Prove that for square matrices $tr(Atimes B)=tr(A)tr(B).$

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Prove that for square matrices $ A,(mtimes m) $ and $ B,(ntimes n) $, $tr(Atimes B)=tr(A)tr(B).$
$tr(A)=sum_i=1^ma_ii=a_11+a_22+...+a_mm$
$tr(B)=sum_i=1^nb_ii=b_11+b_22+...+b_nn$
Since $Atimes B$ has to be true, the matrices have to be the same size and $m=n$.
$Atimes B=sum_k=1^m a_ikb_kj=a_i1b_1j+...+a_nmb_mn$
I don't know if what I've done is correct so far and I'm not sure how to go on with solving the trace of $Atimes B$.
linear-algebra matrices
add a comment |Â
up vote
0
down vote
favorite
Prove that for square matrices $ A,(mtimes m) $ and $ B,(ntimes n) $, $tr(Atimes B)=tr(A)tr(B).$
$tr(A)=sum_i=1^ma_ii=a_11+a_22+...+a_mm$
$tr(B)=sum_i=1^nb_ii=b_11+b_22+...+b_nn$
Since $Atimes B$ has to be true, the matrices have to be the same size and $m=n$.
$Atimes B=sum_k=1^m a_ikb_kj=a_i1b_1j+...+a_nmb_mn$
I don't know if what I've done is correct so far and I'm not sure how to go on with solving the trace of $Atimes B$.
linear-algebra matrices
1
See this
– mrs
Sep 10 at 9:09
3
The statement is false.
– Kavi Rama Murthy
Sep 10 at 9:10
11
Are you considering Kronecker product? Then $operatornametr(Aotimes B)=(operatornametrA)(operatornametrB)$ is true for square matrices $A$ and $B$.
– Sangchul Lee
Sep 10 at 9:11
1
Your notation is not standard. Please clarify if by $times$ you mean the Kronecker product or the standard matrix product.
– leonbloy
Sep 10 at 13:58
Hi! I am sorry for the unclear presentation. By $times$ I mean the Kronecker product. Thank you to all who have taken time to help me out!
– Zoë
Sep 11 at 9:58
add a comment |Â
up vote
0
down vote
favorite
up vote
0
down vote
favorite
Prove that for square matrices $ A,(mtimes m) $ and $ B,(ntimes n) $, $tr(Atimes B)=tr(A)tr(B).$
$tr(A)=sum_i=1^ma_ii=a_11+a_22+...+a_mm$
$tr(B)=sum_i=1^nb_ii=b_11+b_22+...+b_nn$
Since $Atimes B$ has to be true, the matrices have to be the same size and $m=n$.
$Atimes B=sum_k=1^m a_ikb_kj=a_i1b_1j+...+a_nmb_mn$
I don't know if what I've done is correct so far and I'm not sure how to go on with solving the trace of $Atimes B$.
linear-algebra matrices
Prove that for square matrices $ A,(mtimes m) $ and $ B,(ntimes n) $, $tr(Atimes B)=tr(A)tr(B).$
$tr(A)=sum_i=1^ma_ii=a_11+a_22+...+a_mm$
$tr(B)=sum_i=1^nb_ii=b_11+b_22+...+b_nn$
Since $Atimes B$ has to be true, the matrices have to be the same size and $m=n$.
$Atimes B=sum_k=1^m a_ikb_kj=a_i1b_1j+...+a_nmb_mn$
I don't know if what I've done is correct so far and I'm not sure how to go on with solving the trace of $Atimes B$.
linear-algebra matrices
linear-algebra matrices
asked Sep 10 at 9:08
Zoë
1285
1285
1
See this
– mrs
Sep 10 at 9:09
3
The statement is false.
– Kavi Rama Murthy
Sep 10 at 9:10
11
Are you considering Kronecker product? Then $operatornametr(Aotimes B)=(operatornametrA)(operatornametrB)$ is true for square matrices $A$ and $B$.
– Sangchul Lee
Sep 10 at 9:11
1
Your notation is not standard. Please clarify if by $times$ you mean the Kronecker product or the standard matrix product.
– leonbloy
Sep 10 at 13:58
Hi! I am sorry for the unclear presentation. By $times$ I mean the Kronecker product. Thank you to all who have taken time to help me out!
– Zoë
Sep 11 at 9:58
add a comment |Â
1
See this
– mrs
Sep 10 at 9:09
3
The statement is false.
– Kavi Rama Murthy
Sep 10 at 9:10
11
Are you considering Kronecker product? Then $operatornametr(Aotimes B)=(operatornametrA)(operatornametrB)$ is true for square matrices $A$ and $B$.
– Sangchul Lee
Sep 10 at 9:11
1
Your notation is not standard. Please clarify if by $times$ you mean the Kronecker product or the standard matrix product.
– leonbloy
Sep 10 at 13:58
Hi! I am sorry for the unclear presentation. By $times$ I mean the Kronecker product. Thank you to all who have taken time to help me out!
– Zoë
Sep 11 at 9:58
1
1
See this
– mrs
Sep 10 at 9:09
See this
– mrs
Sep 10 at 9:09
3
3
The statement is false.
– Kavi Rama Murthy
Sep 10 at 9:10
The statement is false.
– Kavi Rama Murthy
Sep 10 at 9:10
11
11
Are you considering Kronecker product? Then $operatornametr(Aotimes B)=(operatornametrA)(operatornametrB)$ is true for square matrices $A$ and $B$.
– Sangchul Lee
Sep 10 at 9:11
Are you considering Kronecker product? Then $operatornametr(Aotimes B)=(operatornametrA)(operatornametrB)$ is true for square matrices $A$ and $B$.
– Sangchul Lee
Sep 10 at 9:11
1
1
Your notation is not standard. Please clarify if by $times$ you mean the Kronecker product or the standard matrix product.
– leonbloy
Sep 10 at 13:58
Your notation is not standard. Please clarify if by $times$ you mean the Kronecker product or the standard matrix product.
– leonbloy
Sep 10 at 13:58
Hi! I am sorry for the unclear presentation. By $times$ I mean the Kronecker product. Thank you to all who have taken time to help me out!
– Zoë
Sep 11 at 9:58
Hi! I am sorry for the unclear presentation. By $times$ I mean the Kronecker product. Thank you to all who have taken time to help me out!
– Zoë
Sep 11 at 9:58
add a comment |Â
2 Answers
2
active
oldest
votes
up vote
2
down vote
accepted
Suppose that $A$ is $mtimes m$ with typical elements $A_ij$ and $B$ is $ntimes n$ with typical elements $B_hk$. We have
$$
Aotimes B=beginpmatrix
A_11B & A_12B & cdots & A_1mB\
A_21B & A_22B & cdots & A_2mB \
vdots & vdots & ddots & vdots \
A_m1B & A_m2B & cdots & A_mmB
endpmatrix
$$
so the diagonal elements of $Aotimes B$ are
$$
A_11B_11,ldots,A_11B_nn,A_22B_11,ldots,A_22B_nn,ldots,A_mmB_11,ldots,A_mmB_nn.
$$
Summing these yields
beginalign*
&quadoperatornameTr(Aotimes B)\
&=A_11B_11+cdots+A_11B_nn+A_22B_11+cdots+A_22B_nn+cdots+A_mmB_11+cdots+A_mmB_nn\
&=A_11(B_11+cdots+B_nn)+A_22(B_11+cdots+B_nn)+cdots+A_mm(B_11+cdots+B_nn)\
&=(A_11+cdots+A_mm)(B_11+cdots+B_nn)=operatornameTr(A)operatornameTr(B).
endalign*
add a comment |Â
up vote
1
down vote
If you meant $operatornametr(Atimes B)$ as $operatornametr(Aotimes B)$ then as @Sangchul Lee mentioned, we have:
$displaystyle beginbmatrixa&b\c&d\endbmatrixotimes beginbmatrixp&q\r&s\endbmatrix=beginbmatrixacdot beginbmatrixp&q\r&s\endbmatrix&bcdot beginbmatrixp&q\r&s\endbmatrix\ccdot beginbmatrixp&q\r&s\endbmatrix&dcdot beginbmatrixp&q\r&s\endbmatrix\endbmatrix=beginbmatrixacdot p&acdot q&bcdot p&bcdot q\acdot r&acdot s&bcdot r&bcdot s\ccdot p&ccdot q&dcdot p&dcdot q\ccdot r&ccdot s&dcdot r&dcdot s\endbmatrix$
So we have:
$$(operatornametrA)(operatornametrB)=(a+d)(p+s)=acdot p+a cdot s+dcdot p+dcdot s=operatornametr(Aotimes B)$$
Where $otimes$ is the Kronecker Product and $operatornametr(.)$ is the trace of a matrix.
If you meant $operatornametr(Atimes B)$ as $operatornametr(AB)$, which is a simple Matrix multiplication, then :
$displaystyle beginbmatrixa&b\c&d\endbmatrix beginbmatrixp&q\r&s\endbmatrix=beginbmatrixap+br&aq+bs\cp+dr&cq+ds\endbmatrix$
So now we can see that:
$$(operatornametrA)(operatornametrB)=(a+d)(p+s)=acdot p+a cdot s+dcdot p+dcdot s ne acdot p+bcdot r+ccdot q+dcdot s=operatornametr(AB)$$
You can follow the same methodology and it would be true for any $ntimes n$ matrices.
What about cases beyond the $2times 2$ one?
– anomaly
Sep 10 at 12:28
1
@anomaly the calculations are perfectly the same
– Riccardo Ceccon
Sep 10 at 12:30
@anomaly As ricardo said, the calculations are exactly the same. Moreover, I personally feel that this kind of small matrix products will help develop intuitions required to generalise the method. I also feel that it might look a bit "cluttered" when you try to generalise something with dots ($cdot cdot cdot$) and $n^th$ terms. It's just my way of thinking though :)
– paulplusx
Sep 10 at 14:10
@paulplusx: The solution to that is using better notation (e.g., yurnero's solution below), not grinding through the details of a particular case.
– anomaly
Sep 10 at 17:27
@anomaly Well, you are correct and your argument applies to all such generalization perfectly but I feel that if there is another method (shouldn't call it a method) of "understanding" it by using simple examples (similar to induction) and then generalizing it intuitively, sometimes it helps a lot, much better than notations(at least for me). I do accept that yurnero's solution is perfect for this question (because it literally answers it to the point).
– paulplusx
Sep 10 at 17:44
add a comment |Â
2 Answers
2
active
oldest
votes
2 Answers
2
active
oldest
votes
active
oldest
votes
active
oldest
votes
up vote
2
down vote
accepted
Suppose that $A$ is $mtimes m$ with typical elements $A_ij$ and $B$ is $ntimes n$ with typical elements $B_hk$. We have
$$
Aotimes B=beginpmatrix
A_11B & A_12B & cdots & A_1mB\
A_21B & A_22B & cdots & A_2mB \
vdots & vdots & ddots & vdots \
A_m1B & A_m2B & cdots & A_mmB
endpmatrix
$$
so the diagonal elements of $Aotimes B$ are
$$
A_11B_11,ldots,A_11B_nn,A_22B_11,ldots,A_22B_nn,ldots,A_mmB_11,ldots,A_mmB_nn.
$$
Summing these yields
beginalign*
&quadoperatornameTr(Aotimes B)\
&=A_11B_11+cdots+A_11B_nn+A_22B_11+cdots+A_22B_nn+cdots+A_mmB_11+cdots+A_mmB_nn\
&=A_11(B_11+cdots+B_nn)+A_22(B_11+cdots+B_nn)+cdots+A_mm(B_11+cdots+B_nn)\
&=(A_11+cdots+A_mm)(B_11+cdots+B_nn)=operatornameTr(A)operatornameTr(B).
endalign*
add a comment |Â
up vote
2
down vote
accepted
Suppose that $A$ is $mtimes m$ with typical elements $A_ij$ and $B$ is $ntimes n$ with typical elements $B_hk$. We have
$$
Aotimes B=beginpmatrix
A_11B & A_12B & cdots & A_1mB\
A_21B & A_22B & cdots & A_2mB \
vdots & vdots & ddots & vdots \
A_m1B & A_m2B & cdots & A_mmB
endpmatrix
$$
so the diagonal elements of $Aotimes B$ are
$$
A_11B_11,ldots,A_11B_nn,A_22B_11,ldots,A_22B_nn,ldots,A_mmB_11,ldots,A_mmB_nn.
$$
Summing these yields
beginalign*
&quadoperatornameTr(Aotimes B)\
&=A_11B_11+cdots+A_11B_nn+A_22B_11+cdots+A_22B_nn+cdots+A_mmB_11+cdots+A_mmB_nn\
&=A_11(B_11+cdots+B_nn)+A_22(B_11+cdots+B_nn)+cdots+A_mm(B_11+cdots+B_nn)\
&=(A_11+cdots+A_mm)(B_11+cdots+B_nn)=operatornameTr(A)operatornameTr(B).
endalign*
add a comment |Â
up vote
2
down vote
accepted
up vote
2
down vote
accepted
Suppose that $A$ is $mtimes m$ with typical elements $A_ij$ and $B$ is $ntimes n$ with typical elements $B_hk$. We have
$$
Aotimes B=beginpmatrix
A_11B & A_12B & cdots & A_1mB\
A_21B & A_22B & cdots & A_2mB \
vdots & vdots & ddots & vdots \
A_m1B & A_m2B & cdots & A_mmB
endpmatrix
$$
so the diagonal elements of $Aotimes B$ are
$$
A_11B_11,ldots,A_11B_nn,A_22B_11,ldots,A_22B_nn,ldots,A_mmB_11,ldots,A_mmB_nn.
$$
Summing these yields
beginalign*
&quadoperatornameTr(Aotimes B)\
&=A_11B_11+cdots+A_11B_nn+A_22B_11+cdots+A_22B_nn+cdots+A_mmB_11+cdots+A_mmB_nn\
&=A_11(B_11+cdots+B_nn)+A_22(B_11+cdots+B_nn)+cdots+A_mm(B_11+cdots+B_nn)\
&=(A_11+cdots+A_mm)(B_11+cdots+B_nn)=operatornameTr(A)operatornameTr(B).
endalign*
Suppose that $A$ is $mtimes m$ with typical elements $A_ij$ and $B$ is $ntimes n$ with typical elements $B_hk$. We have
$$
Aotimes B=beginpmatrix
A_11B & A_12B & cdots & A_1mB\
A_21B & A_22B & cdots & A_2mB \
vdots & vdots & ddots & vdots \
A_m1B & A_m2B & cdots & A_mmB
endpmatrix
$$
so the diagonal elements of $Aotimes B$ are
$$
A_11B_11,ldots,A_11B_nn,A_22B_11,ldots,A_22B_nn,ldots,A_mmB_11,ldots,A_mmB_nn.
$$
Summing these yields
beginalign*
&quadoperatornameTr(Aotimes B)\
&=A_11B_11+cdots+A_11B_nn+A_22B_11+cdots+A_22B_nn+cdots+A_mmB_11+cdots+A_mmB_nn\
&=A_11(B_11+cdots+B_nn)+A_22(B_11+cdots+B_nn)+cdots+A_mm(B_11+cdots+B_nn)\
&=(A_11+cdots+A_mm)(B_11+cdots+B_nn)=operatornameTr(A)operatornameTr(B).
endalign*
answered Sep 10 at 12:45
yurnero
6,9541824
6,9541824
add a comment |Â
add a comment |Â
up vote
1
down vote
If you meant $operatornametr(Atimes B)$ as $operatornametr(Aotimes B)$ then as @Sangchul Lee mentioned, we have:
$displaystyle beginbmatrixa&b\c&d\endbmatrixotimes beginbmatrixp&q\r&s\endbmatrix=beginbmatrixacdot beginbmatrixp&q\r&s\endbmatrix&bcdot beginbmatrixp&q\r&s\endbmatrix\ccdot beginbmatrixp&q\r&s\endbmatrix&dcdot beginbmatrixp&q\r&s\endbmatrix\endbmatrix=beginbmatrixacdot p&acdot q&bcdot p&bcdot q\acdot r&acdot s&bcdot r&bcdot s\ccdot p&ccdot q&dcdot p&dcdot q\ccdot r&ccdot s&dcdot r&dcdot s\endbmatrix$
So we have:
$$(operatornametrA)(operatornametrB)=(a+d)(p+s)=acdot p+a cdot s+dcdot p+dcdot s=operatornametr(Aotimes B)$$
Where $otimes$ is the Kronecker Product and $operatornametr(.)$ is the trace of a matrix.
If you meant $operatornametr(Atimes B)$ as $operatornametr(AB)$, which is a simple Matrix multiplication, then :
$displaystyle beginbmatrixa&b\c&d\endbmatrix beginbmatrixp&q\r&s\endbmatrix=beginbmatrixap+br&aq+bs\cp+dr&cq+ds\endbmatrix$
So now we can see that:
$$(operatornametrA)(operatornametrB)=(a+d)(p+s)=acdot p+a cdot s+dcdot p+dcdot s ne acdot p+bcdot r+ccdot q+dcdot s=operatornametr(AB)$$
You can follow the same methodology and it would be true for any $ntimes n$ matrices.
What about cases beyond the $2times 2$ one?
– anomaly
Sep 10 at 12:28
1
@anomaly the calculations are perfectly the same
– Riccardo Ceccon
Sep 10 at 12:30
@anomaly As ricardo said, the calculations are exactly the same. Moreover, I personally feel that this kind of small matrix products will help develop intuitions required to generalise the method. I also feel that it might look a bit "cluttered" when you try to generalise something with dots ($cdot cdot cdot$) and $n^th$ terms. It's just my way of thinking though :)
– paulplusx
Sep 10 at 14:10
@paulplusx: The solution to that is using better notation (e.g., yurnero's solution below), not grinding through the details of a particular case.
– anomaly
Sep 10 at 17:27
@anomaly Well, you are correct and your argument applies to all such generalization perfectly but I feel that if there is another method (shouldn't call it a method) of "understanding" it by using simple examples (similar to induction) and then generalizing it intuitively, sometimes it helps a lot, much better than notations(at least for me). I do accept that yurnero's solution is perfect for this question (because it literally answers it to the point).
– paulplusx
Sep 10 at 17:44
add a comment |Â
up vote
1
down vote
If you meant $operatornametr(Atimes B)$ as $operatornametr(Aotimes B)$ then as @Sangchul Lee mentioned, we have:
$displaystyle beginbmatrixa&b\c&d\endbmatrixotimes beginbmatrixp&q\r&s\endbmatrix=beginbmatrixacdot beginbmatrixp&q\r&s\endbmatrix&bcdot beginbmatrixp&q\r&s\endbmatrix\ccdot beginbmatrixp&q\r&s\endbmatrix&dcdot beginbmatrixp&q\r&s\endbmatrix\endbmatrix=beginbmatrixacdot p&acdot q&bcdot p&bcdot q\acdot r&acdot s&bcdot r&bcdot s\ccdot p&ccdot q&dcdot p&dcdot q\ccdot r&ccdot s&dcdot r&dcdot s\endbmatrix$
So we have:
$$(operatornametrA)(operatornametrB)=(a+d)(p+s)=acdot p+a cdot s+dcdot p+dcdot s=operatornametr(Aotimes B)$$
Where $otimes$ is the Kronecker Product and $operatornametr(.)$ is the trace of a matrix.
If you meant $operatornametr(Atimes B)$ as $operatornametr(AB)$, which is a simple Matrix multiplication, then :
$displaystyle beginbmatrixa&b\c&d\endbmatrix beginbmatrixp&q\r&s\endbmatrix=beginbmatrixap+br&aq+bs\cp+dr&cq+ds\endbmatrix$
So now we can see that:
$$(operatornametrA)(operatornametrB)=(a+d)(p+s)=acdot p+a cdot s+dcdot p+dcdot s ne acdot p+bcdot r+ccdot q+dcdot s=operatornametr(AB)$$
You can follow the same methodology and it would be true for any $ntimes n$ matrices.
What about cases beyond the $2times 2$ one?
– anomaly
Sep 10 at 12:28
1
@anomaly the calculations are perfectly the same
– Riccardo Ceccon
Sep 10 at 12:30
@anomaly As ricardo said, the calculations are exactly the same. Moreover, I personally feel that this kind of small matrix products will help develop intuitions required to generalise the method. I also feel that it might look a bit "cluttered" when you try to generalise something with dots ($cdot cdot cdot$) and $n^th$ terms. It's just my way of thinking though :)
– paulplusx
Sep 10 at 14:10
@paulplusx: The solution to that is using better notation (e.g., yurnero's solution below), not grinding through the details of a particular case.
– anomaly
Sep 10 at 17:27
@anomaly Well, you are correct and your argument applies to all such generalization perfectly but I feel that if there is another method (shouldn't call it a method) of "understanding" it by using simple examples (similar to induction) and then generalizing it intuitively, sometimes it helps a lot, much better than notations(at least for me). I do accept that yurnero's solution is perfect for this question (because it literally answers it to the point).
– paulplusx
Sep 10 at 17:44
add a comment |Â
up vote
1
down vote
up vote
1
down vote
If you meant $operatornametr(Atimes B)$ as $operatornametr(Aotimes B)$ then as @Sangchul Lee mentioned, we have:
$displaystyle beginbmatrixa&b\c&d\endbmatrixotimes beginbmatrixp&q\r&s\endbmatrix=beginbmatrixacdot beginbmatrixp&q\r&s\endbmatrix&bcdot beginbmatrixp&q\r&s\endbmatrix\ccdot beginbmatrixp&q\r&s\endbmatrix&dcdot beginbmatrixp&q\r&s\endbmatrix\endbmatrix=beginbmatrixacdot p&acdot q&bcdot p&bcdot q\acdot r&acdot s&bcdot r&bcdot s\ccdot p&ccdot q&dcdot p&dcdot q\ccdot r&ccdot s&dcdot r&dcdot s\endbmatrix$
So we have:
$$(operatornametrA)(operatornametrB)=(a+d)(p+s)=acdot p+a cdot s+dcdot p+dcdot s=operatornametr(Aotimes B)$$
Where $otimes$ is the Kronecker Product and $operatornametr(.)$ is the trace of a matrix.
If you meant $operatornametr(Atimes B)$ as $operatornametr(AB)$, which is a simple Matrix multiplication, then :
$displaystyle beginbmatrixa&b\c&d\endbmatrix beginbmatrixp&q\r&s\endbmatrix=beginbmatrixap+br&aq+bs\cp+dr&cq+ds\endbmatrix$
So now we can see that:
$$(operatornametrA)(operatornametrB)=(a+d)(p+s)=acdot p+a cdot s+dcdot p+dcdot s ne acdot p+bcdot r+ccdot q+dcdot s=operatornametr(AB)$$
You can follow the same methodology and it would be true for any $ntimes n$ matrices.
If you meant $operatornametr(Atimes B)$ as $operatornametr(Aotimes B)$ then as @Sangchul Lee mentioned, we have:
$displaystyle beginbmatrixa&b\c&d\endbmatrixotimes beginbmatrixp&q\r&s\endbmatrix=beginbmatrixacdot beginbmatrixp&q\r&s\endbmatrix&bcdot beginbmatrixp&q\r&s\endbmatrix\ccdot beginbmatrixp&q\r&s\endbmatrix&dcdot beginbmatrixp&q\r&s\endbmatrix\endbmatrix=beginbmatrixacdot p&acdot q&bcdot p&bcdot q\acdot r&acdot s&bcdot r&bcdot s\ccdot p&ccdot q&dcdot p&dcdot q\ccdot r&ccdot s&dcdot r&dcdot s\endbmatrix$
So we have:
$$(operatornametrA)(operatornametrB)=(a+d)(p+s)=acdot p+a cdot s+dcdot p+dcdot s=operatornametr(Aotimes B)$$
Where $otimes$ is the Kronecker Product and $operatornametr(.)$ is the trace of a matrix.
If you meant $operatornametr(Atimes B)$ as $operatornametr(AB)$, which is a simple Matrix multiplication, then :
$displaystyle beginbmatrixa&b\c&d\endbmatrix beginbmatrixp&q\r&s\endbmatrix=beginbmatrixap+br&aq+bs\cp+dr&cq+ds\endbmatrix$
So now we can see that:
$$(operatornametrA)(operatornametrB)=(a+d)(p+s)=acdot p+a cdot s+dcdot p+dcdot s ne acdot p+bcdot r+ccdot q+dcdot s=operatornametr(AB)$$
You can follow the same methodology and it would be true for any $ntimes n$ matrices.
edited Sep 10 at 16:14
answered Sep 10 at 11:08


paulplusx
1,086318
1,086318
What about cases beyond the $2times 2$ one?
– anomaly
Sep 10 at 12:28
1
@anomaly the calculations are perfectly the same
– Riccardo Ceccon
Sep 10 at 12:30
@anomaly As ricardo said, the calculations are exactly the same. Moreover, I personally feel that this kind of small matrix products will help develop intuitions required to generalise the method. I also feel that it might look a bit "cluttered" when you try to generalise something with dots ($cdot cdot cdot$) and $n^th$ terms. It's just my way of thinking though :)
– paulplusx
Sep 10 at 14:10
@paulplusx: The solution to that is using better notation (e.g., yurnero's solution below), not grinding through the details of a particular case.
– anomaly
Sep 10 at 17:27
@anomaly Well, you are correct and your argument applies to all such generalization perfectly but I feel that if there is another method (shouldn't call it a method) of "understanding" it by using simple examples (similar to induction) and then generalizing it intuitively, sometimes it helps a lot, much better than notations(at least for me). I do accept that yurnero's solution is perfect for this question (because it literally answers it to the point).
– paulplusx
Sep 10 at 17:44
add a comment |Â
What about cases beyond the $2times 2$ one?
– anomaly
Sep 10 at 12:28
1
@anomaly the calculations are perfectly the same
– Riccardo Ceccon
Sep 10 at 12:30
@anomaly As ricardo said, the calculations are exactly the same. Moreover, I personally feel that this kind of small matrix products will help develop intuitions required to generalise the method. I also feel that it might look a bit "cluttered" when you try to generalise something with dots ($cdot cdot cdot$) and $n^th$ terms. It's just my way of thinking though :)
– paulplusx
Sep 10 at 14:10
@paulplusx: The solution to that is using better notation (e.g., yurnero's solution below), not grinding through the details of a particular case.
– anomaly
Sep 10 at 17:27
@anomaly Well, you are correct and your argument applies to all such generalization perfectly but I feel that if there is another method (shouldn't call it a method) of "understanding" it by using simple examples (similar to induction) and then generalizing it intuitively, sometimes it helps a lot, much better than notations(at least for me). I do accept that yurnero's solution is perfect for this question (because it literally answers it to the point).
– paulplusx
Sep 10 at 17:44
What about cases beyond the $2times 2$ one?
– anomaly
Sep 10 at 12:28
What about cases beyond the $2times 2$ one?
– anomaly
Sep 10 at 12:28
1
1
@anomaly the calculations are perfectly the same
– Riccardo Ceccon
Sep 10 at 12:30
@anomaly the calculations are perfectly the same
– Riccardo Ceccon
Sep 10 at 12:30
@anomaly As ricardo said, the calculations are exactly the same. Moreover, I personally feel that this kind of small matrix products will help develop intuitions required to generalise the method. I also feel that it might look a bit "cluttered" when you try to generalise something with dots ($cdot cdot cdot$) and $n^th$ terms. It's just my way of thinking though :)
– paulplusx
Sep 10 at 14:10
@anomaly As ricardo said, the calculations are exactly the same. Moreover, I personally feel that this kind of small matrix products will help develop intuitions required to generalise the method. I also feel that it might look a bit "cluttered" when you try to generalise something with dots ($cdot cdot cdot$) and $n^th$ terms. It's just my way of thinking though :)
– paulplusx
Sep 10 at 14:10
@paulplusx: The solution to that is using better notation (e.g., yurnero's solution below), not grinding through the details of a particular case.
– anomaly
Sep 10 at 17:27
@paulplusx: The solution to that is using better notation (e.g., yurnero's solution below), not grinding through the details of a particular case.
– anomaly
Sep 10 at 17:27
@anomaly Well, you are correct and your argument applies to all such generalization perfectly but I feel that if there is another method (shouldn't call it a method) of "understanding" it by using simple examples (similar to induction) and then generalizing it intuitively, sometimes it helps a lot, much better than notations(at least for me). I do accept that yurnero's solution is perfect for this question (because it literally answers it to the point).
– paulplusx
Sep 10 at 17:44
@anomaly Well, you are correct and your argument applies to all such generalization perfectly but I feel that if there is another method (shouldn't call it a method) of "understanding" it by using simple examples (similar to induction) and then generalizing it intuitively, sometimes it helps a lot, much better than notations(at least for me). I do accept that yurnero's solution is perfect for this question (because it literally answers it to the point).
– paulplusx
Sep 10 at 17:44
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1
See this
– mrs
Sep 10 at 9:09
3
The statement is false.
– Kavi Rama Murthy
Sep 10 at 9:10
11
Are you considering Kronecker product? Then $operatornametr(Aotimes B)=(operatornametrA)(operatornametrB)$ is true for square matrices $A$ and $B$.
– Sangchul Lee
Sep 10 at 9:11
1
Your notation is not standard. Please clarify if by $times$ you mean the Kronecker product or the standard matrix product.
– leonbloy
Sep 10 at 13:58
Hi! I am sorry for the unclear presentation. By $times$ I mean the Kronecker product. Thank you to all who have taken time to help me out!
– Zoë
Sep 11 at 9:58