Problem related to find dimension of a subspace

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I am studying linear algebra.
I found this exercise
Let V be a subspace of all n X n square matrices such that every nonzero element of V is invertible. Show that V is atmost n dimensional. Also prove that if n is odd then dimV =1.
I am unable to approach that exactly which type of matrices will be there in V?
linear-algebra matrix-analysis
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up vote
1
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I am studying linear algebra.
I found this exercise
Let V be a subspace of all n X n square matrices such that every nonzero element of V is invertible. Show that V is atmost n dimensional. Also prove that if n is odd then dimV =1.
I am unable to approach that exactly which type of matrices will be there in V?
linear-algebra matrix-analysis
1
Closely related to math.stackexchange.com/q/66877/265466, from the handy list at right.
â amd
Aug 22 at 3:13
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up vote
1
down vote
favorite
up vote
1
down vote
favorite
I am studying linear algebra.
I found this exercise
Let V be a subspace of all n X n square matrices such that every nonzero element of V is invertible. Show that V is atmost n dimensional. Also prove that if n is odd then dimV =1.
I am unable to approach that exactly which type of matrices will be there in V?
linear-algebra matrix-analysis
I am studying linear algebra.
I found this exercise
Let V be a subspace of all n X n square matrices such that every nonzero element of V is invertible. Show that V is atmost n dimensional. Also prove that if n is odd then dimV =1.
I am unable to approach that exactly which type of matrices will be there in V?
linear-algebra matrix-analysis
asked Aug 22 at 2:59
Prakash Nainwal
265
265
1
Closely related to math.stackexchange.com/q/66877/265466, from the handy list at right.
â amd
Aug 22 at 3:13
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Closely related to math.stackexchange.com/q/66877/265466, from the handy list at right.
â amd
Aug 22 at 3:13
1
1
Closely related to math.stackexchange.com/q/66877/265466, from the handy list at right.
â amd
Aug 22 at 3:13
Closely related to math.stackexchange.com/q/66877/265466, from the handy list at right.
â amd
Aug 22 at 3:13
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1 Answer
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Assume that $K$ is the base field. Let $m:=dim_K(V)$ and denote by $leftA_1,A_2,ldots,A_mright$ a basis of $V$. Note that the first columns of the matrices $A_i$'s must be linearly independent; otherwise, there are scalars $a_1,a_2,ldots,a_m$, not all being zero, such that the first column of $sumlimits_i=1^m,a_iA_i$ is zero. Since all nonzero elements of $V$ are invertible, we must have
$$sumlimits_i=1^m,a_iA_i=0,,$$ which contradicts the assumption that the $A_i$'s form a basis of $V$. As the first columns of the matrices $A_i$'s are linearly independent elements of $K^n$, we conclude that $mleq n$.
If $n$ is odd and $K:=mathbbR$, then note that, for any two invertible matrices $A$ and $B$, there exists $lambdainmathbbR$ such that $A-lambda,B$ is singular. This is because $A^-1B$ has a real eigenvalue and we can take $lambda$ to be such an eigenvalue. This proves that $mleq 1$ when $n$ is odd and $K$ is the field of real numbers. The same argument also shows that, if $K$ is algebraically closed (and $n$ is an arbitrary positive integer), then $mleq 1$.
Thanks a lot. You have explained it nicely. May I ask you one more question which is not exactly related to this, of course, that if p(x) be a polynomial with real coefficients then how many matrices will be there which satisfies this polynomial? For example how many matrices satisfies x^3 =1?
â Prakash Nainwal
Aug 22 at 9:01
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1 Answer
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1 Answer
1
active
oldest
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active
oldest
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active
oldest
votes
up vote
1
down vote
Assume that $K$ is the base field. Let $m:=dim_K(V)$ and denote by $leftA_1,A_2,ldots,A_mright$ a basis of $V$. Note that the first columns of the matrices $A_i$'s must be linearly independent; otherwise, there are scalars $a_1,a_2,ldots,a_m$, not all being zero, such that the first column of $sumlimits_i=1^m,a_iA_i$ is zero. Since all nonzero elements of $V$ are invertible, we must have
$$sumlimits_i=1^m,a_iA_i=0,,$$ which contradicts the assumption that the $A_i$'s form a basis of $V$. As the first columns of the matrices $A_i$'s are linearly independent elements of $K^n$, we conclude that $mleq n$.
If $n$ is odd and $K:=mathbbR$, then note that, for any two invertible matrices $A$ and $B$, there exists $lambdainmathbbR$ such that $A-lambda,B$ is singular. This is because $A^-1B$ has a real eigenvalue and we can take $lambda$ to be such an eigenvalue. This proves that $mleq 1$ when $n$ is odd and $K$ is the field of real numbers. The same argument also shows that, if $K$ is algebraically closed (and $n$ is an arbitrary positive integer), then $mleq 1$.
Thanks a lot. You have explained it nicely. May I ask you one more question which is not exactly related to this, of course, that if p(x) be a polynomial with real coefficients then how many matrices will be there which satisfies this polynomial? For example how many matrices satisfies x^3 =1?
â Prakash Nainwal
Aug 22 at 9:01
add a comment |Â
up vote
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Assume that $K$ is the base field. Let $m:=dim_K(V)$ and denote by $leftA_1,A_2,ldots,A_mright$ a basis of $V$. Note that the first columns of the matrices $A_i$'s must be linearly independent; otherwise, there are scalars $a_1,a_2,ldots,a_m$, not all being zero, such that the first column of $sumlimits_i=1^m,a_iA_i$ is zero. Since all nonzero elements of $V$ are invertible, we must have
$$sumlimits_i=1^m,a_iA_i=0,,$$ which contradicts the assumption that the $A_i$'s form a basis of $V$. As the first columns of the matrices $A_i$'s are linearly independent elements of $K^n$, we conclude that $mleq n$.
If $n$ is odd and $K:=mathbbR$, then note that, for any two invertible matrices $A$ and $B$, there exists $lambdainmathbbR$ such that $A-lambda,B$ is singular. This is because $A^-1B$ has a real eigenvalue and we can take $lambda$ to be such an eigenvalue. This proves that $mleq 1$ when $n$ is odd and $K$ is the field of real numbers. The same argument also shows that, if $K$ is algebraically closed (and $n$ is an arbitrary positive integer), then $mleq 1$.
Thanks a lot. You have explained it nicely. May I ask you one more question which is not exactly related to this, of course, that if p(x) be a polynomial with real coefficients then how many matrices will be there which satisfies this polynomial? For example how many matrices satisfies x^3 =1?
â Prakash Nainwal
Aug 22 at 9:01
add a comment |Â
up vote
1
down vote
up vote
1
down vote
Assume that $K$ is the base field. Let $m:=dim_K(V)$ and denote by $leftA_1,A_2,ldots,A_mright$ a basis of $V$. Note that the first columns of the matrices $A_i$'s must be linearly independent; otherwise, there are scalars $a_1,a_2,ldots,a_m$, not all being zero, such that the first column of $sumlimits_i=1^m,a_iA_i$ is zero. Since all nonzero elements of $V$ are invertible, we must have
$$sumlimits_i=1^m,a_iA_i=0,,$$ which contradicts the assumption that the $A_i$'s form a basis of $V$. As the first columns of the matrices $A_i$'s are linearly independent elements of $K^n$, we conclude that $mleq n$.
If $n$ is odd and $K:=mathbbR$, then note that, for any two invertible matrices $A$ and $B$, there exists $lambdainmathbbR$ such that $A-lambda,B$ is singular. This is because $A^-1B$ has a real eigenvalue and we can take $lambda$ to be such an eigenvalue. This proves that $mleq 1$ when $n$ is odd and $K$ is the field of real numbers. The same argument also shows that, if $K$ is algebraically closed (and $n$ is an arbitrary positive integer), then $mleq 1$.
Assume that $K$ is the base field. Let $m:=dim_K(V)$ and denote by $leftA_1,A_2,ldots,A_mright$ a basis of $V$. Note that the first columns of the matrices $A_i$'s must be linearly independent; otherwise, there are scalars $a_1,a_2,ldots,a_m$, not all being zero, such that the first column of $sumlimits_i=1^m,a_iA_i$ is zero. Since all nonzero elements of $V$ are invertible, we must have
$$sumlimits_i=1^m,a_iA_i=0,,$$ which contradicts the assumption that the $A_i$'s form a basis of $V$. As the first columns of the matrices $A_i$'s are linearly independent elements of $K^n$, we conclude that $mleq n$.
If $n$ is odd and $K:=mathbbR$, then note that, for any two invertible matrices $A$ and $B$, there exists $lambdainmathbbR$ such that $A-lambda,B$ is singular. This is because $A^-1B$ has a real eigenvalue and we can take $lambda$ to be such an eigenvalue. This proves that $mleq 1$ when $n$ is odd and $K$ is the field of real numbers. The same argument also shows that, if $K$ is algebraically closed (and $n$ is an arbitrary positive integer), then $mleq 1$.
edited Aug 22 at 4:47
answered Aug 22 at 4:10
Batominovski
24.7k22881
24.7k22881
Thanks a lot. You have explained it nicely. May I ask you one more question which is not exactly related to this, of course, that if p(x) be a polynomial with real coefficients then how many matrices will be there which satisfies this polynomial? For example how many matrices satisfies x^3 =1?
â Prakash Nainwal
Aug 22 at 9:01
add a comment |Â
Thanks a lot. You have explained it nicely. May I ask you one more question which is not exactly related to this, of course, that if p(x) be a polynomial with real coefficients then how many matrices will be there which satisfies this polynomial? For example how many matrices satisfies x^3 =1?
â Prakash Nainwal
Aug 22 at 9:01
Thanks a lot. You have explained it nicely. May I ask you one more question which is not exactly related to this, of course, that if p(x) be a polynomial with real coefficients then how many matrices will be there which satisfies this polynomial? For example how many matrices satisfies x^3 =1?
â Prakash Nainwal
Aug 22 at 9:01
Thanks a lot. You have explained it nicely. May I ask you one more question which is not exactly related to this, of course, that if p(x) be a polynomial with real coefficients then how many matrices will be there which satisfies this polynomial? For example how many matrices satisfies x^3 =1?
â Prakash Nainwal
Aug 22 at 9:01
add a comment |Â
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1
Closely related to math.stackexchange.com/q/66877/265466, from the handy list at right.
â amd
Aug 22 at 3:13