Equalities for Paulimatrix averages

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In summary, the formula <S_x^2> = <S_y^2>=<S_z^2>=\hbar^2/4 holds even for random spinors because each component, such as S_x, has a corresponding formula that gives the expected value of that component. The formula for S_x^2 is not the same as the formula for <S_x>^2, which can result in different values.
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I've come across this a few times:

[tex] <S_x^2> = <S_y^2>=<S_z^2>=\hbar^2/4[/tex]

But I can't seem to understand why this holds, as <S_x>, <S_y> and <S_z> sometimes give really strange values for a random spinor, with no correlation at all.

Can anyone explain this to me? Thanks!
 
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If [itex]S_x=\frac{\hbar}{2}\sigma_x[/itex], then [itex]S_x^2=\hbar^2/4[/itex], and the same for other components, thus your formula holds even without expectation values.

You should not mix [itex]<S_x>^2[/itex] with [itex]<S_x^2>[/itex]. These are different things. If you jump to the left (-1) and to the right (+1) then the average can be zero, but the average of the squares will be >0.
 
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FAQ: Equalities for Paulimatrix averages

What is the concept of "Equalities for Paulimatrix averages"?

The concept of "Equalities for Paulimatrix averages" refers to a mathematical framework for calculating the average value of a set of matrices, which are used to represent quantum states in quantum mechanics. It is based on the concept of Pauli matrices, which are a set of three matrices used to describe the spin of a particle in quantum mechanics.

Why is "Equalities for Paulimatrix averages" important in quantum mechanics?

"Equalities for Paulimatrix averages" is important in quantum mechanics because it allows for the calculation of the average value of a quantum state, which is a crucial aspect of understanding and predicting the behavior of quantum systems. It also provides a way to compare different quantum states and determine their similarities and differences.

How is the average value of a set of Pauli matrices calculated?

The average value of a set of Pauli matrices is calculated using the concept of trace, which is a mathematical operation that sums the diagonal elements of a matrix. The trace of a set of Pauli matrices is then divided by the number of matrices in the set to obtain the average value.

What are some real-world applications of "Equalities for Paulimatrix averages"?

One real-world application of "Equalities for Paulimatrix averages" is in quantum computing, where it is used to analyze and manipulate quantum states. It is also used in quantum chemistry to calculate the electronic structure of molecules and in quantum cryptography to ensure the security of communication.

Are there any limitations to the use of "Equalities for Paulimatrix averages"?

Yes, there are some limitations to the use of "Equalities for Paulimatrix averages". It is only applicable to Pauli matrices or matrices that can be expressed as a linear combination of Pauli matrices. It also assumes that the matrices in the set are independent and identically distributed, which may not always be the case in real-world situations.

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