Understanding Bras and Kets as Vectors and Tensors

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Bras and kets can be understood as vectors in a Hilbert space, with kets represented as vectors with upper indices and bras as vectors with lower indices. In finite-dimensional spaces, bras exist in the dual space, which is isomorphic to the primal space, but this distinction becomes significant in infinite dimensions. The Hermitian inner product in finite dimensions can be defined similarly to how it's done with real vectors, using complex conjugation for inner products. While kets can be considered as elements of a vector space, the concept of a coordinate basis is less applicable, as the basis vectors are typically eigenvectors of Hermitian operators. Overall, the discussion emphasizes the relationship between bras, kets, and tensor products within the framework of linear algebra and functional analysis.
  • #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?
 
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  • #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.)
 

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