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?







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  • 2




    A necessary conddition is an eigenvalue with multiplicity greater than $1$.
    – Peter
    Aug 7 at 19:56







  • 4




    What is the criterion for a matrix to be diagonalizable? Try to establish this in dependence of $a$.
    – zzuussee
    Aug 7 at 19:57










  • Just make the first row a linear combination of the others
    – 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.
    – zzuussee
    Aug 7 at 20:39






  • 1




    Are we talking about diagonalization over the reals or over the complex numbers?
    – Arnaud Mortier
    Aug 7 at 22:22














up vote
9
down vote

favorite
1












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?







share|cite|improve this question

















  • 2




    A necessary conddition is an eigenvalue with multiplicity greater than $1$.
    – Peter
    Aug 7 at 19:56







  • 4




    What is the criterion for a matrix to be diagonalizable? Try to establish this in dependence of $a$.
    – zzuussee
    Aug 7 at 19:57










  • Just make the first row a linear combination of the others
    – 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.
    – zzuussee
    Aug 7 at 20:39






  • 1




    Are we talking about diagonalization over the reals or over the complex numbers?
    – Arnaud Mortier
    Aug 7 at 22:22












up vote
9
down vote

favorite
1









up vote
9
down vote

favorite
1






1





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?







share|cite|improve this question













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?









share|cite|improve this question












share|cite|improve this question




share|cite|improve this question








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 $1$.
    – Peter
    Aug 7 at 19:56







  • 4




    What is the criterion for a matrix to be diagonalizable? Try to establish this in dependence of $a$.
    – zzuussee
    Aug 7 at 19:57










  • Just make the first row a linear combination of the others
    – 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.
    – zzuussee
    Aug 7 at 20:39






  • 1




    Are we talking about diagonalization over the reals or over the complex numbers?
    – Arnaud Mortier
    Aug 7 at 22:22












  • 2




    A necessary conddition is an eigenvalue with multiplicity greater than $1$.
    – Peter
    Aug 7 at 19:56







  • 4




    What is the criterion for a matrix to be diagonalizable? Try to establish this in dependence of $a$.
    – zzuussee
    Aug 7 at 19:57










  • Just make the first row a linear combination of the others
    – 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.
    – zzuussee
    Aug 7 at 20:39






  • 1




    Are we talking about diagonalization over the reals or over the complex numbers?
    – Arnaud Mortier
    Aug 7 at 22:22







2




2




A necessary conddition is an eigenvalue with multiplicity greater than $1$.
– Peter
Aug 7 at 19:56





A necessary conddition is an eigenvalue with multiplicity greater than $1$.
– 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 $a$.
– zzuussee
Aug 7 at 19:57




What is the criterion for a matrix to be diagonalizable? Try to establish this in dependence of $a$.
– zzuussee
Aug 7 at 19:57












Just make the first row a linear combination of the others
– N74
Aug 7 at 20:06




Just make the first row a linear combination of the others
– 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.
– 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.
– zzuussee
Aug 7 at 20:39




1




1




Are we talking about diagonalization over the reals or over the complex numbers?
– Arnaud Mortier
Aug 7 at 22:22




Are we talking about diagonalization over the reals or over the complex numbers?
– Arnaud Mortier
Aug 7 at 22:22










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.






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  • 1




    a matrix can be diagionalizable even if it has repeated eigenvalues. Take $diag(1,1,1)$ for example.
    – dezdichado
    Aug 7 at 21:34










  • As it happens, nontrivial Jordan form occurs for both endpoints, $a=5$ and $a=-27$
    – Will Jagy
    Aug 8 at 0:55










  • Perfect answer. Thank you so much
    – David Hughes
    Aug 9 at 18:54

















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



$$
frac136 ;
left(
beginarrayccc
1&-17&-3 \
1&19&-3 \
6&6&18 \
endarray
right)
left(
beginarrayccc
2&-27&-1 \
0&2&1 \
-1&0&-1 \
endarray
right)
left(
beginarrayccc
10&8&3 \
-1&1&0 \
-3&-3&1 \
endarray
right) =
left(
beginarrayccc
5&0&0 \
0&-1&1 \
0&0&-1 \
endarray
right)
$$



$$
frac136 ;
left(
beginarrayccc
10&8&3 \
-1&1&0 \
-3&-3&1 \
endarray
right)
left(
beginarrayccc
5&0&0 \
0&-1&1 \
0&0&-1 \
endarray
right)
left(
beginarrayccc
1&-17&-3 \
1&19&-3 \
6&6&18 \
endarray
right) =
left(
beginarrayccc
2&-27&-1 \
0&2&1 \
-1&0&-1 \
endarray
right)
$$



=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=






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  • In case you weren't aware, you can write ---------- or <hr> to get clean HTML breaks, instead of the manual =-=
    – Gabriel Romon
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  • @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.
    – Will Jagy
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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.






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    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.






    share|cite|improve this answer



















    • 1




      a matrix can be diagionalizable even if it has repeated eigenvalues. Take $diag(1,1,1)$ for example.
      – dezdichado
      Aug 7 at 21:34










    • As it happens, nontrivial Jordan form occurs for both endpoints, $a=5$ and $a=-27$
      – Will Jagy
      Aug 8 at 0:55










    • Perfect answer. Thank you so much
      – David Hughes
      Aug 9 at 18:54














    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.






    share|cite|improve this answer



















    • 1




      a matrix can be diagionalizable even if it has repeated eigenvalues. Take $diag(1,1,1)$ for example.
      – dezdichado
      Aug 7 at 21:34










    • As it happens, nontrivial Jordan form occurs for both endpoints, $a=5$ and $a=-27$
      – Will Jagy
      Aug 8 at 0:55










    • Perfect answer. Thank you so much
      – David Hughes
      Aug 9 at 18:54












    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.






    share|cite|improve this answer















    (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.







    share|cite|improve this answer















    share|cite|improve this answer



    share|cite|improve this answer








    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.
      – dezdichado
      Aug 7 at 21:34










    • As it happens, nontrivial Jordan form occurs for both endpoints, $a=5$ and $a=-27$
      – Will Jagy
      Aug 8 at 0:55










    • Perfect answer. Thank you so much
      – David Hughes
      Aug 9 at 18:54












    • 1




      a matrix can be diagionalizable even if it has repeated eigenvalues. Take $diag(1,1,1)$ for example.
      – dezdichado
      Aug 7 at 21:34










    • As it happens, nontrivial Jordan form occurs for both endpoints, $a=5$ and $a=-27$
      – Will Jagy
      Aug 8 at 0:55










    • Perfect answer. Thank you so much
      – 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.
    – dezdichado
    Aug 7 at 21:34




    a matrix can be diagionalizable even if it has repeated eigenvalues. Take $diag(1,1,1)$ for example.
    – dezdichado
    Aug 7 at 21:34












    As it happens, nontrivial Jordan form occurs for both endpoints, $a=5$ and $a=-27$
    – Will Jagy
    Aug 8 at 0:55




    As it happens, nontrivial Jordan form occurs for both endpoints, $a=5$ and $a=-27$
    – Will Jagy
    Aug 8 at 0:55












    Perfect answer. Thank you so much
    – David Hughes
    Aug 9 at 18:54




    Perfect answer. Thank you so much
    – David Hughes
    Aug 9 at 18:54










    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



    $$
    frac136 ;
    left(
    beginarrayccc
    1&-17&-3 \
    1&19&-3 \
    6&6&18 \
    endarray
    right)
    left(
    beginarrayccc
    2&-27&-1 \
    0&2&1 \
    -1&0&-1 \
    endarray
    right)
    left(
    beginarrayccc
    10&8&3 \
    -1&1&0 \
    -3&-3&1 \
    endarray
    right) =
    left(
    beginarrayccc
    5&0&0 \
    0&-1&1 \
    0&0&-1 \
    endarray
    right)
    $$



    $$
    frac136 ;
    left(
    beginarrayccc
    10&8&3 \
    -1&1&0 \
    -3&-3&1 \
    endarray
    right)
    left(
    beginarrayccc
    5&0&0 \
    0&-1&1 \
    0&0&-1 \
    endarray
    right)
    left(
    beginarrayccc
    1&-17&-3 \
    1&19&-3 \
    6&6&18 \
    endarray
    right) =
    left(
    beginarrayccc
    2&-27&-1 \
    0&2&1 \
    -1&0&-1 \
    endarray
    right)
    $$



    =-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=






    share|cite|improve this answer























    • In case you weren't aware, you can write ---------- or <hr> to get clean HTML breaks, instead of the manual =-=
      – 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.
      – Will Jagy
      Aug 10 at 17:37














    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



    $$
    frac136 ;
    left(
    beginarrayccc
    1&-17&-3 \
    1&19&-3 \
    6&6&18 \
    endarray
    right)
    left(
    beginarrayccc
    2&-27&-1 \
    0&2&1 \
    -1&0&-1 \
    endarray
    right)
    left(
    beginarrayccc
    10&8&3 \
    -1&1&0 \
    -3&-3&1 \
    endarray
    right) =
    left(
    beginarrayccc
    5&0&0 \
    0&-1&1 \
    0&0&-1 \
    endarray
    right)
    $$



    $$
    frac136 ;
    left(
    beginarrayccc
    10&8&3 \
    -1&1&0 \
    -3&-3&1 \
    endarray
    right)
    left(
    beginarrayccc
    5&0&0 \
    0&-1&1 \
    0&0&-1 \
    endarray
    right)
    left(
    beginarrayccc
    1&-17&-3 \
    1&19&-3 \
    6&6&18 \
    endarray
    right) =
    left(
    beginarrayccc
    2&-27&-1 \
    0&2&1 \
    -1&0&-1 \
    endarray
    right)
    $$



    =-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=






    share|cite|improve this answer























    • In case you weren't aware, you can write ---------- or <hr> to get clean HTML breaks, instead of the manual =-=
      – 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.
      – Will Jagy
      Aug 10 at 17:37












    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



    $$
    frac136 ;
    left(
    beginarrayccc
    1&-17&-3 \
    1&19&-3 \
    6&6&18 \
    endarray
    right)
    left(
    beginarrayccc
    2&-27&-1 \
    0&2&1 \
    -1&0&-1 \
    endarray
    right)
    left(
    beginarrayccc
    10&8&3 \
    -1&1&0 \
    -3&-3&1 \
    endarray
    right) =
    left(
    beginarrayccc
    5&0&0 \
    0&-1&1 \
    0&0&-1 \
    endarray
    right)
    $$



    $$
    frac136 ;
    left(
    beginarrayccc
    10&8&3 \
    -1&1&0 \
    -3&-3&1 \
    endarray
    right)
    left(
    beginarrayccc
    5&0&0 \
    0&-1&1 \
    0&0&-1 \
    endarray
    right)
    left(
    beginarrayccc
    1&-17&-3 \
    1&19&-3 \
    6&6&18 \
    endarray
    right) =
    left(
    beginarrayccc
    2&-27&-1 \
    0&2&1 \
    -1&0&-1 \
    endarray
    right)
    $$



    =-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=






    share|cite|improve this answer















    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



    $$
    frac136 ;
    left(
    beginarrayccc
    1&-17&-3 \
    1&19&-3 \
    6&6&18 \
    endarray
    right)
    left(
    beginarrayccc
    2&-27&-1 \
    0&2&1 \
    -1&0&-1 \
    endarray
    right)
    left(
    beginarrayccc
    10&8&3 \
    -1&1&0 \
    -3&-3&1 \
    endarray
    right) =
    left(
    beginarrayccc
    5&0&0 \
    0&-1&1 \
    0&0&-1 \
    endarray
    right)
    $$



    $$
    frac136 ;
    left(
    beginarrayccc
    10&8&3 \
    -1&1&0 \
    -3&-3&1 \
    endarray
    right)
    left(
    beginarrayccc
    5&0&0 \
    0&-1&1 \
    0&0&-1 \
    endarray
    right)
    left(
    beginarrayccc
    1&-17&-3 \
    1&19&-3 \
    6&6&18 \
    endarray
    right) =
    left(
    beginarrayccc
    2&-27&-1 \
    0&2&1 \
    -1&0&-1 \
    endarray
    right)
    $$



    =-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=







    share|cite|improve this answer















    share|cite|improve this answer



    share|cite|improve this answer








    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 =-=
      – 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.
      – 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 =-=
      – 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.
      – 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 =-=
    – 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 =-=
    – 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.
    – 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.
    – Will Jagy
    Aug 10 at 17:37










    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.






    share|cite|improve this answer

























      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.






      share|cite|improve this answer























        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.






        share|cite|improve this answer













        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.







        share|cite|improve this answer













        share|cite|improve this answer



        share|cite|improve this answer











        answered Aug 7 at 21:26









        dezdichado

        5,3951827




        5,3951827






















             

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