Why are mutually exclusive states orthogonal?

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In summary, it is important for two eigenvectors to be orthogonal in order to have mutually exclusive states. This is because, by the rule of probability in quantum mechanics, orthogonal states are mutually exclusive. This can be shown through calculations using the eigenvalues of self-adjoint operators. However, it is not entirely clear what is meant by "mutually exclusive" and it may refer to zero transition probability between states.
  • #1
Demon117
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I understand that it is important for two eigenvectors to be orthogonal, but what is it exactly about mutually exclusive states that makes them orthogonal?
 
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  • #2
they don't have to be orthogonal because if they were when you express one of then in the orthogonal base of the other observable you would get a null vector
 
  • #3
facenian said:
they don't have to be orthogonal because if they were when you express one of then in the orthogonal base of the other observable you would get a null vector

Thats strange, maybe I just misunderstood but my professor said that mutually exclusive states must be represented by orthogonal kets. So, why would he say that if its not true?
 
  • #4
Well, maybe he is right and there's something wrong in my reasoning. Let's wait and see if someone else has something to say
 
  • #5
It's the other way around. Orthogonal states, by the rule of probability in quantum mechanics, are mutually exclusive. Otherwise, you can't distinguish different outcomes of a measurement. (There is a generalization to this though.)
 
  • #6
Eigenvectors corresponding to different eigenvalues of a self-adjoint operator are always orthogonal.

\begin{align}
&Ax=\lambda x\\
&Ay=\mu y\\
\\
& \lambda^*\langle x,y\rangle=\langle\lambda x,y\rangle=\langle Ax,y\rangle=\langle x,A^*y\rangle=\langle x,Ay\rangle\\
& \mu\langle x,y\rangle=\langle x,\mu y\rangle=\langle x,Ay\rangle\\
&\Rightarrow\ (\lambda^*-\mu)\langle x,y\rangle=\langle x,Ay\rangle-\langle x,Ay\rangle=0
\end{align}
This calculation shows that eigenvalues of self-adjoint operators are real (because if x=y, then [itex]\mu=\lambda[/itex], and the result we found says that [itex](\lambda^*-\lambda)\|x\|^2=0[/itex], which implies that I am λ=0). This implies that our result can be written as [itex](\lambda-\mu)\langle x,y\rangle=0[/itex], and if [itex]\lambda\neq\mu[/itex], this implies that [itex]\langle x,y\rangle=0[/itex].
 
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  • #7
After this other two contributions I think know I understand better what your professor might have said, he was not talking of general states he had in mind eingenstates of the same obsevable then his assertion is simply the theorem of linear algebra that Fredrik explained.
 
  • #8
It's not entirely clear to me what he meant by "mutually exclusive". If it refers to the states corresponding to different results of the same measurement, then the theorem above is the answer. But he might have been talking about zero transition probability, and in that case, the statement is kind of trivial, once we understand what it says.

The probability that a system prepared in state [itex]|\psi\rangle[/itex] will end up in state [itex]|\phi\rangle[/itex] after a measurement of an observable that has [itex]|\phi\rangle[/itex] as the only eigenvector corresponding to some specific result, is [itex]|\langle\phi|\psi\rangle|^2[/itex]. He could mean that [itex]|\psi\rangle[/itex] and [itex]|\phi\rangle[/itex] are mutually exclusive if that probability is 0. That would of course imply that these state vectors are orthogonal.
 
  • #9
Fredrik said:
It's not entirely clear to me what he meant by "mutually exclusive". If it refers to the states corresponding to different results of the same measurement, then the theorem above is the answer. But he might have been talking about zero transition probability, and in that case, the statement is kind of trivial, once we understand what it says.

The probability that a system prepared in state [itex]|\psi\rangle[/itex] will end up in state [itex]|\phi\rangle[/itex] after a measurement of an observable that has [itex]|\phi\rangle[/itex] as the only eigenvector corresponding to some specific result, is [itex]|\langle\phi|\psi\rangle|^2[/itex]. He could mean that [itex]|\psi\rangle[/itex] and [itex]|\phi\rangle[/itex] are mutually exclusive if that probability is 0. That would of course imply that these state vectors are orthogonal.

After looking at a few of these explanations it seems like you are explaining exactly what he had in mind, if I am looking at my notes correctly. It is a rather trivial statement, but once and a while you come across vocabulary which tricks you into thinking it is a far more difficult concept than what is reality.
 

FAQ: Why are mutually exclusive states orthogonal?

1. What is the definition of mutually exclusive states?

Mutually exclusive states refer to a situation in which two or more outcomes or events cannot occur simultaneously. This means that if one state is present, the other state(s) cannot be present at the same time.

2. How do mutually exclusive states differ from independent events?

Mutually exclusive states are different from independent events because in mutually exclusive states, the occurrence of one event excludes the possibility of the other event happening. In independent events, the occurrence of one event does not affect the probability of the other event occurring.

3. What is the significance of understanding mutually exclusive states in scientific research?

Understanding mutually exclusive states is crucial in scientific research as it allows researchers to accurately analyze and interpret data. By identifying and controlling for mutually exclusive states, researchers can ensure that their results are not influenced by other factors and can draw more accurate conclusions.

4. Can mutually exclusive states change over time?

Yes, mutually exclusive states can change over time. This can happen due to various factors such as external influences, changes in conditions, or interactions between different states. It is important for researchers to continuously monitor and account for these changes in order to accurately interpret their data.

5. How can mutually exclusive states be represented in data analysis?

Mutually exclusive states can be represented in data analysis using techniques such as contingency tables, Venn diagrams, or tree diagrams. These visual representations help to clearly show the relationship between different states and can aid in analyzing the data more effectively.

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