In mathematical analysis, the Schur test, named after German mathematician Issai Schur, is a bound on the
operator norm of an integral operator in terms of its Schwartz kernel (see Schwartz kernel theorem).
Here is one version.
be two measurable spaces (such as
be an integral operator with the non-negative Schwartz kernel
: If there exist real functions
and numbers
α , β > 0
extends to a continuous operator
with the operator norm Such functions
are called the Schur test functions.
In the original version,
is a matrix and
α = β = 1
[2] A common usage of the Schur test is to take
Then we get: This inequality is valid no matter whether the Schwartz kernel
is non-negative or not.
A similar statement about
operator norms is known as Young's inequality for integral operators:[3] if where
satisfies
, then the operator
{\displaystyle Tf(x)=\int _{Y}K(x,y)f(y)\,dy}
extends to a continuous operator
Using the Cauchy–Schwarz inequality and inequality (1), we get: Integrating the above relation in
, using Fubini's Theorem, and applying inequality (2), we get: It follows that
α β