Kevin McHugh said:
Given the definition:
δ(x) = 0 for all x ≠ 0
∞ for x = 0
∫-∞∞δ(x)dx = 1
I don't understand how the integral can equal unity. The integral from -∞ to zero is zero, and the integral from 0 to ∞ is zero. How can one integrate the discontinuity at zero to equal one? What am I missing? TIA for your insight.
There are two different ways to think of the delta function: (1) As a limit of functions, and (2) as a distribution.
As a limit of functions:
One approach to dealing with the delta function that almost always works is to think of it as an ordinary function that has a parameter, [itex]W[/itex] that in some sense measures how sharp the function is. The delta function is sort of (in a sense to be explained) a limit as [itex]W \rightarrow 0[/itex]
Some examples:
- [itex]\delta(x) \approx \frac{1}{W \sqrt{\pi}} e^{-\frac{x^2}{W^2}}[/itex]
- [itex]\delta(x) \approx \frac{1}{\pi} \frac{sin(\frac{x}{W})}{x}[/itex]
- [itex]\delta(x) \approx \frac{1}{2W}[/itex], if [itex]-W \leq x \leq +W[/itex]), and zero otherwise.
In all three cases, the function tends to zero when [itex]|x| \gg W[/itex], and the integral over all space is equal to 1.
These functions don't actually have a limit as [itex]W \rightarrow 0[/itex], but in most cases of interest, integrals involving those functions do have limits as [itex]W \rightarrow 0[/itex], so you can solve the problem under the assumption that [itex]W[/itex] is small, but nonzero, and then let [itex]W \rightarrow 0[/itex] at the end.
As a distribution:
This is the mathematically rigorous way to reason about delta functions.
Let [itex]\mathcal{H}[/itex] be a set of square-integrable complex-valued functions of the real numbers. Then we can say that [itex]F[/itex] is a "distribution" for [itex]\mathcal{H}[/itex] if
- [itex]F[/itex] takes any element of [itex]\mathcal{H}[/itex] and returns a complex number. That is, if [itex]f[/itex] is a function in [itex]\mathcal{H}[/itex], then [itex]F(f)[/itex] is a complex number.
- [itex]F[/itex] is linear: For any two functions [itex]f(x)[/itex] and [itex]g(x)[/itex], and for any complex number [itex]\alpha[/itex], if [itex]h(x) = f(x) + \alpha g(x)[/itex], then [itex]F(h) = F(f) + \alpha F(g)[/itex].
So any function satisfying 1 and 2 is a distribution. We can then use integrals to define some particular distributions: For any function [itex]\phi[/itex] in [itex]H[/itex], there is a corresponding distribution [itex]F_\phi[/itex] defined via:
[itex]F_\phi(f) = \int_{-\infty}^{+\infty} \phi^*(x) f(x) dx[/itex] (where [itex]^*[/itex] means complex-conjugate)
But there are distributions that don't correspond to any actual function [itex]\phi[/itex]. For example:
[itex]F(f) \equiv f(0)[/itex]
That's a distribution, since it takes any function and returns a complex number, and it's linear. But it doesn't correspond to [itex]F_\phi[/itex] for any actual function [itex]\phi[/itex]. But we can pretend that it is of that form, by writing: [itex]F(f) = \int_{-\infty}^{+\infty} \delta(x) f(x) dx[/itex]. The right-hand side is just suggestive notation; it's not really an integral, although for many purposes, it works as if it were an integral.