Find projective matrix with given null space
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Find an $n times n$ projective matrix, $P$, such that its null space is spanned by vector $(1,1,...,1)^T$.
My attempt at solution:
A projective matrix is a matrix such that $P^2=P$ and $P^T=P$, i.e., it is a symmetric matrix, whose square is itself.
Now by rank-nullity theorem, we know that $P$ is supposed to have $(n-1)$ linearly independent columns. So my solution would be the following $n times n$ matrix
$$
beginpmatrix
1 & 0 & 0 & 0 & cdots & 0 & -1\
0 & 1 & 0 & 0 & cdots & 0 & -1\
&&& vdots &&&\
0 & 0 & 0 & 0 & cdots & 1 & -1\
0 & 0 & 0 & 0 & cdots & 0 & 0
endpmatrix
$$
It easy to see that the null space is indeed given by $(1,1,1,...,1)^T$. On the other hand, $P^2=P$, which satisfies one of the requirements of being a projective matrix. However, I canâÂÂt think of any way of making this a symmetric matrix.
Any help would be appreciated.
linear-algebra abstract-algebra
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up vote
-1
down vote
favorite
Find an $n times n$ projective matrix, $P$, such that its null space is spanned by vector $(1,1,...,1)^T$.
My attempt at solution:
A projective matrix is a matrix such that $P^2=P$ and $P^T=P$, i.e., it is a symmetric matrix, whose square is itself.
Now by rank-nullity theorem, we know that $P$ is supposed to have $(n-1)$ linearly independent columns. So my solution would be the following $n times n$ matrix
$$
beginpmatrix
1 & 0 & 0 & 0 & cdots & 0 & -1\
0 & 1 & 0 & 0 & cdots & 0 & -1\
&&& vdots &&&\
0 & 0 & 0 & 0 & cdots & 1 & -1\
0 & 0 & 0 & 0 & cdots & 0 & 0
endpmatrix
$$
It easy to see that the null space is indeed given by $(1,1,1,...,1)^T$. On the other hand, $P^2=P$, which satisfies one of the requirements of being a projective matrix. However, I canâÂÂt think of any way of making this a symmetric matrix.
Any help would be appreciated.
linear-algebra abstract-algebra
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â Quasicoherent
Aug 28 at 15:13
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up vote
-1
down vote
favorite
up vote
-1
down vote
favorite
Find an $n times n$ projective matrix, $P$, such that its null space is spanned by vector $(1,1,...,1)^T$.
My attempt at solution:
A projective matrix is a matrix such that $P^2=P$ and $P^T=P$, i.e., it is a symmetric matrix, whose square is itself.
Now by rank-nullity theorem, we know that $P$ is supposed to have $(n-1)$ linearly independent columns. So my solution would be the following $n times n$ matrix
$$
beginpmatrix
1 & 0 & 0 & 0 & cdots & 0 & -1\
0 & 1 & 0 & 0 & cdots & 0 & -1\
&&& vdots &&&\
0 & 0 & 0 & 0 & cdots & 1 & -1\
0 & 0 & 0 & 0 & cdots & 0 & 0
endpmatrix
$$
It easy to see that the null space is indeed given by $(1,1,1,...,1)^T$. On the other hand, $P^2=P$, which satisfies one of the requirements of being a projective matrix. However, I canâÂÂt think of any way of making this a symmetric matrix.
Any help would be appreciated.
linear-algebra abstract-algebra
Find an $n times n$ projective matrix, $P$, such that its null space is spanned by vector $(1,1,...,1)^T$.
My attempt at solution:
A projective matrix is a matrix such that $P^2=P$ and $P^T=P$, i.e., it is a symmetric matrix, whose square is itself.
Now by rank-nullity theorem, we know that $P$ is supposed to have $(n-1)$ linearly independent columns. So my solution would be the following $n times n$ matrix
$$
beginpmatrix
1 & 0 & 0 & 0 & cdots & 0 & -1\
0 & 1 & 0 & 0 & cdots & 0 & -1\
&&& vdots &&&\
0 & 0 & 0 & 0 & cdots & 1 & -1\
0 & 0 & 0 & 0 & cdots & 0 & 0
endpmatrix
$$
It easy to see that the null space is indeed given by $(1,1,1,...,1)^T$. On the other hand, $P^2=P$, which satisfies one of the requirements of being a projective matrix. However, I canâÂÂt think of any way of making this a symmetric matrix.
Any help would be appreciated.
linear-algebra abstract-algebra
edited Aug 28 at 15:12
Quasicoherent
11.7k22041
11.7k22041
asked Aug 28 at 15:06
Renat Sergazinov
33
33
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â Quasicoherent
Aug 28 at 15:13
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Welcome to math.se! Here is a page on how to typeset math here.
â Quasicoherent
Aug 28 at 15:13
Welcome to math.se! Here is a page on how to typeset math here.
â Quasicoherent
Aug 28 at 15:13
Welcome to math.se! Here is a page on how to typeset math here.
â Quasicoherent
Aug 28 at 15:13
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2 Answers
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up vote
0
down vote
accepted
Since $P^2=P$, you have a perfectly good projection matrix. However, the definition of âÂÂprojective matrixâ that you have also requires that $P^T=P$, which makes it specifically an orthogonal projection. For that, the column space of the matrix must be the orthogonal complement of the null space.
There are several ways that you might construct such a matrix. A somewhat brute-force method is to find a basis $v_1,dots,v_n-1$ for the orthogonal complement of $W=operatornamespan(1,1,dots,1)^T$. Assemble these vectors and $w=(1,1,dots,1)^T$ itself into a matrix $B$. The desired projective matrix is then $$BbeginbmatrixI_n-1&0\0&0endbmatrixB^-1.$$ (Do you see why?) Note that the non-zero rows of the matrix that youâÂÂve constructed are a basis for $W^perp$.
A simpler way is to observe that orthogonal projections onto $W$ and $W^perp$ are complementary in the sense that if $P$ is the orthogonal projection onto $W$, then $I-P$ is the orthogonal projection onto $W^perp$. Since $W$ is one-dimensional, the orthogonal projection matrix onto this subspace is quite easy to construct: the projection of a vector $v$ onto $w$ is $w^Tv over w^Tww = ww^Tover w^Twv$, so the projection matrix onto $W^perp$ is $I-ww^Tover w^Tw$. This is clearly symmetric, as required. For the vector in your problem, this will be $I_n-frac1nmathbb 1_n$, where $mathbb 1_n$ is the $ntimes n$ matrix of all $1$âÂÂs, i.e., $P$ has $(n-1)/n$ down its main diagonal and $-1/n$ elsewhere.
add a comment |Â
up vote
1
down vote
The projection that you are looking for is $Px = x - frac 1langle x,vrangle v$, i.e.,
$$
P = I - fracvv^Tv^Tv,
$$
where $v = (1,1,ldots,1)^T$.
add a comment |Â
2 Answers
2
active
oldest
votes
2 Answers
2
active
oldest
votes
active
oldest
votes
active
oldest
votes
up vote
0
down vote
accepted
Since $P^2=P$, you have a perfectly good projection matrix. However, the definition of âÂÂprojective matrixâ that you have also requires that $P^T=P$, which makes it specifically an orthogonal projection. For that, the column space of the matrix must be the orthogonal complement of the null space.
There are several ways that you might construct such a matrix. A somewhat brute-force method is to find a basis $v_1,dots,v_n-1$ for the orthogonal complement of $W=operatornamespan(1,1,dots,1)^T$. Assemble these vectors and $w=(1,1,dots,1)^T$ itself into a matrix $B$. The desired projective matrix is then $$BbeginbmatrixI_n-1&0\0&0endbmatrixB^-1.$$ (Do you see why?) Note that the non-zero rows of the matrix that youâÂÂve constructed are a basis for $W^perp$.
A simpler way is to observe that orthogonal projections onto $W$ and $W^perp$ are complementary in the sense that if $P$ is the orthogonal projection onto $W$, then $I-P$ is the orthogonal projection onto $W^perp$. Since $W$ is one-dimensional, the orthogonal projection matrix onto this subspace is quite easy to construct: the projection of a vector $v$ onto $w$ is $w^Tv over w^Tww = ww^Tover w^Twv$, so the projection matrix onto $W^perp$ is $I-ww^Tover w^Tw$. This is clearly symmetric, as required. For the vector in your problem, this will be $I_n-frac1nmathbb 1_n$, where $mathbb 1_n$ is the $ntimes n$ matrix of all $1$âÂÂs, i.e., $P$ has $(n-1)/n$ down its main diagonal and $-1/n$ elsewhere.
add a comment |Â
up vote
0
down vote
accepted
Since $P^2=P$, you have a perfectly good projection matrix. However, the definition of âÂÂprojective matrixâ that you have also requires that $P^T=P$, which makes it specifically an orthogonal projection. For that, the column space of the matrix must be the orthogonal complement of the null space.
There are several ways that you might construct such a matrix. A somewhat brute-force method is to find a basis $v_1,dots,v_n-1$ for the orthogonal complement of $W=operatornamespan(1,1,dots,1)^T$. Assemble these vectors and $w=(1,1,dots,1)^T$ itself into a matrix $B$. The desired projective matrix is then $$BbeginbmatrixI_n-1&0\0&0endbmatrixB^-1.$$ (Do you see why?) Note that the non-zero rows of the matrix that youâÂÂve constructed are a basis for $W^perp$.
A simpler way is to observe that orthogonal projections onto $W$ and $W^perp$ are complementary in the sense that if $P$ is the orthogonal projection onto $W$, then $I-P$ is the orthogonal projection onto $W^perp$. Since $W$ is one-dimensional, the orthogonal projection matrix onto this subspace is quite easy to construct: the projection of a vector $v$ onto $w$ is $w^Tv over w^Tww = ww^Tover w^Twv$, so the projection matrix onto $W^perp$ is $I-ww^Tover w^Tw$. This is clearly symmetric, as required. For the vector in your problem, this will be $I_n-frac1nmathbb 1_n$, where $mathbb 1_n$ is the $ntimes n$ matrix of all $1$âÂÂs, i.e., $P$ has $(n-1)/n$ down its main diagonal and $-1/n$ elsewhere.
add a comment |Â
up vote
0
down vote
accepted
up vote
0
down vote
accepted
Since $P^2=P$, you have a perfectly good projection matrix. However, the definition of âÂÂprojective matrixâ that you have also requires that $P^T=P$, which makes it specifically an orthogonal projection. For that, the column space of the matrix must be the orthogonal complement of the null space.
There are several ways that you might construct such a matrix. A somewhat brute-force method is to find a basis $v_1,dots,v_n-1$ for the orthogonal complement of $W=operatornamespan(1,1,dots,1)^T$. Assemble these vectors and $w=(1,1,dots,1)^T$ itself into a matrix $B$. The desired projective matrix is then $$BbeginbmatrixI_n-1&0\0&0endbmatrixB^-1.$$ (Do you see why?) Note that the non-zero rows of the matrix that youâÂÂve constructed are a basis for $W^perp$.
A simpler way is to observe that orthogonal projections onto $W$ and $W^perp$ are complementary in the sense that if $P$ is the orthogonal projection onto $W$, then $I-P$ is the orthogonal projection onto $W^perp$. Since $W$ is one-dimensional, the orthogonal projection matrix onto this subspace is quite easy to construct: the projection of a vector $v$ onto $w$ is $w^Tv over w^Tww = ww^Tover w^Twv$, so the projection matrix onto $W^perp$ is $I-ww^Tover w^Tw$. This is clearly symmetric, as required. For the vector in your problem, this will be $I_n-frac1nmathbb 1_n$, where $mathbb 1_n$ is the $ntimes n$ matrix of all $1$âÂÂs, i.e., $P$ has $(n-1)/n$ down its main diagonal and $-1/n$ elsewhere.
Since $P^2=P$, you have a perfectly good projection matrix. However, the definition of âÂÂprojective matrixâ that you have also requires that $P^T=P$, which makes it specifically an orthogonal projection. For that, the column space of the matrix must be the orthogonal complement of the null space.
There are several ways that you might construct such a matrix. A somewhat brute-force method is to find a basis $v_1,dots,v_n-1$ for the orthogonal complement of $W=operatornamespan(1,1,dots,1)^T$. Assemble these vectors and $w=(1,1,dots,1)^T$ itself into a matrix $B$. The desired projective matrix is then $$BbeginbmatrixI_n-1&0\0&0endbmatrixB^-1.$$ (Do you see why?) Note that the non-zero rows of the matrix that youâÂÂve constructed are a basis for $W^perp$.
A simpler way is to observe that orthogonal projections onto $W$ and $W^perp$ are complementary in the sense that if $P$ is the orthogonal projection onto $W$, then $I-P$ is the orthogonal projection onto $W^perp$. Since $W$ is one-dimensional, the orthogonal projection matrix onto this subspace is quite easy to construct: the projection of a vector $v$ onto $w$ is $w^Tv over w^Tww = ww^Tover w^Twv$, so the projection matrix onto $W^perp$ is $I-ww^Tover w^Tw$. This is clearly symmetric, as required. For the vector in your problem, this will be $I_n-frac1nmathbb 1_n$, where $mathbb 1_n$ is the $ntimes n$ matrix of all $1$âÂÂs, i.e., $P$ has $(n-1)/n$ down its main diagonal and $-1/n$ elsewhere.
edited Aug 28 at 20:54
answered Aug 28 at 19:18
amd
26.6k21046
26.6k21046
add a comment |Â
add a comment |Â
up vote
1
down vote
The projection that you are looking for is $Px = x - frac 1langle x,vrangle v$, i.e.,
$$
P = I - fracvv^Tv^Tv,
$$
where $v = (1,1,ldots,1)^T$.
add a comment |Â
up vote
1
down vote
The projection that you are looking for is $Px = x - frac 1langle x,vrangle v$, i.e.,
$$
P = I - fracvv^Tv^Tv,
$$
where $v = (1,1,ldots,1)^T$.
add a comment |Â
up vote
1
down vote
up vote
1
down vote
The projection that you are looking for is $Px = x - frac 1langle x,vrangle v$, i.e.,
$$
P = I - fracvv^Tv^Tv,
$$
where $v = (1,1,ldots,1)^T$.
The projection that you are looking for is $Px = x - frac 1langle x,vrangle v$, i.e.,
$$
P = I - fracvv^Tv^Tv,
$$
where $v = (1,1,ldots,1)^T$.
answered Aug 28 at 15:18
amsmath
2,397114
2,397114
add a comment |Â
add a comment |Â
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Welcome to math.se! Here is a page on how to typeset math here.
â Quasicoherent
Aug 28 at 15:13