Linear Map Adjoint or Inverse?
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In my lecture notes, we have a linear map $mathcal{A}(X)=X_{11}$ that maps $Xin S^2$ to its first element. It then claims that $mathcal{A}^*(X_{11})=
begin{bmatrix}
X_{11}&0\
0&0
end{bmatrix}$ is the adjoint.
To me I understand it by $mathcal{A}(X)=
begin{bmatrix}1&0end{bmatrix}
X
begin{bmatrix}1\0end{bmatrix}
=X_{11}$
, so we solve for $X$:
$$
begin{align}
X&=begin{bmatrix}1\0end{bmatrix}
Bigg(begin{bmatrix}1&0end{bmatrix}
X
begin{bmatrix}1\0end{bmatrix}Bigg)
begin{bmatrix}1&0end{bmatrix}\
&=
begin{bmatrix}1\0end{bmatrix}
X_{11}
begin{bmatrix}1&0end{bmatrix}\
&=mathcal{A}^*(X_{11}).
end{align}$$
However, (coming from a physics background) this seems like we found the inverse $mathcal{A}^{-1}$, not $mathcal{A}^*$ the adjoint. From what I know (from physics), the adjoint of an operator is its (conjugate) transpose, which we would have derived by doing:
$$mathcal{A}^*(X_{11})=
begin{bmatrix}1&0end{bmatrix}^T
X_{11}
begin{bmatrix}1\0end{bmatrix}^T
=
begin{bmatrix}1\0end{bmatrix}
X_{11}
begin{bmatrix}1&0end{bmatrix}.
$$
Is either of these the correct way? I'm guessing it's probably the latter, and that here we happen to have $mathcal{A}^*=mathcal{A}^{-1}$, but I'm confused because I've never seen this done before, and I've also never seen a map/operator not represented just by a single matrix.
adjoint-operators
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In my lecture notes, we have a linear map $mathcal{A}(X)=X_{11}$ that maps $Xin S^2$ to its first element. It then claims that $mathcal{A}^*(X_{11})=
begin{bmatrix}
X_{11}&0\
0&0
end{bmatrix}$ is the adjoint.
To me I understand it by $mathcal{A}(X)=
begin{bmatrix}1&0end{bmatrix}
X
begin{bmatrix}1\0end{bmatrix}
=X_{11}$
, so we solve for $X$:
$$
begin{align}
X&=begin{bmatrix}1\0end{bmatrix}
Bigg(begin{bmatrix}1&0end{bmatrix}
X
begin{bmatrix}1\0end{bmatrix}Bigg)
begin{bmatrix}1&0end{bmatrix}\
&=
begin{bmatrix}1\0end{bmatrix}
X_{11}
begin{bmatrix}1&0end{bmatrix}\
&=mathcal{A}^*(X_{11}).
end{align}$$
However, (coming from a physics background) this seems like we found the inverse $mathcal{A}^{-1}$, not $mathcal{A}^*$ the adjoint. From what I know (from physics), the adjoint of an operator is its (conjugate) transpose, which we would have derived by doing:
$$mathcal{A}^*(X_{11})=
begin{bmatrix}1&0end{bmatrix}^T
X_{11}
begin{bmatrix}1\0end{bmatrix}^T
=
begin{bmatrix}1\0end{bmatrix}
X_{11}
begin{bmatrix}1&0end{bmatrix}.
$$
Is either of these the correct way? I'm guessing it's probably the latter, and that here we happen to have $mathcal{A}^*=mathcal{A}^{-1}$, but I'm confused because I've never seen this done before, and I've also never seen a map/operator not represented just by a single matrix.
adjoint-operators
The linear map is defined on vector space. In particular, if we choose orthonormal bases of both spaces, one can show that the matrix representations of $L^∗$ and $L$ are related by $[L^∗]=[L]^T$. You can read more about it here math.stackexchange.com/questions/1769834/…
– Jimmy
Nov 18 at 20:01
add a comment |
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0
down vote
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up vote
0
down vote
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In my lecture notes, we have a linear map $mathcal{A}(X)=X_{11}$ that maps $Xin S^2$ to its first element. It then claims that $mathcal{A}^*(X_{11})=
begin{bmatrix}
X_{11}&0\
0&0
end{bmatrix}$ is the adjoint.
To me I understand it by $mathcal{A}(X)=
begin{bmatrix}1&0end{bmatrix}
X
begin{bmatrix}1\0end{bmatrix}
=X_{11}$
, so we solve for $X$:
$$
begin{align}
X&=begin{bmatrix}1\0end{bmatrix}
Bigg(begin{bmatrix}1&0end{bmatrix}
X
begin{bmatrix}1\0end{bmatrix}Bigg)
begin{bmatrix}1&0end{bmatrix}\
&=
begin{bmatrix}1\0end{bmatrix}
X_{11}
begin{bmatrix}1&0end{bmatrix}\
&=mathcal{A}^*(X_{11}).
end{align}$$
However, (coming from a physics background) this seems like we found the inverse $mathcal{A}^{-1}$, not $mathcal{A}^*$ the adjoint. From what I know (from physics), the adjoint of an operator is its (conjugate) transpose, which we would have derived by doing:
$$mathcal{A}^*(X_{11})=
begin{bmatrix}1&0end{bmatrix}^T
X_{11}
begin{bmatrix}1\0end{bmatrix}^T
=
begin{bmatrix}1\0end{bmatrix}
X_{11}
begin{bmatrix}1&0end{bmatrix}.
$$
Is either of these the correct way? I'm guessing it's probably the latter, and that here we happen to have $mathcal{A}^*=mathcal{A}^{-1}$, but I'm confused because I've never seen this done before, and I've also never seen a map/operator not represented just by a single matrix.
adjoint-operators
In my lecture notes, we have a linear map $mathcal{A}(X)=X_{11}$ that maps $Xin S^2$ to its first element. It then claims that $mathcal{A}^*(X_{11})=
begin{bmatrix}
X_{11}&0\
0&0
end{bmatrix}$ is the adjoint.
To me I understand it by $mathcal{A}(X)=
begin{bmatrix}1&0end{bmatrix}
X
begin{bmatrix}1\0end{bmatrix}
=X_{11}$
, so we solve for $X$:
$$
begin{align}
X&=begin{bmatrix}1\0end{bmatrix}
Bigg(begin{bmatrix}1&0end{bmatrix}
X
begin{bmatrix}1\0end{bmatrix}Bigg)
begin{bmatrix}1&0end{bmatrix}\
&=
begin{bmatrix}1\0end{bmatrix}
X_{11}
begin{bmatrix}1&0end{bmatrix}\
&=mathcal{A}^*(X_{11}).
end{align}$$
However, (coming from a physics background) this seems like we found the inverse $mathcal{A}^{-1}$, not $mathcal{A}^*$ the adjoint. From what I know (from physics), the adjoint of an operator is its (conjugate) transpose, which we would have derived by doing:
$$mathcal{A}^*(X_{11})=
begin{bmatrix}1&0end{bmatrix}^T
X_{11}
begin{bmatrix}1\0end{bmatrix}^T
=
begin{bmatrix}1\0end{bmatrix}
X_{11}
begin{bmatrix}1&0end{bmatrix}.
$$
Is either of these the correct way? I'm guessing it's probably the latter, and that here we happen to have $mathcal{A}^*=mathcal{A}^{-1}$, but I'm confused because I've never seen this done before, and I've also never seen a map/operator not represented just by a single matrix.
adjoint-operators
adjoint-operators
asked Nov 18 at 19:53
Dan
153
153
The linear map is defined on vector space. In particular, if we choose orthonormal bases of both spaces, one can show that the matrix representations of $L^∗$ and $L$ are related by $[L^∗]=[L]^T$. You can read more about it here math.stackexchange.com/questions/1769834/…
– Jimmy
Nov 18 at 20:01
add a comment |
The linear map is defined on vector space. In particular, if we choose orthonormal bases of both spaces, one can show that the matrix representations of $L^∗$ and $L$ are related by $[L^∗]=[L]^T$. You can read more about it here math.stackexchange.com/questions/1769834/…
– Jimmy
Nov 18 at 20:01
The linear map is defined on vector space. In particular, if we choose orthonormal bases of both spaces, one can show that the matrix representations of $L^∗$ and $L$ are related by $[L^∗]=[L]^T$. You can read more about it here math.stackexchange.com/questions/1769834/…
– Jimmy
Nov 18 at 20:01
The linear map is defined on vector space. In particular, if we choose orthonormal bases of both spaces, one can show that the matrix representations of $L^∗$ and $L$ are related by $[L^∗]=[L]^T$. You can read more about it here math.stackexchange.com/questions/1769834/…
– Jimmy
Nov 18 at 20:01
add a comment |
1 Answer
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I figured out the correct way to derive the answer. It is important to note (and something I forgot to mention above) that we are working with a trace inner product. We derive $mathcal{A}^*$ as follows:
$$
DeclareMathOperator{Tr}{Tr}
langle y,mathcal{A}(X)rangle
=langle mathcal{A}^*(y),Xrangle
=yX_{11}
=Trbig(mathcal{A}^*(y)Xbig)
=sum_{i,j} big(mathcal{A}^*(y)big)_{ij}X_{ij}
$$
Thus for a general $Xin S^2$, we must have that $mathcal{A}^*(y)=begin{bmatrix}y&0\0&0end{bmatrix}.$
I'm not $100$% certain about the other two ways I proposed, but this is the way to derive $mathcal{A}^*$ in general.
add a comment |
1 Answer
1
active
oldest
votes
1 Answer
1
active
oldest
votes
active
oldest
votes
active
oldest
votes
up vote
0
down vote
accepted
I figured out the correct way to derive the answer. It is important to note (and something I forgot to mention above) that we are working with a trace inner product. We derive $mathcal{A}^*$ as follows:
$$
DeclareMathOperator{Tr}{Tr}
langle y,mathcal{A}(X)rangle
=langle mathcal{A}^*(y),Xrangle
=yX_{11}
=Trbig(mathcal{A}^*(y)Xbig)
=sum_{i,j} big(mathcal{A}^*(y)big)_{ij}X_{ij}
$$
Thus for a general $Xin S^2$, we must have that $mathcal{A}^*(y)=begin{bmatrix}y&0\0&0end{bmatrix}.$
I'm not $100$% certain about the other two ways I proposed, but this is the way to derive $mathcal{A}^*$ in general.
add a comment |
up vote
0
down vote
accepted
I figured out the correct way to derive the answer. It is important to note (and something I forgot to mention above) that we are working with a trace inner product. We derive $mathcal{A}^*$ as follows:
$$
DeclareMathOperator{Tr}{Tr}
langle y,mathcal{A}(X)rangle
=langle mathcal{A}^*(y),Xrangle
=yX_{11}
=Trbig(mathcal{A}^*(y)Xbig)
=sum_{i,j} big(mathcal{A}^*(y)big)_{ij}X_{ij}
$$
Thus for a general $Xin S^2$, we must have that $mathcal{A}^*(y)=begin{bmatrix}y&0\0&0end{bmatrix}.$
I'm not $100$% certain about the other two ways I proposed, but this is the way to derive $mathcal{A}^*$ in general.
add a comment |
up vote
0
down vote
accepted
up vote
0
down vote
accepted
I figured out the correct way to derive the answer. It is important to note (and something I forgot to mention above) that we are working with a trace inner product. We derive $mathcal{A}^*$ as follows:
$$
DeclareMathOperator{Tr}{Tr}
langle y,mathcal{A}(X)rangle
=langle mathcal{A}^*(y),Xrangle
=yX_{11}
=Trbig(mathcal{A}^*(y)Xbig)
=sum_{i,j} big(mathcal{A}^*(y)big)_{ij}X_{ij}
$$
Thus for a general $Xin S^2$, we must have that $mathcal{A}^*(y)=begin{bmatrix}y&0\0&0end{bmatrix}.$
I'm not $100$% certain about the other two ways I proposed, but this is the way to derive $mathcal{A}^*$ in general.
I figured out the correct way to derive the answer. It is important to note (and something I forgot to mention above) that we are working with a trace inner product. We derive $mathcal{A}^*$ as follows:
$$
DeclareMathOperator{Tr}{Tr}
langle y,mathcal{A}(X)rangle
=langle mathcal{A}^*(y),Xrangle
=yX_{11}
=Trbig(mathcal{A}^*(y)Xbig)
=sum_{i,j} big(mathcal{A}^*(y)big)_{ij}X_{ij}
$$
Thus for a general $Xin S^2$, we must have that $mathcal{A}^*(y)=begin{bmatrix}y&0\0&0end{bmatrix}.$
I'm not $100$% certain about the other two ways I proposed, but this is the way to derive $mathcal{A}^*$ in general.
answered Nov 18 at 20:09
Dan
153
153
add a comment |
add a comment |
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The linear map is defined on vector space. In particular, if we choose orthonormal bases of both spaces, one can show that the matrix representations of $L^∗$ and $L$ are related by $[L^∗]=[L]^T$. You can read more about it here math.stackexchange.com/questions/1769834/…
– Jimmy
Nov 18 at 20:01