Show that $0$ has multiplicity $3$ in $M-4I$?

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Question from an exam:
Consider the matrix $M=$
beginbmatrix 5&1&1&1&1&1\1&5&1&1&1&1\1&1&5&1&1&1\1&1&1&4&1&0\1&1&1&1&4&0\1&1&1&0&0&3endbmatrix
Show that $4$ is an eigen value of the above matrix with multiplicity $3$.
I considered $M-4I$ from which I got
beginbmatrix 1&1&1&1&1&1\1&1&1&1&1&1\1&1&1&1&1&1\1&1&1&0&1&0\1&1&1&1&0&0\1&1&1&0&0&-1endbmatrix
By elementary row operations:
$$M-4I=$$
beginbmatrix 1&1&1&1&1&1\0&0&0&0&0&0\0&0&0&0&0&0\1&1&1&0&1&0\1&1&1&1&0&0\1&1&1&0&0&-1endbmatrix
So $0$ is an eigen value with multiplicity at least $2$ since $M-2I$ has two zero rows.
How to show that $0$ has multiplicity $3$ in $M-4I$?
If one can show how to proceed after this,I will be really grateful.
Please help
linear-algebra matrices
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up vote
1
down vote
favorite
Question from an exam:
Consider the matrix $M=$
beginbmatrix 5&1&1&1&1&1\1&5&1&1&1&1\1&1&5&1&1&1\1&1&1&4&1&0\1&1&1&1&4&0\1&1&1&0&0&3endbmatrix
Show that $4$ is an eigen value of the above matrix with multiplicity $3$.
I considered $M-4I$ from which I got
beginbmatrix 1&1&1&1&1&1\1&1&1&1&1&1\1&1&1&1&1&1\1&1&1&0&1&0\1&1&1&1&0&0\1&1&1&0&0&-1endbmatrix
By elementary row operations:
$$M-4I=$$
beginbmatrix 1&1&1&1&1&1\0&0&0&0&0&0\0&0&0&0&0&0\1&1&1&0&1&0\1&1&1&1&0&0\1&1&1&0&0&-1endbmatrix
So $0$ is an eigen value with multiplicity at least $2$ since $M-2I$ has two zero rows.
How to show that $0$ has multiplicity $3$ in $M-4I$?
If one can show how to proceed after this,I will be really grateful.
Please help
linear-algebra matrices
You esssentially need to find the column space of the matrix $M - 4I$ i.e. what is the dimension of the vector space which is spanned by the columns of the matrix $M - 4I$. Look at the columns of $M-4I$, and try to see why the dimension is $3$. You have two rows of zeros, which is very good, but you can go one dimension better. The below answers will serve as hints. Now, by the rank nullity theorem, the kernel dimension is the space dimension minus the rank, which is $6 - 3 = 3$.
â Ã°ÃÂÃÂþý òÃÂûûð þûþàüÃÂûûñÃÂÃÂó
Aug 29 at 6:47
add a comment |Â
up vote
1
down vote
favorite
up vote
1
down vote
favorite
Question from an exam:
Consider the matrix $M=$
beginbmatrix 5&1&1&1&1&1\1&5&1&1&1&1\1&1&5&1&1&1\1&1&1&4&1&0\1&1&1&1&4&0\1&1&1&0&0&3endbmatrix
Show that $4$ is an eigen value of the above matrix with multiplicity $3$.
I considered $M-4I$ from which I got
beginbmatrix 1&1&1&1&1&1\1&1&1&1&1&1\1&1&1&1&1&1\1&1&1&0&1&0\1&1&1&1&0&0\1&1&1&0&0&-1endbmatrix
By elementary row operations:
$$M-4I=$$
beginbmatrix 1&1&1&1&1&1\0&0&0&0&0&0\0&0&0&0&0&0\1&1&1&0&1&0\1&1&1&1&0&0\1&1&1&0&0&-1endbmatrix
So $0$ is an eigen value with multiplicity at least $2$ since $M-2I$ has two zero rows.
How to show that $0$ has multiplicity $3$ in $M-4I$?
If one can show how to proceed after this,I will be really grateful.
Please help
linear-algebra matrices
Question from an exam:
Consider the matrix $M=$
beginbmatrix 5&1&1&1&1&1\1&5&1&1&1&1\1&1&5&1&1&1\1&1&1&4&1&0\1&1&1&1&4&0\1&1&1&0&0&3endbmatrix
Show that $4$ is an eigen value of the above matrix with multiplicity $3$.
I considered $M-4I$ from which I got
beginbmatrix 1&1&1&1&1&1\1&1&1&1&1&1\1&1&1&1&1&1\1&1&1&0&1&0\1&1&1&1&0&0\1&1&1&0&0&-1endbmatrix
By elementary row operations:
$$M-4I=$$
beginbmatrix 1&1&1&1&1&1\0&0&0&0&0&0\0&0&0&0&0&0\1&1&1&0&1&0\1&1&1&1&0&0\1&1&1&0&0&-1endbmatrix
So $0$ is an eigen value with multiplicity at least $2$ since $M-2I$ has two zero rows.
How to show that $0$ has multiplicity $3$ in $M-4I$?
If one can show how to proceed after this,I will be really grateful.
Please help
linear-algebra matrices
edited Aug 29 at 6:13
asked Aug 29 at 5:38
PureMathematics
976
976
You esssentially need to find the column space of the matrix $M - 4I$ i.e. what is the dimension of the vector space which is spanned by the columns of the matrix $M - 4I$. Look at the columns of $M-4I$, and try to see why the dimension is $3$. You have two rows of zeros, which is very good, but you can go one dimension better. The below answers will serve as hints. Now, by the rank nullity theorem, the kernel dimension is the space dimension minus the rank, which is $6 - 3 = 3$.
â Ã°ÃÂÃÂþý òÃÂûûð þûþàüÃÂûûñÃÂÃÂó
Aug 29 at 6:47
add a comment |Â
You esssentially need to find the column space of the matrix $M - 4I$ i.e. what is the dimension of the vector space which is spanned by the columns of the matrix $M - 4I$. Look at the columns of $M-4I$, and try to see why the dimension is $3$. You have two rows of zeros, which is very good, but you can go one dimension better. The below answers will serve as hints. Now, by the rank nullity theorem, the kernel dimension is the space dimension minus the rank, which is $6 - 3 = 3$.
â Ã°ÃÂÃÂþý òÃÂûûð þûþàüÃÂûûñÃÂÃÂó
Aug 29 at 6:47
You esssentially need to find the column space of the matrix $M - 4I$ i.e. what is the dimension of the vector space which is spanned by the columns of the matrix $M - 4I$. Look at the columns of $M-4I$, and try to see why the dimension is $3$. You have two rows of zeros, which is very good, but you can go one dimension better. The below answers will serve as hints. Now, by the rank nullity theorem, the kernel dimension is the space dimension minus the rank, which is $6 - 3 = 3$.
â Ã°ÃÂÃÂþý òÃÂûûð þûþàüÃÂûûñÃÂÃÂó
Aug 29 at 6:47
You esssentially need to find the column space of the matrix $M - 4I$ i.e. what is the dimension of the vector space which is spanned by the columns of the matrix $M - 4I$. Look at the columns of $M-4I$, and try to see why the dimension is $3$. You have two rows of zeros, which is very good, but you can go one dimension better. The below answers will serve as hints. Now, by the rank nullity theorem, the kernel dimension is the space dimension minus the rank, which is $6 - 3 = 3$.
â Ã°ÃÂÃÂþý òÃÂûûð þûþàüÃÂûûñÃÂÃÂó
Aug 29 at 6:47
add a comment |Â
2 Answers
2
active
oldest
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up vote
0
down vote
accepted
Since $M$ is symmetric, the geometric and algebraic multiplicity of its eigenvalues coincide.
If you finish your row reduction, you get
$$
beginbmatrix 1&1&1&1&1&1\1&1&1&1&1&1\1&1&1&1&1&1\1&1&1&0&1&0\1&1&1&1&0&0\1&1&1&0&0&-1endbmatrix
xrightarrow
beginbmatrix 1&1&1&0&0&-1\0&0&0&1&0&1\0&0&0&0&1&1\0&0&0&0&0&0\ 0&0&0&0&0&0\ 0&0&0&0&0&0endbmatrix
$$
As there are three leading ones, this shows that the set of solutions of $(M-4I)x=0$ has three dependent solutions, and three independent. Thus $dim ker(M-4I)=3$. This means that the eigenvalue 4 has geometric and algebraic multiplicity 3.
Will u please explain how $3$ leading ones give the existence of $3$ dependent solutions
â PureMathematics
Aug 29 at 6:28
The equations are $$x_1+x_2+x_3-x_6=0, x_4+x_6=0, x_5+x_6=0. $$Taking $x_2=r, x_3=s, x_6=t $ as parameters you get to express the solutions as $$x_1=-r-s+t, x_4=x_5=-t.$$ Having three parameters means that the solution space has dimension three. If you have trouble with linear systems, you won't be able to do much with eigenvalues.
â Martin Argerami
Aug 29 at 6:39
add a comment |Â
up vote
0
down vote
If it only had multiplicity $2$, $M-4I$ would have rank $4$, i.e. four of its rows would be linearly independent. Since the top three rows are the same, that would have to be the last four rows. But $(row 3) - (row 4) - (row 5) + (row 6) = 0$, so they are linearly dependent.
Sir will you please go through my edits I did in the question,it will help me a lot
â PureMathematics
Aug 29 at 6:14
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 $M$ is symmetric, the geometric and algebraic multiplicity of its eigenvalues coincide.
If you finish your row reduction, you get
$$
beginbmatrix 1&1&1&1&1&1\1&1&1&1&1&1\1&1&1&1&1&1\1&1&1&0&1&0\1&1&1&1&0&0\1&1&1&0&0&-1endbmatrix
xrightarrow
beginbmatrix 1&1&1&0&0&-1\0&0&0&1&0&1\0&0&0&0&1&1\0&0&0&0&0&0\ 0&0&0&0&0&0\ 0&0&0&0&0&0endbmatrix
$$
As there are three leading ones, this shows that the set of solutions of $(M-4I)x=0$ has three dependent solutions, and three independent. Thus $dim ker(M-4I)=3$. This means that the eigenvalue 4 has geometric and algebraic multiplicity 3.
Will u please explain how $3$ leading ones give the existence of $3$ dependent solutions
â PureMathematics
Aug 29 at 6:28
The equations are $$x_1+x_2+x_3-x_6=0, x_4+x_6=0, x_5+x_6=0. $$Taking $x_2=r, x_3=s, x_6=t $ as parameters you get to express the solutions as $$x_1=-r-s+t, x_4=x_5=-t.$$ Having three parameters means that the solution space has dimension three. If you have trouble with linear systems, you won't be able to do much with eigenvalues.
â Martin Argerami
Aug 29 at 6:39
add a comment |Â
up vote
0
down vote
accepted
Since $M$ is symmetric, the geometric and algebraic multiplicity of its eigenvalues coincide.
If you finish your row reduction, you get
$$
beginbmatrix 1&1&1&1&1&1\1&1&1&1&1&1\1&1&1&1&1&1\1&1&1&0&1&0\1&1&1&1&0&0\1&1&1&0&0&-1endbmatrix
xrightarrow
beginbmatrix 1&1&1&0&0&-1\0&0&0&1&0&1\0&0&0&0&1&1\0&0&0&0&0&0\ 0&0&0&0&0&0\ 0&0&0&0&0&0endbmatrix
$$
As there are three leading ones, this shows that the set of solutions of $(M-4I)x=0$ has three dependent solutions, and three independent. Thus $dim ker(M-4I)=3$. This means that the eigenvalue 4 has geometric and algebraic multiplicity 3.
Will u please explain how $3$ leading ones give the existence of $3$ dependent solutions
â PureMathematics
Aug 29 at 6:28
The equations are $$x_1+x_2+x_3-x_6=0, x_4+x_6=0, x_5+x_6=0. $$Taking $x_2=r, x_3=s, x_6=t $ as parameters you get to express the solutions as $$x_1=-r-s+t, x_4=x_5=-t.$$ Having three parameters means that the solution space has dimension three. If you have trouble with linear systems, you won't be able to do much with eigenvalues.
â Martin Argerami
Aug 29 at 6:39
add a comment |Â
up vote
0
down vote
accepted
up vote
0
down vote
accepted
Since $M$ is symmetric, the geometric and algebraic multiplicity of its eigenvalues coincide.
If you finish your row reduction, you get
$$
beginbmatrix 1&1&1&1&1&1\1&1&1&1&1&1\1&1&1&1&1&1\1&1&1&0&1&0\1&1&1&1&0&0\1&1&1&0&0&-1endbmatrix
xrightarrow
beginbmatrix 1&1&1&0&0&-1\0&0&0&1&0&1\0&0&0&0&1&1\0&0&0&0&0&0\ 0&0&0&0&0&0\ 0&0&0&0&0&0endbmatrix
$$
As there are three leading ones, this shows that the set of solutions of $(M-4I)x=0$ has three dependent solutions, and three independent. Thus $dim ker(M-4I)=3$. This means that the eigenvalue 4 has geometric and algebraic multiplicity 3.
Since $M$ is symmetric, the geometric and algebraic multiplicity of its eigenvalues coincide.
If you finish your row reduction, you get
$$
beginbmatrix 1&1&1&1&1&1\1&1&1&1&1&1\1&1&1&1&1&1\1&1&1&0&1&0\1&1&1&1&0&0\1&1&1&0&0&-1endbmatrix
xrightarrow
beginbmatrix 1&1&1&0&0&-1\0&0&0&1&0&1\0&0&0&0&1&1\0&0&0&0&0&0\ 0&0&0&0&0&0\ 0&0&0&0&0&0endbmatrix
$$
As there are three leading ones, this shows that the set of solutions of $(M-4I)x=0$ has three dependent solutions, and three independent. Thus $dim ker(M-4I)=3$. This means that the eigenvalue 4 has geometric and algebraic multiplicity 3.
answered Aug 29 at 6:16
Martin Argerami
117k1071165
117k1071165
Will u please explain how $3$ leading ones give the existence of $3$ dependent solutions
â PureMathematics
Aug 29 at 6:28
The equations are $$x_1+x_2+x_3-x_6=0, x_4+x_6=0, x_5+x_6=0. $$Taking $x_2=r, x_3=s, x_6=t $ as parameters you get to express the solutions as $$x_1=-r-s+t, x_4=x_5=-t.$$ Having three parameters means that the solution space has dimension three. If you have trouble with linear systems, you won't be able to do much with eigenvalues.
â Martin Argerami
Aug 29 at 6:39
add a comment |Â
Will u please explain how $3$ leading ones give the existence of $3$ dependent solutions
â PureMathematics
Aug 29 at 6:28
The equations are $$x_1+x_2+x_3-x_6=0, x_4+x_6=0, x_5+x_6=0. $$Taking $x_2=r, x_3=s, x_6=t $ as parameters you get to express the solutions as $$x_1=-r-s+t, x_4=x_5=-t.$$ Having three parameters means that the solution space has dimension three. If you have trouble with linear systems, you won't be able to do much with eigenvalues.
â Martin Argerami
Aug 29 at 6:39
Will u please explain how $3$ leading ones give the existence of $3$ dependent solutions
â PureMathematics
Aug 29 at 6:28
Will u please explain how $3$ leading ones give the existence of $3$ dependent solutions
â PureMathematics
Aug 29 at 6:28
The equations are $$x_1+x_2+x_3-x_6=0, x_4+x_6=0, x_5+x_6=0. $$Taking $x_2=r, x_3=s, x_6=t $ as parameters you get to express the solutions as $$x_1=-r-s+t, x_4=x_5=-t.$$ Having three parameters means that the solution space has dimension three. If you have trouble with linear systems, you won't be able to do much with eigenvalues.
â Martin Argerami
Aug 29 at 6:39
The equations are $$x_1+x_2+x_3-x_6=0, x_4+x_6=0, x_5+x_6=0. $$Taking $x_2=r, x_3=s, x_6=t $ as parameters you get to express the solutions as $$x_1=-r-s+t, x_4=x_5=-t.$$ Having three parameters means that the solution space has dimension three. If you have trouble with linear systems, you won't be able to do much with eigenvalues.
â Martin Argerami
Aug 29 at 6:39
add a comment |Â
up vote
0
down vote
If it only had multiplicity $2$, $M-4I$ would have rank $4$, i.e. four of its rows would be linearly independent. Since the top three rows are the same, that would have to be the last four rows. But $(row 3) - (row 4) - (row 5) + (row 6) = 0$, so they are linearly dependent.
Sir will you please go through my edits I did in the question,it will help me a lot
â PureMathematics
Aug 29 at 6:14
add a comment |Â
up vote
0
down vote
If it only had multiplicity $2$, $M-4I$ would have rank $4$, i.e. four of its rows would be linearly independent. Since the top three rows are the same, that would have to be the last four rows. But $(row 3) - (row 4) - (row 5) + (row 6) = 0$, so they are linearly dependent.
Sir will you please go through my edits I did in the question,it will help me a lot
â PureMathematics
Aug 29 at 6:14
add a comment |Â
up vote
0
down vote
up vote
0
down vote
If it only had multiplicity $2$, $M-4I$ would have rank $4$, i.e. four of its rows would be linearly independent. Since the top three rows are the same, that would have to be the last four rows. But $(row 3) - (row 4) - (row 5) + (row 6) = 0$, so they are linearly dependent.
If it only had multiplicity $2$, $M-4I$ would have rank $4$, i.e. four of its rows would be linearly independent. Since the top three rows are the same, that would have to be the last four rows. But $(row 3) - (row 4) - (row 5) + (row 6) = 0$, so they are linearly dependent.
answered Aug 29 at 6:03
Robert Israel
306k22201443
306k22201443
Sir will you please go through my edits I did in the question,it will help me a lot
â PureMathematics
Aug 29 at 6:14
add a comment |Â
Sir will you please go through my edits I did in the question,it will help me a lot
â PureMathematics
Aug 29 at 6:14
Sir will you please go through my edits I did in the question,it will help me a lot
â PureMathematics
Aug 29 at 6:14
Sir will you please go through my edits I did in the question,it will help me a lot
â PureMathematics
Aug 29 at 6:14
add a comment |Â
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You esssentially need to find the column space of the matrix $M - 4I$ i.e. what is the dimension of the vector space which is spanned by the columns of the matrix $M - 4I$. Look at the columns of $M-4I$, and try to see why the dimension is $3$. You have two rows of zeros, which is very good, but you can go one dimension better. The below answers will serve as hints. Now, by the rank nullity theorem, the kernel dimension is the space dimension minus the rank, which is $6 - 3 = 3$.
â Ã°ÃÂÃÂþý òÃÂûûð þûþàüÃÂûûñÃÂÃÂó
Aug 29 at 6:47