How Can Hermitian Operators Prove Key Quantum Mechanics Equations?

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Homework Help Overview

The discussion revolves around proving a quantum mechanics equation involving Hermitian operators. The original poster presents an equation relating a Hermitian operator \( A \), its expectation value \( \langle A \rangle \), and the standard deviation \( \Delta A \) in the context of quantum states.

Discussion Character

  • Exploratory, Conceptual clarification, Mathematical reasoning

Approaches and Questions Raised

  • Participants discuss the representation of the quantum state as a superposition of eigenfunctions of the Hermitian operator. There are attempts to calculate inner products and explore the implications of orthogonality in quantum states. Questions arise regarding the assumptions made about the spectrum of the operator and the implications of certain calculations yielding zero.

Discussion Status

The discussion is active, with participants exploring different interpretations and calculations related to the equation. Some guidance has been offered regarding the implications of inner products and the relationship between the constants involved. There is a recognition of the need to clarify assumptions and definitions related to the problem.

Contextual Notes

Participants note potential constraints regarding the assumptions about the operator's spectrum and the definitions of the quantum states involved. The discussion reflects a variety of interpretations and approaches without reaching a consensus on the next steps.

Raz91
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Prove the equation

A\left|\psi\right\rangle = \left\langle A\right\rangle\left|\psi\right\rangle + \Delta A\left|\psi\bot\right\rangle

where A is a Hermitian operator and \left\langle\psi |\psi\bot\right\rangle = 0


\left\langle A\right\rangle = The expectation value of A.
\Delta A = The standard deviation of A.


My attempt :

I tried to write \left|\psi\right\rangle as a superposition of the eigenfuncion of the operator A and used the fact that it's a Hermitian operator

A\left|\phi_{n}\right\rangle = \lambda_{n}\left|\phi_{n}\right\rangle , \left|\psi\right\rangle = \sum a_{n}\left|\phi_{n}\right\rangle

so that A\left|\psi\right\rangle = \sum a_{n}\lambda_{n}\left|\phi_{n}\right\rangle

and \left\langle A\right\rangle = \sum |a_{n}|^{2}\lambda_{n}


\Delta A = \sqrt{\left\langle A^{2}\right\rangle - \left\langle A\right\rangle ^{2}}

and I wrote \left|\psi\bot\right\rangle as \left|\psi\bot\right\rangle = \sum b_{n}\left|\phi_{n}\right\rangle

\sum a^{*}_{n}b_{n} = 0

I don't know how to go on from here...
any ideas?

thank you! :)
 
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Hmm, using that the s-adj A has a purely discrete spectrum is not ok, it's not assumed in the problem. And I think you left out a square. I get

A\psi = \langle A \rangle \psi + (\Delta A)^2 \psi_{\perp}

under the simplifying assumptions \psi_{\perp} \in D(A) and \mbox{Ran}(A)\subset D(A).
 
The first step I found to resolution is to calculate:

\langle \psi,(A-\langle A\rangle ) \psi\rangle

What do you get and what do you conclude ?
 
I didn't miss the squar.. this is the question.
you get wrong units if you put the squar there ...
 
dextercioby said:
The first step I found to resolution is to calculate:

\langle \psi,(A-\langle A\rangle ) \psi\rangle

What do you get and what do you conclude ?

this yields zero .. i didn't understand how it can help me

thank you
 
If it yields zero, then the vector in the rhs of the scalar product is perpendicular on psi, so it's psi perp times a non-zero constant.
 
I don't understand something -
there are lots of functions that can be perpendicular to psi

e.g (euclidean space)- the vector z (cartesian coordinates) , x is prep to z and y is prep to z but also the superposition (x+y) is prep to z.

so by writing psi prep do u mean to the superposition of all the functions that prep to psi or it's enough to choose only one?
 
Yes, Psi_perp is an arbitrary vector perpendicular to the psi already chosen. You get from ⟨ψ,(A−⟨A⟩)ψ⟩ = 0 that C psi_perp = A psi - <A> psi. All you need to show is that C is related to the standard deviation in square.
 

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