Find real number $a$ such that matrix $A$ is NOT diagonalisable
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Consider the matrix:
$beginbmatrix2 & a & -1\0 & 2 & 1\-1 & 8 & -1endbmatrix$
Find all $a in mathbb R$ such that $A$ is not diagonalisable.
I've never thought of such a problem before. What is the systematic way to make a matrix non-diagonalisable?
linear-algebra matrices diagonalization
 |Â
show 10 more comments
up vote
9
down vote
favorite
Consider the matrix:
$beginbmatrix2 & a & -1\0 & 2 & 1\-1 & 8 & -1endbmatrix$
Find all $a in mathbb R$ such that $A$ is not diagonalisable.
I've never thought of such a problem before. What is the systematic way to make a matrix non-diagonalisable?
linear-algebra matrices diagonalization
2
A necessary conddition is an eigenvalue with multiplicity greater than $1$.
â Peter
Aug 7 at 19:56
4
What is the criterion for a matrix to be diagonalizable? Try to establish this in dependence of $a$.
â zzuussee
Aug 7 at 19:57
Just make the first row a linear combination of the others
â N74
Aug 7 at 20:06
2
The characteristic polynomial, if I'm not mistaken, is $-x^3+3x^2+9x-(22+a)$. Thus, for $-27<a<5$, this equation should on the first glimpse have three roots, i.e. three distinct eigenvalues and thus be diagonalizable for these values. As it is a cubic function, it always has at least one root in every case, i.e. there is always one eigenvalue at least. I don't know about the geometric multiplicities in these cases.
â zzuussee
Aug 7 at 20:39
1
Are we talking about diagonalization over the reals or over the complex numbers?
â Arnaud Mortier
Aug 7 at 22:22
 |Â
show 10 more comments
up vote
9
down vote
favorite
up vote
9
down vote
favorite
Consider the matrix:
$beginbmatrix2 & a & -1\0 & 2 & 1\-1 & 8 & -1endbmatrix$
Find all $a in mathbb R$ such that $A$ is not diagonalisable.
I've never thought of such a problem before. What is the systematic way to make a matrix non-diagonalisable?
linear-algebra matrices diagonalization
Consider the matrix:
$beginbmatrix2 & a & -1\0 & 2 & 1\-1 & 8 & -1endbmatrix$
Find all $a in mathbb R$ such that $A$ is not diagonalisable.
I've never thought of such a problem before. What is the systematic way to make a matrix non-diagonalisable?
linear-algebra matrices diagonalization
edited Aug 7 at 20:08
Andrei
7,5852822
7,5852822
asked Aug 7 at 19:55
David Hughes
1065
1065
2
A necessary conddition is an eigenvalue with multiplicity greater than $1$.
â Peter
Aug 7 at 19:56
4
What is the criterion for a matrix to be diagonalizable? Try to establish this in dependence of $a$.
â zzuussee
Aug 7 at 19:57
Just make the first row a linear combination of the others
â N74
Aug 7 at 20:06
2
The characteristic polynomial, if I'm not mistaken, is $-x^3+3x^2+9x-(22+a)$. Thus, for $-27<a<5$, this equation should on the first glimpse have three roots, i.e. three distinct eigenvalues and thus be diagonalizable for these values. As it is a cubic function, it always has at least one root in every case, i.e. there is always one eigenvalue at least. I don't know about the geometric multiplicities in these cases.
â zzuussee
Aug 7 at 20:39
1
Are we talking about diagonalization over the reals or over the complex numbers?
â Arnaud Mortier
Aug 7 at 22:22
 |Â
show 10 more comments
2
A necessary conddition is an eigenvalue with multiplicity greater than $1$.
â Peter
Aug 7 at 19:56
4
What is the criterion for a matrix to be diagonalizable? Try to establish this in dependence of $a$.
â zzuussee
Aug 7 at 19:57
Just make the first row a linear combination of the others
â N74
Aug 7 at 20:06
2
The characteristic polynomial, if I'm not mistaken, is $-x^3+3x^2+9x-(22+a)$. Thus, for $-27<a<5$, this equation should on the first glimpse have three roots, i.e. three distinct eigenvalues and thus be diagonalizable for these values. As it is a cubic function, it always has at least one root in every case, i.e. there is always one eigenvalue at least. I don't know about the geometric multiplicities in these cases.
â zzuussee
Aug 7 at 20:39
1
Are we talking about diagonalization over the reals or over the complex numbers?
â Arnaud Mortier
Aug 7 at 22:22
2
2
A necessary conddition is an eigenvalue with multiplicity greater than $1$.
â Peter
Aug 7 at 19:56
A necessary conddition is an eigenvalue with multiplicity greater than $1$.
â Peter
Aug 7 at 19:56
4
4
What is the criterion for a matrix to be diagonalizable? Try to establish this in dependence of $a$.
â zzuussee
Aug 7 at 19:57
What is the criterion for a matrix to be diagonalizable? Try to establish this in dependence of $a$.
â zzuussee
Aug 7 at 19:57
Just make the first row a linear combination of the others
â N74
Aug 7 at 20:06
Just make the first row a linear combination of the others
â N74
Aug 7 at 20:06
2
2
The characteristic polynomial, if I'm not mistaken, is $-x^3+3x^2+9x-(22+a)$. Thus, for $-27<a<5$, this equation should on the first glimpse have three roots, i.e. three distinct eigenvalues and thus be diagonalizable for these values. As it is a cubic function, it always has at least one root in every case, i.e. there is always one eigenvalue at least. I don't know about the geometric multiplicities in these cases.
â zzuussee
Aug 7 at 20:39
The characteristic polynomial, if I'm not mistaken, is $-x^3+3x^2+9x-(22+a)$. Thus, for $-27<a<5$, this equation should on the first glimpse have three roots, i.e. three distinct eigenvalues and thus be diagonalizable for these values. As it is a cubic function, it always has at least one root in every case, i.e. there is always one eigenvalue at least. I don't know about the geometric multiplicities in these cases.
â zzuussee
Aug 7 at 20:39
1
1
Are we talking about diagonalization over the reals or over the complex numbers?
â Arnaud Mortier
Aug 7 at 22:22
Are we talking about diagonalization over the reals or over the complex numbers?
â Arnaud Mortier
Aug 7 at 22:22
 |Â
show 10 more comments
3 Answers
3
active
oldest
votes
up vote
3
down vote
accepted
(These Linear Algebra course notes by Michael Stoll, 2007 provide good background to my following assertions. As does the Wikipedia page on characteristic polynomials.)
Use the following facts:
a) A matrix $M in mathrmMat(n,F)$ (where $n$ is the size of the matrix and $F$ is some field) is diagonalisable if and only if its minimal polynomial $m_M(x)$ is a product of distinct monic linear factors.
b) The characteristic polynomial of a matrix $M$ is defined as $p_M(x)=mathrmdet(xI-M)$
c) Matrices satisfy their own characteristic equations: $p_M(M)=0$ for all $M$. Hence a matrix's minimal polynomial always divides its characteristic polynomial: $m_M(x) , vert , p_M(x)$.
d) The discriminant of a cubic polynomial $ax^3+bx^2+cx+d$ is given by:
$$ Delta_3 = b^2c^2-4ac^3-4b^3d-27a^2d^2+18abcd$$
If $Delta_3>0$ then the equation as three distinct real roots. If $Delta_3=0$ then the equation has a repeated root and all its roots are real. If $Delta_3<0$ then the equation has just one real root.
For your matrix,
$$ A:= left( beginmatrix2 & a & -1\0 & 2 & 1\-1 & 8 & -1endmatrix right) $$
we have that
$$
beginalign
p_A(x) &= mathrmdet left( beginmatrix x-2 & -a & 1\0 & x-2 & -1\1 & -8 & x+1endmatrix right)
\
\ &= (x-2)((x-2)(x+1)-8) + (a - (x-2))
\ &= x^3 -3x^2-9x+22+a
endalign
$$
With some calculation, the discriminant of $p_A$ is equal to $$Delta_3 = -27(a-5)(a+27)$$
Firstly,
$$Delta_3>0 iff -27<a<5$$
In this case, $p_A$ has three distinct real roots then it will factorise into three distinct linear factors. Hence $m_A(x)$ will also factorise into distinct linear factors and $A$ will be diagonalisable.
So $-27<a<5$ implies that $A$ is diagonalisable.
Secondly,
$$Delta_3=0 iff a in -27,5$$
If $a=-27$ then
$$ A:= left( beginmatrix2 & a & -1\0 & 2 & 1\-1 & 8 & -1endmatrix right) $$
and this matrix can be checked to have a maximum of two linearly independent eigenvectors
$$ v_1:= left( beginmatrix-10\1\3endmatrix right) qquad v_2:= left( beginmatrix-8\-1\3endmatrix right)$$
and so $A$ is not diagonalisable. (We could also consider the Jordan Form of $A$ as calculated by @WillJagy in their answer to this question.)
Similarly for $a=5$, $A$ turns out to not be diagonalisable.
Thirdly,
$$Delta_3<0 iff a in (-infty , -27) cup (5, infty )$$
In this case $p_A(x)=(x- lambda )(x^2+ beta x + gamma )$ where $lambda$ , $beta$ and $gamma$ are real and $(x^2+ beta x + gamma )$ cannot be factorised over the reals. Since $m_A$ divides $p_A$ we have three options:
$$ beginalign
mathrm(i) qquad & m_A(x)=(x- lambda )
\mathrm(ii) qquad & m_A(x)=(x^2+ beta x + gamma )
\mathrm(iii) qquad & m_A(x)=(x- lambda )(x^2+ beta x + gamma )
endalign$$
It is obvious that $(A-lambda I )$ is not equal to $0$ for any $lambda$ so we can rule out option $mathrm(i)$. But in both of the options $mathrm(ii)$ and $mathrm(iii)$, $m_A$ is not a product of distinct monic linear factors and hence $A$ is not diagonalisable.
Therefore:
$A$ is not diagonalisable over $mathbbR$ if and only if $a in (-infty , -27] cup [5, infty )$
Edit: diagonalisability over $mathbbC$
Even if working in $mathbbC$, the cases $Delta_3>0$ and $Delta_3=0$ above remain exactly the same: in these cases the characteristic polynomial has no complex roots.
However, $Delta_3<0$ now gives us that $p_A$ can be factorised into three distinct linear factors in $mathbbC[x]$. Hence $m_A(x)$ will also factorise into distinct linear factors in $mathbbC[x]$ and $A$ will be diagonalisable.
Hence $A$ is not diagonalisable over $mathbbC$ if and only if $a in -27,5$.
In general, for $A in mathrmMat(n,mathbbC)$, if the discriminant of $p_A$ is not equal to $0$ then $p_A$ has no repeated roots and $A$ will be diagonalisable over $mathbbC$. If the discriminant of $p_A$ is equal to $0$ then check the eigenvectors of $A$ (or form the Jordan Form of $A$) in order to check individual cases of diagonalisability.
1
a matrix can be diagionalizable even if it has repeated eigenvalues. Take $diag(1,1,1)$ for example.
â dezdichado
Aug 7 at 21:34
As it happens, nontrivial Jordan form occurs for both endpoints, $a=5$ and $a=-27$
â Will Jagy
Aug 8 at 0:55
Perfect answer. Thank you so much
â David Hughes
Aug 9 at 18:54
add a comment |Â
up vote
2
down vote
Addendum. I have been slow on one point; if $a$ lies outside a certain range, then there must be complex eigenvalues, that is, not real numbers. That is what the other answers and comments are emphasizing, that it might not be possible to diagonalize over the real numbers.
Another way for non-diagonal Jordan form is real but repeated (generalized) eigenvalues, where there is not a basis of eigenvectors. This is the aspect I address below.
ORIGINAL: The derivative of the characteristic polynomial is $3(x-3)(x+1).$ When $a=5,$ we do get the characteristic polynomial as a multiple of $(x-3)^2.$ When $a=-27,$ we get the characteristic polynomial as a multiple of $(x+1)^2.$ These lead to non-diagonal (but real) Jordan forms, see below.
=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=
With $a=5$ and
$$
left(
beginarrayccc
1&-9&5 \
1&27&5 \
-6&18&6 \
endarray
right)
left(
beginarrayccc
2&4&5 \
-1&1&0 \
5&1&1 \
endarray
right) =
left(
beginarrayccc
36&0&0 \
0&36&0 \
0&0&36 \
endarray
right)
$$
we get
$$
frac136 ;
left(
beginarrayccc
1&-9&5 \
1&27&5 \
-6&18&6 \
endarray
right)
left(
beginarrayccc
2&5&-1 \
0&2&1 \
-1&0&-1 \
endarray
right)
left(
beginarrayccc
2&4&5 \
-1&1&0 \
5&1&1 \
endarray
right) =
left(
beginarrayccc
-3&0&0 \
0&3&1 \
0&0&3 \
endarray
right)
$$
The final version is called Jordan Normal Form. In the U.S. it is taught with the nilpotent part above the diagonal. In some countries, for example Uruguay, it is taught with any extra $1$s below the diagonal.
Actually using the Jordan form for something merely requires writing out
$$
frac136 ;
left(
beginarrayccc
2&4&5 \
-1&1&0 \
5&1&1 \
endarray
right)
left(
beginarrayccc
-3&0&0 \
0&3&1 \
0&0&3 \
endarray
right)
left(
beginarrayccc
1&-9&5 \
1&27&5 \
-6&18&6 \
endarray
right) =
left(
beginarrayccc
2&5&-1 \
0&2&1 \
-1&0&-1 \
endarray
right)
$$
=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=
WHEN $a=-27,$
With
$$
left(
beginarrayccc
1&-17&-3 \
1&19&-3 \
6&6&18 \
endarray
right)
left(
beginarrayccc
10&8&3 \
-1&1&0 \
-3&-3&1 \
endarray
right) =
left(
beginarrayccc
36&0&0 \
0&36&0 \
0&0&36 \
endarray
right)
$$
we get
$$
frac136 ;
left(
beginarrayccc
1&-17&-3 \
1&19&-3 \
6&6&18 \
endarray
right)
left(
beginarrayccc
2&-27&-1 \
0&2&1 \
-1&0&-1 \
endarray
right)
left(
beginarrayccc
10&8&3 \
-1&1&0 \
-3&-3&1 \
endarray
right) =
left(
beginarrayccc
5&0&0 \
0&-1&1 \
0&0&-1 \
endarray
right)
$$
$$
frac136 ;
left(
beginarrayccc
10&8&3 \
-1&1&0 \
-3&-3&1 \
endarray
right)
left(
beginarrayccc
5&0&0 \
0&-1&1 \
0&0&-1 \
endarray
right)
left(
beginarrayccc
1&-17&-3 \
1&19&-3 \
6&6&18 \
endarray
right) =
left(
beginarrayccc
2&-27&-1 \
0&2&1 \
-1&0&-1 \
endarray
right)
$$
=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=
In case you weren't aware, you can write----------
or<hr>
to get clean HTML breaks, instead of the manual =-=
â Gabriel Romon
Aug 9 at 12:11
@GabrielRomon thanks. I had saved that visual divider in a text file, perfect width for the horizontal spacing of an answer window. Then just paste in. As the layout has changed in the past few days, I will need to experiment.
â Will Jagy
Aug 10 at 17:37
add a comment |Â
up vote
1
down vote
Let's consider such an $a$. Then $A$ must necessarily have a repeated eigenvalue, otherwise it would be diagonalizable. If $f(t) = det(tI-A)$ is the characteristic polynomial, then $f$ and $f'$ must have a common root. This severely restricts the values that $a$ can take.
Can you continue from here? Note that above is a necessary condition - after you figure out all potential candidates for $a$, you need to check if it actually makes $A$ non-diagionalizable.
add a comment |Â
3 Answers
3
active
oldest
votes
3 Answers
3
active
oldest
votes
active
oldest
votes
active
oldest
votes
up vote
3
down vote
accepted
(These Linear Algebra course notes by Michael Stoll, 2007 provide good background to my following assertions. As does the Wikipedia page on characteristic polynomials.)
Use the following facts:
a) A matrix $M in mathrmMat(n,F)$ (where $n$ is the size of the matrix and $F$ is some field) is diagonalisable if and only if its minimal polynomial $m_M(x)$ is a product of distinct monic linear factors.
b) The characteristic polynomial of a matrix $M$ is defined as $p_M(x)=mathrmdet(xI-M)$
c) Matrices satisfy their own characteristic equations: $p_M(M)=0$ for all $M$. Hence a matrix's minimal polynomial always divides its characteristic polynomial: $m_M(x) , vert , p_M(x)$.
d) The discriminant of a cubic polynomial $ax^3+bx^2+cx+d$ is given by:
$$ Delta_3 = b^2c^2-4ac^3-4b^3d-27a^2d^2+18abcd$$
If $Delta_3>0$ then the equation as three distinct real roots. If $Delta_3=0$ then the equation has a repeated root and all its roots are real. If $Delta_3<0$ then the equation has just one real root.
For your matrix,
$$ A:= left( beginmatrix2 & a & -1\0 & 2 & 1\-1 & 8 & -1endmatrix right) $$
we have that
$$
beginalign
p_A(x) &= mathrmdet left( beginmatrix x-2 & -a & 1\0 & x-2 & -1\1 & -8 & x+1endmatrix right)
\
\ &= (x-2)((x-2)(x+1)-8) + (a - (x-2))
\ &= x^3 -3x^2-9x+22+a
endalign
$$
With some calculation, the discriminant of $p_A$ is equal to $$Delta_3 = -27(a-5)(a+27)$$
Firstly,
$$Delta_3>0 iff -27<a<5$$
In this case, $p_A$ has three distinct real roots then it will factorise into three distinct linear factors. Hence $m_A(x)$ will also factorise into distinct linear factors and $A$ will be diagonalisable.
So $-27<a<5$ implies that $A$ is diagonalisable.
Secondly,
$$Delta_3=0 iff a in -27,5$$
If $a=-27$ then
$$ A:= left( beginmatrix2 & a & -1\0 & 2 & 1\-1 & 8 & -1endmatrix right) $$
and this matrix can be checked to have a maximum of two linearly independent eigenvectors
$$ v_1:= left( beginmatrix-10\1\3endmatrix right) qquad v_2:= left( beginmatrix-8\-1\3endmatrix right)$$
and so $A$ is not diagonalisable. (We could also consider the Jordan Form of $A$ as calculated by @WillJagy in their answer to this question.)
Similarly for $a=5$, $A$ turns out to not be diagonalisable.
Thirdly,
$$Delta_3<0 iff a in (-infty , -27) cup (5, infty )$$
In this case $p_A(x)=(x- lambda )(x^2+ beta x + gamma )$ where $lambda$ , $beta$ and $gamma$ are real and $(x^2+ beta x + gamma )$ cannot be factorised over the reals. Since $m_A$ divides $p_A$ we have three options:
$$ beginalign
mathrm(i) qquad & m_A(x)=(x- lambda )
\mathrm(ii) qquad & m_A(x)=(x^2+ beta x + gamma )
\mathrm(iii) qquad & m_A(x)=(x- lambda )(x^2+ beta x + gamma )
endalign$$
It is obvious that $(A-lambda I )$ is not equal to $0$ for any $lambda$ so we can rule out option $mathrm(i)$. But in both of the options $mathrm(ii)$ and $mathrm(iii)$, $m_A$ is not a product of distinct monic linear factors and hence $A$ is not diagonalisable.
Therefore:
$A$ is not diagonalisable over $mathbbR$ if and only if $a in (-infty , -27] cup [5, infty )$
Edit: diagonalisability over $mathbbC$
Even if working in $mathbbC$, the cases $Delta_3>0$ and $Delta_3=0$ above remain exactly the same: in these cases the characteristic polynomial has no complex roots.
However, $Delta_3<0$ now gives us that $p_A$ can be factorised into three distinct linear factors in $mathbbC[x]$. Hence $m_A(x)$ will also factorise into distinct linear factors in $mathbbC[x]$ and $A$ will be diagonalisable.
Hence $A$ is not diagonalisable over $mathbbC$ if and only if $a in -27,5$.
In general, for $A in mathrmMat(n,mathbbC)$, if the discriminant of $p_A$ is not equal to $0$ then $p_A$ has no repeated roots and $A$ will be diagonalisable over $mathbbC$. If the discriminant of $p_A$ is equal to $0$ then check the eigenvectors of $A$ (or form the Jordan Form of $A$) in order to check individual cases of diagonalisability.
1
a matrix can be diagionalizable even if it has repeated eigenvalues. Take $diag(1,1,1)$ for example.
â dezdichado
Aug 7 at 21:34
As it happens, nontrivial Jordan form occurs for both endpoints, $a=5$ and $a=-27$
â Will Jagy
Aug 8 at 0:55
Perfect answer. Thank you so much
â David Hughes
Aug 9 at 18:54
add a comment |Â
up vote
3
down vote
accepted
(These Linear Algebra course notes by Michael Stoll, 2007 provide good background to my following assertions. As does the Wikipedia page on characteristic polynomials.)
Use the following facts:
a) A matrix $M in mathrmMat(n,F)$ (where $n$ is the size of the matrix and $F$ is some field) is diagonalisable if and only if its minimal polynomial $m_M(x)$ is a product of distinct monic linear factors.
b) The characteristic polynomial of a matrix $M$ is defined as $p_M(x)=mathrmdet(xI-M)$
c) Matrices satisfy their own characteristic equations: $p_M(M)=0$ for all $M$. Hence a matrix's minimal polynomial always divides its characteristic polynomial: $m_M(x) , vert , p_M(x)$.
d) The discriminant of a cubic polynomial $ax^3+bx^2+cx+d$ is given by:
$$ Delta_3 = b^2c^2-4ac^3-4b^3d-27a^2d^2+18abcd$$
If $Delta_3>0$ then the equation as three distinct real roots. If $Delta_3=0$ then the equation has a repeated root and all its roots are real. If $Delta_3<0$ then the equation has just one real root.
For your matrix,
$$ A:= left( beginmatrix2 & a & -1\0 & 2 & 1\-1 & 8 & -1endmatrix right) $$
we have that
$$
beginalign
p_A(x) &= mathrmdet left( beginmatrix x-2 & -a & 1\0 & x-2 & -1\1 & -8 & x+1endmatrix right)
\
\ &= (x-2)((x-2)(x+1)-8) + (a - (x-2))
\ &= x^3 -3x^2-9x+22+a
endalign
$$
With some calculation, the discriminant of $p_A$ is equal to $$Delta_3 = -27(a-5)(a+27)$$
Firstly,
$$Delta_3>0 iff -27<a<5$$
In this case, $p_A$ has three distinct real roots then it will factorise into three distinct linear factors. Hence $m_A(x)$ will also factorise into distinct linear factors and $A$ will be diagonalisable.
So $-27<a<5$ implies that $A$ is diagonalisable.
Secondly,
$$Delta_3=0 iff a in -27,5$$
If $a=-27$ then
$$ A:= left( beginmatrix2 & a & -1\0 & 2 & 1\-1 & 8 & -1endmatrix right) $$
and this matrix can be checked to have a maximum of two linearly independent eigenvectors
$$ v_1:= left( beginmatrix-10\1\3endmatrix right) qquad v_2:= left( beginmatrix-8\-1\3endmatrix right)$$
and so $A$ is not diagonalisable. (We could also consider the Jordan Form of $A$ as calculated by @WillJagy in their answer to this question.)
Similarly for $a=5$, $A$ turns out to not be diagonalisable.
Thirdly,
$$Delta_3<0 iff a in (-infty , -27) cup (5, infty )$$
In this case $p_A(x)=(x- lambda )(x^2+ beta x + gamma )$ where $lambda$ , $beta$ and $gamma$ are real and $(x^2+ beta x + gamma )$ cannot be factorised over the reals. Since $m_A$ divides $p_A$ we have three options:
$$ beginalign
mathrm(i) qquad & m_A(x)=(x- lambda )
\mathrm(ii) qquad & m_A(x)=(x^2+ beta x + gamma )
\mathrm(iii) qquad & m_A(x)=(x- lambda )(x^2+ beta x + gamma )
endalign$$
It is obvious that $(A-lambda I )$ is not equal to $0$ for any $lambda$ so we can rule out option $mathrm(i)$. But in both of the options $mathrm(ii)$ and $mathrm(iii)$, $m_A$ is not a product of distinct monic linear factors and hence $A$ is not diagonalisable.
Therefore:
$A$ is not diagonalisable over $mathbbR$ if and only if $a in (-infty , -27] cup [5, infty )$
Edit: diagonalisability over $mathbbC$
Even if working in $mathbbC$, the cases $Delta_3>0$ and $Delta_3=0$ above remain exactly the same: in these cases the characteristic polynomial has no complex roots.
However, $Delta_3<0$ now gives us that $p_A$ can be factorised into three distinct linear factors in $mathbbC[x]$. Hence $m_A(x)$ will also factorise into distinct linear factors in $mathbbC[x]$ and $A$ will be diagonalisable.
Hence $A$ is not diagonalisable over $mathbbC$ if and only if $a in -27,5$.
In general, for $A in mathrmMat(n,mathbbC)$, if the discriminant of $p_A$ is not equal to $0$ then $p_A$ has no repeated roots and $A$ will be diagonalisable over $mathbbC$. If the discriminant of $p_A$ is equal to $0$ then check the eigenvectors of $A$ (or form the Jordan Form of $A$) in order to check individual cases of diagonalisability.
1
a matrix can be diagionalizable even if it has repeated eigenvalues. Take $diag(1,1,1)$ for example.
â dezdichado
Aug 7 at 21:34
As it happens, nontrivial Jordan form occurs for both endpoints, $a=5$ and $a=-27$
â Will Jagy
Aug 8 at 0:55
Perfect answer. Thank you so much
â David Hughes
Aug 9 at 18:54
add a comment |Â
up vote
3
down vote
accepted
up vote
3
down vote
accepted
(These Linear Algebra course notes by Michael Stoll, 2007 provide good background to my following assertions. As does the Wikipedia page on characteristic polynomials.)
Use the following facts:
a) A matrix $M in mathrmMat(n,F)$ (where $n$ is the size of the matrix and $F$ is some field) is diagonalisable if and only if its minimal polynomial $m_M(x)$ is a product of distinct monic linear factors.
b) The characteristic polynomial of a matrix $M$ is defined as $p_M(x)=mathrmdet(xI-M)$
c) Matrices satisfy their own characteristic equations: $p_M(M)=0$ for all $M$. Hence a matrix's minimal polynomial always divides its characteristic polynomial: $m_M(x) , vert , p_M(x)$.
d) The discriminant of a cubic polynomial $ax^3+bx^2+cx+d$ is given by:
$$ Delta_3 = b^2c^2-4ac^3-4b^3d-27a^2d^2+18abcd$$
If $Delta_3>0$ then the equation as three distinct real roots. If $Delta_3=0$ then the equation has a repeated root and all its roots are real. If $Delta_3<0$ then the equation has just one real root.
For your matrix,
$$ A:= left( beginmatrix2 & a & -1\0 & 2 & 1\-1 & 8 & -1endmatrix right) $$
we have that
$$
beginalign
p_A(x) &= mathrmdet left( beginmatrix x-2 & -a & 1\0 & x-2 & -1\1 & -8 & x+1endmatrix right)
\
\ &= (x-2)((x-2)(x+1)-8) + (a - (x-2))
\ &= x^3 -3x^2-9x+22+a
endalign
$$
With some calculation, the discriminant of $p_A$ is equal to $$Delta_3 = -27(a-5)(a+27)$$
Firstly,
$$Delta_3>0 iff -27<a<5$$
In this case, $p_A$ has three distinct real roots then it will factorise into three distinct linear factors. Hence $m_A(x)$ will also factorise into distinct linear factors and $A$ will be diagonalisable.
So $-27<a<5$ implies that $A$ is diagonalisable.
Secondly,
$$Delta_3=0 iff a in -27,5$$
If $a=-27$ then
$$ A:= left( beginmatrix2 & a & -1\0 & 2 & 1\-1 & 8 & -1endmatrix right) $$
and this matrix can be checked to have a maximum of two linearly independent eigenvectors
$$ v_1:= left( beginmatrix-10\1\3endmatrix right) qquad v_2:= left( beginmatrix-8\-1\3endmatrix right)$$
and so $A$ is not diagonalisable. (We could also consider the Jordan Form of $A$ as calculated by @WillJagy in their answer to this question.)
Similarly for $a=5$, $A$ turns out to not be diagonalisable.
Thirdly,
$$Delta_3<0 iff a in (-infty , -27) cup (5, infty )$$
In this case $p_A(x)=(x- lambda )(x^2+ beta x + gamma )$ where $lambda$ , $beta$ and $gamma$ are real and $(x^2+ beta x + gamma )$ cannot be factorised over the reals. Since $m_A$ divides $p_A$ we have three options:
$$ beginalign
mathrm(i) qquad & m_A(x)=(x- lambda )
\mathrm(ii) qquad & m_A(x)=(x^2+ beta x + gamma )
\mathrm(iii) qquad & m_A(x)=(x- lambda )(x^2+ beta x + gamma )
endalign$$
It is obvious that $(A-lambda I )$ is not equal to $0$ for any $lambda$ so we can rule out option $mathrm(i)$. But in both of the options $mathrm(ii)$ and $mathrm(iii)$, $m_A$ is not a product of distinct monic linear factors and hence $A$ is not diagonalisable.
Therefore:
$A$ is not diagonalisable over $mathbbR$ if and only if $a in (-infty , -27] cup [5, infty )$
Edit: diagonalisability over $mathbbC$
Even if working in $mathbbC$, the cases $Delta_3>0$ and $Delta_3=0$ above remain exactly the same: in these cases the characteristic polynomial has no complex roots.
However, $Delta_3<0$ now gives us that $p_A$ can be factorised into three distinct linear factors in $mathbbC[x]$. Hence $m_A(x)$ will also factorise into distinct linear factors in $mathbbC[x]$ and $A$ will be diagonalisable.
Hence $A$ is not diagonalisable over $mathbbC$ if and only if $a in -27,5$.
In general, for $A in mathrmMat(n,mathbbC)$, if the discriminant of $p_A$ is not equal to $0$ then $p_A$ has no repeated roots and $A$ will be diagonalisable over $mathbbC$. If the discriminant of $p_A$ is equal to $0$ then check the eigenvectors of $A$ (or form the Jordan Form of $A$) in order to check individual cases of diagonalisability.
(These Linear Algebra course notes by Michael Stoll, 2007 provide good background to my following assertions. As does the Wikipedia page on characteristic polynomials.)
Use the following facts:
a) A matrix $M in mathrmMat(n,F)$ (where $n$ is the size of the matrix and $F$ is some field) is diagonalisable if and only if its minimal polynomial $m_M(x)$ is a product of distinct monic linear factors.
b) The characteristic polynomial of a matrix $M$ is defined as $p_M(x)=mathrmdet(xI-M)$
c) Matrices satisfy their own characteristic equations: $p_M(M)=0$ for all $M$. Hence a matrix's minimal polynomial always divides its characteristic polynomial: $m_M(x) , vert , p_M(x)$.
d) The discriminant of a cubic polynomial $ax^3+bx^2+cx+d$ is given by:
$$ Delta_3 = b^2c^2-4ac^3-4b^3d-27a^2d^2+18abcd$$
If $Delta_3>0$ then the equation as three distinct real roots. If $Delta_3=0$ then the equation has a repeated root and all its roots are real. If $Delta_3<0$ then the equation has just one real root.
For your matrix,
$$ A:= left( beginmatrix2 & a & -1\0 & 2 & 1\-1 & 8 & -1endmatrix right) $$
we have that
$$
beginalign
p_A(x) &= mathrmdet left( beginmatrix x-2 & -a & 1\0 & x-2 & -1\1 & -8 & x+1endmatrix right)
\
\ &= (x-2)((x-2)(x+1)-8) + (a - (x-2))
\ &= x^3 -3x^2-9x+22+a
endalign
$$
With some calculation, the discriminant of $p_A$ is equal to $$Delta_3 = -27(a-5)(a+27)$$
Firstly,
$$Delta_3>0 iff -27<a<5$$
In this case, $p_A$ has three distinct real roots then it will factorise into three distinct linear factors. Hence $m_A(x)$ will also factorise into distinct linear factors and $A$ will be diagonalisable.
So $-27<a<5$ implies that $A$ is diagonalisable.
Secondly,
$$Delta_3=0 iff a in -27,5$$
If $a=-27$ then
$$ A:= left( beginmatrix2 & a & -1\0 & 2 & 1\-1 & 8 & -1endmatrix right) $$
and this matrix can be checked to have a maximum of two linearly independent eigenvectors
$$ v_1:= left( beginmatrix-10\1\3endmatrix right) qquad v_2:= left( beginmatrix-8\-1\3endmatrix right)$$
and so $A$ is not diagonalisable. (We could also consider the Jordan Form of $A$ as calculated by @WillJagy in their answer to this question.)
Similarly for $a=5$, $A$ turns out to not be diagonalisable.
Thirdly,
$$Delta_3<0 iff a in (-infty , -27) cup (5, infty )$$
In this case $p_A(x)=(x- lambda )(x^2+ beta x + gamma )$ where $lambda$ , $beta$ and $gamma$ are real and $(x^2+ beta x + gamma )$ cannot be factorised over the reals. Since $m_A$ divides $p_A$ we have three options:
$$ beginalign
mathrm(i) qquad & m_A(x)=(x- lambda )
\mathrm(ii) qquad & m_A(x)=(x^2+ beta x + gamma )
\mathrm(iii) qquad & m_A(x)=(x- lambda )(x^2+ beta x + gamma )
endalign$$
It is obvious that $(A-lambda I )$ is not equal to $0$ for any $lambda$ so we can rule out option $mathrm(i)$. But in both of the options $mathrm(ii)$ and $mathrm(iii)$, $m_A$ is not a product of distinct monic linear factors and hence $A$ is not diagonalisable.
Therefore:
$A$ is not diagonalisable over $mathbbR$ if and only if $a in (-infty , -27] cup [5, infty )$
Edit: diagonalisability over $mathbbC$
Even if working in $mathbbC$, the cases $Delta_3>0$ and $Delta_3=0$ above remain exactly the same: in these cases the characteristic polynomial has no complex roots.
However, $Delta_3<0$ now gives us that $p_A$ can be factorised into three distinct linear factors in $mathbbC[x]$. Hence $m_A(x)$ will also factorise into distinct linear factors in $mathbbC[x]$ and $A$ will be diagonalisable.
Hence $A$ is not diagonalisable over $mathbbC$ if and only if $a in -27,5$.
In general, for $A in mathrmMat(n,mathbbC)$, if the discriminant of $p_A$ is not equal to $0$ then $p_A$ has no repeated roots and $A$ will be diagonalisable over $mathbbC$. If the discriminant of $p_A$ is equal to $0$ then check the eigenvectors of $A$ (or form the Jordan Form of $A$) in order to check individual cases of diagonalisability.
edited Aug 9 at 12:06
answered Aug 7 at 21:30
Malkin
1,428523
1,428523
1
a matrix can be diagionalizable even if it has repeated eigenvalues. Take $diag(1,1,1)$ for example.
â dezdichado
Aug 7 at 21:34
As it happens, nontrivial Jordan form occurs for both endpoints, $a=5$ and $a=-27$
â Will Jagy
Aug 8 at 0:55
Perfect answer. Thank you so much
â David Hughes
Aug 9 at 18:54
add a comment |Â
1
a matrix can be diagionalizable even if it has repeated eigenvalues. Take $diag(1,1,1)$ for example.
â dezdichado
Aug 7 at 21:34
As it happens, nontrivial Jordan form occurs for both endpoints, $a=5$ and $a=-27$
â Will Jagy
Aug 8 at 0:55
Perfect answer. Thank you so much
â David Hughes
Aug 9 at 18:54
1
1
a matrix can be diagionalizable even if it has repeated eigenvalues. Take $diag(1,1,1)$ for example.
â dezdichado
Aug 7 at 21:34
a matrix can be diagionalizable even if it has repeated eigenvalues. Take $diag(1,1,1)$ for example.
â dezdichado
Aug 7 at 21:34
As it happens, nontrivial Jordan form occurs for both endpoints, $a=5$ and $a=-27$
â Will Jagy
Aug 8 at 0:55
As it happens, nontrivial Jordan form occurs for both endpoints, $a=5$ and $a=-27$
â Will Jagy
Aug 8 at 0:55
Perfect answer. Thank you so much
â David Hughes
Aug 9 at 18:54
Perfect answer. Thank you so much
â David Hughes
Aug 9 at 18:54
add a comment |Â
up vote
2
down vote
Addendum. I have been slow on one point; if $a$ lies outside a certain range, then there must be complex eigenvalues, that is, not real numbers. That is what the other answers and comments are emphasizing, that it might not be possible to diagonalize over the real numbers.
Another way for non-diagonal Jordan form is real but repeated (generalized) eigenvalues, where there is not a basis of eigenvectors. This is the aspect I address below.
ORIGINAL: The derivative of the characteristic polynomial is $3(x-3)(x+1).$ When $a=5,$ we do get the characteristic polynomial as a multiple of $(x-3)^2.$ When $a=-27,$ we get the characteristic polynomial as a multiple of $(x+1)^2.$ These lead to non-diagonal (but real) Jordan forms, see below.
=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=
With $a=5$ and
$$
left(
beginarrayccc
1&-9&5 \
1&27&5 \
-6&18&6 \
endarray
right)
left(
beginarrayccc
2&4&5 \
-1&1&0 \
5&1&1 \
endarray
right) =
left(
beginarrayccc
36&0&0 \
0&36&0 \
0&0&36 \
endarray
right)
$$
we get
$$
frac136 ;
left(
beginarrayccc
1&-9&5 \
1&27&5 \
-6&18&6 \
endarray
right)
left(
beginarrayccc
2&5&-1 \
0&2&1 \
-1&0&-1 \
endarray
right)
left(
beginarrayccc
2&4&5 \
-1&1&0 \
5&1&1 \
endarray
right) =
left(
beginarrayccc
-3&0&0 \
0&3&1 \
0&0&3 \
endarray
right)
$$
The final version is called Jordan Normal Form. In the U.S. it is taught with the nilpotent part above the diagonal. In some countries, for example Uruguay, it is taught with any extra $1$s below the diagonal.
Actually using the Jordan form for something merely requires writing out
$$
frac136 ;
left(
beginarrayccc
2&4&5 \
-1&1&0 \
5&1&1 \
endarray
right)
left(
beginarrayccc
-3&0&0 \
0&3&1 \
0&0&3 \
endarray
right)
left(
beginarrayccc
1&-9&5 \
1&27&5 \
-6&18&6 \
endarray
right) =
left(
beginarrayccc
2&5&-1 \
0&2&1 \
-1&0&-1 \
endarray
right)
$$
=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=
WHEN $a=-27,$
With
$$
left(
beginarrayccc
1&-17&-3 \
1&19&-3 \
6&6&18 \
endarray
right)
left(
beginarrayccc
10&8&3 \
-1&1&0 \
-3&-3&1 \
endarray
right) =
left(
beginarrayccc
36&0&0 \
0&36&0 \
0&0&36 \
endarray
right)
$$
we get
$$
frac136 ;
left(
beginarrayccc
1&-17&-3 \
1&19&-3 \
6&6&18 \
endarray
right)
left(
beginarrayccc
2&-27&-1 \
0&2&1 \
-1&0&-1 \
endarray
right)
left(
beginarrayccc
10&8&3 \
-1&1&0 \
-3&-3&1 \
endarray
right) =
left(
beginarrayccc
5&0&0 \
0&-1&1 \
0&0&-1 \
endarray
right)
$$
$$
frac136 ;
left(
beginarrayccc
10&8&3 \
-1&1&0 \
-3&-3&1 \
endarray
right)
left(
beginarrayccc
5&0&0 \
0&-1&1 \
0&0&-1 \
endarray
right)
left(
beginarrayccc
1&-17&-3 \
1&19&-3 \
6&6&18 \
endarray
right) =
left(
beginarrayccc
2&-27&-1 \
0&2&1 \
-1&0&-1 \
endarray
right)
$$
=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=
In case you weren't aware, you can write----------
or<hr>
to get clean HTML breaks, instead of the manual =-=
â Gabriel Romon
Aug 9 at 12:11
@GabrielRomon thanks. I had saved that visual divider in a text file, perfect width for the horizontal spacing of an answer window. Then just paste in. As the layout has changed in the past few days, I will need to experiment.
â Will Jagy
Aug 10 at 17:37
add a comment |Â
up vote
2
down vote
Addendum. I have been slow on one point; if $a$ lies outside a certain range, then there must be complex eigenvalues, that is, not real numbers. That is what the other answers and comments are emphasizing, that it might not be possible to diagonalize over the real numbers.
Another way for non-diagonal Jordan form is real but repeated (generalized) eigenvalues, where there is not a basis of eigenvectors. This is the aspect I address below.
ORIGINAL: The derivative of the characteristic polynomial is $3(x-3)(x+1).$ When $a=5,$ we do get the characteristic polynomial as a multiple of $(x-3)^2.$ When $a=-27,$ we get the characteristic polynomial as a multiple of $(x+1)^2.$ These lead to non-diagonal (but real) Jordan forms, see below.
=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=
With $a=5$ and
$$
left(
beginarrayccc
1&-9&5 \
1&27&5 \
-6&18&6 \
endarray
right)
left(
beginarrayccc
2&4&5 \
-1&1&0 \
5&1&1 \
endarray
right) =
left(
beginarrayccc
36&0&0 \
0&36&0 \
0&0&36 \
endarray
right)
$$
we get
$$
frac136 ;
left(
beginarrayccc
1&-9&5 \
1&27&5 \
-6&18&6 \
endarray
right)
left(
beginarrayccc
2&5&-1 \
0&2&1 \
-1&0&-1 \
endarray
right)
left(
beginarrayccc
2&4&5 \
-1&1&0 \
5&1&1 \
endarray
right) =
left(
beginarrayccc
-3&0&0 \
0&3&1 \
0&0&3 \
endarray
right)
$$
The final version is called Jordan Normal Form. In the U.S. it is taught with the nilpotent part above the diagonal. In some countries, for example Uruguay, it is taught with any extra $1$s below the diagonal.
Actually using the Jordan form for something merely requires writing out
$$
frac136 ;
left(
beginarrayccc
2&4&5 \
-1&1&0 \
5&1&1 \
endarray
right)
left(
beginarrayccc
-3&0&0 \
0&3&1 \
0&0&3 \
endarray
right)
left(
beginarrayccc
1&-9&5 \
1&27&5 \
-6&18&6 \
endarray
right) =
left(
beginarrayccc
2&5&-1 \
0&2&1 \
-1&0&-1 \
endarray
right)
$$
=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=
WHEN $a=-27,$
With
$$
left(
beginarrayccc
1&-17&-3 \
1&19&-3 \
6&6&18 \
endarray
right)
left(
beginarrayccc
10&8&3 \
-1&1&0 \
-3&-3&1 \
endarray
right) =
left(
beginarrayccc
36&0&0 \
0&36&0 \
0&0&36 \
endarray
right)
$$
we get
$$
frac136 ;
left(
beginarrayccc
1&-17&-3 \
1&19&-3 \
6&6&18 \
endarray
right)
left(
beginarrayccc
2&-27&-1 \
0&2&1 \
-1&0&-1 \
endarray
right)
left(
beginarrayccc
10&8&3 \
-1&1&0 \
-3&-3&1 \
endarray
right) =
left(
beginarrayccc
5&0&0 \
0&-1&1 \
0&0&-1 \
endarray
right)
$$
$$
frac136 ;
left(
beginarrayccc
10&8&3 \
-1&1&0 \
-3&-3&1 \
endarray
right)
left(
beginarrayccc
5&0&0 \
0&-1&1 \
0&0&-1 \
endarray
right)
left(
beginarrayccc
1&-17&-3 \
1&19&-3 \
6&6&18 \
endarray
right) =
left(
beginarrayccc
2&-27&-1 \
0&2&1 \
-1&0&-1 \
endarray
right)
$$
=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=
In case you weren't aware, you can write----------
or<hr>
to get clean HTML breaks, instead of the manual =-=
â Gabriel Romon
Aug 9 at 12:11
@GabrielRomon thanks. I had saved that visual divider in a text file, perfect width for the horizontal spacing of an answer window. Then just paste in. As the layout has changed in the past few days, I will need to experiment.
â Will Jagy
Aug 10 at 17:37
add a comment |Â
up vote
2
down vote
up vote
2
down vote
Addendum. I have been slow on one point; if $a$ lies outside a certain range, then there must be complex eigenvalues, that is, not real numbers. That is what the other answers and comments are emphasizing, that it might not be possible to diagonalize over the real numbers.
Another way for non-diagonal Jordan form is real but repeated (generalized) eigenvalues, where there is not a basis of eigenvectors. This is the aspect I address below.
ORIGINAL: The derivative of the characteristic polynomial is $3(x-3)(x+1).$ When $a=5,$ we do get the characteristic polynomial as a multiple of $(x-3)^2.$ When $a=-27,$ we get the characteristic polynomial as a multiple of $(x+1)^2.$ These lead to non-diagonal (but real) Jordan forms, see below.
=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=
With $a=5$ and
$$
left(
beginarrayccc
1&-9&5 \
1&27&5 \
-6&18&6 \
endarray
right)
left(
beginarrayccc
2&4&5 \
-1&1&0 \
5&1&1 \
endarray
right) =
left(
beginarrayccc
36&0&0 \
0&36&0 \
0&0&36 \
endarray
right)
$$
we get
$$
frac136 ;
left(
beginarrayccc
1&-9&5 \
1&27&5 \
-6&18&6 \
endarray
right)
left(
beginarrayccc
2&5&-1 \
0&2&1 \
-1&0&-1 \
endarray
right)
left(
beginarrayccc
2&4&5 \
-1&1&0 \
5&1&1 \
endarray
right) =
left(
beginarrayccc
-3&0&0 \
0&3&1 \
0&0&3 \
endarray
right)
$$
The final version is called Jordan Normal Form. In the U.S. it is taught with the nilpotent part above the diagonal. In some countries, for example Uruguay, it is taught with any extra $1$s below the diagonal.
Actually using the Jordan form for something merely requires writing out
$$
frac136 ;
left(
beginarrayccc
2&4&5 \
-1&1&0 \
5&1&1 \
endarray
right)
left(
beginarrayccc
-3&0&0 \
0&3&1 \
0&0&3 \
endarray
right)
left(
beginarrayccc
1&-9&5 \
1&27&5 \
-6&18&6 \
endarray
right) =
left(
beginarrayccc
2&5&-1 \
0&2&1 \
-1&0&-1 \
endarray
right)
$$
=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=
WHEN $a=-27,$
With
$$
left(
beginarrayccc
1&-17&-3 \
1&19&-3 \
6&6&18 \
endarray
right)
left(
beginarrayccc
10&8&3 \
-1&1&0 \
-3&-3&1 \
endarray
right) =
left(
beginarrayccc
36&0&0 \
0&36&0 \
0&0&36 \
endarray
right)
$$
we get
$$
frac136 ;
left(
beginarrayccc
1&-17&-3 \
1&19&-3 \
6&6&18 \
endarray
right)
left(
beginarrayccc
2&-27&-1 \
0&2&1 \
-1&0&-1 \
endarray
right)
left(
beginarrayccc
10&8&3 \
-1&1&0 \
-3&-3&1 \
endarray
right) =
left(
beginarrayccc
5&0&0 \
0&-1&1 \
0&0&-1 \
endarray
right)
$$
$$
frac136 ;
left(
beginarrayccc
10&8&3 \
-1&1&0 \
-3&-3&1 \
endarray
right)
left(
beginarrayccc
5&0&0 \
0&-1&1 \
0&0&-1 \
endarray
right)
left(
beginarrayccc
1&-17&-3 \
1&19&-3 \
6&6&18 \
endarray
right) =
left(
beginarrayccc
2&-27&-1 \
0&2&1 \
-1&0&-1 \
endarray
right)
$$
=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=
Addendum. I have been slow on one point; if $a$ lies outside a certain range, then there must be complex eigenvalues, that is, not real numbers. That is what the other answers and comments are emphasizing, that it might not be possible to diagonalize over the real numbers.
Another way for non-diagonal Jordan form is real but repeated (generalized) eigenvalues, where there is not a basis of eigenvectors. This is the aspect I address below.
ORIGINAL: The derivative of the characteristic polynomial is $3(x-3)(x+1).$ When $a=5,$ we do get the characteristic polynomial as a multiple of $(x-3)^2.$ When $a=-27,$ we get the characteristic polynomial as a multiple of $(x+1)^2.$ These lead to non-diagonal (but real) Jordan forms, see below.
=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=
With $a=5$ and
$$
left(
beginarrayccc
1&-9&5 \
1&27&5 \
-6&18&6 \
endarray
right)
left(
beginarrayccc
2&4&5 \
-1&1&0 \
5&1&1 \
endarray
right) =
left(
beginarrayccc
36&0&0 \
0&36&0 \
0&0&36 \
endarray
right)
$$
we get
$$
frac136 ;
left(
beginarrayccc
1&-9&5 \
1&27&5 \
-6&18&6 \
endarray
right)
left(
beginarrayccc
2&5&-1 \
0&2&1 \
-1&0&-1 \
endarray
right)
left(
beginarrayccc
2&4&5 \
-1&1&0 \
5&1&1 \
endarray
right) =
left(
beginarrayccc
-3&0&0 \
0&3&1 \
0&0&3 \
endarray
right)
$$
The final version is called Jordan Normal Form. In the U.S. it is taught with the nilpotent part above the diagonal. In some countries, for example Uruguay, it is taught with any extra $1$s below the diagonal.
Actually using the Jordan form for something merely requires writing out
$$
frac136 ;
left(
beginarrayccc
2&4&5 \
-1&1&0 \
5&1&1 \
endarray
right)
left(
beginarrayccc
-3&0&0 \
0&3&1 \
0&0&3 \
endarray
right)
left(
beginarrayccc
1&-9&5 \
1&27&5 \
-6&18&6 \
endarray
right) =
left(
beginarrayccc
2&5&-1 \
0&2&1 \
-1&0&-1 \
endarray
right)
$$
=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=
WHEN $a=-27,$
With
$$
left(
beginarrayccc
1&-17&-3 \
1&19&-3 \
6&6&18 \
endarray
right)
left(
beginarrayccc
10&8&3 \
-1&1&0 \
-3&-3&1 \
endarray
right) =
left(
beginarrayccc
36&0&0 \
0&36&0 \
0&0&36 \
endarray
right)
$$
we get
$$
frac136 ;
left(
beginarrayccc
1&-17&-3 \
1&19&-3 \
6&6&18 \
endarray
right)
left(
beginarrayccc
2&-27&-1 \
0&2&1 \
-1&0&-1 \
endarray
right)
left(
beginarrayccc
10&8&3 \
-1&1&0 \
-3&-3&1 \
endarray
right) =
left(
beginarrayccc
5&0&0 \
0&-1&1 \
0&0&-1 \
endarray
right)
$$
$$
frac136 ;
left(
beginarrayccc
10&8&3 \
-1&1&0 \
-3&-3&1 \
endarray
right)
left(
beginarrayccc
5&0&0 \
0&-1&1 \
0&0&-1 \
endarray
right)
left(
beginarrayccc
1&-17&-3 \
1&19&-3 \
6&6&18 \
endarray
right) =
left(
beginarrayccc
2&-27&-1 \
0&2&1 \
-1&0&-1 \
endarray
right)
$$
=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=
edited Aug 8 at 0:49
answered Aug 7 at 22:19
Will Jagy
97.3k594196
97.3k594196
In case you weren't aware, you can write----------
or<hr>
to get clean HTML breaks, instead of the manual =-=
â Gabriel Romon
Aug 9 at 12:11
@GabrielRomon thanks. I had saved that visual divider in a text file, perfect width for the horizontal spacing of an answer window. Then just paste in. As the layout has changed in the past few days, I will need to experiment.
â Will Jagy
Aug 10 at 17:37
add a comment |Â
In case you weren't aware, you can write----------
or<hr>
to get clean HTML breaks, instead of the manual =-=
â Gabriel Romon
Aug 9 at 12:11
@GabrielRomon thanks. I had saved that visual divider in a text file, perfect width for the horizontal spacing of an answer window. Then just paste in. As the layout has changed in the past few days, I will need to experiment.
â Will Jagy
Aug 10 at 17:37
In case you weren't aware, you can write
----------
or <hr>
to get clean HTML breaks, instead of the manual =-=â Gabriel Romon
Aug 9 at 12:11
In case you weren't aware, you can write
----------
or <hr>
to get clean HTML breaks, instead of the manual =-=â Gabriel Romon
Aug 9 at 12:11
@GabrielRomon thanks. I had saved that visual divider in a text file, perfect width for the horizontal spacing of an answer window. Then just paste in. As the layout has changed in the past few days, I will need to experiment.
â Will Jagy
Aug 10 at 17:37
@GabrielRomon thanks. I had saved that visual divider in a text file, perfect width for the horizontal spacing of an answer window. Then just paste in. As the layout has changed in the past few days, I will need to experiment.
â Will Jagy
Aug 10 at 17:37
add a comment |Â
up vote
1
down vote
Let's consider such an $a$. Then $A$ must necessarily have a repeated eigenvalue, otherwise it would be diagonalizable. If $f(t) = det(tI-A)$ is the characteristic polynomial, then $f$ and $f'$ must have a common root. This severely restricts the values that $a$ can take.
Can you continue from here? Note that above is a necessary condition - after you figure out all potential candidates for $a$, you need to check if it actually makes $A$ non-diagionalizable.
add a comment |Â
up vote
1
down vote
Let's consider such an $a$. Then $A$ must necessarily have a repeated eigenvalue, otherwise it would be diagonalizable. If $f(t) = det(tI-A)$ is the characteristic polynomial, then $f$ and $f'$ must have a common root. This severely restricts the values that $a$ can take.
Can you continue from here? Note that above is a necessary condition - after you figure out all potential candidates for $a$, you need to check if it actually makes $A$ non-diagionalizable.
add a comment |Â
up vote
1
down vote
up vote
1
down vote
Let's consider such an $a$. Then $A$ must necessarily have a repeated eigenvalue, otherwise it would be diagonalizable. If $f(t) = det(tI-A)$ is the characteristic polynomial, then $f$ and $f'$ must have a common root. This severely restricts the values that $a$ can take.
Can you continue from here? Note that above is a necessary condition - after you figure out all potential candidates for $a$, you need to check if it actually makes $A$ non-diagionalizable.
Let's consider such an $a$. Then $A$ must necessarily have a repeated eigenvalue, otherwise it would be diagonalizable. If $f(t) = det(tI-A)$ is the characteristic polynomial, then $f$ and $f'$ must have a common root. This severely restricts the values that $a$ can take.
Can you continue from here? Note that above is a necessary condition - after you figure out all potential candidates for $a$, you need to check if it actually makes $A$ non-diagionalizable.
answered Aug 7 at 21:26
dezdichado
5,3951827
5,3951827
add a comment |Â
add a comment |Â
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2
A necessary conddition is an eigenvalue with multiplicity greater than $1$.
â Peter
Aug 7 at 19:56
4
What is the criterion for a matrix to be diagonalizable? Try to establish this in dependence of $a$.
â zzuussee
Aug 7 at 19:57
Just make the first row a linear combination of the others
â N74
Aug 7 at 20:06
2
The characteristic polynomial, if I'm not mistaken, is $-x^3+3x^2+9x-(22+a)$. Thus, for $-27<a<5$, this equation should on the first glimpse have three roots, i.e. three distinct eigenvalues and thus be diagonalizable for these values. As it is a cubic function, it always has at least one root in every case, i.e. there is always one eigenvalue at least. I don't know about the geometric multiplicities in these cases.
â zzuussee
Aug 7 at 20:39
1
Are we talking about diagonalization over the reals or over the complex numbers?
â Arnaud Mortier
Aug 7 at 22:22