In mathematics, mollifiers are smooth functions with special properties, used in distribution theory to create a sequences of smooth functions approximating nonsmooth (generalized) functions, via convolution.
General idea
If φ is a compactly supported smooth function
on Rs
of integral equal to one, then the sequence
- φn(x) = ns φ(n x) (1)
converges to the Dirac delta function in the space of Schwartz distributions.
This means, that for any distribution T, the sequence
Tn = T * φn,
where * denotes convolution, converges to T.
On the other hand, this is a sequence of smooth functions.
Concrete example
More precisely, consider the function ψ
defined by ψ(x)=exp(1/(x ²-1)) for |x| < 1,
and zero elsewhere.
It is easily seen that this function is infinitely differentiable,
with vanishing derivative for |x| = 1.
Divide this function by its integral over the whole space to get a function φ of integral one, which can be used as mollifier as described above.
Smooth cutoff function
By convolution of the characteristic function of the
unit ball B = { x | |x|<1 } with φ2
(defined as in (1) with n=2), one obtains a smooth function
equal to 1 on { x | |x|<1/2 }, with support contained in { x | |x|<3/2 }.
It is easy to see how this can be generalized to obtain a smooth function
identical to one on a given set, and equal to zero in every point of
distance greater than a given ε to this set. Such a function is called (smooth) cutoff function .