Matrix of reflection in $R^3$
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Please, can you explain me how do we get this formula
$$ A = I - 2nn^{T} $$ in $$ R^{3} $$? This should be matrix of reflection, but I don't know how to prove that.
linear-algebra geometry matrix-equations reflection
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up vote
1
down vote
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Please, can you explain me how do we get this formula
$$ A = I - 2nn^{T} $$ in $$ R^{3} $$? This should be matrix of reflection, but I don't know how to prove that.
linear-algebra geometry matrix-equations reflection
1
Welcome to MSE. Your question is phrased as an isolated problem, without any further information or context. This does not match many users' quality standards, so it may attract downvotes, or be put on hold. To prevent that, please edit the question. This will help you recognise and resolve the issues. Concretely: please provide context, and include your work and thoughts on the problem. These changes can help in formulating more appropriate answers.
– José Carlos Santos
Nov 26 at 9:43
1
This form is called "Householder transform" in the domain of Numerical Analysis.
– Jean Marie
Nov 26 at 10:32
add a comment |
up vote
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up vote
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down vote
favorite
Please, can you explain me how do we get this formula
$$ A = I - 2nn^{T} $$ in $$ R^{3} $$? This should be matrix of reflection, but I don't know how to prove that.
linear-algebra geometry matrix-equations reflection
Please, can you explain me how do we get this formula
$$ A = I - 2nn^{T} $$ in $$ R^{3} $$? This should be matrix of reflection, but I don't know how to prove that.
linear-algebra geometry matrix-equations reflection
linear-algebra geometry matrix-equations reflection
edited Nov 26 at 10:20
Darío A. Gutiérrez
2,57341530
2,57341530
asked Nov 26 at 9:37
Lazar
63
63
1
Welcome to MSE. Your question is phrased as an isolated problem, without any further information or context. This does not match many users' quality standards, so it may attract downvotes, or be put on hold. To prevent that, please edit the question. This will help you recognise and resolve the issues. Concretely: please provide context, and include your work and thoughts on the problem. These changes can help in formulating more appropriate answers.
– José Carlos Santos
Nov 26 at 9:43
1
This form is called "Householder transform" in the domain of Numerical Analysis.
– Jean Marie
Nov 26 at 10:32
add a comment |
1
Welcome to MSE. Your question is phrased as an isolated problem, without any further information or context. This does not match many users' quality standards, so it may attract downvotes, or be put on hold. To prevent that, please edit the question. This will help you recognise and resolve the issues. Concretely: please provide context, and include your work and thoughts on the problem. These changes can help in formulating more appropriate answers.
– José Carlos Santos
Nov 26 at 9:43
1
This form is called "Householder transform" in the domain of Numerical Analysis.
– Jean Marie
Nov 26 at 10:32
1
1
Welcome to MSE. Your question is phrased as an isolated problem, without any further information or context. This does not match many users' quality standards, so it may attract downvotes, or be put on hold. To prevent that, please edit the question. This will help you recognise and resolve the issues. Concretely: please provide context, and include your work and thoughts on the problem. These changes can help in formulating more appropriate answers.
– José Carlos Santos
Nov 26 at 9:43
Welcome to MSE. Your question is phrased as an isolated problem, without any further information or context. This does not match many users' quality standards, so it may attract downvotes, or be put on hold. To prevent that, please edit the question. This will help you recognise and resolve the issues. Concretely: please provide context, and include your work and thoughts on the problem. These changes can help in formulating more appropriate answers.
– José Carlos Santos
Nov 26 at 9:43
1
1
This form is called "Householder transform" in the domain of Numerical Analysis.
– Jean Marie
Nov 26 at 10:32
This form is called "Householder transform" in the domain of Numerical Analysis.
– Jean Marie
Nov 26 at 10:32
add a comment |
2 Answers
2
active
oldest
votes
up vote
1
down vote
Let $a,b,n$ be unit vectors orthogonal to each other - $a,b$ basis for the plane, $n$ orthogonal to the plane.
You can easily check that any vector $v$ is represented in the basis {$a,b,n$} as
$v=a(a^Tv)+b(b^Tv)+n(n^Tv)=(aa^T+bb^T+nn^T)v$
($a^Tv, b^Tv, n^Tv$ are here scalars)
hence $aa^T+bb^T+nn^T=I$.
During the reflection components in the plane are unchanged, component orthogonal to the plane is negated.
Hence we have $w= (aa^T+bb^T-nn^T)v=(I-2nn^T)v$.
Very nice! Thank you.
– Giuseppe Negro
Dec 3 at 11:06
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up vote
0
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This is maybe more of a trick than of a proof, but I find this approach much easier to memorize.
Let $x_1, x_2, x_3$ be the Cartesian coordinates of the space. It is clear that the reflection around the plane $x_1x_2$ is the map
$$
(x_1, x_2, x_3)mapsto (x_1, x_2, -x_3), $$
and this is a linear map that can be written in matrix form as
$$
A_{(0,0,1)}begin{bmatrix} x_1 \ x_2 \ x_3end{bmatrix} = left( I-begin{bmatrix} 0 & 0 &0\ 0 & 0 & 0 \ 0 & 0 & 2end{bmatrix}right)begin{bmatrix}x_1\ x_2 \ x_3end{bmatrix},$$
that is,
$$
A_{(0,0,1)}=I-2begin{bmatrix} 0 \ 0 \ 1end{bmatrix}begin{bmatrix} 0 &0 &1end{bmatrix}.$$
We write
$$tag{1}
A_{(0,0,1)}vec x = vec y.$$
Now, to obtain the formula for the reflection around the plane having $vec{n}$ as normal vector, we change variables;
$$
vec x = Rvec x ', quad vec y = Rvec y', $$
where $R$ is a rotation matrix such that
$$
Rvec n = begin{bmatrix} 0 \0 \ 1end{bmatrix}.$$
Applying this change of variable in (1) yields
$$tag{2}
A_{vec n}vec x ' =vec y ',$$
where $A_{vec n}$ is the reflection matrix we want to compute. And now it is a matter of unwrapping $vec x', vec y'$ in (2) and computing, using the fact that $R^TR=I$, because $R$ is a rotation.
add a comment |
2 Answers
2
active
oldest
votes
2 Answers
2
active
oldest
votes
active
oldest
votes
active
oldest
votes
up vote
1
down vote
Let $a,b,n$ be unit vectors orthogonal to each other - $a,b$ basis for the plane, $n$ orthogonal to the plane.
You can easily check that any vector $v$ is represented in the basis {$a,b,n$} as
$v=a(a^Tv)+b(b^Tv)+n(n^Tv)=(aa^T+bb^T+nn^T)v$
($a^Tv, b^Tv, n^Tv$ are here scalars)
hence $aa^T+bb^T+nn^T=I$.
During the reflection components in the plane are unchanged, component orthogonal to the plane is negated.
Hence we have $w= (aa^T+bb^T-nn^T)v=(I-2nn^T)v$.
Very nice! Thank you.
– Giuseppe Negro
Dec 3 at 11:06
add a comment |
up vote
1
down vote
Let $a,b,n$ be unit vectors orthogonal to each other - $a,b$ basis for the plane, $n$ orthogonal to the plane.
You can easily check that any vector $v$ is represented in the basis {$a,b,n$} as
$v=a(a^Tv)+b(b^Tv)+n(n^Tv)=(aa^T+bb^T+nn^T)v$
($a^Tv, b^Tv, n^Tv$ are here scalars)
hence $aa^T+bb^T+nn^T=I$.
During the reflection components in the plane are unchanged, component orthogonal to the plane is negated.
Hence we have $w= (aa^T+bb^T-nn^T)v=(I-2nn^T)v$.
Very nice! Thank you.
– Giuseppe Negro
Dec 3 at 11:06
add a comment |
up vote
1
down vote
up vote
1
down vote
Let $a,b,n$ be unit vectors orthogonal to each other - $a,b$ basis for the plane, $n$ orthogonal to the plane.
You can easily check that any vector $v$ is represented in the basis {$a,b,n$} as
$v=a(a^Tv)+b(b^Tv)+n(n^Tv)=(aa^T+bb^T+nn^T)v$
($a^Tv, b^Tv, n^Tv$ are here scalars)
hence $aa^T+bb^T+nn^T=I$.
During the reflection components in the plane are unchanged, component orthogonal to the plane is negated.
Hence we have $w= (aa^T+bb^T-nn^T)v=(I-2nn^T)v$.
Let $a,b,n$ be unit vectors orthogonal to each other - $a,b$ basis for the plane, $n$ orthogonal to the plane.
You can easily check that any vector $v$ is represented in the basis {$a,b,n$} as
$v=a(a^Tv)+b(b^Tv)+n(n^Tv)=(aa^T+bb^T+nn^T)v$
($a^Tv, b^Tv, n^Tv$ are here scalars)
hence $aa^T+bb^T+nn^T=I$.
During the reflection components in the plane are unchanged, component orthogonal to the plane is negated.
Hence we have $w= (aa^T+bb^T-nn^T)v=(I-2nn^T)v$.
edited Nov 26 at 15:55
answered Nov 26 at 14:42
Widawensen
4,38921445
4,38921445
Very nice! Thank you.
– Giuseppe Negro
Dec 3 at 11:06
add a comment |
Very nice! Thank you.
– Giuseppe Negro
Dec 3 at 11:06
Very nice! Thank you.
– Giuseppe Negro
Dec 3 at 11:06
Very nice! Thank you.
– Giuseppe Negro
Dec 3 at 11:06
add a comment |
up vote
0
down vote
This is maybe more of a trick than of a proof, but I find this approach much easier to memorize.
Let $x_1, x_2, x_3$ be the Cartesian coordinates of the space. It is clear that the reflection around the plane $x_1x_2$ is the map
$$
(x_1, x_2, x_3)mapsto (x_1, x_2, -x_3), $$
and this is a linear map that can be written in matrix form as
$$
A_{(0,0,1)}begin{bmatrix} x_1 \ x_2 \ x_3end{bmatrix} = left( I-begin{bmatrix} 0 & 0 &0\ 0 & 0 & 0 \ 0 & 0 & 2end{bmatrix}right)begin{bmatrix}x_1\ x_2 \ x_3end{bmatrix},$$
that is,
$$
A_{(0,0,1)}=I-2begin{bmatrix} 0 \ 0 \ 1end{bmatrix}begin{bmatrix} 0 &0 &1end{bmatrix}.$$
We write
$$tag{1}
A_{(0,0,1)}vec x = vec y.$$
Now, to obtain the formula for the reflection around the plane having $vec{n}$ as normal vector, we change variables;
$$
vec x = Rvec x ', quad vec y = Rvec y', $$
where $R$ is a rotation matrix such that
$$
Rvec n = begin{bmatrix} 0 \0 \ 1end{bmatrix}.$$
Applying this change of variable in (1) yields
$$tag{2}
A_{vec n}vec x ' =vec y ',$$
where $A_{vec n}$ is the reflection matrix we want to compute. And now it is a matter of unwrapping $vec x', vec y'$ in (2) and computing, using the fact that $R^TR=I$, because $R$ is a rotation.
add a comment |
up vote
0
down vote
This is maybe more of a trick than of a proof, but I find this approach much easier to memorize.
Let $x_1, x_2, x_3$ be the Cartesian coordinates of the space. It is clear that the reflection around the plane $x_1x_2$ is the map
$$
(x_1, x_2, x_3)mapsto (x_1, x_2, -x_3), $$
and this is a linear map that can be written in matrix form as
$$
A_{(0,0,1)}begin{bmatrix} x_1 \ x_2 \ x_3end{bmatrix} = left( I-begin{bmatrix} 0 & 0 &0\ 0 & 0 & 0 \ 0 & 0 & 2end{bmatrix}right)begin{bmatrix}x_1\ x_2 \ x_3end{bmatrix},$$
that is,
$$
A_{(0,0,1)}=I-2begin{bmatrix} 0 \ 0 \ 1end{bmatrix}begin{bmatrix} 0 &0 &1end{bmatrix}.$$
We write
$$tag{1}
A_{(0,0,1)}vec x = vec y.$$
Now, to obtain the formula for the reflection around the plane having $vec{n}$ as normal vector, we change variables;
$$
vec x = Rvec x ', quad vec y = Rvec y', $$
where $R$ is a rotation matrix such that
$$
Rvec n = begin{bmatrix} 0 \0 \ 1end{bmatrix}.$$
Applying this change of variable in (1) yields
$$tag{2}
A_{vec n}vec x ' =vec y ',$$
where $A_{vec n}$ is the reflection matrix we want to compute. And now it is a matter of unwrapping $vec x', vec y'$ in (2) and computing, using the fact that $R^TR=I$, because $R$ is a rotation.
add a comment |
up vote
0
down vote
up vote
0
down vote
This is maybe more of a trick than of a proof, but I find this approach much easier to memorize.
Let $x_1, x_2, x_3$ be the Cartesian coordinates of the space. It is clear that the reflection around the plane $x_1x_2$ is the map
$$
(x_1, x_2, x_3)mapsto (x_1, x_2, -x_3), $$
and this is a linear map that can be written in matrix form as
$$
A_{(0,0,1)}begin{bmatrix} x_1 \ x_2 \ x_3end{bmatrix} = left( I-begin{bmatrix} 0 & 0 &0\ 0 & 0 & 0 \ 0 & 0 & 2end{bmatrix}right)begin{bmatrix}x_1\ x_2 \ x_3end{bmatrix},$$
that is,
$$
A_{(0,0,1)}=I-2begin{bmatrix} 0 \ 0 \ 1end{bmatrix}begin{bmatrix} 0 &0 &1end{bmatrix}.$$
We write
$$tag{1}
A_{(0,0,1)}vec x = vec y.$$
Now, to obtain the formula for the reflection around the plane having $vec{n}$ as normal vector, we change variables;
$$
vec x = Rvec x ', quad vec y = Rvec y', $$
where $R$ is a rotation matrix such that
$$
Rvec n = begin{bmatrix} 0 \0 \ 1end{bmatrix}.$$
Applying this change of variable in (1) yields
$$tag{2}
A_{vec n}vec x ' =vec y ',$$
where $A_{vec n}$ is the reflection matrix we want to compute. And now it is a matter of unwrapping $vec x', vec y'$ in (2) and computing, using the fact that $R^TR=I$, because $R$ is a rotation.
This is maybe more of a trick than of a proof, but I find this approach much easier to memorize.
Let $x_1, x_2, x_3$ be the Cartesian coordinates of the space. It is clear that the reflection around the plane $x_1x_2$ is the map
$$
(x_1, x_2, x_3)mapsto (x_1, x_2, -x_3), $$
and this is a linear map that can be written in matrix form as
$$
A_{(0,0,1)}begin{bmatrix} x_1 \ x_2 \ x_3end{bmatrix} = left( I-begin{bmatrix} 0 & 0 &0\ 0 & 0 & 0 \ 0 & 0 & 2end{bmatrix}right)begin{bmatrix}x_1\ x_2 \ x_3end{bmatrix},$$
that is,
$$
A_{(0,0,1)}=I-2begin{bmatrix} 0 \ 0 \ 1end{bmatrix}begin{bmatrix} 0 &0 &1end{bmatrix}.$$
We write
$$tag{1}
A_{(0,0,1)}vec x = vec y.$$
Now, to obtain the formula for the reflection around the plane having $vec{n}$ as normal vector, we change variables;
$$
vec x = Rvec x ', quad vec y = Rvec y', $$
where $R$ is a rotation matrix such that
$$
Rvec n = begin{bmatrix} 0 \0 \ 1end{bmatrix}.$$
Applying this change of variable in (1) yields
$$tag{2}
A_{vec n}vec x ' =vec y ',$$
where $A_{vec n}$ is the reflection matrix we want to compute. And now it is a matter of unwrapping $vec x', vec y'$ in (2) and computing, using the fact that $R^TR=I$, because $R$ is a rotation.
answered Nov 26 at 10:15
community wiki
Giuseppe Negro
add a comment |
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Welcome to MSE. Your question is phrased as an isolated problem, without any further information or context. This does not match many users' quality standards, so it may attract downvotes, or be put on hold. To prevent that, please edit the question. This will help you recognise and resolve the issues. Concretely: please provide context, and include your work and thoughts on the problem. These changes can help in formulating more appropriate answers.
– José Carlos Santos
Nov 26 at 9:43
1
This form is called "Householder transform" in the domain of Numerical Analysis.
– Jean Marie
Nov 26 at 10:32