Linear PDEs: A Simple Explanation

In summary, Wolfram says that the sum of solutions to a linear differential equation is not necessarily a solution, and that the solution is linear in the 'x' argument, but the operator is not linear on its 'argument' i.e. the function it is acting on.
  • #1
malignant
42
1
This isn't a homework problem so hopefully this section is fine.

I came across something that's bothering me while reviewing PDEs.
Take something like: [tex]u_{x}(x,t) = 1.[/tex] which has the general solution: [tex]u(x,t) = c_{1}(t) + x.[/tex] Wolfram says this is linear but if I take a different solution: [tex]v(x,t) = c_{2}(t) + x[/tex] and add it to u it's not also a solution: [tex]u + v = c_{1}(t) + c_{2}(t) + 2x\\ (u + v)_{x} = 2 \neq 1[/tex]

I must be missing something really simple here.
 
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  • #2
It is a linear differential equation, but it is not homogeneous.
 
  • #3
Orodruin said:
It is a linear differential equation, but it is not homogeneous.

Ahh, so the sum of solutions being a solution generally only applies to homogeneous equations?
 
  • #4
yeah... you can think about it another way. Your operator is not linear. And so a sum of solutions is not necessarily a solution. Your solution is linear in the 'x' argument, but the operator is not linear on its 'argument' i.e. the function it is acting on.

edit: uh... wait, I did not say this properly... If you define your operator as ##\partial_x## then the operator is linear, but as you said, the operator is mapping to something nonzero (i.e. 1). And if you can somehow rewrite the equation so that it is mapping to zero, then the operator would no longer be a linear operator. But now that I think about it, maybe it is not possible to re-write this as a map going to 'zero'. So maybe ignore my post hehe sorry about that.
 
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  • #5
In terms of homomorphisms, let's call the linear operator ##\partial_x## a homomorphism from the vector space of functions to itself. (i.e. we have functions as the vectors and real numbers as the scalars of this vector space). Then the kernel of this homomorphism is simply the set of all functions such that the linear operator gives zero when it acts on them. And, generally the kernel of a homomorphism is a vector space itself. Therefore, the set of solutions are a vector space. Which is why adding two solutions gives another solution.

Instead, if we consider the set of functions such that the linear operator gives the constant function 1, what can we say about this set of functions? They all map to the same function. So this means that you can get one function by adding an element of the kernel to the other function. This is what we know more intuitively as particular solutions and homogeneous solutions. If you find one particular solution, then you can just add any solution of the homogeneous solution, to get the general solution.

So in your case, the kernel of the homomorphism is given by the set of all solutions to the equation ##\partial_x(f(x,t))=0## (which are of the form ##u(t)##). Also, one possible function which gets mapped to 1, is simply 'x'. Therefore, the set of all functions which get mapped to 1 are of the form ##u(t) + x##. I hope this explanation helped a bit.
 

1. What is a linear PDE?

A linear partial differential equation (PDE) is an equation that involves partial derivatives of a function and its variables, and the coefficients of the derivatives are linear functions of the variables. This means that the function and its derivatives are raised to the first power and there are no products, powers, or other nonlinear operations involved.

2. How are linear PDEs different from nonlinear PDEs?

The main difference between linear and nonlinear PDEs is that in linear PDEs, the function and its derivatives are raised to the first power and there are no products, powers, or other nonlinear operations involved. In nonlinear PDEs, there are nonlinear operations involved, such as products, powers, or other nonlinear operations of the function and its derivatives.

3. What are some real-life applications of linear PDEs?

Linear PDEs have many applications in various fields of science and engineering, such as in modeling heat flow, diffusion, wave propagation, and fluid dynamics. They are also used in financial mathematics to model option pricing and in image processing to enhance images.

4. How do you solve a linear PDE?

The general method for solving a linear PDE involves transforming the equation into a simpler form, such as a separable equation or an equation with constant coefficients, and then using specific techniques to solve the simplified equation. These techniques may include separation of variables, Fourier series, Laplace transform, or Green's function method.

5. Are there any limitations to using linear PDEs?

While linear PDEs have many useful applications, they also have their limitations. They are only applicable to systems that can be described by linear relationships, and they may not accurately model highly complex or nonlinear systems. Additionally, the solutions to linear PDEs may not always be physically meaningful and may require additional conditions to be satisfied.

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