What Does Commutation Mean for Matrices A and B?

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Commutation of matrices A and B means that they satisfy the equation A·B = B·A, which is not true for most matrices. The discussion highlights the importance of matrix inverses, noting that (A·B)⁻¹ equals B⁻¹·A⁻¹, demonstrating that the order of multiplication matters. Participants confirm the correctness of using the identity matrix in their calculations, emphasizing that both left and right identities are equivalent. The conversation encourages exploring proofs related to these properties, suggesting a methodical approach to understanding matrix operations. Overall, the thread focuses on clarifying the implications of matrix commutation and the uniqueness of inverses.
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Homework Statement
Please see below
Relevant Equations
Please see below
For this,
1682209044875.png

Dose someone pleas know where they get ##C = CI## from?

Also,
1682209425978.png

What dose it mean when A and B commute?

Many thanks!
 
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ChiralSuperfields said:
Homework Statement: Please see below
Relevant Equations: Please see below

For this,
View attachment 325350
Dose someone pleas know where they get ##C = CI## from?

Also,
View attachment 325351
What dose it mean when A and B commute?

Many thanks!
Commuting matrices means that ##A\cdot B = B\cdot A.## Most matrices do not commute. That means
$$
(A\cdot B)^{-1} =B^{-1} \cdot A^{-1} \neq A^{-1}\cdot B^{-1} = (B\cdot A)^{-1}
$$

Inversion and transposition, too, change the order. You can see this by checking ##(A\cdot B)\cdot (A\cdot B)^{-1} =I.##
 
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fresh_42 said:
Commuting matrices means that ##A\cdot B = B\cdot A.## Most matrices do not commute. That means
$$
(A\cdot B)^{-1} =B^{-1} \cdot A^{-1} \neq A^{-1}\cdot B^{-1} = (B\cdot A)^{-1}
$$

Inversion and transposition, too, change the order. You can see this by checking ##(A\cdot B)\cdot (A\cdot B)^{-1} =I.##
Thank you for your reply @fresh_42 !

Is my checking correct ##A \cdot A^{-1} \cdot B \cdot B^{-1} = I_A \cdot I_B = I##?

Many thanks!
 
ChiralSuperfields said:
Thank you for your reply @fresh_42 !

Is my checking correct ##A \cdot A^{-1} \cdot B \cdot B^{-1} = I_A \cdot I_B = I##?

Many thanks!
Yes, but a bit short. The long version is:

\begin{align*}
(A\cdot B) \cdot (A\cdot B)^{-1}&=(A\cdot B) \cdot (B^{-1}\cdot A^{-1}) \\
&= A \cdot (B \cdot (B^{-1}\cdot A^{-1}))\\
&= A\cdot (( B\cdot B^{-1})\cdot A^{-1})\\
&= A\cdot (I\cdot A^{-1})\\
&= A \cdot A^{-1} \\
&= I
\end{align*}
This proves by using the associative law of multiplication that ##B^{-1}\cdot A^{-1}## is a inverse of ##(AB)^{-1}.##

I leave it to you to show that there cannot be more than one inverse, making ##B^{-1}\cdot A^{-1}## the inverse of ##(AB)^{-1}.## Same with the identity matrix. There can only be one so we do not need to distinguish between ##I_A## and ##I_B## or between left-identity ##I_L\cdot A=A## and right-identity ##A\cdot I_R=A.## Both are the same. This can also be proven.

These proofs are a bit like a puzzle playing around with the associative, possibly distributive law. A nice Sunday afternoon exercise. The trick is to proceed step by step and only use these laws plus the definitions, e.g. that ##I_L\cdot A=A## and ##A\cdot I_R=A.## Show that ##I_L=I_R\,!##
 
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The working out suggests first equating ## \sqrt{i} = x + iy ## and suggests that squaring and equating real and imaginary parts of both sides results in ## \sqrt{i} = \pm (1+i)/ \sqrt{2} ## Squaring both sides results in: $$ i = (x + iy)^2 $$ $$ i = x^2 + 2ixy -y^2 $$ equating real parts gives $$ x^2 - y^2 = 0 $$ $$ (x+y)(x-y) = 0 $$ $$ x = \pm y $$ equating imaginary parts gives: $$ i = 2ixy $$ $$ 2xy = 1 $$ I'm not really sure how to proceed from here.