A little notation help, on quantum coding

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Discussion Overview

The discussion revolves around understanding the notation and operations involved in quantum coding, specifically focusing on the representation of operators as matrices using complex vectors. Participants explore how to derive matrix representations from given vector states and clarify the distinction between conjugate transposes and regular transposes in the context of complex and real vectors.

Discussion Character

  • Exploratory
  • Technical explanation
  • Conceptual clarification
  • Debate/contested
  • Mathematical reasoning

Main Points Raised

  • One participant seeks general guidance on solving a problem related to quantum coding and expresses confusion about matrix formation.
  • Another participant explains that \langle v_2| represents the conjugate transpose of |v_2\rangle and provides its specific form.
  • A question arises about whether \langle v_2| is simply the transpose of v_2, which is clarified to be the conjugate transpose due to the involvement of complex vectors.
  • Participants discuss the necessity of choosing a basis to represent an operator as a matrix, with specific examples of |v_1\rangle and |v_2\rangle provided.
  • One participant expresses confusion about how a matrix can be derived from the operator |v_1\rangle \langle v_2| and requests a general case demonstration.
  • A later reply explains the multiplication of vectors to form a matrix and provides a specific matrix representation derived from the operator.
  • A participant questions whether the discussed concepts apply only to complex vectors or if they also hold for real-valued vectors.
  • Responses confirm that the same principles apply to real vectors, noting that the only difference is the use of the normal transpose instead of the conjugate transpose.

Areas of Agreement / Disagreement

Participants generally agree on the principles of matrix representation and the distinction between conjugate and regular transposes. However, there remains some uncertainty regarding the application of these concepts to different types of vectors, particularly in the context of real versus complex values.

Contextual Notes

Some participants express confusion about specific steps in deriving matrix elements, indicating that there may be missing assumptions or unresolved mathematical details in the discussion.

monica1977
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Hi, I wanted to know how to solve this question , its not a homework question i am really asking for , more the general way to solve these types of questions... I don't understand how it forms into another matrix. I have the answer attached as well , but could some one explain ? (I don't think the matrix A is needed , i just copied it as well )

Cheers for any help guys :)
 

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Do you know what \langle v_2| represents? It is the conjugate transpose of |v_2 \rangle. So \langle v_2|=\frac{1}{\sqrt{2}}(-i,-1).

Therefore
<br /> |v_1 \rangle \langle v_2|=\frac{1}{2} \binom{i}{1}(-i,-1)<br />
 
Last edited:
aint <v2 is the transpose of v2> ?
 
Almost, we are working with complex vectors here so it is the conjugate transpose. Do you know how to form a matrix from the the expression in my previous post?
 
To represent an operator as a matrix, you must choose a basis. In this case, the question presumably wants you to write it in the same basis that |v_1\rangle and |v_2\rangle are given in. You are given that

|v_1\rangle = \frac{1}{\sqrt{2}} ( i|1\rangle + |2\rangle)

|v_2\rangle = \frac{1}{\sqrt{2}} (i|1\rangle -|2\rangle)

The operator is

|v_1\rangle\langle v_2|.

The matrix elements of this operator in the basis |1\rangle, |2\rangle are

A_{ij} = \langle i|v_1\rangle\langle v_2|j\rangle.

For example, the (1,1) element of the matrix will be

A_{11} = \langle 1|v_1\rangle\langle v_2|1\rangle = \langle 1|v_1\rangle \langle 1 | v_2 \rangle ^{*} = \frac{i}{\sqrt{2}}\frac{-i}{\sqrt{2}} = \frac{1}{2}.
 
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Cheers Cyosis I understand that better now , but i still don't understand how what you wrote is i matrix and not a scalar ? , can u show me for a general case ? , or just show me how the answer is acheived ?
 
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To calculate |v_1 \rangle \langle v_2|=\frac{1}{2} \binom{i}{1}(-i,-1) just think of it as two matrices. You multiply the first row of v1 (i) with the first column of v2 (-i).

What you will get is this:
\frac{1}{2}\left( \begin{matrix} i*-i &amp; i*-1 \\ 1*-i &amp; 1*-1 \end{matrix}\right)= \frac{1}{2}\left( \begin{matrix} 1 &amp; -i \\ -i &amp; -1 \end{matrix}\right)
 
Hi I just wanted to ask quickly , does this only apply to only complex vectors ? , what if they was all real values ? , is it still the same then ?
 
Last edited:
Any one ?
 
  • #10
Yes it's the same. The only difference is that you usually take the normal transpose for real valued vectors since there is nothing to conjugate.
 
  • #11
Cyosis said:
Yes it's the same. The only difference is that you usually take the normal transpose for real valued vectors since there is nothing to conjugate.
Or the way I like to think about it, the conjugate transpose for real vectors (or matrices) is the normal transpose, since the conjugate of a real number is just the same number.
 

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