Fourier analysis and the sinusoidal plane wave

In summary, the Fourier transform is a mathematical tool used to analyze functions in terms of their frequency components. It involves taking a function in the time domain and converting it to the frequency domain, and vice versa. The signs and factors used in the Fourier transformation are arbitrary, but it is important to stick to conventions in the field. The Fourier transform can also be used to analyze waves in terms of their frequency components, and can help in solving linear equations by breaking them down into individual frequency components.
  • #1
BacalhauGT
21
1
hey

So Fourrier transform is

##f(t) = \frac{1}{2 \pi} \int_{-\infty}^{\infty} F(\omega) e^{i \omega t} d\omega##

with

##F(\omega) = \int_{-\infty}^{\infty} f(t) e^{-i \omega t} dt##

Question 1 - The Fourier mode for the continuous case is ## \frac{1}{2 \pi} F(\omega) e^{i \omega t}##, is it right?

So a function can be written as a superposition of Fourier modes.

Question 2 - Why does the sinusoidal plane wave is always considered in the form

##\phi(x,t) = A \exp [i (k x - \omega t)]## ?

I mean, Should it be ##\phi(x,t) = A \exp [i (kx + \omega t)]## ? Because this is the form of two dimensional Fourier mode for x and t.

So using this, it makes sense for me analysing the linear equations using a Fourier mode, because since it is linear, any function can be given by a sum of Fourier modes, so we can see what happens to one frequency and k.

Thank you
 
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  • #2
All the signs and factors in front of the Fourier transformation are arbitrary, but it's good to stick to conventions of your field. You have the sign for the time-frequency FT opposite to what physicists are used to. I've seen this convention in some engineering textbook once. That said concerning question 1, it's correct.

Question 2 adresses the Fourier transform in time and space for the wave equation (setting the phase velocity of the waves to 1 for convenience)
$$(\partial_t^2-\partial_x^2) \phi(x,t)=0.$$
The plane wave you've given first is the one describing a wave moving in positive ##x##-direction, i.e., setting the phase constant, ##k x-\omega t=\text{const}## implies that
$$x=\frac{\omega}{k} t + \text{const}.$$
For the same reason your 2nd mode describes a wave moving in the negative ##x##-direction. A general wave is a superposition of both (and a superposition over ##\omega##).

Here, btw. you use the physicists' sign convention (i.e., a ##-## in front of time in your Fourier mode). Here you can write the solutions of the wave equation as
$$\phi(x,t)=\frac{1}{2 \pi} \int_{\mathbb{R}} \mathrm{d} \omega \left \{A(\omega) \exp[-\mathrm{i} \omega (t-x)] + B(\omega) \exp[-\mathrm{i} \omega (t+x)] \right \},$$
where I used the wave equation to get ##k=\pm \omega##.

Since the wave equation is 2nd order in time you need to give two initial conditions to get a unique solution, i.e., you need to give as initial conditions
$$\phi(0,x)=\phi_0(x), \quad \dot{\phi}(0,x)=\psi_0(x).$$
You can think about, how to determine ##A(\omega)## and ##B(\omega)## given these initial conditions!
 
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  • #3
vanhees71 said:
All the signs and factors in front of the Fourier transformation are arbitrary, but it's good to stick to conventions of your field. You have the sign for the time-frequency FT opposite to what physicists are used to. I've seen this convention in some engineering textbook once. That said concerning question 1, it's correct.

Question 2 adresses the Fourier transform in time and space for the wave equation (setting the phase velocity of the waves to 1 for convenience)
$$(\partial_t^2-\partial_x^2) \phi(x,t)=0.$$
The plane wave you've given first is the one describing a wave moving in positive ##x##-direction, i.e., setting the phase constant, ##k x-\omega t=\text{const}## implies that
$$x=\frac{\omega}{k} t + \text{const}.$$
For the same reason your 2nd mode describes a wave moving in the negative ##x##-direction. A general wave is a superposition of both (and a superposition over ##\omega##).

Here, btw. you use the physicists' sign convention (i.e., a ##-## in front of time in your Fourier mode). Here you can write the solutions of the wave equation as
$$\phi(x,t)=\frac{1}{2 \pi} \int_{\mathbb{R}} \mathrm{d} \omega \left \{A(\omega) \exp[-\mathrm{i} \omega (t-x)] + B(\omega) \exp[-\mathrm{i} \omega (t+x)] \right \},$$
where I used the wave equation to get ##k=\pm \omega##.

Since the wave equation is 2nd order in time you need to give two initial conditions to get a unique solution, i.e., you need to give as initial conditions
$$\phi(0,x)=\phi_0(x), \quad \dot{\phi}(0,x)=\psi_0(x).$$
You can think about, how to determine ##A(\omega)## and ##B(\omega)## given these initial conditions!

Thank you. But please let me clarify one thing. I still don't get why the signs of the Fourier transformation are arbitrary. Can you explain me?

So Fourrier transform is

##f(t) = \frac{1}{2 \pi} \int_{-\infty}^{\infty} F(\omega) e^{i \omega t} d\omega## with ##F(\omega) = \int_{-\infty}^{\infty} f(t) e^{-i \omega t} dt##

can i write:

##f(t) = \frac{1}{2 \pi} \int_{-\infty}^{\infty} F(\omega) e^{-i \omega t} d\omega## with ##F(\omega) = \int_{-\infty}^{\infty} f(t) e^{+i \omega t} dt##

Please check if that's the reason: This is because since the domain is ##-\infty## to ##\infty##, so integrating in ##\omega## covers the positive and negative ##\omega##. So making ##\omega \rightarrow -\omega'##:

##f(t) = \frac{1}{2 \pi} \int_{-\infty}^{\infty} F(\omega) e^{i \omega t} d\omega = \frac{1}{2 \pi} \int_{\infty}^{-\infty} F(-\omega') e^{i -\omega' t} - d\omega' =\frac{1}{2 \pi} \int_{-\infty}^{\infty} F(-\omega') e^{i -\omega' t} d\omega' = \frac{1}{2 \pi} \int_{-\infty}^{\infty} F'(\omega') e^{i -\omega' t} d\omega'##

Is this correct?

So:

##f(t) = \frac{1}{2 \pi} \int_{-\infty}^{\infty} F(\omega) e^{ \pm i \omega t} d\omega## with ##F(\omega) = \int_{-\infty}^{\infty} f(t) e^{\mp i \omega t} dt##
 
  • #4
The signs are indeed arbitrary and so is the place where we put the 2pi normalization constant. That's indeed because we can just as easily use ##\omega'=-\omega##, and we can put the 2pi also in the other equation, or divide a ##\sqrt{2\pi}## over the 2 of them.

However, the first equation that you have called the Fourier transform is usually called the inverse Fourier transform. And the 2nd equation is usually called the Fourier transform. Together they form a Fourier transform pair.
 
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  • #5
I like Serena said:
The signs are indeed arbitrary and so is the place where we put the 2pi normalization constant. That's indeed because we can just as easily use ##\omega'=-\omega##, and we can put the 2pi also in the other equation, or divide a ##\sqrt{2\pi}## over the 2 of them.

However, the first equation that you have called the Fourier transform is usually called the inverse Fourier transform. And the 2nd equation is usually called the Fourier transform. Together they form a Fourier transform pair.
thank you. It was a distraction
 
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  • #6
btw, can anyone recommend me a book for Fourier analysis with applications in physics? thank you
 
  • #8

FAQ: Fourier analysis and the sinusoidal plane wave

1. What is Fourier analysis?

Fourier analysis is a mathematical tool used to break down complex signals or functions into simpler components. It is based on the idea that any signal can be represented as a combination of sinusoidal waves with different frequencies, amplitudes, and phases.

2. What is a sinusoidal plane wave?

A sinusoidal plane wave is a type of wave that travels in a straight line through space. It is characterized by a sinusoidal shape, with a constant amplitude and frequency. These waves are used in Fourier analysis as building blocks to represent more complex signals.

3. Why is Fourier analysis important?

Fourier analysis has many applications in science and engineering. It is used to analyze and process signals in fields such as communication, audio and image processing, and physics. It also has applications in solving differential equations and studying the behavior of physical systems.

4. How is Fourier analysis performed?

Fourier analysis involves decomposing a signal into its constituent sinusoidal waves through a process called Fourier transform. This can be done using mathematical formulas or with the help of computer algorithms. The result is a representation of the signal in the frequency domain, where the amplitude and phase of each component wave can be analyzed.

5. Are there any limitations to Fourier analysis?

While Fourier analysis is a powerful tool, it does have some limitations. It assumes that the signal being analyzed is periodic, meaning it repeats itself infinitely. It also assumes that the signal is continuous and has a well-defined Fourier transform. In some cases, these assumptions may not hold true, leading to errors in the analysis.

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