Separation of variables
In mathematics, separation of variables (also known as the Fourier method) is any of several methods for solving ordinary and partial differential equations, in which algebra allows one to rewrite an equation so that each of two variables occurs on a different side of the equation.

Ordinary differential equations (ODE) 

A differential equation for the unknown  will be separable if it can be written in the form

where  and  are given functions. This is perhaps more transparent when written using  as:

So now as long as h(y) ≠ 0, we can rearrange terms to obtain:

where the two variables x and y have been separated. Note  dx (and dy) can be viewed, at a simple level, as just a convenient notation, which provides a handy mnemonic aid for assisting with manipulations. A formal definition of dx as a differential (infinitesimal) is somewhat advanced.

Alternative notation 

Those who dislike Leibniz's notation may prefer to write this as

but that fails to make it quite as obvious why this is called "separation of variables". Integrating both sides of the equation with respect to , we have

or equivalently,

because of the substitution rule for integrals.

If one can evaluate the two integrals, one can find a solution to the differential equation.  Observe that this process effectively allows us to treat the derivative  as a fraction which can be separated.  This allows us to solve separable differential equations more conveniently, as demonstrated in the example below.

(Note that we do not need to use two constants of integration, in equation () as in

because a single constant  is equivalent.)

Example 
Population growth is often modeled by the "logistic" differential equation

 

where  is the population with respect to time ,  is the rate of growth, and  is the carrying capacity of the environment.
Separation of variables now leads to

 
which is readily integrated using partial fractions on the left side yielding

 

where A is the constant of integration. We can find   in terms of  at t=0. Noting  we get

Generalization of separable ODEs to the nth order 
Much like one can speak of a separable first-order ODE, one can speak of a separable second-order, third-order or nth-order ODE. Consider the separable first-order ODE:

The derivative can alternatively be written the following way to underscore that it is an operator working on the unknown function, y:

Thus, when one separates variables for first-order equations, one in fact moves the dx denominator of the operator to the side with the x variable, and the d(y) is left on the side with the y variable. The second-derivative operator, by analogy, breaks down as follows:

The third-, fourth- and nth-derivative operators break down in the same way. Thus, much like a first-order separable ODE is reducible to the form

a separable second-order ODE is reducible to the form

and an nth-order separable ODE is reducible to

Example 
Consider the simple nonlinear second-order differential equation:This equation is an equation only of y'' and y', meaning it is reducible to the general form described above and is, therefore, separable. Since it is a second-order separable equation, collect all x variables on one side and all y' variables on the other to get:Now, integrate the right side with respect to x and the left with respect to y''':This giveswhich simplifies to:This is now a simple integral problem that gives the final answer:

 Partial differential equations 

The method of separation of variables is also used to solve a wide range of linear partial differential equations with boundary and initial conditions, such as the heat equation, wave equation, Laplace equation, Helmholtz equation and biharmonic equation.

The analytical method of separation of variables for solving partial differential equations has also been generalized into a computational method of decomposition in invariant structures that can be used to solve systems of partial differential equations.

 Example: homogeneous case 

Consider the one-dimensional heat equation. The equation is

The variable u denotes temperature. The boundary condition is homogeneous, that is

Let us attempt to find a solution which is not identically zero satisfying the boundary conditions but with the following property: u is a product in which the dependence of u on x, t is separated, that is:

Substituting u back into equation  and using the product rule,

Since the right hand side depends only on x and the left hand side only on t, both sides are equal to some constant value −λ. Thus:

and

−λ here is the eigenvalue for both differential operators, and T(t) and X(x) are corresponding eigenfunctions.

We will now show that solutions for X(x) for values of λ ≤ 0 cannot occur:

Suppose that λ < 0. Then there exist real numbers B, C such that

From  we get

and therefore B = 0 = C which implies u is identically 0.

Suppose that λ = 0. Then there exist real numbers B, C such that

From  we conclude in the same manner as in 1 that u is identically 0.

Therefore, it must be the case that λ > 0. Then there exist real numbers A, B, C such that

and

From  we get C = 0 and that for some positive integer n,

This solves the heat equation in the special case that the dependence of u has the special form of .

In general, the sum of solutions to  which satisfy the boundary conditions  also satisfies  and . Hence a complete solution can be given as

where Dn are coefficients determined by initial condition.

Given the initial condition

we can get

This is the sine series expansion of f(x) which is amenable to Fourier analysis. Multiplying both sides with  and integrating over  results in

This method requires that the eigenfunctions X, here , are orthogonal and complete. In general this is guaranteed by Sturm–Liouville theory.

 Example: nonhomogeneous case 

Suppose the equation is nonhomogeneous,

with the boundary condition the same as .

Expand h(x,t), u(x,t) and f(x) into

where hn(t) and bn can be calculated by integration, while un(t) is to be determined.

Substitute  and  back to  and considering the orthogonality of sine functions we get

 

which are a sequence of linear differential equations that can be readily solved with, for instance, Laplace transform, or Integrating factor. Finally, we can get
 

If the boundary condition is nonhomogeneous, then the expansion of  and  is no longer valid. One has to find a function v that satisfies the boundary condition only, and subtract it from u. The function u-v then satisfies homogeneous boundary condition, and can be solved with the above method.

 Example: mixed derivatives 

For some equations involving mixed derivatives, the equation does not separate as easily as the heat equation did in the first example above, but nonetheless separation of variables may still be applied. Consider the two-dimensional biharmonic equation

Proceeding in the usual manner, we look for solutions of the form

and we obtain the equation

Writing this equation in the form

Taking the derivative of this expression with respect to  gives  which means  and likewise, taking derivative with respect to  leads to  and thus , hence either F(x) or G(y) must be a constant, say −λ. This further implies that either  or  are constant. Returning to the equation for X and Y, we have two cases

and

which can each be solved by considering the separate cases for  and noting that .

 Curvilinear coordinates 

In orthogonal curvilinear coordinates, separation of variables can still be used, but in some details different from that in Cartesian coordinates. For instance, regularity or periodic condition may determine the eigenvalues in place of boundary conditions. See spherical harmonics for example.

 Applicability 
Partial differential equations

For many PDEs, such as the wave equation, Helmholtz equation and Schrodinger equation, the applicability of separation of variables is a result of the spectral theorem. In some cases, separation of variables may not be possible. Separation of variables may be possible in some coordinate systems but not others, and which coordinate systems allow for separation depends on the symmetry properties of the equation. Below is an outline of an argument demonstrating the applicability of the method to certain linear equations, although the precise method may differ in individual cases (for instance in the biharmonic equation above).

Consider an initial boundary value problem for a function  on  in two variables:

where  is a differential operator with respect to  and  is a differential operator with respect to  with boundary data:

 for  
 for 

where  is a known function.

We look for solutions of the form . Dividing the PDE through by  gives

The right hand side depends only on  and the left hand side only on  so both must be equal to a constant , which gives two ordinary differential equations

which we can recognize as eigenvalue problems for the operators for  and . If  is a compact, self-adjoint operator on the space  along with the relevant boundary conditions, then by the Spectral theorem there exists a basis for  consisting of eigenfunctions for . Let the spectrum of  be  and let  be an eigenfunction with eigenvalue . Then for any function which at each time  is square-integrable with respect to , we can write this function as a linear combination of the . In particular, we know the solution  can be written as

For some functions . In the separation of variables, these functions are given by solutions to 

Hence, the spectral theorem ensures that the separation of variables will (when it is possible) find all the solutions.

For many differential operators, such as , we can show that they are self-adjoint by integration by parts. While these operators may not be compact, their inverses (when they exist) may be, as in the case of the wave equation, and these inverses have the same eigenfunctions and eigenvalues as the original operator (with the possible exception of zero).

 Matrices 
The matrix form of the separation of variables is the Kronecker sum.

As an example we consider the 2D discrete Laplacian on a regular grid:

where  and  are 1D discrete Laplacians in the x- and y''-directions, correspondingly, and  are the identities of appropriate sizes. See the main article Kronecker sum of discrete Laplacians for details.

Software 
Some mathematical programs are able to do separation of variables: Xcas among others.

See also
Inseparable differential equation

Notes

References

External links 
 
 
 Methods of Generalized and Functional Separation of Variables at EqWorld: The World of Mathematical Equations
 Examples of separating variables to solve PDEs
 "A Short Justification of Separation of Variables"

Ordinary differential equations
Partial differential equations