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Distinctness of solutions to a determinant equation.
Determinant of a random matrixJacobian determinant of unitary transformationValidity of this Determinant property.Is maximizing the trace of the inverse of a positive definite matrix with eigenvalues greater than $1$ the same as minimizing the determinant?Determinant of a symmetric almost-tridiagonal matrixThe meaning and logic of the determinant of a matrix, and matrices' cofactorsWhy can the determinant be assumed to be 0?Determinant of large square matrix (term by term multiplication with same size matrix)Using Cholesky decomposition to compute covariance matrix determinantHow to find the determinant of this matrix? (A spherical-Cartesian transformation Jacobian matrix)
$begingroup$
Lets say I have a matrix A with constants x and paramater Y in the following form:
$$A=
beginbmatrix
Y & x_12 & x_13 \
x_12 & Y & x_23 \
x_13 & x_23 & Y
endbmatrix
$$
I know that if all x are the same, then $det[A] = 0$ has only one solution for Y.
My proof here is to directly compute the determinant, and then solve the suppressed cubic.
I want to also prove that if not all x are the same, that det[A]=0 has 3 distinct solutions. This is slightly more than just the converse. Directly computing is very painful, and I was able to show it only with Mathematica.
My question is how to justify these two statements more elegantly.
matrices determinant
$endgroup$
add a comment |
$begingroup$
Lets say I have a matrix A with constants x and paramater Y in the following form:
$$A=
beginbmatrix
Y & x_12 & x_13 \
x_12 & Y & x_23 \
x_13 & x_23 & Y
endbmatrix
$$
I know that if all x are the same, then $det[A] = 0$ has only one solution for Y.
My proof here is to directly compute the determinant, and then solve the suppressed cubic.
I want to also prove that if not all x are the same, that det[A]=0 has 3 distinct solutions. This is slightly more than just the converse. Directly computing is very painful, and I was able to show it only with Mathematica.
My question is how to justify these two statements more elegantly.
matrices determinant
$endgroup$
1
$begingroup$
I disagree with your first conclusion. If all $x_ij = 1$ for instance, then we end up with the solutions $Y = 1,-2$.
$endgroup$
– Omnomnomnom
3 hours ago
1
$begingroup$
In any case, your question is equivalent to asking about the multiplicity of the eigenvalues of the matrix $$ A = pmatrix0&x_12 & x_13\x_12&0&x_23\x_13&x_23&0 $$
$endgroup$
– Omnomnomnom
3 hours ago
$begingroup$
An example of a matrix where $det(A) = 0$ fails to have distinct solutions: $$ A = pmatrixY&2&3\4&Y&12\5&10&Y $$
$endgroup$
– Omnomnomnom
3 hours ago
1
$begingroup$
Please note that the proposed matrix $A$ is symmetric! This means your conterexample isn't one.
$endgroup$
– Ingix
3 hours ago
add a comment |
$begingroup$
Lets say I have a matrix A with constants x and paramater Y in the following form:
$$A=
beginbmatrix
Y & x_12 & x_13 \
x_12 & Y & x_23 \
x_13 & x_23 & Y
endbmatrix
$$
I know that if all x are the same, then $det[A] = 0$ has only one solution for Y.
My proof here is to directly compute the determinant, and then solve the suppressed cubic.
I want to also prove that if not all x are the same, that det[A]=0 has 3 distinct solutions. This is slightly more than just the converse. Directly computing is very painful, and I was able to show it only with Mathematica.
My question is how to justify these two statements more elegantly.
matrices determinant
$endgroup$
Lets say I have a matrix A with constants x and paramater Y in the following form:
$$A=
beginbmatrix
Y & x_12 & x_13 \
x_12 & Y & x_23 \
x_13 & x_23 & Y
endbmatrix
$$
I know that if all x are the same, then $det[A] = 0$ has only one solution for Y.
My proof here is to directly compute the determinant, and then solve the suppressed cubic.
I want to also prove that if not all x are the same, that det[A]=0 has 3 distinct solutions. This is slightly more than just the converse. Directly computing is very painful, and I was able to show it only with Mathematica.
My question is how to justify these two statements more elegantly.
matrices determinant
matrices determinant
edited 4 hours ago
Ion Sme
asked 4 hours ago
Ion SmeIon Sme
12510
12510
1
$begingroup$
I disagree with your first conclusion. If all $x_ij = 1$ for instance, then we end up with the solutions $Y = 1,-2$.
$endgroup$
– Omnomnomnom
3 hours ago
1
$begingroup$
In any case, your question is equivalent to asking about the multiplicity of the eigenvalues of the matrix $$ A = pmatrix0&x_12 & x_13\x_12&0&x_23\x_13&x_23&0 $$
$endgroup$
– Omnomnomnom
3 hours ago
$begingroup$
An example of a matrix where $det(A) = 0$ fails to have distinct solutions: $$ A = pmatrixY&2&3\4&Y&12\5&10&Y $$
$endgroup$
– Omnomnomnom
3 hours ago
1
$begingroup$
Please note that the proposed matrix $A$ is symmetric! This means your conterexample isn't one.
$endgroup$
– Ingix
3 hours ago
add a comment |
1
$begingroup$
I disagree with your first conclusion. If all $x_ij = 1$ for instance, then we end up with the solutions $Y = 1,-2$.
$endgroup$
– Omnomnomnom
3 hours ago
1
$begingroup$
In any case, your question is equivalent to asking about the multiplicity of the eigenvalues of the matrix $$ A = pmatrix0&x_12 & x_13\x_12&0&x_23\x_13&x_23&0 $$
$endgroup$
– Omnomnomnom
3 hours ago
$begingroup$
An example of a matrix where $det(A) = 0$ fails to have distinct solutions: $$ A = pmatrixY&2&3\4&Y&12\5&10&Y $$
$endgroup$
– Omnomnomnom
3 hours ago
1
$begingroup$
Please note that the proposed matrix $A$ is symmetric! This means your conterexample isn't one.
$endgroup$
– Ingix
3 hours ago
1
1
$begingroup$
I disagree with your first conclusion. If all $x_ij = 1$ for instance, then we end up with the solutions $Y = 1,-2$.
$endgroup$
– Omnomnomnom
3 hours ago
$begingroup$
I disagree with your first conclusion. If all $x_ij = 1$ for instance, then we end up with the solutions $Y = 1,-2$.
$endgroup$
– Omnomnomnom
3 hours ago
1
1
$begingroup$
In any case, your question is equivalent to asking about the multiplicity of the eigenvalues of the matrix $$ A = pmatrix0&x_12 & x_13\x_12&0&x_23\x_13&x_23&0 $$
$endgroup$
– Omnomnomnom
3 hours ago
$begingroup$
In any case, your question is equivalent to asking about the multiplicity of the eigenvalues of the matrix $$ A = pmatrix0&x_12 & x_13\x_12&0&x_23\x_13&x_23&0 $$
$endgroup$
– Omnomnomnom
3 hours ago
$begingroup$
An example of a matrix where $det(A) = 0$ fails to have distinct solutions: $$ A = pmatrixY&2&3\4&Y&12\5&10&Y $$
$endgroup$
– Omnomnomnom
3 hours ago
$begingroup$
An example of a matrix where $det(A) = 0$ fails to have distinct solutions: $$ A = pmatrixY&2&3\4&Y&12\5&10&Y $$
$endgroup$
– Omnomnomnom
3 hours ago
1
1
$begingroup$
Please note that the proposed matrix $A$ is symmetric! This means your conterexample isn't one.
$endgroup$
– Ingix
3 hours ago
$begingroup$
Please note that the proposed matrix $A$ is symmetric! This means your conterexample isn't one.
$endgroup$
– Ingix
3 hours ago
add a comment |
2 Answers
2
active
oldest
votes
$begingroup$
Your first proposition is generally incorrect. If $x_12=x_13=x_23=x$, then both $Y_1,2=x$ and $Y_3=-2x$ are solutions of $det[A]=0$. Those are different for $x neq0$. In that case, the first solution has algebraic and geometric multiplicity $2$, the second algebraic and geometric multiplicity $1$.
ADDED after more thoughts about the second proposition:
The second proposition is true. It is easy to see that
$$det[A]=f(Y)=Y^3 + 2x_12x_13x_23 - Y(x^2_12 + x^2_13 + x^2_23)$$.
In order for $f(Y)=0$ to have a root with multiplicity > 1, it has to be also a root of $f'(Y)=0$, which means
$$f'(Y)=3Y^2-(x^2_12 + x^2_13 + x^2_23)=0,$$
which implies
$$Y=pmsqrtfracx^2_12 + x^2_13 + x^2_233.$$
Putting this into $f(Y)=0$ we get
$$0 = f(Y)=Y(Y^2-(x^2_12 + x^2_13 + x^2_23)) + 2x_12x_13x_23=-frac23(x^2_12 + x^2_13 + x^2_23)Y + 2x_12x_13x_23$$
which implies
$$x_12x_13x_23 = frac13(x^2_12 + x^2_13 + x^2_23)Y.$$
Squaring both sides yields to
$$(x_12x_13x_23)^2=frac19(x^2_12 + x^2_13 + x^2_23)^2Y^2 = frac19(x^2_12 + x^2_13 + x^2_23)^2fracx^2_12 + x^2_13 + x^2_233 =frac127(x^2_12 + x^2_13 + x^2_23)^3$$
This is the same condition as Yves Daoust arrived in his answer.
Now if we assume that all the $x_ij$ are real numbers, then this condition indeed implies that all $x_ij$ must be the same. That's because, as every $x_ij$ appears squared, we can generally assume that all $x_ij ge 0$. The one can apply the theorem of the inequality of quadratic and geometric mean:
$$sqrt[3]x_12x_13x_23 le sqrtfracx^2_12 + x^2_13 + x^2_233$$
Putting this inequality to the 6th power leads to
$$(x_12x_13x_23)^2le frac127(x^2_12 + x^2_13 + x^2_23)^3$$
and we know that equality (as required for a solution for $Y$ with multiplicity > 1) only happens if $x_12=x_13=x_23$.
$endgroup$
add a comment |
$begingroup$
The polynomial is
$$y^3-(x_12^2+x_23^2+x_13^2)y+2x_12x_23x_13.$$
The multiplicity of the roots is determined by the discriminant,
$$4p^3+27q^2propto-(x_12^2+x_23^2+x_13^2)^3+27(x_12x_23x_13)^2.$$
$endgroup$
add a comment |
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2 Answers
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active
oldest
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2 Answers
2
active
oldest
votes
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oldest
votes
$begingroup$
Your first proposition is generally incorrect. If $x_12=x_13=x_23=x$, then both $Y_1,2=x$ and $Y_3=-2x$ are solutions of $det[A]=0$. Those are different for $x neq0$. In that case, the first solution has algebraic and geometric multiplicity $2$, the second algebraic and geometric multiplicity $1$.
ADDED after more thoughts about the second proposition:
The second proposition is true. It is easy to see that
$$det[A]=f(Y)=Y^3 + 2x_12x_13x_23 - Y(x^2_12 + x^2_13 + x^2_23)$$.
In order for $f(Y)=0$ to have a root with multiplicity > 1, it has to be also a root of $f'(Y)=0$, which means
$$f'(Y)=3Y^2-(x^2_12 + x^2_13 + x^2_23)=0,$$
which implies
$$Y=pmsqrtfracx^2_12 + x^2_13 + x^2_233.$$
Putting this into $f(Y)=0$ we get
$$0 = f(Y)=Y(Y^2-(x^2_12 + x^2_13 + x^2_23)) + 2x_12x_13x_23=-frac23(x^2_12 + x^2_13 + x^2_23)Y + 2x_12x_13x_23$$
which implies
$$x_12x_13x_23 = frac13(x^2_12 + x^2_13 + x^2_23)Y.$$
Squaring both sides yields to
$$(x_12x_13x_23)^2=frac19(x^2_12 + x^2_13 + x^2_23)^2Y^2 = frac19(x^2_12 + x^2_13 + x^2_23)^2fracx^2_12 + x^2_13 + x^2_233 =frac127(x^2_12 + x^2_13 + x^2_23)^3$$
This is the same condition as Yves Daoust arrived in his answer.
Now if we assume that all the $x_ij$ are real numbers, then this condition indeed implies that all $x_ij$ must be the same. That's because, as every $x_ij$ appears squared, we can generally assume that all $x_ij ge 0$. The one can apply the theorem of the inequality of quadratic and geometric mean:
$$sqrt[3]x_12x_13x_23 le sqrtfracx^2_12 + x^2_13 + x^2_233$$
Putting this inequality to the 6th power leads to
$$(x_12x_13x_23)^2le frac127(x^2_12 + x^2_13 + x^2_23)^3$$
and we know that equality (as required for a solution for $Y$ with multiplicity > 1) only happens if $x_12=x_13=x_23$.
$endgroup$
add a comment |
$begingroup$
Your first proposition is generally incorrect. If $x_12=x_13=x_23=x$, then both $Y_1,2=x$ and $Y_3=-2x$ are solutions of $det[A]=0$. Those are different for $x neq0$. In that case, the first solution has algebraic and geometric multiplicity $2$, the second algebraic and geometric multiplicity $1$.
ADDED after more thoughts about the second proposition:
The second proposition is true. It is easy to see that
$$det[A]=f(Y)=Y^3 + 2x_12x_13x_23 - Y(x^2_12 + x^2_13 + x^2_23)$$.
In order for $f(Y)=0$ to have a root with multiplicity > 1, it has to be also a root of $f'(Y)=0$, which means
$$f'(Y)=3Y^2-(x^2_12 + x^2_13 + x^2_23)=0,$$
which implies
$$Y=pmsqrtfracx^2_12 + x^2_13 + x^2_233.$$
Putting this into $f(Y)=0$ we get
$$0 = f(Y)=Y(Y^2-(x^2_12 + x^2_13 + x^2_23)) + 2x_12x_13x_23=-frac23(x^2_12 + x^2_13 + x^2_23)Y + 2x_12x_13x_23$$
which implies
$$x_12x_13x_23 = frac13(x^2_12 + x^2_13 + x^2_23)Y.$$
Squaring both sides yields to
$$(x_12x_13x_23)^2=frac19(x^2_12 + x^2_13 + x^2_23)^2Y^2 = frac19(x^2_12 + x^2_13 + x^2_23)^2fracx^2_12 + x^2_13 + x^2_233 =frac127(x^2_12 + x^2_13 + x^2_23)^3$$
This is the same condition as Yves Daoust arrived in his answer.
Now if we assume that all the $x_ij$ are real numbers, then this condition indeed implies that all $x_ij$ must be the same. That's because, as every $x_ij$ appears squared, we can generally assume that all $x_ij ge 0$. The one can apply the theorem of the inequality of quadratic and geometric mean:
$$sqrt[3]x_12x_13x_23 le sqrtfracx^2_12 + x^2_13 + x^2_233$$
Putting this inequality to the 6th power leads to
$$(x_12x_13x_23)^2le frac127(x^2_12 + x^2_13 + x^2_23)^3$$
and we know that equality (as required for a solution for $Y$ with multiplicity > 1) only happens if $x_12=x_13=x_23$.
$endgroup$
add a comment |
$begingroup$
Your first proposition is generally incorrect. If $x_12=x_13=x_23=x$, then both $Y_1,2=x$ and $Y_3=-2x$ are solutions of $det[A]=0$. Those are different for $x neq0$. In that case, the first solution has algebraic and geometric multiplicity $2$, the second algebraic and geometric multiplicity $1$.
ADDED after more thoughts about the second proposition:
The second proposition is true. It is easy to see that
$$det[A]=f(Y)=Y^3 + 2x_12x_13x_23 - Y(x^2_12 + x^2_13 + x^2_23)$$.
In order for $f(Y)=0$ to have a root with multiplicity > 1, it has to be also a root of $f'(Y)=0$, which means
$$f'(Y)=3Y^2-(x^2_12 + x^2_13 + x^2_23)=0,$$
which implies
$$Y=pmsqrtfracx^2_12 + x^2_13 + x^2_233.$$
Putting this into $f(Y)=0$ we get
$$0 = f(Y)=Y(Y^2-(x^2_12 + x^2_13 + x^2_23)) + 2x_12x_13x_23=-frac23(x^2_12 + x^2_13 + x^2_23)Y + 2x_12x_13x_23$$
which implies
$$x_12x_13x_23 = frac13(x^2_12 + x^2_13 + x^2_23)Y.$$
Squaring both sides yields to
$$(x_12x_13x_23)^2=frac19(x^2_12 + x^2_13 + x^2_23)^2Y^2 = frac19(x^2_12 + x^2_13 + x^2_23)^2fracx^2_12 + x^2_13 + x^2_233 =frac127(x^2_12 + x^2_13 + x^2_23)^3$$
This is the same condition as Yves Daoust arrived in his answer.
Now if we assume that all the $x_ij$ are real numbers, then this condition indeed implies that all $x_ij$ must be the same. That's because, as every $x_ij$ appears squared, we can generally assume that all $x_ij ge 0$. The one can apply the theorem of the inequality of quadratic and geometric mean:
$$sqrt[3]x_12x_13x_23 le sqrtfracx^2_12 + x^2_13 + x^2_233$$
Putting this inequality to the 6th power leads to
$$(x_12x_13x_23)^2le frac127(x^2_12 + x^2_13 + x^2_23)^3$$
and we know that equality (as required for a solution for $Y$ with multiplicity > 1) only happens if $x_12=x_13=x_23$.
$endgroup$
Your first proposition is generally incorrect. If $x_12=x_13=x_23=x$, then both $Y_1,2=x$ and $Y_3=-2x$ are solutions of $det[A]=0$. Those are different for $x neq0$. In that case, the first solution has algebraic and geometric multiplicity $2$, the second algebraic and geometric multiplicity $1$.
ADDED after more thoughts about the second proposition:
The second proposition is true. It is easy to see that
$$det[A]=f(Y)=Y^3 + 2x_12x_13x_23 - Y(x^2_12 + x^2_13 + x^2_23)$$.
In order for $f(Y)=0$ to have a root with multiplicity > 1, it has to be also a root of $f'(Y)=0$, which means
$$f'(Y)=3Y^2-(x^2_12 + x^2_13 + x^2_23)=0,$$
which implies
$$Y=pmsqrtfracx^2_12 + x^2_13 + x^2_233.$$
Putting this into $f(Y)=0$ we get
$$0 = f(Y)=Y(Y^2-(x^2_12 + x^2_13 + x^2_23)) + 2x_12x_13x_23=-frac23(x^2_12 + x^2_13 + x^2_23)Y + 2x_12x_13x_23$$
which implies
$$x_12x_13x_23 = frac13(x^2_12 + x^2_13 + x^2_23)Y.$$
Squaring both sides yields to
$$(x_12x_13x_23)^2=frac19(x^2_12 + x^2_13 + x^2_23)^2Y^2 = frac19(x^2_12 + x^2_13 + x^2_23)^2fracx^2_12 + x^2_13 + x^2_233 =frac127(x^2_12 + x^2_13 + x^2_23)^3$$
This is the same condition as Yves Daoust arrived in his answer.
Now if we assume that all the $x_ij$ are real numbers, then this condition indeed implies that all $x_ij$ must be the same. That's because, as every $x_ij$ appears squared, we can generally assume that all $x_ij ge 0$. The one can apply the theorem of the inequality of quadratic and geometric mean:
$$sqrt[3]x_12x_13x_23 le sqrtfracx^2_12 + x^2_13 + x^2_233$$
Putting this inequality to the 6th power leads to
$$(x_12x_13x_23)^2le frac127(x^2_12 + x^2_13 + x^2_23)^3$$
and we know that equality (as required for a solution for $Y$ with multiplicity > 1) only happens if $x_12=x_13=x_23$.
edited 3 hours ago
answered 3 hours ago
IngixIngix
5,477259
5,477259
add a comment |
add a comment |
$begingroup$
The polynomial is
$$y^3-(x_12^2+x_23^2+x_13^2)y+2x_12x_23x_13.$$
The multiplicity of the roots is determined by the discriminant,
$$4p^3+27q^2propto-(x_12^2+x_23^2+x_13^2)^3+27(x_12x_23x_13)^2.$$
$endgroup$
add a comment |
$begingroup$
The polynomial is
$$y^3-(x_12^2+x_23^2+x_13^2)y+2x_12x_23x_13.$$
The multiplicity of the roots is determined by the discriminant,
$$4p^3+27q^2propto-(x_12^2+x_23^2+x_13^2)^3+27(x_12x_23x_13)^2.$$
$endgroup$
add a comment |
$begingroup$
The polynomial is
$$y^3-(x_12^2+x_23^2+x_13^2)y+2x_12x_23x_13.$$
The multiplicity of the roots is determined by the discriminant,
$$4p^3+27q^2propto-(x_12^2+x_23^2+x_13^2)^3+27(x_12x_23x_13)^2.$$
$endgroup$
The polynomial is
$$y^3-(x_12^2+x_23^2+x_13^2)y+2x_12x_23x_13.$$
The multiplicity of the roots is determined by the discriminant,
$$4p^3+27q^2propto-(x_12^2+x_23^2+x_13^2)^3+27(x_12x_23x_13)^2.$$
answered 3 hours ago
Yves DaoustYves Daoust
135k676233
135k676233
add a comment |
add a comment |
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1
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I disagree with your first conclusion. If all $x_ij = 1$ for instance, then we end up with the solutions $Y = 1,-2$.
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– Omnomnomnom
3 hours ago
1
$begingroup$
In any case, your question is equivalent to asking about the multiplicity of the eigenvalues of the matrix $$ A = pmatrix0&x_12 & x_13\x_12&0&x_23\x_13&x_23&0 $$
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– Omnomnomnom
3 hours ago
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An example of a matrix where $det(A) = 0$ fails to have distinct solutions: $$ A = pmatrixY&2&3\4&Y&12\5&10&Y $$
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– Omnomnomnom
3 hours ago
1
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Please note that the proposed matrix $A$ is symmetric! This means your conterexample isn't one.
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– Ingix
3 hours ago