Suppose square matrix $A$ is positive-definite and $B$ is similar to $A$. Is B positive-definite too?
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Suppose square matrix $A$ is positive-definite and $B$ is similar to $A$. Is B positive-definite too?
I know a square matrix $A$ is positive-definite equal that $A$ is congruent to identity matrix $E$, i.e there exists an invertible matrix $C$ such that $C'AC=E$. So every matrix congruent to a positive-definite matrix is positive-definite. But what it will behavior when it's similar to a positive-definite matrix. I suppose it may not be positive-definite. But I can't get a counterexample. I tried from the definition...
linear-algebra
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up vote
1
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favorite
Suppose square matrix $A$ is positive-definite and $B$ is similar to $A$. Is B positive-definite too?
I know a square matrix $A$ is positive-definite equal that $A$ is congruent to identity matrix $E$, i.e there exists an invertible matrix $C$ such that $C'AC=E$. So every matrix congruent to a positive-definite matrix is positive-definite. But what it will behavior when it's similar to a positive-definite matrix. I suppose it may not be positive-definite. But I can't get a counterexample. I tried from the definition...
linear-algebra
1
Hint: Positive definiteness is connected to the eigenvalues of a matrix and eigenvalues are preserved under similarity.
â Wraith1995
Aug 12 at 3:00
2
If you conjugate a symmetric matrix by a non-orthogonal matrix, chances are that you're not going to get a symmetric matrix back.
â Theo Bendit
Aug 12 at 3:12
In some definitions, symmetry is implicitly assume when one talks about a positive definite matrix. In other definitions, it is now.
â ulaff.net
Aug 12 at 3:27
add a comment |Â
up vote
1
down vote
favorite
up vote
1
down vote
favorite
Suppose square matrix $A$ is positive-definite and $B$ is similar to $A$. Is B positive-definite too?
I know a square matrix $A$ is positive-definite equal that $A$ is congruent to identity matrix $E$, i.e there exists an invertible matrix $C$ such that $C'AC=E$. So every matrix congruent to a positive-definite matrix is positive-definite. But what it will behavior when it's similar to a positive-definite matrix. I suppose it may not be positive-definite. But I can't get a counterexample. I tried from the definition...
linear-algebra
Suppose square matrix $A$ is positive-definite and $B$ is similar to $A$. Is B positive-definite too?
I know a square matrix $A$ is positive-definite equal that $A$ is congruent to identity matrix $E$, i.e there exists an invertible matrix $C$ such that $C'AC=E$. So every matrix congruent to a positive-definite matrix is positive-definite. But what it will behavior when it's similar to a positive-definite matrix. I suppose it may not be positive-definite. But I can't get a counterexample. I tried from the definition...
linear-algebra
asked Aug 12 at 2:41
Jaqen Chou
3377
3377
1
Hint: Positive definiteness is connected to the eigenvalues of a matrix and eigenvalues are preserved under similarity.
â Wraith1995
Aug 12 at 3:00
2
If you conjugate a symmetric matrix by a non-orthogonal matrix, chances are that you're not going to get a symmetric matrix back.
â Theo Bendit
Aug 12 at 3:12
In some definitions, symmetry is implicitly assume when one talks about a positive definite matrix. In other definitions, it is now.
â ulaff.net
Aug 12 at 3:27
add a comment |Â
1
Hint: Positive definiteness is connected to the eigenvalues of a matrix and eigenvalues are preserved under similarity.
â Wraith1995
Aug 12 at 3:00
2
If you conjugate a symmetric matrix by a non-orthogonal matrix, chances are that you're not going to get a symmetric matrix back.
â Theo Bendit
Aug 12 at 3:12
In some definitions, symmetry is implicitly assume when one talks about a positive definite matrix. In other definitions, it is now.
â ulaff.net
Aug 12 at 3:27
1
1
Hint: Positive definiteness is connected to the eigenvalues of a matrix and eigenvalues are preserved under similarity.
â Wraith1995
Aug 12 at 3:00
Hint: Positive definiteness is connected to the eigenvalues of a matrix and eigenvalues are preserved under similarity.
â Wraith1995
Aug 12 at 3:00
2
2
If you conjugate a symmetric matrix by a non-orthogonal matrix, chances are that you're not going to get a symmetric matrix back.
â Theo Bendit
Aug 12 at 3:12
If you conjugate a symmetric matrix by a non-orthogonal matrix, chances are that you're not going to get a symmetric matrix back.
â Theo Bendit
Aug 12 at 3:12
In some definitions, symmetry is implicitly assume when one talks about a positive definite matrix. In other definitions, it is now.
â ulaff.net
Aug 12 at 3:27
In some definitions, symmetry is implicitly assume when one talks about a positive definite matrix. In other definitions, it is now.
â ulaff.net
Aug 12 at 3:27
add a comment |Â
1 Answer
1
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oldest
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up vote
1
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I assume $B$ is also symmetric, which is for most of the sources a precondition to talk about positive-definiteness, etc.
Try using the fact that an $ntimes n$ symmetric matrix $A$ is positive-definite iff for every $n$-dimensional column vector $vneq 0$ it is true that
$$v^T! cdot A cdot v >0$$
(which makes sense, since this is a $1times 1$ matrix.)
Now, if $B$ is similar to $A$, being $A$ and $B$ both symmetric, there exists a matrix $Q$ such that
$$B=Q^Tcdot A cdot Q.quad (*)$$
So what can you say about
$$v^T! cdot B cdot v$$
for any $vneq0$?
Solution:
Since
$$v^T! cdot B cdot v=v^T! cdot Q^Tcdot Acdot Q cdot v=(Qv)^T! cdot Acdot (Qv),$$
and being $(Qv)$ a vector of dimension $n$, say $w$, because $A$ is positive-definite we have
$$v^T! cdot B cdot v=w^T!cdot Acdot w>0,$$
which proves $B$ is also positive-definite.
(*) It is a theorem that if $A$ is a symmetric (real valued) matrix, then there exists an orthogonal matrix $P$ and a diagonal matrix $D$ such that
$$A=P^T D P.$$
Since the same is valid for $B$, say
$$B=tilde P^T tilde D tilde P^,$$
and being $P^T=P^-1$ and also $D=tilde D$ (because $A$ and $B$ are similar), we have
$$B=tilde P^T P A P^T tilde P=(P^Ttilde P)^T A (P^T tilde P),$$
and the desired result follows if we name $Q=P^Ttilde P$.
How do you know such a matrix $Q$ exists?
â Robert Lewis
Aug 12 at 3:09
Similarity means $exists S mid B = S^-1AS$.
â Robert Lewis
Aug 12 at 3:11
How can we get $B=Q^TAQ$ by $B$ is similar to $A$. Shouldn't it is be $B=Q^-1AQ$?
â Jaqen Chou
Aug 12 at 3:12
1
I grant your argument if we assume $B^T = B$, so endorsed, +1; but I think you've added a assumption the OP may not have intended. Nevertheless, thanks for the explanation! Cheers!
â Robert Lewis
Aug 12 at 3:44
Maybe, but it turns out that symmetry is usually assumed to study definiteness of a squared matrix/quadratic form. While it is possible to define the usual positive/negative/indefinite notions even if the matrix is not symmetric, most of the theory needs symmetry: just to say something, if a matrix is not symmetric, you can't even be sure that it will be diagonalizable, or that its eigenvalues will be real numbers at all. =S
â Alejandro Nasif Salum
Aug 12 at 3:49
add a comment |Â
1 Answer
1
active
oldest
votes
1 Answer
1
active
oldest
votes
active
oldest
votes
active
oldest
votes
up vote
1
down vote
I assume $B$ is also symmetric, which is for most of the sources a precondition to talk about positive-definiteness, etc.
Try using the fact that an $ntimes n$ symmetric matrix $A$ is positive-definite iff for every $n$-dimensional column vector $vneq 0$ it is true that
$$v^T! cdot A cdot v >0$$
(which makes sense, since this is a $1times 1$ matrix.)
Now, if $B$ is similar to $A$, being $A$ and $B$ both symmetric, there exists a matrix $Q$ such that
$$B=Q^Tcdot A cdot Q.quad (*)$$
So what can you say about
$$v^T! cdot B cdot v$$
for any $vneq0$?
Solution:
Since
$$v^T! cdot B cdot v=v^T! cdot Q^Tcdot Acdot Q cdot v=(Qv)^T! cdot Acdot (Qv),$$
and being $(Qv)$ a vector of dimension $n$, say $w$, because $A$ is positive-definite we have
$$v^T! cdot B cdot v=w^T!cdot Acdot w>0,$$
which proves $B$ is also positive-definite.
(*) It is a theorem that if $A$ is a symmetric (real valued) matrix, then there exists an orthogonal matrix $P$ and a diagonal matrix $D$ such that
$$A=P^T D P.$$
Since the same is valid for $B$, say
$$B=tilde P^T tilde D tilde P^,$$
and being $P^T=P^-1$ and also $D=tilde D$ (because $A$ and $B$ are similar), we have
$$B=tilde P^T P A P^T tilde P=(P^Ttilde P)^T A (P^T tilde P),$$
and the desired result follows if we name $Q=P^Ttilde P$.
How do you know such a matrix $Q$ exists?
â Robert Lewis
Aug 12 at 3:09
Similarity means $exists S mid B = S^-1AS$.
â Robert Lewis
Aug 12 at 3:11
How can we get $B=Q^TAQ$ by $B$ is similar to $A$. Shouldn't it is be $B=Q^-1AQ$?
â Jaqen Chou
Aug 12 at 3:12
1
I grant your argument if we assume $B^T = B$, so endorsed, +1; but I think you've added a assumption the OP may not have intended. Nevertheless, thanks for the explanation! Cheers!
â Robert Lewis
Aug 12 at 3:44
Maybe, but it turns out that symmetry is usually assumed to study definiteness of a squared matrix/quadratic form. While it is possible to define the usual positive/negative/indefinite notions even if the matrix is not symmetric, most of the theory needs symmetry: just to say something, if a matrix is not symmetric, you can't even be sure that it will be diagonalizable, or that its eigenvalues will be real numbers at all. =S
â Alejandro Nasif Salum
Aug 12 at 3:49
add a comment |Â
up vote
1
down vote
I assume $B$ is also symmetric, which is for most of the sources a precondition to talk about positive-definiteness, etc.
Try using the fact that an $ntimes n$ symmetric matrix $A$ is positive-definite iff for every $n$-dimensional column vector $vneq 0$ it is true that
$$v^T! cdot A cdot v >0$$
(which makes sense, since this is a $1times 1$ matrix.)
Now, if $B$ is similar to $A$, being $A$ and $B$ both symmetric, there exists a matrix $Q$ such that
$$B=Q^Tcdot A cdot Q.quad (*)$$
So what can you say about
$$v^T! cdot B cdot v$$
for any $vneq0$?
Solution:
Since
$$v^T! cdot B cdot v=v^T! cdot Q^Tcdot Acdot Q cdot v=(Qv)^T! cdot Acdot (Qv),$$
and being $(Qv)$ a vector of dimension $n$, say $w$, because $A$ is positive-definite we have
$$v^T! cdot B cdot v=w^T!cdot Acdot w>0,$$
which proves $B$ is also positive-definite.
(*) It is a theorem that if $A$ is a symmetric (real valued) matrix, then there exists an orthogonal matrix $P$ and a diagonal matrix $D$ such that
$$A=P^T D P.$$
Since the same is valid for $B$, say
$$B=tilde P^T tilde D tilde P^,$$
and being $P^T=P^-1$ and also $D=tilde D$ (because $A$ and $B$ are similar), we have
$$B=tilde P^T P A P^T tilde P=(P^Ttilde P)^T A (P^T tilde P),$$
and the desired result follows if we name $Q=P^Ttilde P$.
How do you know such a matrix $Q$ exists?
â Robert Lewis
Aug 12 at 3:09
Similarity means $exists S mid B = S^-1AS$.
â Robert Lewis
Aug 12 at 3:11
How can we get $B=Q^TAQ$ by $B$ is similar to $A$. Shouldn't it is be $B=Q^-1AQ$?
â Jaqen Chou
Aug 12 at 3:12
1
I grant your argument if we assume $B^T = B$, so endorsed, +1; but I think you've added a assumption the OP may not have intended. Nevertheless, thanks for the explanation! Cheers!
â Robert Lewis
Aug 12 at 3:44
Maybe, but it turns out that symmetry is usually assumed to study definiteness of a squared matrix/quadratic form. While it is possible to define the usual positive/negative/indefinite notions even if the matrix is not symmetric, most of the theory needs symmetry: just to say something, if a matrix is not symmetric, you can't even be sure that it will be diagonalizable, or that its eigenvalues will be real numbers at all. =S
â Alejandro Nasif Salum
Aug 12 at 3:49
add a comment |Â
up vote
1
down vote
up vote
1
down vote
I assume $B$ is also symmetric, which is for most of the sources a precondition to talk about positive-definiteness, etc.
Try using the fact that an $ntimes n$ symmetric matrix $A$ is positive-definite iff for every $n$-dimensional column vector $vneq 0$ it is true that
$$v^T! cdot A cdot v >0$$
(which makes sense, since this is a $1times 1$ matrix.)
Now, if $B$ is similar to $A$, being $A$ and $B$ both symmetric, there exists a matrix $Q$ such that
$$B=Q^Tcdot A cdot Q.quad (*)$$
So what can you say about
$$v^T! cdot B cdot v$$
for any $vneq0$?
Solution:
Since
$$v^T! cdot B cdot v=v^T! cdot Q^Tcdot Acdot Q cdot v=(Qv)^T! cdot Acdot (Qv),$$
and being $(Qv)$ a vector of dimension $n$, say $w$, because $A$ is positive-definite we have
$$v^T! cdot B cdot v=w^T!cdot Acdot w>0,$$
which proves $B$ is also positive-definite.
(*) It is a theorem that if $A$ is a symmetric (real valued) matrix, then there exists an orthogonal matrix $P$ and a diagonal matrix $D$ such that
$$A=P^T D P.$$
Since the same is valid for $B$, say
$$B=tilde P^T tilde D tilde P^,$$
and being $P^T=P^-1$ and also $D=tilde D$ (because $A$ and $B$ are similar), we have
$$B=tilde P^T P A P^T tilde P=(P^Ttilde P)^T A (P^T tilde P),$$
and the desired result follows if we name $Q=P^Ttilde P$.
I assume $B$ is also symmetric, which is for most of the sources a precondition to talk about positive-definiteness, etc.
Try using the fact that an $ntimes n$ symmetric matrix $A$ is positive-definite iff for every $n$-dimensional column vector $vneq 0$ it is true that
$$v^T! cdot A cdot v >0$$
(which makes sense, since this is a $1times 1$ matrix.)
Now, if $B$ is similar to $A$, being $A$ and $B$ both symmetric, there exists a matrix $Q$ such that
$$B=Q^Tcdot A cdot Q.quad (*)$$
So what can you say about
$$v^T! cdot B cdot v$$
for any $vneq0$?
Solution:
Since
$$v^T! cdot B cdot v=v^T! cdot Q^Tcdot Acdot Q cdot v=(Qv)^T! cdot Acdot (Qv),$$
and being $(Qv)$ a vector of dimension $n$, say $w$, because $A$ is positive-definite we have
$$v^T! cdot B cdot v=w^T!cdot Acdot w>0,$$
which proves $B$ is also positive-definite.
(*) It is a theorem that if $A$ is a symmetric (real valued) matrix, then there exists an orthogonal matrix $P$ and a diagonal matrix $D$ such that
$$A=P^T D P.$$
Since the same is valid for $B$, say
$$B=tilde P^T tilde D tilde P^,$$
and being $P^T=P^-1$ and also $D=tilde D$ (because $A$ and $B$ are similar), we have
$$B=tilde P^T P A P^T tilde P=(P^Ttilde P)^T A (P^T tilde P),$$
and the desired result follows if we name $Q=P^Ttilde P$.
edited Aug 12 at 3:39
answered Aug 12 at 3:02
Alejandro Nasif Salum
3,10617
3,10617
How do you know such a matrix $Q$ exists?
â Robert Lewis
Aug 12 at 3:09
Similarity means $exists S mid B = S^-1AS$.
â Robert Lewis
Aug 12 at 3:11
How can we get $B=Q^TAQ$ by $B$ is similar to $A$. Shouldn't it is be $B=Q^-1AQ$?
â Jaqen Chou
Aug 12 at 3:12
1
I grant your argument if we assume $B^T = B$, so endorsed, +1; but I think you've added a assumption the OP may not have intended. Nevertheless, thanks for the explanation! Cheers!
â Robert Lewis
Aug 12 at 3:44
Maybe, but it turns out that symmetry is usually assumed to study definiteness of a squared matrix/quadratic form. While it is possible to define the usual positive/negative/indefinite notions even if the matrix is not symmetric, most of the theory needs symmetry: just to say something, if a matrix is not symmetric, you can't even be sure that it will be diagonalizable, or that its eigenvalues will be real numbers at all. =S
â Alejandro Nasif Salum
Aug 12 at 3:49
add a comment |Â
How do you know such a matrix $Q$ exists?
â Robert Lewis
Aug 12 at 3:09
Similarity means $exists S mid B = S^-1AS$.
â Robert Lewis
Aug 12 at 3:11
How can we get $B=Q^TAQ$ by $B$ is similar to $A$. Shouldn't it is be $B=Q^-1AQ$?
â Jaqen Chou
Aug 12 at 3:12
1
I grant your argument if we assume $B^T = B$, so endorsed, +1; but I think you've added a assumption the OP may not have intended. Nevertheless, thanks for the explanation! Cheers!
â Robert Lewis
Aug 12 at 3:44
Maybe, but it turns out that symmetry is usually assumed to study definiteness of a squared matrix/quadratic form. While it is possible to define the usual positive/negative/indefinite notions even if the matrix is not symmetric, most of the theory needs symmetry: just to say something, if a matrix is not symmetric, you can't even be sure that it will be diagonalizable, or that its eigenvalues will be real numbers at all. =S
â Alejandro Nasif Salum
Aug 12 at 3:49
How do you know such a matrix $Q$ exists?
â Robert Lewis
Aug 12 at 3:09
How do you know such a matrix $Q$ exists?
â Robert Lewis
Aug 12 at 3:09
Similarity means $exists S mid B = S^-1AS$.
â Robert Lewis
Aug 12 at 3:11
Similarity means $exists S mid B = S^-1AS$.
â Robert Lewis
Aug 12 at 3:11
How can we get $B=Q^TAQ$ by $B$ is similar to $A$. Shouldn't it is be $B=Q^-1AQ$?
â Jaqen Chou
Aug 12 at 3:12
How can we get $B=Q^TAQ$ by $B$ is similar to $A$. Shouldn't it is be $B=Q^-1AQ$?
â Jaqen Chou
Aug 12 at 3:12
1
1
I grant your argument if we assume $B^T = B$, so endorsed, +1; but I think you've added a assumption the OP may not have intended. Nevertheless, thanks for the explanation! Cheers!
â Robert Lewis
Aug 12 at 3:44
I grant your argument if we assume $B^T = B$, so endorsed, +1; but I think you've added a assumption the OP may not have intended. Nevertheless, thanks for the explanation! Cheers!
â Robert Lewis
Aug 12 at 3:44
Maybe, but it turns out that symmetry is usually assumed to study definiteness of a squared matrix/quadratic form. While it is possible to define the usual positive/negative/indefinite notions even if the matrix is not symmetric, most of the theory needs symmetry: just to say something, if a matrix is not symmetric, you can't even be sure that it will be diagonalizable, or that its eigenvalues will be real numbers at all. =S
â Alejandro Nasif Salum
Aug 12 at 3:49
Maybe, but it turns out that symmetry is usually assumed to study definiteness of a squared matrix/quadratic form. While it is possible to define the usual positive/negative/indefinite notions even if the matrix is not symmetric, most of the theory needs symmetry: just to say something, if a matrix is not symmetric, you can't even be sure that it will be diagonalizable, or that its eigenvalues will be real numbers at all. =S
â Alejandro Nasif Salum
Aug 12 at 3:49
add a comment |Â
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1
Hint: Positive definiteness is connected to the eigenvalues of a matrix and eigenvalues are preserved under similarity.
â Wraith1995
Aug 12 at 3:00
2
If you conjugate a symmetric matrix by a non-orthogonal matrix, chances are that you're not going to get a symmetric matrix back.
â Theo Bendit
Aug 12 at 3:12
In some definitions, symmetry is implicitly assume when one talks about a positive definite matrix. In other definitions, it is now.
â ulaff.net
Aug 12 at 3:27