Collapse and projection-valued measures

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Discussion Overview

The discussion revolves around the concept of collapse in quantum mechanics as it relates to projection-valued measures (PVM). Participants explore the implications of measuring an observable and how the state of a system changes post-measurement, particularly in cases involving degenerate eigenvalues.

Discussion Character

  • Technical explanation
  • Conceptual clarification
  • Debate/contested

Main Points Raised

  • One participant proposes that measuring an observable ##A## results in a collapse to a state ##\rho' = \mu_A(\{a\})## if the outcome falls within a measurable subset ##S##.
  • Another participant questions the correctness of the formulas for states after collapse, particularly when dealing with degenerate eigenvalues, suggesting that ##\mu_A(\{a\})## is not a valid state in such cases.
  • A participant asserts that collapse is not part of the formalism of quantum mechanics but is rather an interpretation, indicating a divergence in understanding the nature of collapse.
  • There is a mention of Lüders rule as a method to project the state onto the degenerate subspace before measurement, which some participants agree is relevant to the discussion.
  • Further clarification is provided on the correct expressions for the post-collapse state, with specific formulas being suggested by participants.

Areas of Agreement / Disagreement

Participants express differing views on the nature of collapse in quantum mechanics, with some arguing for its relevance in calculations while others emphasize its interpretative status. There is no consensus on the correctness of the initial formulas presented for the post-collapse states.

Contextual Notes

Participants note limitations regarding the treatment of degenerate eigenvalues and the implications of using PVM in expressing collapse, indicating unresolved aspects of the discussion.

burakumin
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Let suppose I have an observable ##A## with associated projection-valued measure ##\mu_A##
$$A = \int_{a \in \mathbb{R}} a \cdot \textrm{d}\mu_A(a)$$
for a system in the (possibly mixed) state ##\rho##. Let ##S \subset \mathbb{R}## be a measurable subset and let ##Z = \mu_A(S)## be the observable equating 1 if ##A## falls in ##S## and 0 otherwise.

Is this statement meaningful and correct:

If measuring ##A##, with probability ##\textrm{tr}( \rho \cdot \mu_A(S) )## the result will be a point in ##S## (let's call it ##a##) and the system will collapse to state ##\rho' = \mu_A(\{a\})##

Again is this statement meaningful and correct:

If measuring ##Z##, with probability ##\textrm{tr}( \rho \cdot \mu_A(S) )## the result will be 1 and the system will collapse to state $$\rho' = \frac{1}{\textrm{tr} (\rho \cdot \mu_A(S))} \cdot \int_{a \in S} \textrm{tr} ( \rho \cdot \mu_A(\{a\}) ) \cdot \textrm{d} \mu_A(a) $$ with any subsequent measurement of ##A## producing a value inside ##S##
 
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Rethinking about that, it seems that my formulas for states after collapse are incorrect as ##\mu_A(\{a\})## is not a state at all in case ##a## is degenerate eigenvalue. But what would be the correct answer?

My question can basically be rephrased as "how do you express collapse with PVM?"
 
Bhobba, I think the OP just want an FAPP collapse to do calculation.

burakumin said:
it seems that my formulas for states after collapse are incorrect as ##\mu_A(\{a\})## is not a state at all in case ##a## is degenerate eigenvalue. But what would be the correct answer?"

Typically one projects the state before the PVM measurement onto the degenerate subspace. This is called Lüders rule.
 
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Truecrimson said:
Bhobba, I think the OP just want an FAPP collapse to do calculation.

Typically one projects the state before the PVM measurement onto the degenerate subspace. This is called Lüders rule.

Thanks Truecrimson, "Lüders rule" seems definitely the appropriate keyword. So AFAIU the correct answers would be:
$$ \rho' = \frac{1}{\textrm{tr} (\rho \cdot \mu_A(\{a\})) } \cdot \mu_A(\{a\}) \cdot \rho \cdot \mu_A(\{a\}) $$
and
$$ \rho' = \frac{1}{\textrm{tr} (\rho \cdot \mu_A(S)) } \cdot \mu_A(S) \cdot \rho \cdot \mu_A(S) $$
 
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