The equations to be solved are
To simplify the use of perturbation theory, it is convenient to use a
trick that gets rid of half the terms in these equations. The trick
is to define new coefficients
and
by
The evolution equations for
and
are
It will from now on be assumed that the original Hamiltonian
coefficients are independent of time. That makes the difference in
expectation energies
constant too.
Now the formal way to perform time-dependent perturbation theory is to
assume that the matrix element
is small. Write
as
where
is a scale factor. Then
you can find the behavior of the solution in the limiting process
by expanding the solution in powers of
.
is not important. You might identify it with a small physical
parameter in the matrix element. But in fact you can take
the same as
and
as an additional mathematical
parameter with no meaning for the physical problem. In that approach,
disappears when you take it to be 1 in the final answer.
But because the problem here is so trivial, there is really no need
for a formal time-dependent perturbation expansion. In particular, by
assumption the system stays close to state
,
must remain small. Then the evolution
equations above show that
will hardly change. That allows
it to be treated as a constant in the evolution equation for
.
to be found by simple
integration. The integration constant follows from the condition that
is zero at the initial time. That then gives the result cited
in the text.
It may be noted that for the analysis to be valid, ![]()
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must be small. That ensures that
is correspondingly small
according to its evolution equation. And then the change in
from its original value is small of order
according to its evolution equation. So the
assumption that it is about constant in the equation for
is verified. The error will be of order
.
To be sure, this does not verify that this error in
decays
to zero when ![]()
![]()
tends to infinity. But it does, as can
be seen from the exact solution,
Finally, consider the case that the state cannot just transition to
one state
but to a large number
of them, each with its
own coefficient
.
.
must definitely stay approximately constant for the
above analysis to be valid. Fortunately, if you plug the approximate
expressions for the
into the evolution equation for
,
stays approximately
constant as long as the sum of all the transition probabilities does.
So as long as there is little probability of any transition at
time
,