Separation of Variable - What's REALLY going on?

In summary, separation of variables is a method used to solve differential equations by writing the equation in a form where the variables can be separated and then integrating both sides. This method is an abuse of notation, but it is still valid because it can be justified by integrating both sides with respect to x instead of y.
  • #1
MaxL
60
0
So I've always done simple ODEs by the method of separation of variables. You know,

dy/dx = A*y
dy/y = A*dx
IndefiniteIntegral[1/y dy] = IndefiniteIntegral[A dx]
ln(y) = A*x + Constant
y = Constant*e^(A*x)

It's easy to remember and it usually works. A lot of the PDEs I know how to do involve this process at some point.

The problem is, all my professors were quick to point out that this is an abuse of notation. That is, dy/dx isn't really a fraction, and can't necessarily be treated as such--it just happens to work out well if you pretend in a simple ODE.

So what's the rigorous way to do this ODE? What's really going on when you use the 'pretend derivatives are fractions' trick?
 
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  • #2
When writing equations linear in terms lik dx, it is "shorthand" for expressions that are within integrals.

dy/dx = A*y

1/y * dy/dx = A

\int 1/y * (dy/dx) dx = A*\int dx

\int 1/y dy =A*\int dx

ln(y) = A*x + C

y = const*exp(A*x)

When the integral on the left is converted to an x-integral, I have used a change of integration variables from x to y. So it's the same, only more correctly written.

Torquil
 
  • #3
The type of DE which you can separate always has this form:

h(y)y' = g(x)

In separation of variables you write it as

h(y)dy = g(x)dx

Then you integrate the left side with respect to y and the right side with respect to x yielding

H(y) = G(x) + C

where H and G are the antiderivatives of h and g. Why indeed should this work, given that you did different things to opposite sides of the equation? Should be a no-no shouldn't it?

Let's instead integrate both sides with respect to x in the first place

[tex]\int h(y)y'\, dx = \int g(x)\, dx[/tex]

Now, notice that if H is an antiderivative of h then:

[tex]\frac d {dx} H(y) = H'(y)\frac{dy}{dx}= h(y)y'[/tex]

where the first step is the chain rule. So H(y) is an antiderivative on the left side and G(x) on the right and we get:

H(y) = G(x) + C.

That is what justifies the shortcut method of separation of variables. It gives the correct answer and this shows why.
 
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FAQ: Separation of Variable - What's REALLY going on?

What is separation of variables?

Separation of variables is a mathematical method used to solve certain types of differential equations. It involves separating a multi-variable function into simpler functions that depend on a single variable each, in order to make the equation easier to solve.

How does separation of variables work?

The method of separation of variables involves assuming that the solution to the differential equation can be written as a product of two simpler functions, each depending on only one of the variables involved. This allows the equation to be rewritten in terms of these simpler functions, which can then be solved separately.

When is separation of variables used?

Separation of variables is commonly used to solve partial differential equations with boundary conditions, particularly in physics and engineering applications. It is also used in solving some ordinary differential equations.

What are the limitations of separation of variables?

Separation of variables can only be used for certain types of differential equations where the variables can be easily separated. In addition, the method may not always yield a complete solution and may require additional techniques to find the general solution.

What are some real-world applications of separation of variables?

Separation of variables has many applications in physics and engineering, such as in solving the heat equation to model heat transfer, the wave equation to model vibrations, and the Schrödinger equation to model quantum systems. It is also used in financial mathematics to model option pricing and in population dynamics to model growth and decay.

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