Can the Other Eigenvalue Be Measured After an Initial Measurement?

In summary: The state ##\vert \nu \rangle## is not going to be a state that you can evolve forward in time.In summary, it is possible to measure the other eigenvalue a2 at a time t after the first measurement, depending on whether the operator associated with the eigenstates commutes with the Hamiltonian or not. After a measurement produces a result, the state will be the corresponding eigenstate for future time evolution.
  • #1
mangokiller
1
0
A ket is expanded as [itex] \vert \nu \rangle = c_1\vert \nu_1\rangle+c_2\vert \nu_{2}\rangle [/itex].

A measurement results in the eigenvalue a1. Is it possible to measure the other eigenvalue a2 at a time t after the first measurement?

Could I write something like

[itex] \vert \psi(t)\rangle = e^{-i \hat H t / \hbar}\vert \psi(0) \rangle =e^{-i \hat H t / \hbar}\vert \nu_1 \rangle= e^{-i \hat H t / \hbar} \big(c_1\vert \nu_1 \rangle+c_2\vert \nu_2\rangle \big) =e^{-i E_1 t / \hbar} c_1\vert \nu_1 \rangle+e^{-i E_2 t / \hbar}c_2\vert \nu_{2}\rangle. [/itex]
 
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  • #2
You could measure a2 after the first measurement, but the equations in that last line are not quite right. You cannot expand ## | \nu_1 \rangle ## in terms of itself and ## | \nu_2 \rangle ##, because these vectors are linearly independent of each other. Instead, the time evolution operator could transform ## | \nu_1 \rangle ## into a different vector, which is itself expandable in terms of ## | \nu_1 \rangle ## and ## | \nu_2 \rangle ##. That is, you could have ## e^{-i\hat{H}t/ \hbar} | \nu_1 \rangle = c_1 | \nu_1 \rangle + c_2 | \nu_2 \rangle ##. Of course, this assumes that the two eigenstates form a basis, so that any state can be expanded in terms of them.
 
  • #3
mangokiller said:
A ket is expanded as [itex] \vert \nu \rangle = c_1\vert \nu_1\rangle+c_2\vert \nu_{2}\rangle [/itex].

A measurement results in the eigenvalue a1. Is it possible to measure the other eigenvalue a2 at a time t after the first measurement?

It depends on what operator ##\vert \nu_1 \rangle## and ##\vert \nu_2 \rangle## are eigenstates of. If that operator commutes with the Hamiltonian, then the answer is no; if it does not, the answer is yes.

Even though the initial state would have been [itex] \vert \nu \rangle = c_1\vert \nu_1\rangle+c_2\vert \nu_{2}\rangle [/itex], after a measurement produces the result ##a_1## (and assuming that that's the eigenvalue associated with ##\vert \nu_1 \rangle##) the state is going to be ##\psi = \vert \nu_1 \rangle##, so that's the state that you want to be evolving forward in time.
 
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FAQ: Can the Other Eigenvalue Be Measured After an Initial Measurement?

What is a repeated measurement question?

A repeated measurement question is a type of research question that involves collecting data multiple times from the same participants or subjects. This allows for comparisons and analysis of changes over time or under different conditions.

Why is it important to use repeated measurement in research?

Using repeated measurement in research allows for a more thorough understanding of the data and can help to identify patterns or trends. It also allows for the examination of how variables may change over time or under different circumstances.

What are the advantages of using repeated measurement?

The advantages of using repeated measurement include the ability to examine changes over time, increased accuracy and precision of data, and a more comprehensive understanding of the research topic. It also allows for the control of individual differences among participants.

Are there any limitations to using repeated measurement?

One limitation of using repeated measurement is the potential for participant fatigue or boredom, which can affect the validity of the data. Additionally, it may require more resources and time to collect and analyze data from multiple time points.

How can potential sources of error be minimized in repeated measurement studies?

To minimize potential sources of error in repeated measurement studies, researchers can use standardized procedures, clearly define variables and measurements, and carefully select and train participants. It is also important to use statistical techniques to account for any potential confounding variables.

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