How can I solve this integral: $\int_{-\infty}^{\infty}\frac{e^{-x^2}(2x^2-1)}{1+x^2}dx.$ Can I solve this problem using the Laplace transform? How can I do this?
How can I evaluate $\int_{-\infty}^{\infty}\frac{e^{-x^2}(2x^2-1)}{1+x^2}dx$?
-
0Thank you all for your help to solve this problem! – 2011-12-24
5 Answers
I will evaluate the integral
$I=\int_{-\infty}^\infty\frac{e^{-x^2}}{1+x^2}dx$
using one of my favorite techniques (which I have heard was also Richard Feynman's favorite). This will solve your problem since, as Dilip points out, your integral can be written as
$\int_{-\infty}^\infty\frac{e^{-x^2}(2x^2+2-3)}{1+x^2}dx=2\sqrt{\pi}-3I.$
To find the value of $I$, we let, for $t\geq 0$,
$I(t)=\int_{-\infty}^\infty\frac{e^{-tx^2}}{1+x^2}dx.$
Then $I(0)=\arctan{\infty}-\arctan{(-\infty)} = \pi$, and $I'(t)=\int_{-\infty}^\infty\frac{-x^2e^{-tx^2}}{1+x^2}dx.$
Hence $I(t)$ satisfies the differential equation
$I(t)-I'(t)=\int_{-\infty}^\infty e^{-tx^2}dx = \sqrt{\frac{\pi}{t}}.$
Multiplying throughout by $e^{-t}$ we have
$-\frac{d}{dt}(e^{-t}I(t)) = e^{-t}\sqrt{\frac{\pi}{t}}.$
Integrating from $t=0$ to $t$, we find
$-e^{-t}I(t)+I(0) = \sqrt{\pi} \int_0^t \frac{e^{-t}}{\sqrt t}dt = 2\sqrt{\pi} \int_0^\sqrt{t}e^{-u^2} du = \pi \text{ erf}\sqrt{t}$
Since $I(0)=\pi$, we have
$I(t)=e^t(\pi - \pi \text{ erf}(\sqrt{t})) = e^{t}\pi \text{ erfc}(\sqrt{t}).$
Thus $I=I(1) = e\pi\: \text{erfc}(1)$, and your integral is $2\sqrt\pi - 3e\pi\text{erfc}(1)$. (Look!)
Note: my other solution below is much quicker, but not as much fun.
-
2Ah, this is what I wanted to see... +1! I suppose integration by parts will take care of the higher moments $\int_{-\infty}^\infty\frac{e^{-x^2}}{1+x^2}x^{2k}\mathrm dx$ – 2011-12-24
Here is yet another way to evaluate the integral
$I=\int_{-\infty}^\infty \frac{e^{-x^2}}{1+x^2}dx.$ Write
$\frac{1}{1+x^2}= \int_0^\infty e^{-s(1+x^2)}ds,$
so that
$I=\int_{-\infty}^\infty e^{-x^2} \int_{0}^\infty e^{-s(1+x^2)}ds\: dx.$
We switch the order of integration to get
$\int_{0}^\infty e^{-s} \int_{-\infty}^\infty e^{-x^2(1+s)}dx\: ds = \int_{0}^\infty e^{-s} \sqrt{\frac{\pi}{1+s}} ds = e\sqrt{\pi}\int_{0}^\infty \frac{e^{-(s+1)}}{\sqrt{1+s}} ds = e\pi \text{ erfc}(1).$
(To see that this last integral is indeed $\sqrt\pi \text{ erfc}(1)$, put $u=\sqrt{1+s}$, $du= \frac{ds}{2\sqrt{1+s}}$.)
-
0Hmm, I forgot a factor of $\frac2{\sqrt\pi}$ in my definition of the complementary error function. Oh well. – 2011-12-24
To find $I=\int_{-\infty}^{\infty}\frac{e^{-x^2}(2x^2-1)}{1+x^2}dx$, let us start by defining for $n \in \mathbb{N}$ $ I_n = \int_{-\infty}^{\infty} x^{2n} e^{-x^2} $ and note that $I_0=\sqrt{\pi}$, also called the Gaussian integral, can be solved either by a beautiful polar coordinate trick or by this technique, and that $I_1=\frac{\sqrt{\pi}}{2}$ was shown here. We can find the rest using integration by parts. With $ \begin{array}{lcl} v=-\frac{1}{2}e^{-x^2} && dv=xe^{-x^2}dx \\ u=x^{2n-1} && du=(2n-1)x^{2n-2}dx, \end{array} $ for $n>1$ we have $ \begin{array}{lcl} I_n &=& \int udv = uv - \int vdu \\ &=& -\frac{1}{2} \left[ x^{2n-1} e^{-x^2} \right]_{-\infty}^{\infty} + \frac{2n-1}{2} \int_{-\infty}^{\infty} x^{2n-2} e^{-x^2} \\ &=& \frac{2n-1}{2} I_{n-1} \end{array} $ where the first right-hand term vanishes because the exponential term dominates all polynomial terms. This shows that, inductively, $ I_n = \frac{(2n)!}{2^{2n}n!} I_0 $ But using $\frac{1}{1-t}=\sum_{n=0}^{\infty}t^n$, we can expand the integrand of $I$: $ \frac{2x^2-1}{1+x^2} = (2x^2-1) \sum_{n=0}^{\infty} (-1)^n x^{2n} = 2-3\sum_{n=0}^{\infty} (-1)^n x^{2n} $ and hence we get (noting that the integrals all converge because of the dominating exponential term) $ \begin{array}{lcl} I &=& 2I_0-3(I_0-I_1+\dots) = 2I_0-3 \sum_{n=0}^{\infty} (-1)^n I_n \\ &=& \left( 2-3 \sum_{n=0}^{\infty} (-1)^n \frac{(2n)!}{2^{2n}n!} \right) I_0 \end{array} $ where the series \sum_{n=0}^{\infty} (-1)^n \frac{(2n)!}{2^{2n}n!} = 1 - \frac{1}{2} + \frac{1 \cdot 3}{2 \cdot 2} - \frac{1 \cdot 3 \cdot 5}{2 \cdot 2 \cdot 2} + \cdots = e \sqrt\pi\; \text{erfc}(1)
can also be expressed using [$\Gamma(\frac{1}{2}-n)=(-1)^n\frac{(2n)!}{4^{n}n!}\sqrt\pi$][4] and a series expansion for the [complementary error function][5] as $ I = 2\sqrt\pi - 3 \; \sum_{n=0}^{\infty} \; \Gamma(\tfrac{1}{2}-n) = 2\sqrt\pi - 3e\pi\;\text{erfc}(1) \;. $
-
0Yes, you caught me between edits, with a nasty mistake! – 2011-12-23
Hint: If you want to use Laplace transform, you'll want a change of variables $x^2 = t$.
-
7Why the downvotes? Using that change of variables (and symmetry) the integral becomes $\int_0^\infty \frac{2t-1}{(t+1)\sqrt{t}} e^{-t}\ dt= 2 \int_0^\infty \frac{1}{\sqrt{t}} e^{-t}\ dt - 3 \int_0^\infty e^{-t} \frac{1}{\sqrt{t} (1+t)}\ dt$. Any decent table of Laplace transforms will handle this. – 2011-12-25
Writing $2x^2-1$ as $2x^2 + 2 - 3$, the integral simplifies to $\begin{align*} \int_{-\infty}^{\infty}\exp(-x^2)\frac{2x^2-1}{1+x^2}\mathrm dx &= 2\int_{-\infty}^{\infty}\exp(-x^2)\mathrm dx -3 \int_{-\infty}^{\infty}\exp(-x^2)\frac{1}{1+x^2}\mathrm dx\\ &= 2\sqrt{\pi} - \frac{3}{2\pi}\int_{-\infty}^{\infty}\sqrt{\pi}\exp(-\omega^2/4) \pi\exp(-|\omega|)\mathrm d\omega\\ &= 2\sqrt{\pi} - 3\sqrt{\pi}\int_{0}^{\infty}\exp(-\omega^2/4) \exp(-\omega)\mathrm d\omega\\ &= 2\sqrt{\pi} - 6\pi e \int_{0}^{\infty}\frac{1}{\sqrt{2}\sqrt{2\pi}} \exp\left(-\frac{(\omega + 2)^2}{2\cdot(\sqrt{2})^2}\right) \mathrm d\omega\\ \end{align*}$ where in the second step, we have used a well-known result (see e.g. the answer by bgins and the links therein) on the first integral, and applied the inner-product form of Parseval's theorem to convert the second integral to the integral of the product of the Fourier transforms $\sqrt{\pi}\exp(-\omega^2/4)$ and $\pi\exp(-|\omega|)$ of $\exp(-x^2)$ and $(1+x^2)^{-1}$ respectively, while the last step follows upon completing the square in the exponent and writing the integrand as the probability density function of a normal random variable with mean $-2$ and variance $2$. Hence we have that $\begin{align*} \int_{-\infty}^{\infty}\exp(-x^2)\frac{2x^2-1}{1+x^2}\mathrm dx &= 2\sqrt{\pi} -6\pi e \Phi(-2/\sqrt{2})\\ &= 2\sqrt{\pi} -6\pi e Q(\sqrt{2}) \end{align*}$ where $\Phi(\cdot)$ is the cumulative standard normal distribution function and $Q(x) = 1-\Phi(x)$ is its complement. Since $\text{erfc}(x) = 2Q(x\sqrt{2})$, the value can also be expressed as $2\sqrt{\pi} - 3e\pi \text{erfc}(1)$ as in the answers by Bruno and bgins.
-
0Would the down-voter care to add a comment? – 2012-03-07