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 can’t think of any way of making this a symmetric matrix.



Any help would be appreciated.







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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 can’t think of any way of making this a symmetric matrix.



Any help would be appreciated.







share|cite|improve this question






















  • Welcome to math.se! Here is a page on how to typeset math here.
    – Quasicoherent
    Aug 28 at 15:13












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 can’t think of any way of making this a symmetric matrix.



Any help would be appreciated.







share|cite|improve this question















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 can’t think of any way of making this a symmetric matrix.



Any help would be appreciated.









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edited Aug 28 at 15:12









Quasicoherent

11.7k22041




11.7k22041










asked Aug 28 at 15:06









Renat Sergazinov

33




33











  • Welcome to math.se! Here is a page on how to typeset math here.
    – Quasicoherent
    Aug 28 at 15:13
















  • Welcome to math.se! Here is a page on how to typeset math here.
    – Quasicoherent
    Aug 28 at 15:13















Welcome to math.se! Here is a page on how to typeset math here.
– Quasicoherent
Aug 28 at 15:13




Welcome to math.se! Here is a page on how to typeset math here.
– Quasicoherent
Aug 28 at 15:13










2 Answers
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Since $P^2=P$, you have a perfectly good projection matrix. However, the definition of “projective matrix” 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 you’ve 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 $1$’s, i.e., $P$ has $(n-1)/n$ down its main diagonal and $-1/n$ elsewhere.






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    The projection that you are looking for is $Px = x - frac 1langle x,vrangle v$, i.e.,
    $$
    P = I - fracvv^Tv^Tv,
    $$
    where $v = (1,1,ldots,1)^T$.






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      2 Answers
      2






      active

      oldest

      votes








      2 Answers
      2






      active

      oldest

      votes









      active

      oldest

      votes






      active

      oldest

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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 “projective matrix” 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 you’ve 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 $1$’s, i.e., $P$ has $(n-1)/n$ down its main diagonal and $-1/n$ elsewhere.






      share|cite|improve this answer


























        up vote
        0
        down vote



        accepted










        Since $P^2=P$, you have a perfectly good projection matrix. However, the definition of “projective matrix” 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 you’ve 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 $1$’s, i.e., $P$ has $(n-1)/n$ down its main diagonal and $-1/n$ elsewhere.






        share|cite|improve this answer
























          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 “projective matrix” 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 you’ve 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 $1$’s, i.e., $P$ has $(n-1)/n$ down its main diagonal and $-1/n$ elsewhere.






          share|cite|improve this answer














          Since $P^2=P$, you have a perfectly good projection matrix. However, the definition of “projective matrix” 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 you’ve 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 $1$’s, i.e., $P$ has $(n-1)/n$ down its main diagonal and $-1/n$ elsewhere.







          share|cite|improve this answer














          share|cite|improve this answer



          share|cite|improve this answer








          edited Aug 28 at 20:54

























          answered Aug 28 at 19:18









          amd

          26.6k21046




          26.6k21046




















              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 $v = (1,1,ldots,1)^T$.






              share|cite|improve this answer
























                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 $v = (1,1,ldots,1)^T$.






                share|cite|improve this answer






















                  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 $v = (1,1,ldots,1)^T$.






                  share|cite|improve this answer












                  The projection that you are looking for is $Px = x - frac 1langle x,vrangle v$, i.e.,
                  $$
                  P = I - fracvv^Tv^Tv,
                  $$
                  where $v = (1,1,ldots,1)^T$.







                  share|cite|improve this answer












                  share|cite|improve this answer



                  share|cite|improve this answer










                  answered Aug 28 at 15:18









                  amsmath

                  2,397114




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