The principle behind the condition is that, for example, if a wave is moving across a discrete spatial grid and we want to compute its amplitude at discrete time steps of equal duration,[2] then this duration must be less than the time for the wave to travel to adjacent grid points. As a corollary, when the grid point separation is reduced, the upper limit for the time step also decreases. In essence, the numerical domain of dependence of any point in space and time (as determined by initial conditions and the parameters of the approximation scheme) must include the analytical domain of dependence (wherein the initial conditions have an effect on the exact value of the solution at that point) to assure that the scheme can access the information required to form the solution.
Statement
To make a reasonably formally precise statement of the condition, it is necessary to define the following quantities:
Spatial dimension of the problem: the number of spatial dimensions, i.e., the number of spatial coordinates of the physical space where the problem is posed. Typical values are , and .
Time: the coordinate, acting as a parameter, which describes the evolution of the system, distinct from the spatial coordinates
The spatial coordinates and the time are discrete-valued independent variables, which are placed at regular distances called the interval length[3] and the time step, respectively. Using these names, the CFL condition relates the length of the time step to a function of the interval lengths of each spatial coordinate and of the maximum speed that information can travel in the physical space.
is the length interval (whose dimension is length).
The value of changes with the method used to solve the discretised equation, especially depending on whether the method is explicit or implicit. If an explicit (time-marching) solver is used then typically . Implicit (matrix) solvers are usually less sensitive to numerical instability and so larger values of may be tolerated.
with the obvious meanings of the symbols involved. By analogy with the two-dimensional case, the general CFL condition for the -dimensional case is the following one:
The interval length is not required to be the same for each spatial variable . This "degree of freedom" can be used to somewhat optimize the value of the time step for a particular problem, by varying the values of the different interval to keep it not too small.
^This quantity is not necessarily the same for each spatial variable, as it is shown in "The two and general n–dimensional case" section of this entry: it can be selected to somewhat relax the condition.
^Precisely, this is the hyperbolic part of the PDE under analysis.
Carlos A. de Moura and Carlos S. Kubrusly (Eds.): "The Courant-Friedrichs-Lewy (CFL) Condition: 80 Years After Its Discovery", Birkhauser, ISBN 978-0-8176-8393-1 (2013).