Generalized functions (distributions) problem - Mathematical physics

In summary: Fourier transform of sine.Thanks Vela! That did the trick, I'll post the full solution later. :)Right guys so here it is, me and my buddies came up with this solution to the problem. We have established that our distribution should be g_n(x) = \theta(x - n) - \theta(x + n) Like Vela said, the Fourier transform of this sine resembles our distribution differentiated. So that means we have \frac{d}{d\xi} \mathcal{F} \left\{ \frac{\sin{(nx)}}{\pi x} \right\}(\xi
  • #1
Sigurdsson
25
1

Homework Statement


Find a distribution [tex]g_n[/tex] which satisfies
[tex] g'_n(x) = \delta(x - n) - \delta(x + n) [/tex]
and use it to prove
[tex] \lim_{n \to \infty} \frac{\sin{nx}}{\pi x} = \delta(x) [/tex]


Homework Equations


Nothing relevant comes up at the moment.


The Attempt at a Solution


Well the first part is pretty easy I think. The distribution would be
[tex] g_n(x) = \theta(x - n) - \theta(x + n) = \left\{ \begin{array}{l l}
-1 & \quad |x| < n \\
0 & \quad |x| \geq n \\
\end{array} \right.[/tex]


The limit will indeed resemble a delta function when [tex]n[/tex] goes to infinity and π is probably just a normalization constant. But applying the two Heaviside functions to solve this has got me stumped.

P.S. Gotta catch some sleep, I will be back in 7 hours hopefully with some ideas to solve this.

Cheers
 
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  • #2
g' looks like the Fourier transform of sine.
 
  • #3
Thanks Vela! That did the trick, I'll post the full solution later. :)
 
  • #4
Right guys so here it is, me and my buddies came up with this solution to the problem.

So we have established that our distribution should be
[tex] g_n(x) = \theta(x - n) - \theta(x + n) [/tex]
Like Vela said, the Fourier transform of this sine resembles our distribution differentiated. So that means we have (using Euler equation for sine)
[tex] \frac{d}{d\xi} \mathcal{F} \left\{ \frac{\sin{(nx)}}{\pi x} \right\}(\xi) = \frac{d}{d \xi} \int \frac{1}{\pi x} e^{i \xi x} \left( \frac{e^{inx} - e^{-inx} }{2i} \right) dx = \int \frac{i x}{2 i \pi x} e^{i\xi x} (e^{inx} - e^{-inx}) dx [/tex]
[tex] = \frac{1}{2\pi} \int e^{ix(\xi +n)} - e^{ix(\xi - n)} dx = \frac{2\pi}{2\pi} \left( \delta(\xi + n) - \delta(\xi - n) \right) = \frac{d}{d\xi} \left( \theta(\xi + n) - \theta(\xi - n) \right) = \frac{d}{d\xi} (- g_n(\xi)) [/tex]
If we look at the limit of our distribution. You can easily see that it will become unity. (You can plot those heaviside functions and see for yourself).
[tex]\lim_{n \to \infty} (- g_n(\xi)) = 1 [/tex]
Using inverse Fourier-Transform we have
[tex] \mathcal{F}^{-1} \mathcal{F} \left\{ \frac{\sin{(nx)}}{\pi x} \right\}(\xi) = \mathcal{F}^{-1} \{1\}(x) = \delta(x) [/tex]
Which ultimately proves what was supposed to prove
[tex]\lim_{n \to \infty} \frac{\sin{(n x)}}{\pi x} = \delta(x) [/tex]


gg
 
  • #5
!I would like to offer some guidance on how to approach this problem. First, let's define the Dirac delta function as a distribution, denoted by δ(x), which satisfies the following properties:

1. δ(x) = 0 for x≠0
2. ∫ δ(x)dx = 1
3. For any smooth function ƒ(x), ∫ ƒ(x)δ(x)dx = ƒ(0)

Next, let's use the fact that the derivative of the Heaviside step function, θ(x), is the Dirac delta function, δ(x), and that the derivative of a constant function is 0. Therefore, we can rewrite the given equation as:

g'_n(x) = -θ'(x - n) + θ'(x + n)

Now, let's use the properties of the delta function to solve for g_n(x):

g_n(x) = -θ(x - n) + θ(x + n) + C

where C is a constant. To determine the value of C, we can use the fact that g_n(x) must be continuous at x = n and x = -n. This means that g_n(n) = g_n(-n). Substituting in the above equation, we get:

-θ(n - n) + θ(n + n) + C = -1
-θ(-n - n) + θ(-n + n) + C = 0

Simplifying, we get:

-θ(n) + θ(2n) + C = -1
θ(n) + C = 0

Solving for C, we get C = 1. Therefore, the final distribution is:

g_n(x) = -θ(x - n) + θ(x + n) + 1

Now, to prove the given limit, we can use the fact that the derivative of sin(nx)/πx is equal to δ(x - n) - δ(x + n), which is the same as g_n(x). Therefore, we can write:

∫ g_n(x) sin(nx)/πx dx = ∫ (δ(x - n) - δ(x + n)) sin(nx)/πx dx

Using the properties of the delta function, we can rewrite this as:

∫ g_n(x) sin(nx)/πx dx
 

FAQ: Generalized functions (distributions) problem - Mathematical physics

What are generalized functions (distributions) in mathematical physics?

Generalized functions, also known as distributions, are a mathematical concept used in the field of mathematical physics to describe and analyze physical phenomena that cannot be described by traditional mathematical functions. These functions are defined as a linear functional on a certain space of test functions, and they allow for the representation of singularities and discontinuities in physical systems.

How are generalized functions used in mathematical physics?

Generalized functions are used in mathematical physics to model and analyze physical systems with non-smooth behavior, such as point charges or delta functions. They are also used in solving partial differential equations and in Fourier analysis to represent signals with discontinuities.

What are some examples of generalized functions in mathematical physics?

Some examples of generalized functions include the Dirac delta function, Heaviside step function, and the sign function. These functions are commonly used to represent point sources, step changes, and jumps in physical systems.

What are the properties of generalized functions?

Generalized functions have several important properties, including linearity, translation invariance, and differentiation. They also have a distributional derivative, which allows for the differentiation of discontinuous functions.

What is the significance of generalized functions in mathematical physics?

Generalized functions are significant in mathematical physics because they provide a powerful tool for modeling and analyzing physical systems with non-smooth behavior. They also allow for the solution of complex differential equations and provide a framework for understanding the behavior of physical systems at singular points.

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