Why linear maps act like matrix multiplication?
$begingroup$
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 $M$.
- Is the shape of $M(Tv)$ m by 1, $M(T)$ m by n, and $M(v)$ n by 1?
- 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
$endgroup$
add a comment |
$begingroup$
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 $M$.
- Is the shape of $M(Tv)$ m by 1, $M(T)$ m by n, and $M(v)$ n by 1?
- 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
$endgroup$
$begingroup$
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
add a comment |
$begingroup$
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 $M$.
- Is the shape of $M(Tv)$ m by 1, $M(T)$ m by n, and $M(v)$ n by 1?
- 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
$endgroup$
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 $M$.
- Is the shape of $M(Tv)$ m by 1, $M(T)$ m by n, and $M(v)$ n by 1?
- 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
matrices linear-transformations
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
add a comment |
$begingroup$
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
add a comment |
2 Answers
2
active
oldest
votes
$begingroup$
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 :( ):
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 $M(T)$.
$endgroup$
$begingroup$
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
add a comment |
$begingroup$
Yes, those would be the shapes of those vectors when represented as matrices. Given that we're multiply by vectors on the right.
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.
$endgroup$
add a comment |
Your Answer
StackExchange.ifUsing("editor", function () {
return StackExchange.using("mathjaxEditing", function () {
StackExchange.MarkdownEditor.creationCallbacks.add(function (editor, postfix) {
StackExchange.mathjaxEditing.prepareWmdForMathJax(editor, postfix, [["$", "$"], ["\\(","\\)"]]);
});
});
}, "mathjax-editing");
StackExchange.ready(function() {
var channelOptions = {
tags: "".split(" "),
id: "69"
};
initTagRenderer("".split(" "), "".split(" "), channelOptions);
StackExchange.using("externalEditor", function() {
// Have to fire editor after snippets, if snippets enabled
if (StackExchange.settings.snippets.snippetsEnabled) {
StackExchange.using("snippets", function() {
createEditor();
});
}
else {
createEditor();
}
});
function createEditor() {
StackExchange.prepareEditor({
heartbeatType: 'answer',
autoActivateHeartbeat: false,
convertImagesToLinks: true,
noModals: true,
showLowRepImageUploadWarning: true,
reputationToPostImages: 10,
bindNavPrevention: true,
postfix: "",
imageUploader: {
brandingHtml: "Powered by u003ca class="icon-imgur-white" href="https://imgur.com/"u003eu003c/au003e",
contentPolicyHtml: "User contributions licensed under u003ca href="https://creativecommons.org/licenses/by-sa/3.0/"u003ecc by-sa 3.0 with attribution requiredu003c/au003e u003ca href="https://stackoverflow.com/legal/content-policy"u003e(content policy)u003c/au003e",
allowUrls: true
},
noCode: true, onDemand: true,
discardSelector: ".discard-answer"
,immediatelyShowMarkdownHelp:true
});
}
});
Sign up or log in
StackExchange.ready(function () {
StackExchange.helpers.onClickDraftSave('#login-link');
});
Sign up using Google
Sign up using Facebook
Sign up using Email and Password
Post as a guest
Required, but never shown
StackExchange.ready(
function () {
StackExchange.openid.initPostLogin('.new-post-login', 'https%3a%2f%2fmath.stackexchange.com%2fquestions%2f3177868%2fwhy-linear-maps-act-like-matrix-multiplication%23new-answer', 'question_page');
}
);
Post as a guest
Required, but never shown
2 Answers
2
active
oldest
votes
2 Answers
2
active
oldest
votes
active
oldest
votes
active
oldest
votes
$begingroup$
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 :( ):
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 $M(T)$.
$endgroup$
$begingroup$
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
add a comment |
$begingroup$
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 :( ):
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 $M(T)$.
$endgroup$
$begingroup$
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
add a comment |
$begingroup$
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 :( ):
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 $M(T)$.
$endgroup$
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 :( ):
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 $M(T)$.
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
add a comment |
$begingroup$
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
add a comment |
$begingroup$
Yes, those would be the shapes of those vectors when represented as matrices. Given that we're multiply by vectors on the right.
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.
$endgroup$
add a comment |
$begingroup$
Yes, those would be the shapes of those vectors when represented as matrices. Given that we're multiply by vectors on the right.
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.
$endgroup$
add a comment |
$begingroup$
Yes, those would be the shapes of those vectors when represented as matrices. Given that we're multiply by vectors on the right.
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.
$endgroup$
Yes, those would be the shapes of those vectors when represented as matrices. Given that we're multiply by vectors on the right.
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.
answered yesterday
MelodyMelody
1,01912
1,01912
add a comment |
add a comment |
Thanks for contributing an answer to Mathematics Stack Exchange!
- Please be sure to answer the question. Provide details and share your research!
But avoid …
- Asking for help, clarification, or responding to other answers.
- Making statements based on opinion; back them up with references or personal experience.
Use MathJax to format equations. MathJax reference.
To learn more, see our tips on writing great answers.
Sign up or log in
StackExchange.ready(function () {
StackExchange.helpers.onClickDraftSave('#login-link');
});
Sign up using Google
Sign up using Facebook
Sign up using Email and Password
Post as a guest
Required, but never shown
StackExchange.ready(
function () {
StackExchange.openid.initPostLogin('.new-post-login', 'https%3a%2f%2fmath.stackexchange.com%2fquestions%2f3177868%2fwhy-linear-maps-act-like-matrix-multiplication%23new-answer', 'question_page');
}
);
Post as a guest
Required, but never shown
Sign up or log in
StackExchange.ready(function () {
StackExchange.helpers.onClickDraftSave('#login-link');
});
Sign up using Google
Sign up using Facebook
Sign up using Email and Password
Post as a guest
Required, but never shown
Sign up or log in
StackExchange.ready(function () {
StackExchange.helpers.onClickDraftSave('#login-link');
});
Sign up using Google
Sign up using Facebook
Sign up using Email and Password
Post as a guest
Required, but never shown
Sign up or log in
StackExchange.ready(function () {
StackExchange.helpers.onClickDraftSave('#login-link');
});
Sign up using Google
Sign up using Facebook
Sign up using Email and Password
Sign up using Google
Sign up using Facebook
Sign up using Email and Password
Post as a guest
Required, but never shown
Required, but never shown
Required, but never shown
Required, but never shown
Required, but never shown
Required, but never shown
Required, but never shown
Required, but never shown
Required, but never shown
$begingroup$
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