## Posts Tagged ‘**hypergeometric**’

## Tricks for inverting a Laplace Transform, part IV: Substitutions

After a few less technical posts recently, I now continue the series of articles on tricks for the inversion of Laplace transforms. You can find the other parts here: part I (guesses based on series expansions), part II (products and convolutions), part III, and part V (pole decomposition).

Today’s trick will be **variable substitutions**. Let’s say we need to find so that

, (1)

where , and are constants. This example is not as absurd as it may seem; it actually came up recently in my research on a variant of the ABBM model.

There is a general formula permitting one to invert the Laplace transform above, in terms of an integral in the complex plane:

.

This so-called Fourier-Mellin integral runs along a contour from to . can be chosen arbitrarily, as long as the integral converges and all singularities (poles, branch cuts, etc.) of lie on the right of it. Note that my convention for the Laplace variable is the convention used for generating functions in probability theory, which has just the opposite sign of of the “analysis” convention for Laplace transforms.

The fact that our Laplace transform is written entirely in terms of the function suggests applying a variable substitution. Instead of performing the Fourier-Mellin integral over , we will integrate over . We then have:

. (2)

Solving the definition of for , we get

and

.

Inserting this into (2), we have

.

The only singularity of the integrand is at , for . We can thus choose the contour to go parallel to the imaginary axis, from to . `Mathematica`

then knows to how to evaluate the resulting integral, giving a complicated expression in terms of Kummer’s confluent hypergeometric function . However, a much simpler expression is obtained if one introduces an auxiliary integral instead:

.

`Mathematica`

knows a simple expression for it:

.

is Tricomi’s confluent hypergeometric function, which is equivalent to Kummer’s confluent hypergeometric function but gives more compact expressions in our case.

Using this auxiliary integral, (2) can be expressed as

.

Simplifying the resulting expressions, one obtains our **final result for **:

(3)

Equivalently, the confluent hypergeometric functions can be replaced by Hermite polynomials:

For complicated Laplace transforms such as these, I find it advisable to check the final result numerically. In the figure below you see a log-linear plot of the original expression (1) for , and a numerical evaluation of , with given by (3). You can see that they match perfectly!

## Tricks for inverting a Laplace Transform, part II: Products and Convolutions

*EDIT: In the meanwhile, I have continued the series of posts on Laplace Transform inversion. You can find the subsequent articles here: part I (guesses based on series expansions), part III, part IV (substitutions), part V (pole decomposition). Enjoy!*

Following the previous post on inverting Laplace transforms, here is another trick up the same alley. This one actually considers a generalization of the previous case

**Find such that .**

As usual, the built-in InverseLaplaceTransform function from* Mathematica 8* fails to give a result. To obtain a closed formula manually, note that each of the factors can be easily inverted:

has the solution

.

Hence, using the fact that Laplace transforms of convolutions give products, the solution for can be written as a convolution:

.

Computing the integral gives the following expression for in terms of the hypergeometric function :

Enjoy!!

## Tricks for inverting a Laplace Transform, part I: Guesses based on Series

*EDIT: In the meanwhile, I have continued the series of posts on Laplace Transform inversion. You can find the subsequent articles here: part II (products and convolutions), part III, part IV (substitutions), part V (pole decomposition). Enjoy!*

Working with probability distributions one frequently meets the problem of inverting a Laplace transform, which is notoriously difficult. An example that I met recently is the following:

**Find such that .**

The built-in InverseLaplaceTransform function from `Mathematica 8`

fails to give a result. However, a closed formula for can be obtained using a trick: Consider integer , for which the right-hand side becomes a rational function. Take its Laplace inverse, and then extend the result analytically for non-integer .

Since this may be useful for other cases, too, here a detailed account of how one proceeds:

For small integer values of , one obtains (e.g. using Mathematica):

By trying out, one can now guess a general formula for integer :

For example using Mathematica’s `Sum`

command, one can re-write this in terms of a hypergeometric function:

This expression now has a well-defined meaning for any , and is the result we looked for. Actually, Mathematica even knows how to take its Laplace transform, which can be used to check its validity.

More tricks for similar problems to come later!