Why linear maps act like matrix multiplication?












4












$begingroup$


In Linear Algebra Done Right, it said




Suppose $T in mathcal{L}(V,W)$ and $v in V$. Suppose $v_1,...,v_n$ is a basis of $V$ and $w_1,...,w_m$ is a basis of $W$. Then $$M(Tv) = M(T)M(v)$$




$M(T)$ is the m-by-n matrix whose entries $A_{j,k}$ are defined by $Tv_k = A_{1,k}w_1 + ... + A_{m,k}w_m$ suppose $T in mathcal{L}(V,W)$ and $v_1,...,v_n$ is a basis of $V$ and $w_1,...,w_m$ is a basis of $W$.



$M(v)$ is the matrix of vector $v$.



I generally follow the following proof:



Suppose $v = c_1v_1 + ... + c_nv_n$, where $c_1,...,c_n in mathbb{F}$. Thus
$$Tv = c_1Tv_1 +...+c_nTv_n$$



Hence



begin{equation}
begin{split}
M(Tv) &= c_1M(Tv_1) + ...+ c_nM(Tv_n)\
& = c_1M(T)_{.,1} +...+c_nM(T)_{.,n} \
& = M(T)M(v)
end{split}
end{equation}



But I have questions on the meaning of the proof. The book said it means each m-by-n matrix $A$ induces a linear map from $mathbb{F}^{n,1}$ to $mathbb{F}^{m,1}$. The result can be used to think of every linear map as a matrix multiplication map after suitable relabeling via the isomorphisms given by $M$.




  1. Is the shape of $M(Tv)$ m by 1, $M(T)$ m by n, and $M(v)$ n by 1?

  2. What is meant by suitable relabeling via the isomorphisms given by $M$? Does it just mean $M(T)$ is a isomorphism linear map between $M(v)$ and $M(Tv)$?










share|cite|improve this question











$endgroup$












  • $begingroup$
    In your blockquote, you haven't told us what $M$ means.
    $endgroup$
    – Gerry Myerson
    yesterday










  • $begingroup$
    @GerryMyerson revised
    $endgroup$
    – JOHN
    yesterday










  • $begingroup$
    Sorry, I don't know what it means for $M(v)$ to be the matrix of the vector $v$. What's the matrix of the vector $(1,2,3)$?
    $endgroup$
    – Gerry Myerson
    yesterday






  • 1




    $begingroup$
    @GerryMyerson Knowing Axler, it will be the coordinate vector for the given basis (in this case, $v_1, ldots, v_n$). For example, if the basis is $(0, 0, 1), (0, 1, 1), (1, 1, 1)$ in the space $Bbb{R}^3$, then $M(1, 2, 3) = begin{bmatrix} 1 \ 1 \ 1 end{bmatrix}$.
    $endgroup$
    – Theo Bendit
    yesterday


















4












$begingroup$


In Linear Algebra Done Right, it said




Suppose $T in mathcal{L}(V,W)$ and $v in V$. Suppose $v_1,...,v_n$ is a basis of $V$ and $w_1,...,w_m$ is a basis of $W$. Then $$M(Tv) = M(T)M(v)$$




$M(T)$ is the m-by-n matrix whose entries $A_{j,k}$ are defined by $Tv_k = A_{1,k}w_1 + ... + A_{m,k}w_m$ suppose $T in mathcal{L}(V,W)$ and $v_1,...,v_n$ is a basis of $V$ and $w_1,...,w_m$ is a basis of $W$.



$M(v)$ is the matrix of vector $v$.



I generally follow the following proof:



Suppose $v = c_1v_1 + ... + c_nv_n$, where $c_1,...,c_n in mathbb{F}$. Thus
$$Tv = c_1Tv_1 +...+c_nTv_n$$



Hence



begin{equation}
begin{split}
M(Tv) &= c_1M(Tv_1) + ...+ c_nM(Tv_n)\
& = c_1M(T)_{.,1} +...+c_nM(T)_{.,n} \
& = M(T)M(v)
end{split}
end{equation}



But I have questions on the meaning of the proof. The book said it means each m-by-n matrix $A$ induces a linear map from $mathbb{F}^{n,1}$ to $mathbb{F}^{m,1}$. The result can be used to think of every linear map as a matrix multiplication map after suitable relabeling via the isomorphisms given by $M$.




  1. Is the shape of $M(Tv)$ m by 1, $M(T)$ m by n, and $M(v)$ n by 1?

  2. What is meant by suitable relabeling via the isomorphisms given by $M$? Does it just mean $M(T)$ is a isomorphism linear map between $M(v)$ and $M(Tv)$?










share|cite|improve this question











$endgroup$












  • $begingroup$
    In your blockquote, you haven't told us what $M$ means.
    $endgroup$
    – Gerry Myerson
    yesterday










  • $begingroup$
    @GerryMyerson revised
    $endgroup$
    – JOHN
    yesterday










  • $begingroup$
    Sorry, I don't know what it means for $M(v)$ to be the matrix of the vector $v$. What's the matrix of the vector $(1,2,3)$?
    $endgroup$
    – Gerry Myerson
    yesterday






  • 1




    $begingroup$
    @GerryMyerson Knowing Axler, it will be the coordinate vector for the given basis (in this case, $v_1, ldots, v_n$). For example, if the basis is $(0, 0, 1), (0, 1, 1), (1, 1, 1)$ in the space $Bbb{R}^3$, then $M(1, 2, 3) = begin{bmatrix} 1 \ 1 \ 1 end{bmatrix}$.
    $endgroup$
    – Theo Bendit
    yesterday
















4












4








4





$begingroup$


In Linear Algebra Done Right, it said




Suppose $T in mathcal{L}(V,W)$ and $v in V$. Suppose $v_1,...,v_n$ is a basis of $V$ and $w_1,...,w_m$ is a basis of $W$. Then $$M(Tv) = M(T)M(v)$$




$M(T)$ is the m-by-n matrix whose entries $A_{j,k}$ are defined by $Tv_k = A_{1,k}w_1 + ... + A_{m,k}w_m$ suppose $T in mathcal{L}(V,W)$ and $v_1,...,v_n$ is a basis of $V$ and $w_1,...,w_m$ is a basis of $W$.



$M(v)$ is the matrix of vector $v$.



I generally follow the following proof:



Suppose $v = c_1v_1 + ... + c_nv_n$, where $c_1,...,c_n in mathbb{F}$. Thus
$$Tv = c_1Tv_1 +...+c_nTv_n$$



Hence



begin{equation}
begin{split}
M(Tv) &= c_1M(Tv_1) + ...+ c_nM(Tv_n)\
& = c_1M(T)_{.,1} +...+c_nM(T)_{.,n} \
& = M(T)M(v)
end{split}
end{equation}



But I have questions on the meaning of the proof. The book said it means each m-by-n matrix $A$ induces a linear map from $mathbb{F}^{n,1}$ to $mathbb{F}^{m,1}$. The result can be used to think of every linear map as a matrix multiplication map after suitable relabeling via the isomorphisms given by $M$.




  1. Is the shape of $M(Tv)$ m by 1, $M(T)$ m by n, and $M(v)$ n by 1?

  2. What is meant by suitable relabeling via the isomorphisms given by $M$? Does it just mean $M(T)$ is a isomorphism linear map between $M(v)$ and $M(Tv)$?










share|cite|improve this question











$endgroup$




In Linear Algebra Done Right, it said




Suppose $T in mathcal{L}(V,W)$ and $v in V$. Suppose $v_1,...,v_n$ is a basis of $V$ and $w_1,...,w_m$ is a basis of $W$. Then $$M(Tv) = M(T)M(v)$$




$M(T)$ is the m-by-n matrix whose entries $A_{j,k}$ are defined by $Tv_k = A_{1,k}w_1 + ... + A_{m,k}w_m$ suppose $T in mathcal{L}(V,W)$ and $v_1,...,v_n$ is a basis of $V$ and $w_1,...,w_m$ is a basis of $W$.



$M(v)$ is the matrix of vector $v$.



I generally follow the following proof:



Suppose $v = c_1v_1 + ... + c_nv_n$, where $c_1,...,c_n in mathbb{F}$. Thus
$$Tv = c_1Tv_1 +...+c_nTv_n$$



Hence



begin{equation}
begin{split}
M(Tv) &= c_1M(Tv_1) + ...+ c_nM(Tv_n)\
& = c_1M(T)_{.,1} +...+c_nM(T)_{.,n} \
& = M(T)M(v)
end{split}
end{equation}



But I have questions on the meaning of the proof. The book said it means each m-by-n matrix $A$ induces a linear map from $mathbb{F}^{n,1}$ to $mathbb{F}^{m,1}$. The result can be used to think of every linear map as a matrix multiplication map after suitable relabeling via the isomorphisms given by $M$.




  1. Is the shape of $M(Tv)$ m by 1, $M(T)$ m by n, and $M(v)$ n by 1?

  2. What is meant by suitable relabeling via the isomorphisms given by $M$? Does it just mean $M(T)$ is a isomorphism linear map between $M(v)$ and $M(Tv)$?







matrices linear-transformations






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edited yesterday







JOHN

















asked yesterday









JOHN JOHN

4589




4589












  • $begingroup$
    In your blockquote, you haven't told us what $M$ means.
    $endgroup$
    – Gerry Myerson
    yesterday










  • $begingroup$
    @GerryMyerson revised
    $endgroup$
    – JOHN
    yesterday










  • $begingroup$
    Sorry, I don't know what it means for $M(v)$ to be the matrix of the vector $v$. What's the matrix of the vector $(1,2,3)$?
    $endgroup$
    – Gerry Myerson
    yesterday






  • 1




    $begingroup$
    @GerryMyerson Knowing Axler, it will be the coordinate vector for the given basis (in this case, $v_1, ldots, v_n$). For example, if the basis is $(0, 0, 1), (0, 1, 1), (1, 1, 1)$ in the space $Bbb{R}^3$, then $M(1, 2, 3) = begin{bmatrix} 1 \ 1 \ 1 end{bmatrix}$.
    $endgroup$
    – Theo Bendit
    yesterday




















  • $begingroup$
    In your blockquote, you haven't told us what $M$ means.
    $endgroup$
    – Gerry Myerson
    yesterday










  • $begingroup$
    @GerryMyerson revised
    $endgroup$
    – JOHN
    yesterday










  • $begingroup$
    Sorry, I don't know what it means for $M(v)$ to be the matrix of the vector $v$. What's the matrix of the vector $(1,2,3)$?
    $endgroup$
    – Gerry Myerson
    yesterday






  • 1




    $begingroup$
    @GerryMyerson Knowing Axler, it will be the coordinate vector for the given basis (in this case, $v_1, ldots, v_n$). For example, if the basis is $(0, 0, 1), (0, 1, 1), (1, 1, 1)$ in the space $Bbb{R}^3$, then $M(1, 2, 3) = begin{bmatrix} 1 \ 1 \ 1 end{bmatrix}$.
    $endgroup$
    – Theo Bendit
    yesterday


















$begingroup$
In your blockquote, you haven't told us what $M$ means.
$endgroup$
– Gerry Myerson
yesterday




$begingroup$
In your blockquote, you haven't told us what $M$ means.
$endgroup$
– Gerry Myerson
yesterday












$begingroup$
@GerryMyerson revised
$endgroup$
– JOHN
yesterday




$begingroup$
@GerryMyerson revised
$endgroup$
– JOHN
yesterday












$begingroup$
Sorry, I don't know what it means for $M(v)$ to be the matrix of the vector $v$. What's the matrix of the vector $(1,2,3)$?
$endgroup$
– Gerry Myerson
yesterday




$begingroup$
Sorry, I don't know what it means for $M(v)$ to be the matrix of the vector $v$. What's the matrix of the vector $(1,2,3)$?
$endgroup$
– Gerry Myerson
yesterday




1




1




$begingroup$
@GerryMyerson Knowing Axler, it will be the coordinate vector for the given basis (in this case, $v_1, ldots, v_n$). For example, if the basis is $(0, 0, 1), (0, 1, 1), (1, 1, 1)$ in the space $Bbb{R}^3$, then $M(1, 2, 3) = begin{bmatrix} 1 \ 1 \ 1 end{bmatrix}$.
$endgroup$
– Theo Bendit
yesterday






$begingroup$
@GerryMyerson Knowing Axler, it will be the coordinate vector for the given basis (in this case, $v_1, ldots, v_n$). For example, if the basis is $(0, 0, 1), (0, 1, 1), (1, 1, 1)$ in the space $Bbb{R}^3$, then $M(1, 2, 3) = begin{bmatrix} 1 \ 1 \ 1 end{bmatrix}$.
$endgroup$
– Theo Bendit
yesterday












2 Answers
2






active

oldest

votes


















16












$begingroup$

In answer to your first question, yes to all three: $v$ is an element of the $n$-dimensional space $V$, so the coordinate vector with respect to the basis will be an $n times 1$ column vector. Similarly, $Tv in W$, which is an $n$-dimensional space, so $M(Tv)$ will be an $m times 1$ column vector. Finally, $M(T)$ is built from transforming the $n$ basis vectors of the domain, forming each an $m times 1$ coordinate column vector, which are put into an $m times n$ matrix.



In answer to your second question, consult the following commutative diagram (made in Paint :( ):



enter image description here



The process of applying $T$ to a vector $v in V$ is the top row of the diagram. However, there's a parallel process happening between $Bbb{F}^n$ and $Bbb{F}^m$, mirroring the same process.



The isomorphism being referred to are the double arrows, taking us between $V$ and $Bbb{F}^n$ and $W$ and $Bbb{F}^m$, by way of coordinate vectors. The coordinate vector map on $V$ is a linear map between $V$ and $Bbb{F}^n$ that is invertible, making it an isomorphism (and similarly for $W$). That is, the two spaces are structurally identical, and anything we can do with one space, we can view it in the other.



In $V$, we have some abstract vectors, and an abstract linear transformation $T$ that maps vectors in $V$ to vectors in $W$. However, using this isomorphism, we can view $V$ slightly differently as $Bbb{F}^n$, and similarly for $W$, which means $T$ boils down to a linear map from $Bbb{F}^n$ to $Bbb{F}^m$, which can be characterised as matrix multiplication. The matrix, in particular, is $M(T)$.






share|cite|improve this answer









$endgroup$













  • $begingroup$
    Very nice graph!
    $endgroup$
    – JOHN
    yesterday






  • 4




    $begingroup$
    Upvote for the commutative paint diagram!
    $endgroup$
    – Jannik Pitt
    yesterday










  • $begingroup$
    it seems that T and M(T) is also isomorphic ?
    $endgroup$
    – JOHN
    yesterday










  • $begingroup$
    Isomorphisms are maps between vector spaces; only vector spaces can be isomorphic (at least, until you study category theory). The map $M$ (given fixed bases) is itself an isomorphism between the space of linear maps from $V$ to $W$ and the $m times n$ matrices, but even then, it's not really correct to say that a map $T$ is "isomorphic" to a matrix $M(T)$. It would be more accurate (though not conventional) to describe the map $T$ as "similar" to the matrix $M(T)$, in a similar sense to similar matrices (bear in mind, $T$ is not a matrix).
    $endgroup$
    – Theo Bendit
    yesterday












  • $begingroup$
    @JOHN Simply put, vectors cannot be isomorphic. Maps cannot be isomorphic. Only spaces can be isomorphic.
    $endgroup$
    – Theo Bendit
    yesterday



















4












$begingroup$


  1. Yes, those would be the shapes of those vectors when represented as matrices. Given that we're multiply by vectors on the right.


  2. There is a theorem that if $V$ is an $n-$dimensional vector space over a field $F,$ then $V$ is isomorphic to $F^n.$ Here the isomorphic mappings assign coordinates to our vectors and our linear transformation. It doesn't mean that $M$ is an isomorphism between $M(v)$ and $M(Tv).$ These are particular vectors. The map $M$ actually induces an isomorphism from $Vto F^n$, isomorphism from $Tto F^{ntimes m}$, and an isomorphism from $Wto F^m.$



I actually like the way that this is done. The Author is telling you that you're representation of $T$ by a matrix depends on your choice of basis in $F^n$. A fact that is important to remember.






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    2 Answers
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    2 Answers
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    16












    $begingroup$

    In answer to your first question, yes to all three: $v$ is an element of the $n$-dimensional space $V$, so the coordinate vector with respect to the basis will be an $n times 1$ column vector. Similarly, $Tv in W$, which is an $n$-dimensional space, so $M(Tv)$ will be an $m times 1$ column vector. Finally, $M(T)$ is built from transforming the $n$ basis vectors of the domain, forming each an $m times 1$ coordinate column vector, which are put into an $m times n$ matrix.



    In answer to your second question, consult the following commutative diagram (made in Paint :( ):



    enter image description here



    The process of applying $T$ to a vector $v in V$ is the top row of the diagram. However, there's a parallel process happening between $Bbb{F}^n$ and $Bbb{F}^m$, mirroring the same process.



    The isomorphism being referred to are the double arrows, taking us between $V$ and $Bbb{F}^n$ and $W$ and $Bbb{F}^m$, by way of coordinate vectors. The coordinate vector map on $V$ is a linear map between $V$ and $Bbb{F}^n$ that is invertible, making it an isomorphism (and similarly for $W$). That is, the two spaces are structurally identical, and anything we can do with one space, we can view it in the other.



    In $V$, we have some abstract vectors, and an abstract linear transformation $T$ that maps vectors in $V$ to vectors in $W$. However, using this isomorphism, we can view $V$ slightly differently as $Bbb{F}^n$, and similarly for $W$, which means $T$ boils down to a linear map from $Bbb{F}^n$ to $Bbb{F}^m$, which can be characterised as matrix multiplication. The matrix, in particular, is $M(T)$.






    share|cite|improve this answer









    $endgroup$













    • $begingroup$
      Very nice graph!
      $endgroup$
      – JOHN
      yesterday






    • 4




      $begingroup$
      Upvote for the commutative paint diagram!
      $endgroup$
      – Jannik Pitt
      yesterday










    • $begingroup$
      it seems that T and M(T) is also isomorphic ?
      $endgroup$
      – JOHN
      yesterday










    • $begingroup$
      Isomorphisms are maps between vector spaces; only vector spaces can be isomorphic (at least, until you study category theory). The map $M$ (given fixed bases) is itself an isomorphism between the space of linear maps from $V$ to $W$ and the $m times n$ matrices, but even then, it's not really correct to say that a map $T$ is "isomorphic" to a matrix $M(T)$. It would be more accurate (though not conventional) to describe the map $T$ as "similar" to the matrix $M(T)$, in a similar sense to similar matrices (bear in mind, $T$ is not a matrix).
      $endgroup$
      – Theo Bendit
      yesterday












    • $begingroup$
      @JOHN Simply put, vectors cannot be isomorphic. Maps cannot be isomorphic. Only spaces can be isomorphic.
      $endgroup$
      – Theo Bendit
      yesterday
















    16












    $begingroup$

    In answer to your first question, yes to all three: $v$ is an element of the $n$-dimensional space $V$, so the coordinate vector with respect to the basis will be an $n times 1$ column vector. Similarly, $Tv in W$, which is an $n$-dimensional space, so $M(Tv)$ will be an $m times 1$ column vector. Finally, $M(T)$ is built from transforming the $n$ basis vectors of the domain, forming each an $m times 1$ coordinate column vector, which are put into an $m times n$ matrix.



    In answer to your second question, consult the following commutative diagram (made in Paint :( ):



    enter image description here



    The process of applying $T$ to a vector $v in V$ is the top row of the diagram. However, there's a parallel process happening between $Bbb{F}^n$ and $Bbb{F}^m$, mirroring the same process.



    The isomorphism being referred to are the double arrows, taking us between $V$ and $Bbb{F}^n$ and $W$ and $Bbb{F}^m$, by way of coordinate vectors. The coordinate vector map on $V$ is a linear map between $V$ and $Bbb{F}^n$ that is invertible, making it an isomorphism (and similarly for $W$). That is, the two spaces are structurally identical, and anything we can do with one space, we can view it in the other.



    In $V$, we have some abstract vectors, and an abstract linear transformation $T$ that maps vectors in $V$ to vectors in $W$. However, using this isomorphism, we can view $V$ slightly differently as $Bbb{F}^n$, and similarly for $W$, which means $T$ boils down to a linear map from $Bbb{F}^n$ to $Bbb{F}^m$, which can be characterised as matrix multiplication. The matrix, in particular, is $M(T)$.






    share|cite|improve this answer









    $endgroup$













    • $begingroup$
      Very nice graph!
      $endgroup$
      – JOHN
      yesterday






    • 4




      $begingroup$
      Upvote for the commutative paint diagram!
      $endgroup$
      – Jannik Pitt
      yesterday










    • $begingroup$
      it seems that T and M(T) is also isomorphic ?
      $endgroup$
      – JOHN
      yesterday










    • $begingroup$
      Isomorphisms are maps between vector spaces; only vector spaces can be isomorphic (at least, until you study category theory). The map $M$ (given fixed bases) is itself an isomorphism between the space of linear maps from $V$ to $W$ and the $m times n$ matrices, but even then, it's not really correct to say that a map $T$ is "isomorphic" to a matrix $M(T)$. It would be more accurate (though not conventional) to describe the map $T$ as "similar" to the matrix $M(T)$, in a similar sense to similar matrices (bear in mind, $T$ is not a matrix).
      $endgroup$
      – Theo Bendit
      yesterday












    • $begingroup$
      @JOHN Simply put, vectors cannot be isomorphic. Maps cannot be isomorphic. Only spaces can be isomorphic.
      $endgroup$
      – Theo Bendit
      yesterday














    16












    16








    16





    $begingroup$

    In answer to your first question, yes to all three: $v$ is an element of the $n$-dimensional space $V$, so the coordinate vector with respect to the basis will be an $n times 1$ column vector. Similarly, $Tv in W$, which is an $n$-dimensional space, so $M(Tv)$ will be an $m times 1$ column vector. Finally, $M(T)$ is built from transforming the $n$ basis vectors of the domain, forming each an $m times 1$ coordinate column vector, which are put into an $m times n$ matrix.



    In answer to your second question, consult the following commutative diagram (made in Paint :( ):



    enter image description here



    The process of applying $T$ to a vector $v in V$ is the top row of the diagram. However, there's a parallel process happening between $Bbb{F}^n$ and $Bbb{F}^m$, mirroring the same process.



    The isomorphism being referred to are the double arrows, taking us between $V$ and $Bbb{F}^n$ and $W$ and $Bbb{F}^m$, by way of coordinate vectors. The coordinate vector map on $V$ is a linear map between $V$ and $Bbb{F}^n$ that is invertible, making it an isomorphism (and similarly for $W$). That is, the two spaces are structurally identical, and anything we can do with one space, we can view it in the other.



    In $V$, we have some abstract vectors, and an abstract linear transformation $T$ that maps vectors in $V$ to vectors in $W$. However, using this isomorphism, we can view $V$ slightly differently as $Bbb{F}^n$, and similarly for $W$, which means $T$ boils down to a linear map from $Bbb{F}^n$ to $Bbb{F}^m$, which can be characterised as matrix multiplication. The matrix, in particular, is $M(T)$.






    share|cite|improve this answer









    $endgroup$



    In answer to your first question, yes to all three: $v$ is an element of the $n$-dimensional space $V$, so the coordinate vector with respect to the basis will be an $n times 1$ column vector. Similarly, $Tv in W$, which is an $n$-dimensional space, so $M(Tv)$ will be an $m times 1$ column vector. Finally, $M(T)$ is built from transforming the $n$ basis vectors of the domain, forming each an $m times 1$ coordinate column vector, which are put into an $m times n$ matrix.



    In answer to your second question, consult the following commutative diagram (made in Paint :( ):



    enter image description here



    The process of applying $T$ to a vector $v in V$ is the top row of the diagram. However, there's a parallel process happening between $Bbb{F}^n$ and $Bbb{F}^m$, mirroring the same process.



    The isomorphism being referred to are the double arrows, taking us between $V$ and $Bbb{F}^n$ and $W$ and $Bbb{F}^m$, by way of coordinate vectors. The coordinate vector map on $V$ is a linear map between $V$ and $Bbb{F}^n$ that is invertible, making it an isomorphism (and similarly for $W$). That is, the two spaces are structurally identical, and anything we can do with one space, we can view it in the other.



    In $V$, we have some abstract vectors, and an abstract linear transformation $T$ that maps vectors in $V$ to vectors in $W$. However, using this isomorphism, we can view $V$ slightly differently as $Bbb{F}^n$, and similarly for $W$, which means $T$ boils down to a linear map from $Bbb{F}^n$ to $Bbb{F}^m$, which can be characterised as matrix multiplication. The matrix, in particular, is $M(T)$.







    share|cite|improve this answer












    share|cite|improve this answer



    share|cite|improve this answer










    answered yesterday









    Theo BenditTheo Bendit

    20.7k12354




    20.7k12354












    • $begingroup$
      Very nice graph!
      $endgroup$
      – JOHN
      yesterday






    • 4




      $begingroup$
      Upvote for the commutative paint diagram!
      $endgroup$
      – Jannik Pitt
      yesterday










    • $begingroup$
      it seems that T and M(T) is also isomorphic ?
      $endgroup$
      – JOHN
      yesterday










    • $begingroup$
      Isomorphisms are maps between vector spaces; only vector spaces can be isomorphic (at least, until you study category theory). The map $M$ (given fixed bases) is itself an isomorphism between the space of linear maps from $V$ to $W$ and the $m times n$ matrices, but even then, it's not really correct to say that a map $T$ is "isomorphic" to a matrix $M(T)$. It would be more accurate (though not conventional) to describe the map $T$ as "similar" to the matrix $M(T)$, in a similar sense to similar matrices (bear in mind, $T$ is not a matrix).
      $endgroup$
      – Theo Bendit
      yesterday












    • $begingroup$
      @JOHN Simply put, vectors cannot be isomorphic. Maps cannot be isomorphic. Only spaces can be isomorphic.
      $endgroup$
      – Theo Bendit
      yesterday


















    • $begingroup$
      Very nice graph!
      $endgroup$
      – JOHN
      yesterday






    • 4




      $begingroup$
      Upvote for the commutative paint diagram!
      $endgroup$
      – Jannik Pitt
      yesterday










    • $begingroup$
      it seems that T and M(T) is also isomorphic ?
      $endgroup$
      – JOHN
      yesterday










    • $begingroup$
      Isomorphisms are maps between vector spaces; only vector spaces can be isomorphic (at least, until you study category theory). The map $M$ (given fixed bases) is itself an isomorphism between the space of linear maps from $V$ to $W$ and the $m times n$ matrices, but even then, it's not really correct to say that a map $T$ is "isomorphic" to a matrix $M(T)$. It would be more accurate (though not conventional) to describe the map $T$ as "similar" to the matrix $M(T)$, in a similar sense to similar matrices (bear in mind, $T$ is not a matrix).
      $endgroup$
      – Theo Bendit
      yesterday












    • $begingroup$
      @JOHN Simply put, vectors cannot be isomorphic. Maps cannot be isomorphic. Only spaces can be isomorphic.
      $endgroup$
      – Theo Bendit
      yesterday
















    $begingroup$
    Very nice graph!
    $endgroup$
    – JOHN
    yesterday




    $begingroup$
    Very nice graph!
    $endgroup$
    – JOHN
    yesterday




    4




    4




    $begingroup$
    Upvote for the commutative paint diagram!
    $endgroup$
    – Jannik Pitt
    yesterday




    $begingroup$
    Upvote for the commutative paint diagram!
    $endgroup$
    – Jannik Pitt
    yesterday












    $begingroup$
    it seems that T and M(T) is also isomorphic ?
    $endgroup$
    – JOHN
    yesterday




    $begingroup$
    it seems that T and M(T) is also isomorphic ?
    $endgroup$
    – JOHN
    yesterday












    $begingroup$
    Isomorphisms are maps between vector spaces; only vector spaces can be isomorphic (at least, until you study category theory). The map $M$ (given fixed bases) is itself an isomorphism between the space of linear maps from $V$ to $W$ and the $m times n$ matrices, but even then, it's not really correct to say that a map $T$ is "isomorphic" to a matrix $M(T)$. It would be more accurate (though not conventional) to describe the map $T$ as "similar" to the matrix $M(T)$, in a similar sense to similar matrices (bear in mind, $T$ is not a matrix).
    $endgroup$
    – Theo Bendit
    yesterday






    $begingroup$
    Isomorphisms are maps between vector spaces; only vector spaces can be isomorphic (at least, until you study category theory). The map $M$ (given fixed bases) is itself an isomorphism between the space of linear maps from $V$ to $W$ and the $m times n$ matrices, but even then, it's not really correct to say that a map $T$ is "isomorphic" to a matrix $M(T)$. It would be more accurate (though not conventional) to describe the map $T$ as "similar" to the matrix $M(T)$, in a similar sense to similar matrices (bear in mind, $T$ is not a matrix).
    $endgroup$
    – Theo Bendit
    yesterday














    $begingroup$
    @JOHN Simply put, vectors cannot be isomorphic. Maps cannot be isomorphic. Only spaces can be isomorphic.
    $endgroup$
    – Theo Bendit
    yesterday




    $begingroup$
    @JOHN Simply put, vectors cannot be isomorphic. Maps cannot be isomorphic. Only spaces can be isomorphic.
    $endgroup$
    – Theo Bendit
    yesterday











    4












    $begingroup$


    1. Yes, those would be the shapes of those vectors when represented as matrices. Given that we're multiply by vectors on the right.


    2. There is a theorem that if $V$ is an $n-$dimensional vector space over a field $F,$ then $V$ is isomorphic to $F^n.$ Here the isomorphic mappings assign coordinates to our vectors and our linear transformation. It doesn't mean that $M$ is an isomorphism between $M(v)$ and $M(Tv).$ These are particular vectors. The map $M$ actually induces an isomorphism from $Vto F^n$, isomorphism from $Tto F^{ntimes m}$, and an isomorphism from $Wto F^m.$



    I actually like the way that this is done. The Author is telling you that you're representation of $T$ by a matrix depends on your choice of basis in $F^n$. A fact that is important to remember.






    share|cite|improve this answer









    $endgroup$


















      4












      $begingroup$


      1. Yes, those would be the shapes of those vectors when represented as matrices. Given that we're multiply by vectors on the right.


      2. There is a theorem that if $V$ is an $n-$dimensional vector space over a field $F,$ then $V$ is isomorphic to $F^n.$ Here the isomorphic mappings assign coordinates to our vectors and our linear transformation. It doesn't mean that $M$ is an isomorphism between $M(v)$ and $M(Tv).$ These are particular vectors. The map $M$ actually induces an isomorphism from $Vto F^n$, isomorphism from $Tto F^{ntimes m}$, and an isomorphism from $Wto F^m.$



      I actually like the way that this is done. The Author is telling you that you're representation of $T$ by a matrix depends on your choice of basis in $F^n$. A fact that is important to remember.






      share|cite|improve this answer









      $endgroup$
















        4












        4








        4





        $begingroup$


        1. Yes, those would be the shapes of those vectors when represented as matrices. Given that we're multiply by vectors on the right.


        2. There is a theorem that if $V$ is an $n-$dimensional vector space over a field $F,$ then $V$ is isomorphic to $F^n.$ Here the isomorphic mappings assign coordinates to our vectors and our linear transformation. It doesn't mean that $M$ is an isomorphism between $M(v)$ and $M(Tv).$ These are particular vectors. The map $M$ actually induces an isomorphism from $Vto F^n$, isomorphism from $Tto F^{ntimes m}$, and an isomorphism from $Wto F^m.$



        I actually like the way that this is done. The Author is telling you that you're representation of $T$ by a matrix depends on your choice of basis in $F^n$. A fact that is important to remember.






        share|cite|improve this answer









        $endgroup$




        1. Yes, those would be the shapes of those vectors when represented as matrices. Given that we're multiply by vectors on the right.


        2. There is a theorem that if $V$ is an $n-$dimensional vector space over a field $F,$ then $V$ is isomorphic to $F^n.$ Here the isomorphic mappings assign coordinates to our vectors and our linear transformation. It doesn't mean that $M$ is an isomorphism between $M(v)$ and $M(Tv).$ These are particular vectors. The map $M$ actually induces an isomorphism from $Vto F^n$, isomorphism from $Tto F^{ntimes m}$, and an isomorphism from $Wto F^m.$



        I actually like the way that this is done. The Author is telling you that you're representation of $T$ by a matrix depends on your choice of basis in $F^n$. A fact that is important to remember.







        share|cite|improve this answer












        share|cite|improve this answer



        share|cite|improve this answer










        answered yesterday









        MelodyMelody

        1,01912




        1,01912






























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