Characteristic polynomial modulo 12
up vote
4
down vote
favorite
Consider the vector space $V =left{a_0+a_1x+cdots+a_{11}x^{11},;a_iinmathbb{R}right}$. Define a linear operator $A$ on $V$ by $A(x^i) = x^{i+4}$ where $i + 4$ is taken modulo $12$.
Find $(a)$ the minimal polynomial of $A$ and $(b)$ the characteristic polynomial of $A$.
My try:
I coulnot find another way so I tried the brute force method. $:$I found the matrix representation of the operator is $$A=begin{bmatrix} 0&0&0&0&0&0&0&0&1&0&0&0\0&0&0&0&0&0&0&0&0&1&0&0\0&0&0&0&0&0&0&0&0&0&1&0\0&0&0&0&0&0&0&0&0&0&0&1\1&0&0&0&0&0&0&0&0&0&0&0\0&1&0&0&0&0&0&0&0&0&0&0\0&0&1&0&0&0&0&0&0&0&0&0\0&0&0&1&0&0&0&0&0&0&0&0\0&0&0&0&1&0&0&0&0&0&0&0\0&0&0&0&0&1&0&0&0&0&0&0\0&0&0&0&0&0&1&0&0&0&0&0\0&0&0&0&0&0&0&1&0&0&0&0\end{bmatrix}.$$
The characteristic polynomial I found to be $lambda^{12}-4lambda^9+6lambda^6-4lambda^3+1$.$:$(It took me almost 40 minutes. $:$Is there another way to do this problem? Provide hints or suggestions please.
$rule{17cm}{1pt}$
Taking forward the answer provided by $textbf{Servaes}$ "The minimal polynomial of $A|_{U_i}$ is still $X^3−1$." Taking $U_1=span{x_1,x_5,x_9}$ we see $A(x)=x^5,:A^2(x)=x^9,:A^3(x)=ximplies (A^3-I)=0$ and since it factors into linear irredeucible factors, we have the minimal polynomial of $A|_{U_i}$ is $X^3−1$.
Completing the proof: We show that characteristic polynomial of $A$ is the product of characteristic polynomials of $A|_{U_i}$ where $V=oplus U_i$. We have seen that minimal polynomial of $A|_{U_i}$ is $X^3−1$ which is precisely the characteristic polynomial. So let $p_i(lambda)$ is characteristic polynomial corresponding to eigenvalue $lambda_i$ and invariant subspace $U_i$ and $p(lambda)$ is the characteristic polynomial of A. Then $displaystyle p(lambda_i)=0 :forall;i implies p_i(lambda)|p(lambda) :forall;i implies p(lambda)=prod_ip_i(lambda)$.
$Big($$p(lambda)$ is atleast $displaystyleprod_ip_i(lambda)$. If $existslambdaneqlambda_i forall: i$ such that $p(lambda)=0$ then $V$ is not $oplus U_i$ $Big)$
$rule{17cm}{1pt}$
Minimal polynomial : $X^3-1qquad$ Characteristic polynomial : $(X^3-1)^4$.
linear-algebra matrices minimal-polynomials
add a comment |
up vote
4
down vote
favorite
Consider the vector space $V =left{a_0+a_1x+cdots+a_{11}x^{11},;a_iinmathbb{R}right}$. Define a linear operator $A$ on $V$ by $A(x^i) = x^{i+4}$ where $i + 4$ is taken modulo $12$.
Find $(a)$ the minimal polynomial of $A$ and $(b)$ the characteristic polynomial of $A$.
My try:
I coulnot find another way so I tried the brute force method. $:$I found the matrix representation of the operator is $$A=begin{bmatrix} 0&0&0&0&0&0&0&0&1&0&0&0\0&0&0&0&0&0&0&0&0&1&0&0\0&0&0&0&0&0&0&0&0&0&1&0\0&0&0&0&0&0&0&0&0&0&0&1\1&0&0&0&0&0&0&0&0&0&0&0\0&1&0&0&0&0&0&0&0&0&0&0\0&0&1&0&0&0&0&0&0&0&0&0\0&0&0&1&0&0&0&0&0&0&0&0\0&0&0&0&1&0&0&0&0&0&0&0\0&0&0&0&0&1&0&0&0&0&0&0\0&0&0&0&0&0&1&0&0&0&0&0\0&0&0&0&0&0&0&1&0&0&0&0\end{bmatrix}.$$
The characteristic polynomial I found to be $lambda^{12}-4lambda^9+6lambda^6-4lambda^3+1$.$:$(It took me almost 40 minutes. $:$Is there another way to do this problem? Provide hints or suggestions please.
$rule{17cm}{1pt}$
Taking forward the answer provided by $textbf{Servaes}$ "The minimal polynomial of $A|_{U_i}$ is still $X^3−1$." Taking $U_1=span{x_1,x_5,x_9}$ we see $A(x)=x^5,:A^2(x)=x^9,:A^3(x)=ximplies (A^3-I)=0$ and since it factors into linear irredeucible factors, we have the minimal polynomial of $A|_{U_i}$ is $X^3−1$.
Completing the proof: We show that characteristic polynomial of $A$ is the product of characteristic polynomials of $A|_{U_i}$ where $V=oplus U_i$. We have seen that minimal polynomial of $A|_{U_i}$ is $X^3−1$ which is precisely the characteristic polynomial. So let $p_i(lambda)$ is characteristic polynomial corresponding to eigenvalue $lambda_i$ and invariant subspace $U_i$ and $p(lambda)$ is the characteristic polynomial of A. Then $displaystyle p(lambda_i)=0 :forall;i implies p_i(lambda)|p(lambda) :forall;i implies p(lambda)=prod_ip_i(lambda)$.
$Big($$p(lambda)$ is atleast $displaystyleprod_ip_i(lambda)$. If $existslambdaneqlambda_i forall: i$ such that $p(lambda)=0$ then $V$ is not $oplus U_i$ $Big)$
$rule{17cm}{1pt}$
Minimal polynomial : $X^3-1qquad$ Characteristic polynomial : $(X^3-1)^4$.
linear-algebra matrices minimal-polynomials
add a comment |
up vote
4
down vote
favorite
up vote
4
down vote
favorite
Consider the vector space $V =left{a_0+a_1x+cdots+a_{11}x^{11},;a_iinmathbb{R}right}$. Define a linear operator $A$ on $V$ by $A(x^i) = x^{i+4}$ where $i + 4$ is taken modulo $12$.
Find $(a)$ the minimal polynomial of $A$ and $(b)$ the characteristic polynomial of $A$.
My try:
I coulnot find another way so I tried the brute force method. $:$I found the matrix representation of the operator is $$A=begin{bmatrix} 0&0&0&0&0&0&0&0&1&0&0&0\0&0&0&0&0&0&0&0&0&1&0&0\0&0&0&0&0&0&0&0&0&0&1&0\0&0&0&0&0&0&0&0&0&0&0&1\1&0&0&0&0&0&0&0&0&0&0&0\0&1&0&0&0&0&0&0&0&0&0&0\0&0&1&0&0&0&0&0&0&0&0&0\0&0&0&1&0&0&0&0&0&0&0&0\0&0&0&0&1&0&0&0&0&0&0&0\0&0&0&0&0&1&0&0&0&0&0&0\0&0&0&0&0&0&1&0&0&0&0&0\0&0&0&0&0&0&0&1&0&0&0&0\end{bmatrix}.$$
The characteristic polynomial I found to be $lambda^{12}-4lambda^9+6lambda^6-4lambda^3+1$.$:$(It took me almost 40 minutes. $:$Is there another way to do this problem? Provide hints or suggestions please.
$rule{17cm}{1pt}$
Taking forward the answer provided by $textbf{Servaes}$ "The minimal polynomial of $A|_{U_i}$ is still $X^3−1$." Taking $U_1=span{x_1,x_5,x_9}$ we see $A(x)=x^5,:A^2(x)=x^9,:A^3(x)=ximplies (A^3-I)=0$ and since it factors into linear irredeucible factors, we have the minimal polynomial of $A|_{U_i}$ is $X^3−1$.
Completing the proof: We show that characteristic polynomial of $A$ is the product of characteristic polynomials of $A|_{U_i}$ where $V=oplus U_i$. We have seen that minimal polynomial of $A|_{U_i}$ is $X^3−1$ which is precisely the characteristic polynomial. So let $p_i(lambda)$ is characteristic polynomial corresponding to eigenvalue $lambda_i$ and invariant subspace $U_i$ and $p(lambda)$ is the characteristic polynomial of A. Then $displaystyle p(lambda_i)=0 :forall;i implies p_i(lambda)|p(lambda) :forall;i implies p(lambda)=prod_ip_i(lambda)$.
$Big($$p(lambda)$ is atleast $displaystyleprod_ip_i(lambda)$. If $existslambdaneqlambda_i forall: i$ such that $p(lambda)=0$ then $V$ is not $oplus U_i$ $Big)$
$rule{17cm}{1pt}$
Minimal polynomial : $X^3-1qquad$ Characteristic polynomial : $(X^3-1)^4$.
linear-algebra matrices minimal-polynomials
Consider the vector space $V =left{a_0+a_1x+cdots+a_{11}x^{11},;a_iinmathbb{R}right}$. Define a linear operator $A$ on $V$ by $A(x^i) = x^{i+4}$ where $i + 4$ is taken modulo $12$.
Find $(a)$ the minimal polynomial of $A$ and $(b)$ the characteristic polynomial of $A$.
My try:
I coulnot find another way so I tried the brute force method. $:$I found the matrix representation of the operator is $$A=begin{bmatrix} 0&0&0&0&0&0&0&0&1&0&0&0\0&0&0&0&0&0&0&0&0&1&0&0\0&0&0&0&0&0&0&0&0&0&1&0\0&0&0&0&0&0&0&0&0&0&0&1\1&0&0&0&0&0&0&0&0&0&0&0\0&1&0&0&0&0&0&0&0&0&0&0\0&0&1&0&0&0&0&0&0&0&0&0\0&0&0&1&0&0&0&0&0&0&0&0\0&0&0&0&1&0&0&0&0&0&0&0\0&0&0&0&0&1&0&0&0&0&0&0\0&0&0&0&0&0&1&0&0&0&0&0\0&0&0&0&0&0&0&1&0&0&0&0\end{bmatrix}.$$
The characteristic polynomial I found to be $lambda^{12}-4lambda^9+6lambda^6-4lambda^3+1$.$:$(It took me almost 40 minutes. $:$Is there another way to do this problem? Provide hints or suggestions please.
$rule{17cm}{1pt}$
Taking forward the answer provided by $textbf{Servaes}$ "The minimal polynomial of $A|_{U_i}$ is still $X^3−1$." Taking $U_1=span{x_1,x_5,x_9}$ we see $A(x)=x^5,:A^2(x)=x^9,:A^3(x)=ximplies (A^3-I)=0$ and since it factors into linear irredeucible factors, we have the minimal polynomial of $A|_{U_i}$ is $X^3−1$.
Completing the proof: We show that characteristic polynomial of $A$ is the product of characteristic polynomials of $A|_{U_i}$ where $V=oplus U_i$. We have seen that minimal polynomial of $A|_{U_i}$ is $X^3−1$ which is precisely the characteristic polynomial. So let $p_i(lambda)$ is characteristic polynomial corresponding to eigenvalue $lambda_i$ and invariant subspace $U_i$ and $p(lambda)$ is the characteristic polynomial of A. Then $displaystyle p(lambda_i)=0 :forall;i implies p_i(lambda)|p(lambda) :forall;i implies p(lambda)=prod_ip_i(lambda)$.
$Big($$p(lambda)$ is atleast $displaystyleprod_ip_i(lambda)$. If $existslambdaneqlambda_i forall: i$ such that $p(lambda)=0$ then $V$ is not $oplus U_i$ $Big)$
$rule{17cm}{1pt}$
Minimal polynomial : $X^3-1qquad$ Characteristic polynomial : $(X^3-1)^4$.
linear-algebra matrices minimal-polynomials
linear-algebra matrices minimal-polynomials
edited Nov 17 at 8:24
asked Nov 16 at 17:00
Yadati Kiran
387113
387113
add a comment |
add a comment |
1 Answer
1
active
oldest
votes
up vote
4
down vote
accepted
It usually helps to find some nontrivial relation that the given operator satisfies. Clearly
$$A^3(x^i)=x^{i+12}=x^i,$$
for all $i$, so $A$ is a zero of $X^3-I$. This factors as
$$X^3-I=(X-I)(X^2+X+I),$$
which has no repeated factors, so this is the minimal polynomial of $A$. The characteristic polynomial has the same irreducible factors and has degree $12$, so the minimal polynomial equals
$$(X-I)^a(X^2+X+I)^b,$$
for some positive integers $a$ and $b$ satisfying $a+2b=12$.
Note that $a$ is the algebraic multiplicity of the eigenvalue $1$, which is at least $4$ because
$$1+x^4+x^8,qquad x+x^5+x^9,qquad x^2+x^6+x^{10},qquad x^3+x^7+x^{11},$$
are four linearly independent eigenvectors with eigenvalue $1$. So $(a,b)$ is either $(4,4)$, $(6,3)$, $(8,2)$ or $(10,1)$.
The following is a bit contrived and implicitly assumes some slightly advanced ideas, but it is an (almost) computation-free way of determining the characteristic polynomial:
For $iin{1,2,3,4}$ let $U_i:=operatorname{span}(x^i,A(x^i),A^2(x^i))$. Then $U_icap U_j=0$ whenever $ineq j$, and the $U_i$ together span $V$ and are invariant under $A$. This yields a decomposition
$$V=U_1oplus U_2oplus U_3oplus U_4,$$
of $A$-invariant subspaces. The minimal polynomial of $Avert_{U_i}$ is still $X^3-1$ (verify this!), hence it is the characteristic polynomial of the restriction. The characteristic polynomial of $A$ is the product of the characteristic polynomials of the $Avert_{U_i}$, so it is $(X^3-1)^4$.
How did you determine the four independent eigenvectors?
– Yadati Kiran
Nov 16 at 17:23
2
Because $A$ acts so nicely on the $x^i$, it is not hard to construct eigenvectors; because for example $A(1)=x^4$ and $A(x^4)=x^8$ and $A(x^8)=1$, their sum is invariant under $A$.
– Servaes
Nov 16 at 17:25
1
I've added a method to compute the characteristic polynomial using similar ideas.
– Servaes
Nov 16 at 17:36
Now I get it! Thanks.
– Yadati Kiran
Nov 16 at 17:42
1
I was initially tried using invariant subspaces. But could not accurately define the linearly independent vectors. Now I understood.
– Yadati Kiran
Nov 16 at 17:44
|
show 1 more comment
1 Answer
1
active
oldest
votes
1 Answer
1
active
oldest
votes
active
oldest
votes
active
oldest
votes
up vote
4
down vote
accepted
It usually helps to find some nontrivial relation that the given operator satisfies. Clearly
$$A^3(x^i)=x^{i+12}=x^i,$$
for all $i$, so $A$ is a zero of $X^3-I$. This factors as
$$X^3-I=(X-I)(X^2+X+I),$$
which has no repeated factors, so this is the minimal polynomial of $A$. The characteristic polynomial has the same irreducible factors and has degree $12$, so the minimal polynomial equals
$$(X-I)^a(X^2+X+I)^b,$$
for some positive integers $a$ and $b$ satisfying $a+2b=12$.
Note that $a$ is the algebraic multiplicity of the eigenvalue $1$, which is at least $4$ because
$$1+x^4+x^8,qquad x+x^5+x^9,qquad x^2+x^6+x^{10},qquad x^3+x^7+x^{11},$$
are four linearly independent eigenvectors with eigenvalue $1$. So $(a,b)$ is either $(4,4)$, $(6,3)$, $(8,2)$ or $(10,1)$.
The following is a bit contrived and implicitly assumes some slightly advanced ideas, but it is an (almost) computation-free way of determining the characteristic polynomial:
For $iin{1,2,3,4}$ let $U_i:=operatorname{span}(x^i,A(x^i),A^2(x^i))$. Then $U_icap U_j=0$ whenever $ineq j$, and the $U_i$ together span $V$ and are invariant under $A$. This yields a decomposition
$$V=U_1oplus U_2oplus U_3oplus U_4,$$
of $A$-invariant subspaces. The minimal polynomial of $Avert_{U_i}$ is still $X^3-1$ (verify this!), hence it is the characteristic polynomial of the restriction. The characteristic polynomial of $A$ is the product of the characteristic polynomials of the $Avert_{U_i}$, so it is $(X^3-1)^4$.
How did you determine the four independent eigenvectors?
– Yadati Kiran
Nov 16 at 17:23
2
Because $A$ acts so nicely on the $x^i$, it is not hard to construct eigenvectors; because for example $A(1)=x^4$ and $A(x^4)=x^8$ and $A(x^8)=1$, their sum is invariant under $A$.
– Servaes
Nov 16 at 17:25
1
I've added a method to compute the characteristic polynomial using similar ideas.
– Servaes
Nov 16 at 17:36
Now I get it! Thanks.
– Yadati Kiran
Nov 16 at 17:42
1
I was initially tried using invariant subspaces. But could not accurately define the linearly independent vectors. Now I understood.
– Yadati Kiran
Nov 16 at 17:44
|
show 1 more comment
up vote
4
down vote
accepted
It usually helps to find some nontrivial relation that the given operator satisfies. Clearly
$$A^3(x^i)=x^{i+12}=x^i,$$
for all $i$, so $A$ is a zero of $X^3-I$. This factors as
$$X^3-I=(X-I)(X^2+X+I),$$
which has no repeated factors, so this is the minimal polynomial of $A$. The characteristic polynomial has the same irreducible factors and has degree $12$, so the minimal polynomial equals
$$(X-I)^a(X^2+X+I)^b,$$
for some positive integers $a$ and $b$ satisfying $a+2b=12$.
Note that $a$ is the algebraic multiplicity of the eigenvalue $1$, which is at least $4$ because
$$1+x^4+x^8,qquad x+x^5+x^9,qquad x^2+x^6+x^{10},qquad x^3+x^7+x^{11},$$
are four linearly independent eigenvectors with eigenvalue $1$. So $(a,b)$ is either $(4,4)$, $(6,3)$, $(8,2)$ or $(10,1)$.
The following is a bit contrived and implicitly assumes some slightly advanced ideas, but it is an (almost) computation-free way of determining the characteristic polynomial:
For $iin{1,2,3,4}$ let $U_i:=operatorname{span}(x^i,A(x^i),A^2(x^i))$. Then $U_icap U_j=0$ whenever $ineq j$, and the $U_i$ together span $V$ and are invariant under $A$. This yields a decomposition
$$V=U_1oplus U_2oplus U_3oplus U_4,$$
of $A$-invariant subspaces. The minimal polynomial of $Avert_{U_i}$ is still $X^3-1$ (verify this!), hence it is the characteristic polynomial of the restriction. The characteristic polynomial of $A$ is the product of the characteristic polynomials of the $Avert_{U_i}$, so it is $(X^3-1)^4$.
How did you determine the four independent eigenvectors?
– Yadati Kiran
Nov 16 at 17:23
2
Because $A$ acts so nicely on the $x^i$, it is not hard to construct eigenvectors; because for example $A(1)=x^4$ and $A(x^4)=x^8$ and $A(x^8)=1$, their sum is invariant under $A$.
– Servaes
Nov 16 at 17:25
1
I've added a method to compute the characteristic polynomial using similar ideas.
– Servaes
Nov 16 at 17:36
Now I get it! Thanks.
– Yadati Kiran
Nov 16 at 17:42
1
I was initially tried using invariant subspaces. But could not accurately define the linearly independent vectors. Now I understood.
– Yadati Kiran
Nov 16 at 17:44
|
show 1 more comment
up vote
4
down vote
accepted
up vote
4
down vote
accepted
It usually helps to find some nontrivial relation that the given operator satisfies. Clearly
$$A^3(x^i)=x^{i+12}=x^i,$$
for all $i$, so $A$ is a zero of $X^3-I$. This factors as
$$X^3-I=(X-I)(X^2+X+I),$$
which has no repeated factors, so this is the minimal polynomial of $A$. The characteristic polynomial has the same irreducible factors and has degree $12$, so the minimal polynomial equals
$$(X-I)^a(X^2+X+I)^b,$$
for some positive integers $a$ and $b$ satisfying $a+2b=12$.
Note that $a$ is the algebraic multiplicity of the eigenvalue $1$, which is at least $4$ because
$$1+x^4+x^8,qquad x+x^5+x^9,qquad x^2+x^6+x^{10},qquad x^3+x^7+x^{11},$$
are four linearly independent eigenvectors with eigenvalue $1$. So $(a,b)$ is either $(4,4)$, $(6,3)$, $(8,2)$ or $(10,1)$.
The following is a bit contrived and implicitly assumes some slightly advanced ideas, but it is an (almost) computation-free way of determining the characteristic polynomial:
For $iin{1,2,3,4}$ let $U_i:=operatorname{span}(x^i,A(x^i),A^2(x^i))$. Then $U_icap U_j=0$ whenever $ineq j$, and the $U_i$ together span $V$ and are invariant under $A$. This yields a decomposition
$$V=U_1oplus U_2oplus U_3oplus U_4,$$
of $A$-invariant subspaces. The minimal polynomial of $Avert_{U_i}$ is still $X^3-1$ (verify this!), hence it is the characteristic polynomial of the restriction. The characteristic polynomial of $A$ is the product of the characteristic polynomials of the $Avert_{U_i}$, so it is $(X^3-1)^4$.
It usually helps to find some nontrivial relation that the given operator satisfies. Clearly
$$A^3(x^i)=x^{i+12}=x^i,$$
for all $i$, so $A$ is a zero of $X^3-I$. This factors as
$$X^3-I=(X-I)(X^2+X+I),$$
which has no repeated factors, so this is the minimal polynomial of $A$. The characteristic polynomial has the same irreducible factors and has degree $12$, so the minimal polynomial equals
$$(X-I)^a(X^2+X+I)^b,$$
for some positive integers $a$ and $b$ satisfying $a+2b=12$.
Note that $a$ is the algebraic multiplicity of the eigenvalue $1$, which is at least $4$ because
$$1+x^4+x^8,qquad x+x^5+x^9,qquad x^2+x^6+x^{10},qquad x^3+x^7+x^{11},$$
are four linearly independent eigenvectors with eigenvalue $1$. So $(a,b)$ is either $(4,4)$, $(6,3)$, $(8,2)$ or $(10,1)$.
The following is a bit contrived and implicitly assumes some slightly advanced ideas, but it is an (almost) computation-free way of determining the characteristic polynomial:
For $iin{1,2,3,4}$ let $U_i:=operatorname{span}(x^i,A(x^i),A^2(x^i))$. Then $U_icap U_j=0$ whenever $ineq j$, and the $U_i$ together span $V$ and are invariant under $A$. This yields a decomposition
$$V=U_1oplus U_2oplus U_3oplus U_4,$$
of $A$-invariant subspaces. The minimal polynomial of $Avert_{U_i}$ is still $X^3-1$ (verify this!), hence it is the characteristic polynomial of the restriction. The characteristic polynomial of $A$ is the product of the characteristic polynomials of the $Avert_{U_i}$, so it is $(X^3-1)^4$.
edited Nov 16 at 17:43
answered Nov 16 at 17:03
Servaes
20.6k33789
20.6k33789
How did you determine the four independent eigenvectors?
– Yadati Kiran
Nov 16 at 17:23
2
Because $A$ acts so nicely on the $x^i$, it is not hard to construct eigenvectors; because for example $A(1)=x^4$ and $A(x^4)=x^8$ and $A(x^8)=1$, their sum is invariant under $A$.
– Servaes
Nov 16 at 17:25
1
I've added a method to compute the characteristic polynomial using similar ideas.
– Servaes
Nov 16 at 17:36
Now I get it! Thanks.
– Yadati Kiran
Nov 16 at 17:42
1
I was initially tried using invariant subspaces. But could not accurately define the linearly independent vectors. Now I understood.
– Yadati Kiran
Nov 16 at 17:44
|
show 1 more comment
How did you determine the four independent eigenvectors?
– Yadati Kiran
Nov 16 at 17:23
2
Because $A$ acts so nicely on the $x^i$, it is not hard to construct eigenvectors; because for example $A(1)=x^4$ and $A(x^4)=x^8$ and $A(x^8)=1$, their sum is invariant under $A$.
– Servaes
Nov 16 at 17:25
1
I've added a method to compute the characteristic polynomial using similar ideas.
– Servaes
Nov 16 at 17:36
Now I get it! Thanks.
– Yadati Kiran
Nov 16 at 17:42
1
I was initially tried using invariant subspaces. But could not accurately define the linearly independent vectors. Now I understood.
– Yadati Kiran
Nov 16 at 17:44
How did you determine the four independent eigenvectors?
– Yadati Kiran
Nov 16 at 17:23
How did you determine the four independent eigenvectors?
– Yadati Kiran
Nov 16 at 17:23
2
2
Because $A$ acts so nicely on the $x^i$, it is not hard to construct eigenvectors; because for example $A(1)=x^4$ and $A(x^4)=x^8$ and $A(x^8)=1$, their sum is invariant under $A$.
– Servaes
Nov 16 at 17:25
Because $A$ acts so nicely on the $x^i$, it is not hard to construct eigenvectors; because for example $A(1)=x^4$ and $A(x^4)=x^8$ and $A(x^8)=1$, their sum is invariant under $A$.
– Servaes
Nov 16 at 17:25
1
1
I've added a method to compute the characteristic polynomial using similar ideas.
– Servaes
Nov 16 at 17:36
I've added a method to compute the characteristic polynomial using similar ideas.
– Servaes
Nov 16 at 17:36
Now I get it! Thanks.
– Yadati Kiran
Nov 16 at 17:42
Now I get it! Thanks.
– Yadati Kiran
Nov 16 at 17:42
1
1
I was initially tried using invariant subspaces. But could not accurately define the linearly independent vectors. Now I understood.
– Yadati Kiran
Nov 16 at 17:44
I was initially tried using invariant subspaces. But could not accurately define the linearly independent vectors. Now I understood.
– Yadati Kiran
Nov 16 at 17:44
|
show 1 more comment
Sign up or log in
StackExchange.ready(function () {
StackExchange.helpers.onClickDraftSave('#login-link');
});
Sign up using Google
Sign up using Facebook
Sign up using Email and Password
Post as a guest
Required, but never shown
StackExchange.ready(
function () {
StackExchange.openid.initPostLogin('.new-post-login', 'https%3a%2f%2fmath.stackexchange.com%2fquestions%2f3001368%2fcharacteristic-polynomial-modulo-12%23new-answer', 'question_page');
}
);
Post as a guest
Required, but never shown
Sign up or log in
StackExchange.ready(function () {
StackExchange.helpers.onClickDraftSave('#login-link');
});
Sign up using Google
Sign up using Facebook
Sign up using Email and Password
Post as a guest
Required, but never shown
Sign up or log in
StackExchange.ready(function () {
StackExchange.helpers.onClickDraftSave('#login-link');
});
Sign up using Google
Sign up using Facebook
Sign up using Email and Password
Post as a guest
Required, but never shown
Sign up or log in
StackExchange.ready(function () {
StackExchange.helpers.onClickDraftSave('#login-link');
});
Sign up using Google
Sign up using Facebook
Sign up using Email and Password
Sign up using Google
Sign up using Facebook
Sign up using Email and Password
Post as a guest
Required, but never shown
Required, but never shown
Required, but never shown
Required, but never shown
Required, but never shown
Required, but never shown
Required, but never shown
Required, but never shown
Required, but never shown