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3.11

Rewriting earlier chapters in Dirac notation

Time to settle the accounts. Redo the derivations that consumed so many pages of chapter 2 in the new language, and see exactly how much was saved.

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After this section you should be able to

  • Recast the infinite square well results in the language of matrices and state vectors
  • Solve the harmonic oscillator completely from the ladder-operator algebra, without solving a single differential equation
  • Redo the uncertainty principle and the Ehrenfest theorem by operator methods

The toolkit is complete. This section settles the accounts: translate every result of chapter 2 into the new language, then tally up what was saved.

This is not revision. Some proofs will shrink from half a page to three lines; others will turn from “solve a partial differential equation” into “do some algebra” — and the second kind is the real prize.

The infinite square well, written as matrices

The harmonic oscillator: a purely algebraic solution

Section 2.9 already used ladder operators, but Dirac notation was not yet available then. Rewritten in the new language, the structure comes out far more clearly.

The uncertainty principle: from derivation to substitution

The Ehrenfest theorem: one line

Settling the accounts

End of chapter

The three questions chapter 2 left open now have answers:

Why do observables correspond to operators? Because demanding “measured values are real, distinct outcomes are distinguishable, every state can be expanded” picks out exactly the Hermitian operators (section 3.5).

By what right is cn2|c_n|^2 a probability? That one remains a postulate (the Born rule). But the spectral theorem guarantees ncn2=1\sum_n|c_n|^2=1, so it is at least self-consistent — and Gleason’s theorem goes further: in dimension 3\ge3 there is essentially no other choice.

What actually happens in a measurement? The projection postulate describes its effect but does not explain its mechanism (section 3.8). On this there is still no consensus — and it is not the sort of problem that computing more carefully can resolve.

With this language in hand, the pace can pick up considerably. Chapter 4 returns to one-dimensional problems — but this time with structural methods like symmetry and the transfer matrix, and with a numerical solver that handles arbitrary potentials.

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