The fact that two operators that commute have a common set of
eigenfunctions can be seen as follows: assume that
is an
eigenfunction of
with eigenvalue
.
and
commute,
.
must be an eigenfunction of
with eigenvalue
just like
itself is. If there is no
degeneracy of the eigenvalue, that must mean that
equals
or is at least proportional to it. That is the same as
saying that
is an eigenfunction of
too. (In the special
case that
is zero,
is still an eigenfunction of
,
If there is degeneracy, the eigenfunctions of
are not unique and
you can mess with them until they all do become eigenfunctions of
too. That can be shown assuming that the problem has been
approximated by a finite-dimensional one. Then
and
become matrices
and the eigenfunction become eigenvectors. Consider each eigenvalue
of
in turn. There will be more than one eigenvector corresponding
to a degenerate eigenvalue
.
can be written as a combination of the
eigenvectors of
,
where
is a combination of the eigenvectors
of
with eigenvalue
and
a combination of the
eigenvectors of
with other eigenvalues.
The vectors
and
separately are still eigenvectors
of
if nonzero, since as noted above,
converts eigenvectors
of
into eigenvectors with the same eigenvalue or zero. (For
example, if
was not
,
would have
to make up the difference, and
can only produce
combinations of eigenvectors of
that do not have eigenvalue
.
by either
or
,
.
you achieve that
the replacement eigenvectors of
are either combinations of the
eigenvectors of
with eigenvalue
or of the other eigenvectors
of
.
that are
combinations of the eigenvectors of
with eigenvalue
can now be
taken as the replacement eigenvectors of
with eigenvalue
.
.
.
Similar arguments can be used recursively to show that more generally, a set of operators that all commute have a common set of eigenvectors.
The operators do not really have to be Hermitian, just “diagonalizable”: they must have a complete set of eigenfunctions.
The above derivation assumed that the problem was