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 $Atimes B$.










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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














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 $Atimes B$.










share|cite|improve this question

















  • 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












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 $Atimes B$.










share|cite|improve this question













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






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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












  • 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










2 Answers
2






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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*






share|cite|improve this answer



























    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.






    share|cite|improve this answer






















    • 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










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    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*






    share|cite|improve this answer
























      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*






      share|cite|improve this answer






















        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*






        share|cite|improve this answer












        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*







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        share|cite|improve this answer



        share|cite|improve this answer










        answered Sep 10 at 12:45









        yurnero

        6,9541824




        6,9541824




















            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.






            share|cite|improve this answer






















            • 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














            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.






            share|cite|improve this answer






















            • 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












            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.






            share|cite|improve this answer














            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.







            share|cite|improve this answer














            share|cite|improve this answer



            share|cite|improve this answer








            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
















            • 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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