Reduction of quadratic form (principal axis)

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The discussion revolves around the challenge of reducing a quadratic form to a simple sum of squares, specifically the equation involving variables x1, x2, and x3. The user encounters nonzero off-diagonal elements in their matrix representation and attempts to diagonalize it using eigenvalues and eigenvectors. Despite calculating complex eigenvalues, it is later confirmed that the characteristic equation has all real solutions due to the symmetry of the matrix. The user learns that symmetric matrices are orthogonally diagonalizable, which resolves some confusion regarding their calculations. Overall, the exchange highlights the importance of understanding matrix properties in quadratic forms.
xman
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i keep getting nonzero off diagonal elements when i try to reduce to simple sum of squares, of the equation
2 x_{1}^{2}+2x_{2}^{2}+x_{3}^{2}+2x_{1}x_{3}+2x_{2}x_{3}
what i have is
\left(\begin{array}{ccc} x_{1} &amp; x_{2} &amp; x_{3} \end{array}\right)<br /> \left(\begin{array}{ccc}<br /> 2 &amp; 1 &amp; 0 \cr<br /> 1 &amp; 2 &amp; 1 \cr<br /> 0 &amp; 1 &amp; 1 <br /> \end{array} \right) <br /> \left(\begin{array}{c} x_{1} \cr x_{2} \cr x_{3} \end{array} \right)<br />
so my thought was to calculate the eigenvalues of the coefficient matrix above, which yield complex solutions from the characteristic equation
1-6 \lambda+5 \lambda^{2}-\lambda^{3}=0
From the complex eigenvalues I obtain complex eigenvectors, which i'll post if necessary, but are rather lengthy. From the eigenvectors I choose to use Gram-Schmidt orthogonalization to form an orthonormal basis set. From which I construct a matrix with the corresponding basis set, and use diagonalize the system I have the diagonalization matrix
D = \left(\mid n \rangle \langle m \mid \right)^{T} A \left( \mid n \rangle \langle m \mid \right)
where the matrix
\left(\mid n \rangle \langle m \mid \right)
is the orthonormal eigenvector matrix. When I'm done with all of this I'm not getting a diagonalized matrix. I was wondering if I am making a mistake in my approach, or if anyone else does get a diagonalized matrix equation.
 
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The equation 1-6x+5x^2-x^3=0 has all real solutions. You could have known this because your matrix is symmetric and symmetric matrices in the reals are orthogonally diagonalizable in the reals.
 
0rthodontist said:
The equation 1-6x+5x^2-x^3=0 has all real solutions. You could have known this because your matrix is symmetric and symmetric matrices in the reals are orthogonally diagonalizable in the reals.
That's interesting, I was bad and usinig Maxima to calculate the roots of the equation and getting imaginary components, interesting, when I plot and find the roots, you're correct the roots are all real. Thanks, for the tip, I didn't know that about symmetric matrices, either. Thanks again.
 
xman said:
That's interesting, I was bad and usinig Maxima to calculate the roots of the equation
:biggrin: I was using my TI-89.
 
Perhaps the -89 is superior to my cas, even mathematica, maple given imaginary components, though on order of 10^{-16} or so. I wonder why that is. Not to mention I'm glad I'm not the only one whose cheats on algebra parts of problems...well that may get you into trouble as I found out today. Hey thanks again.
 
Question: A clock's minute hand has length 4 and its hour hand has length 3. What is the distance between the tips at the moment when it is increasing most rapidly?(Putnam Exam Question) Answer: Making assumption that both the hands moves at constant angular velocities, the answer is ## \sqrt{7} .## But don't you think this assumption is somewhat doubtful and wrong?

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