Differential equations with distributions

In summary, the solution to the differential equation x^2\frac{du}{dx} = 0 in the sense of distributions is c_1 + c_2H(x), where c_1 and c_2 are constants. This can also be written as c_1 + c_2\delta(x) + c_2H(x), showing the two "spikes" at x = 0 and all other points. The delta function is a fundamental solution to this type of differential equation and any linear combination of it will also be a solution. This explains why the book mentions the Heaviside distribution as a solution.
  • #1
tjackson3
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Homework Statement



Solve [itex]x^2\frac{du}{dx} = 0[/itex] in the sense of distributions.


Homework Equations



<u',f> = -<u,f'> for any test function f.

The Attempt at a Solution



My thinking is that since we want to see the action of the left hand side on a general test function f, we try

<x^2u',f> = -<u,(x^2f)'> = 0

so clearly we can drop the negative

<u,(x^2f)> = 0

But I'm stuck as to where to go from here. On one hand, it would seem like the delta function would satisfy this, since [itex]\int_{-\infty}^{\infty} \delta(x)x^2f(x)\ dx = 0[/itex]. However, besides the fact that this seems too easy, there's an example in the book I'm using (Keener) which shows that the solution for the differential equation [itex]x\frac{du}{dx} = 0[/itex] is [itex]c_1 + c_2H(x)[/itex]. Since the solution for [itex]\frac{du}{dx} = 0[/itex] is just the constant distribution, this would seem to imply to met that the solution to my differential equation involves the constant distribution, the Heaviside distribution, and some other distribution. The book is extremely unclear on how to solve these problems. Any tips?

Thanks!
 
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  • #2


Hello,

You are on the right track with using the delta function as a solution to this differential equation. However, as you mentioned, this may seem too easy. In fact, the delta function is a fundamental solution to this type of differential equation, meaning that it forms a basis for the solutions. This means that any linear combination of the delta function will also be a solution. So your solution of c_1 + c_2H(x) is actually correct.

To understand this better, think about what the delta function represents. It is a distribution that has a value of 0 everywhere except at x = 0, where it has a value of infinity. This means that when you integrate the product of the delta function and any test function f, the only term that will contribute to the integral is when x = 0. So in a sense, the delta function acts like a "spike" or "point mass" at x = 0.

Using this understanding, you can see that the solution c_1 + c_2H(x) is actually a combination of two "spikes" - one at x = 0 (represented by c_2H(x)) and one at all other points (represented by c_1). This is why the book mentions the Heaviside distribution as a solution to the equation x\frac{du}{dx} = 0 - because it is a "spike" at all points except x = 0.

So to summarize, the solution to x^2\frac{du}{dx} = 0 in the sense of distributions is c_1 + c_2H(x), where c_1 and c_2 are constants. This can also be written as c_1 + c_2\delta(x) + c_2H(x), showing the two "spikes" at x = 0 and all other points.

I hope this helps clarify things! Keep up the good work in your studies.
 

Related to Differential equations with distributions

What are differential equations with distributions?

Differential equations with distributions are a type of mathematical equation that involves an unknown function and its derivatives. The difference between these equations and regular differential equations is that distributions can be used to represent functions that are not continuous or differentiable. This allows for a broader range of functions to be used in solving the equation.

How are distributions used in solving differential equations?

Distributions are used in solving differential equations by allowing for non-smooth or non-differentiable functions to be represented. This is particularly useful in physics and engineering applications where functions may have sharp discontinuities or singularities. Distributions also allow for the use of generalized derivatives, which can simplify the equations and make them easier to solve.

What are some examples of differential equations with distributions?

Some examples of differential equations with distributions include the Dirac delta function, Heaviside step function, and the generalized function known as the signum function. These equations are commonly used in fields such as quantum mechanics, signal processing, and fluid dynamics.

Can distributions be used to solve any type of differential equation?

No, distributions cannot be used to solve all types of differential equations. They are most commonly used for linear differential equations, which have a linear relationship between the unknown function and its derivatives. However, they can also be used in some cases for non-linear equations.

Are there any limitations or challenges when using distributions in differential equations?

One limitation of using distributions in differential equations is that they may not always have a unique solution. This is because distributions can represent a wide range of functions, and there may be multiple functions that satisfy the equation. Additionally, working with distributions may require more advanced mathematical techniques and can be more challenging than traditional differential equations.

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