How do we solve for equation 1.8.7 on page 33 of Shankar's QM 2nd Edition?

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SUMMARY

The discussion focuses on solving equation 1.8.7 from Shankar's "Quantum Mechanics" 2nd Edition, specifically the expression ##=0##. Participants clarify the decomposition of the vector ##|V>## into basis vectors and the implications of orthogonality in evaluating the inner product. The identity operator's role is debated, with emphasis on its implicit nature in quantum mechanics. The correct application of the identity operator and the handling of bra-ket notation are also addressed, ensuring clarity in the mathematical process.

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  • Understanding of quantum mechanics notation, specifically bra-ket notation.
  • Familiarity with linear algebra concepts, particularly vector decomposition.
  • Knowledge of operator theory in quantum mechanics, including the identity operator.
  • Experience with matrix elements in quantum mechanics, such as ####.
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  • Study the implications of the identity operator in quantum mechanics.
  • Learn about the properties of orthogonal basis vectors in Hilbert spaces.
  • Explore the derivation and applications of matrix elements in quantum mechanics.
  • Review Shankar's "Quantum Mechanics" for deeper insights into operator algebra.
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Students and professionals in quantum mechanics, particularly those working with operator theory and bra-ket notation, will benefit from this discussion. It is especially relevant for those studying Shankar's text or similar quantum mechanics literature.

bugatti79
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Hi Folks,

How do we arrive at equation 1.8.7 page 33.

We have ##<i|\Omega-\omega I|V>=0##, given ##I=\Sigma_{j=1}|i><i|## we can write

##<i|\Omega-\omega \Sigma_{j=1}|i><i||V>=0##

not sure how to proceed from here...
 
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You can decompose
bugatti79 said:
Hi Folks,

How do we arrive at equation 1.8.7 page 33.

We have ##<i|\Omega-\omega I|V>=0##, given ##I=\Sigma_{j=1}|i><i|## we can write

##<i|\Omega-\omega \Sigma_{j=1}|i><i||V>=0##

not sure how to proceed from here...

You can write your vector V as a linear combination of the basis vectors

##|V>=Sigmavj|j>##

and then using the fact that the basis vector are orthogonal with each other you can evaluate the bracket, taking into account that ωij are the matrix element of Ω in the |i> basis (<i|Ω|j>=ωij)
 
Last edited:
I can get as far as

##<I| \Omega - \omega \Sigma_{I} |I><I| \Sigma_{j} v_{j} |j>=0##

##\Sigma_{j} \Omega - \omega \Sigma_{I} |I><I| v_{j} \delta_{ij}=0##

How is the identity dealt with?
 
Don't put the identity in the first place, and remember that <i|Ω|j>=Ωij (eq 1.6.1) (I wrote it wrong in my last post)
 
I do not follow regarding the identity. I do not know how to remove it. Can u clarify?
 
I could show you the whole process but I don't know how to type it.
 
Ok here it is

##\left\langle i\right|\Omega-\omega\left|v\right\rangle = \left\langle i\right|\Omega-\omega(\sum_{j}v_{j}\left|j\right\rangle )##
## = \sum_{j}v_{j}\left\langle i\right|\Omega\left|j\right\rangle -\omega\sum_{j}v_{j}\left\langle i\right.\left|j\right\rangle ##
## =\sum_{j}v_{j} \Omega_{ij}-\omega\sum_{j}v_{j}\delta_{ij}##
## = \sum_{j}v_{j}(\Omega_{ij}-v_{j}\delta_{ij})##
 
Last edited:
Thanks for your efforts, just some questions:

1) How do you justify omitting the identity I?
Are you treating this equal to 1 because the action of the identity operator on a ket is just the same ket?
Additionally, Shankar specifically instructed to apply the identity operator to the left of |V>

2) How did you arrive with a 2nd bra <i| on the second line? There is only one.

regards
 
1) Yeah, the identity is implied, it action of a ket and a bra is to leave it as they are. (reading Shankar I don't know why one would introduce the representation of the identity though)

2)Well, the actual equation is
##\left\langle i\right|(\Omega-\omega\left)|v\right\rangle=0 ##

Look at 1.8.3 and multiply by the left by the i bra.
 
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To clarify, You can't really have

##(\left\langle i\right|\Omega)-(\omega\left|v\right\rangle) ##

because that would be adding a bra to a ket and you can't do that since they belong to different vector spaces.
 
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