are orthogonal, so the dot product "picks off" the component along the x-axis. It's exactly the same in Fourier analysis, even though there are an infinite number of "unit vectors".
 
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  • #9
Ah, that's a nice way to think about it :ok:
 

1. What is Fourier's Trick?

Fourier's Trick is a mathematical technique used to simplify the calculation of complex integrals involving trigonometric functions, by converting them into sums of simpler integrals. This trick involves using the properties of the Fourier series, which is a mathematical representation of a periodic function as a combination of sine and cosine functions.

2. How does Fourier's Trick help in calculating Cn?

Fourier's Trick simplifies the calculation of Cn, which represents the coefficient of the nth term in the Fourier series. By using this technique, we can convert the integral for Cn into a simpler form, which can then be easily evaluated. This saves time and effort in calculating the coefficients for a given function.

3. Can Fourier's Trick be used for any function?

No, Fourier's Trick can only be applied to functions that are periodic and satisfy certain conditions, such as being continuous and having a finite number of discontinuities. It is also important for the function to have a well-defined Fourier series representation.

4. What is the significance of calculating Cn?

Calculating Cn allows us to determine the amplitude and phase of each term in the Fourier series, which helps us understand the behavior of a periodic function. It also enables us to approximate a given function using a finite number of terms in its Fourier series, which can be useful in various applications in mathematics and engineering.

5. Can Fourier's Trick be extended to multidimensional problems?

Yes, Fourier's Trick can be extended to solve multidimensional problems, where the functions are periodic in multiple dimensions. In this case, the Fourier series becomes a multidimensional representation and the calculation of Cn involves multiple integrals. This technique is commonly used in solving partial differential equations in physics and engineering.

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