I know that it's easy to calculate integral $\displaystyle\int_{-\infty}^\infty \frac{e^{itx}}{\pi(1+x^2)} \, dx$ using residue theorem. Is there any other way to calculate this integral (for someone who don't know how to use residue theorem)?
Cauchy distribution characteristic function
28k Views Asked by Bumbble Comm https://math.techqa.club/user/bumbble-comm/detail AtThere are 3 best solutions below
On
There is also another way to calculate this integral. You know that $i$ and $-i$ are to singularities of ur function. Then you can consider the following paths.
\begin{align} \gamma_1 & =(i-i\varepsilon)t,& & t\in [0,1] \\[6pt] \gamma_2 & =\varepsilon e^{it}, & & t\in \left[-\frac{\pi}{2},\frac \pi 2 \right] \\[6pt] \gamma_3 & =(i+\varepsilon)(1-t)+tiR, & & t\in [0,1] \\[6pt] \gamma_4 & =iRe^{-it}, & & t\in \left[0,\frac \pi 2\right] \\[6pt] \gamma_5 & =-Rt, & & t\in [-1,0] \end{align}
We define $\gamma_w:=\gamma_1+\cdots+\gamma_5$ and then our integral is zero (Cauchy's integral theorem). On the other hand, we can calculate the several integrals separately with (let $R \rightarrow \infty$ and $\varepsilon \rightarrow 0$.)
In this way, you can calculate the integral $\int_0^\infty \! \frac{e^{itx}}{\pi (1+x^2)} \, dx $. The other integral can be calculated in the same way.
On
If you have another distribution's characteristic function(c.f.) and distribution function(d.f.) in mind, you might use it to find the c.f. of a desired distribution.
Here I will use the Laplacian d.f. and c.f. to find the c.f. of Cauchy Distribution.
We know the c.f. of Laplace Distribution($f(x) = \frac{1}{2}.e^{-|x|}$) is given by $\varphi(t) = \frac{1}{1+t^2}$.(How? Do the simple integral to find this, if already not known)
Now, we observe that the c.f. of the Laplacian r.v. is some constant(i.e. $\pi$) times the Cauchy pdf. This motivates us to use a result which buds from the Inversion Theorem which is -
If $\varphi$ is an integrable c.f., then the d.f. is continuously differentiable with continuous density given by $f(x)=\frac{1}{2\pi}\int_{-\infty}^{\infty} e^{-itx}\varphi(t)dt$.
Simply plug in the c.f. and density of Laplacian Distribution in the above expression, to get,
$\frac{1}{2}.e^{-|x|} = \frac{1}{2\pi}\int_{-\infty}^{\infty} e^{-itx}\frac{1}{1+t^2}dt = \frac{1}{2}E(e^{-ixY})$, where $Y$ is a Cauchy r.v.
So, we get, c.f. of Cauchy r.v. as $\varphi(-t) = e^{-|x|}\Rightarrow \varphi(t) = e^{-|x|}$.
Consider the function $f(t)=e^{-a|t|}$, then the Fourier transform of $f(t)$ is given by $$ \begin{align} F(x)=\mathcal{F}[f(t)]&=\int_{-\infty}^{\infty}f(t)e^{-ix t}\,dt\\ &=\int_{-\infty}^{\infty}e^{-a|t|}e^{-ix t}\,dt\\ &=\int_{-\infty}^{0}e^{at}e^{-ix t}\,dt+\int_{0}^{\infty}e^{-at}e^{-ix t}\,dt\\ &=\lim_{u\to-\infty}\left. \frac{e^{(a-ix)t}}{a-ix} \right|_{t=u}^0-\lim_{v\to\infty}\left. \frac{e^{-(a+ix)t}}{a+ix} \right|_{0}^{t=v}\\ &=\frac{1}{a-ix}+\frac{1}{a+ix}\\ &=\frac{2a}{x^2+a^2}. \end{align} $$ Next, the inverse Fourier transform of $F(x)$ is $$ \begin{align} f(t)=\mathcal{F}^{-1}[F(x)]&=\frac{1}{2\pi}\int_{-\infty}^{\infty}F(x)e^{ix t}\,dx\\ e^{-a|t|}&=\frac{1}{2\pi}\int_{-\infty}^{\infty}\frac{2a}{x^2+a^2}e^{ix t}\,dx\\ \frac{\pi e^{-a|t|}}{a}&=\int_{-\infty}^{\infty}\frac{e^{ix t}}{x^2+a^2}\,dx. \end{align} $$ Thus, putting $a=1$, the given integral turns out to be $$ \frac1\pi\int_{-\infty}^{\infty}\frac{e^{ix t}}{x^2+1}\,dx=\large\color{blue}{e^{-|t|}}. $$ Other method using double integral technique can be seen here.