3x1²+3x2²+3x3²+2x1x2+2x1x3-2x2x3
Assume the question is as follows:
Reduce the quadratic form "3 x_{1}^{2}+3 x_{2}^{2}+3 x_{3}^{2}+2 x_{1} x_{2}+2 x_{1} x_{3}-2 x_{2} x_{3}" into 'a sum of squares' by an orthogonal transformation and give the matrix of transformation.
On comparing the given quadratic with the general quadratic "a x^{2}+b y^{2}+c z^{2}+2 f y z +2 g z x+2 h x y" , the matrix is given by
"A=\\left[\\begin{array}{lll}\n\na & h & g \\\\\n\nh & b & f \\\\\n\ng & f & c\n\n\\end{array}\\right]=\\left[\\begin{array}{rrr}\n\n3 & 1 & 1 \\\\\n\n1 & 3 & -1 \\\\\n\n1 & -1 & 3\n\n\\end{array}\\right]"
The desired characteristic equation becomes
"|A-\\lambda I|=\\left|\\begin{array}{ccc}\n\n3-\\lambda & 1 & 1 \\\\\n\n1 & 3-\\lambda & -1 \\\\\n\n1 & -1 & 3-\\lambda\n\n\\end{array}\\right|=0"
which is a cubic in "\\lambda" and has three values viz., 1,4,4.
Hence the desired canonical form i.e., 'a sum of squares' is "x^{2}+4 y^{2}+4 z^{2}" . Solving "[A-\\lambda I][X]=0" for three values of "\\lambda"
For "\\lambda=1" , we have "\\left[\\begin{array}{rrr}2 & 1 & 1 \\\\ 1 & 2 & -1 \\\\ 1 & -1 & 2\\end{array}\\right]" "\\left[\\begin{array}{l}x_{1} \\\\ y_{1} \\\\ z_{1}\\end{array}\\right]=0\n\n\\ or \\left.\\quad \\begin{array}{l}2 x_{1}+y_{1}+z_{1}=0 \\\\ x_{1}+2 y_{1}-z_{1}=0\\end{array}\\right\\}, i.e. \\frac{x_{1}}{-1-2}=\\frac{y_{1}}{1+2}=\\frac{z_{1}}{4-1}=k\n\\\\\n\\therefore"
"\\left[\\begin{array}{l}\n\nx_{1} \\\\\n\ny_{1} \\\\\n\nz_{1}\n\n\\end{array}\\right]=\\left[\\begin{array}{r}\n\n-k \\\\\n\nk \\\\\n\nk\n\n\\end{array}\\right]=\\left[\\begin{array}{r}\n\n-1 \\\\\n\n1 \\\\\n\n1\n\n\\end{array}\\right]"
Similarly for "\\lambda=4,\\left[\\begin{array}{rrr}-1 & 1 & 1 \\\\ 1 & -1 & -1 \\\\ 1 & -1 & -1\\end{array}\\right]\\left[\\begin{array}{l}x \\\\ y \\\\ z\\end{array}\\right]=0"
We have two linearly independent vectors "X_{2}=\\left[\\begin{array}{l}1 \\\\ 1 \\\\ 0\\end{array}\\right], X_{3}=\\left[\\begin{array}{l}1 \\\\ 0 \\\\ 1\\end{array}\\right]"
As the transformation has to be an orthogonal one, therefore to obtain ' P ', first divide each elements of a corresponding eigen vector by the square root of sum of the squares of its respective elements and then express as [X Y Z]
Hence the matrix of transformation, "P=\\left[\\begin{array}{ccc}\\frac{1}{\\sqrt{3}} & \\frac{1}{\\sqrt{2}} & \\frac{1}{\\sqrt{2}} \\\\ \\frac{1}{\\sqrt{3}} & \\frac{1}{\\sqrt{2}} & 0 \\\\ \\frac{1}{\\sqrt{3}} & 0 & \\frac{1}{\\sqrt{2}}\\end{array}\\right]"
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