Introduction to Numerical Differential Equations
| NDSolve[eqns,y,{x,xmin,xmax}] | solve numerically for the function y, with the independent variable x in the range to  |
| NDSolve[eqns,{y1,y2,...},{x,xmin,xmax}] |
| solve a system of equations for the  |
Numerical solution of differential equations.
This generates a numerical solution to the equation

with

. The result is given in terms of an
InterpolatingFunction.
| Out[1]= |  |
Here is the value of

.
| Out[2]= |  |
With an algebraic equation such as
, each solution for
is simply a single number. For a differential equation, however, the solution is a function, rather than a single number. For example, in the equation
, you want to get an approximation to the function
as the independent variable
varies over some range.
Mathematica represents numerical approximations to functions as InterpolatingFunction objects. These objects are functions which, when applied to a particular
, return the approximate value of
at that point. The InterpolatingFunction effectively stores a table of values for
, then interpolates this table to find an approximation to
at the particular
you request.
| y[x]/.solution | use the list of rules for the function y to get values for  |
| InterpolatingFunction[data][x] | evaluate an interpolated function at the point x |
| Plot[Evaluate[y[x]/.solution],{x,xmin,xmax}] |
| plot the solution to a differential equation |
Using results from NDSolve.
This solves a system of two coupled differential equations.
| Out[3]= |  |
Here is the value of

found from the solution.
| Out[4]= |  |
| Out[5]= |  |
| NDSolve[eqn,u,{x,xmin,xmax},{t,tmin,tmax},...] |
| solve a partial differential equation |
Numerical solution of partial differential equations.