### D.38 Time-dependent perturbation theory

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

 (D.22)

The new coefficients and are physically just as good as and . For one, the probabilities are given by the square magnitudes of the coefficients, and the square magnitudes of and are exactly the same as those of and . That is because the exponentials have magnitude one. Also, the initial conditions are unchanged, assuming that you choose the integration constants so that the integrals are initially zero.

The evolution equations for and are

 (D.23)

with . Effectively, the two energy expectation values have been turned into zero. However, the matrix element is now time-dependent, if it was not already. To check the above evolution equations, just plug in the definition of the coefficients.

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 . The definition of the scale factor 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 , so the coefficient 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 . That then allows 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, 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,

By splitting it up into ranges no larger than and no larger than 1, you can see that the error is never larger than order for no larger than 1. And it is of order outside that range.

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 . In that case, the individual contributions of all these states add up to change . And 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 , you can see that 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 , time-dependent perturbation theory should be OK.