Understanding Bras and Kets as Vectors and Tensors

  • Context: Graduate 
  • Thread starter Thread starter Phrak
  • Start date Start date
  • Tags Tags
    Tensors
Click For Summary
SUMMARY

The discussion centers on the relationship between bras and kets in quantum mechanics and their representation as vectors and tensors within Hilbert spaces. Kets are defined as vectors in a Hilbert space, while bras correspond to vectors in the dual space, denoted as H*. The distinction between finite and infinite-dimensional spaces is emphasized, particularly regarding the isomorphism of these spaces and the implications for raising and lowering indices. The Hermitian inner product is also discussed, highlighting its role in defining the inner product in finite-dimensional Hilbert spaces.

PREREQUISITES
  • Understanding of Hilbert spaces and their properties
  • Familiarity with linear algebra concepts, particularly vector spaces and dual spaces
  • Knowledge of Hermitian operators and their significance in quantum mechanics
  • Basic grasp of tensor products and their applications in physics
NEXT STEPS
  • Study "Functional Analysis" textbooks to deepen understanding of dual spaces and inner products
  • Learn about Hermitian operators and their eigenvectors in quantum mechanics
  • Explore the concept of tensor products and their applications in quantum state representation
  • Investigate the implications of finite vs. infinite-dimensional Hilbert spaces in quantum theory
USEFUL FOR

Students and professionals in quantum mechanics, physicists exploring the mathematical foundations of quantum theory, and anyone interested in the mathematical representation of quantum states using bras and kets.

  • #151
Phrak said:
mrandersdk-

If |00>,|01>,|10> and |11> (1=up,0=down)

are linear independent vectors, then <01|01> = 0,

rather than <01|01> = <0|0><1|1>, as you suggest.
How do you figure?
 
Physics news on Phys.org
  • #152
Hans de Vries said:
You may have an argument in that I implicitly assume that in R\otimes R one is a row vector and the other is a column vector, so an nx1 vector times a 1xn vector is an nxn matrix, but I wouldn't even know how to express a transpose operation at higher ranks without people loosing track of the otherwise very
simple math.
Regards, Hans

Transposition is more of a notational device, than anything, to keep track of where the rows and columns are.

In higher ranks, you can use labels to keep track rows, columns, depth..., and use a modified Einstein summation to multiply matrices.

Y = M^{T} \Rightarrow Y_{cr} = M_{rc}

(M_{abc...z} N_{abc...z})_{(fg)} = \stackrel{\Sum (M_{abc...z} N_{abc...z})}{f,g=i, i=1...n}, f
__________________________
Any mistakes I blame on LaTex
 
  • #153
Hans de Vries said:
You may have an argument in that I implicitly assume that in R\otimes R one is a row vector and the other is a column vector, so an nx1 vector times a 1xn vector is an nxn matrix, but I wouldn't even know how to express a transpose operation at higher ranks without people loosing track of the otherwise very
simple math.

Regards, Hans

Transposition is more of a notational device, than anything, to keep track of where the rows and columns are. Which elements combine with which elements between two tensors is unchange by

In higher ranks, you can use labels to keep track of rows, columns, depth...etc, and use a modified Einstein summation to multiply matrices.

Y = M^{T} \Rightarrow Y_{cr} = M_{rc}

(M_{abc...f} N_{c\: d\: e...z})_{(dp)} \equiv \sum_{d_i , p_i \ i=1...n} (M_{abc...f} N_{c\: d\: e...z})}\ , \ \ \ \ d \neq p

L_{abc_{m}e_{m}f_{m}c_{n}e_{n}f_{n}ghi...o,qrs...z} = (M_{abcef} N_{efg...z})

______________________________________________________________________
Any mistakes now, in the past, or ever, I blame on LaTex, whether I'm using it or not.
 
  • #154
Phrak said:
mrandersdk-

If |00>,|01>,|10> and |11> (1=up,0=down)

are linear independent vectors, then <01|01> = 0,

rather than <01|01> = <0|0><1|1>, as you suggest.

no, |01&gt;^\dagger = &lt;01|
 
  • #155
mrandersdk, Hurkl-

I posted:
If |00>,|01>,|10> and |11> (1=up,0=down)

are linear independent vectors, then <01|01> = 0,

rather than <01|01> = <0|0><1|1>, as you suggest.

Hurkyl said:
How do you figure?

:eek: I figure, I misread <01|01> as <01|10> :redface:

(I wouldn't mind if someone deleted my extra and partially edited post, #152.)
 

Similar threads

  • · Replies 5 ·
Replies
5
Views
4K
  • · Replies 16 ·
Replies
16
Views
3K
  • · Replies 7 ·
Replies
7
Views
844
  • · Replies 3 ·
Replies
3
Views
2K
  • · Replies 2 ·
Replies
2
Views
2K
  • · Replies 7 ·
Replies
7
Views
3K
  • · Replies 6 ·
Replies
6
Views
918
Replies
6
Views
2K
  • · Replies 3 ·
Replies
3
Views
1K
  • · Replies 4 ·
Replies
4
Views
3K