Quadratic form (maxima and minima problem)

In summary, the largest value of x_{1}^2 + x_{2}^2 + x_{3}^2 when x_{1}^2 + 2x_{2}^2 + 2x_{3}^2 + 2x_{1}x_{2} + 2x_{1}x_{3} + 2x_{2}x_{3} = 1 is equal to the largest eigenvalue, 2+\sqrt{3}, and the smallest value is equal to the smallest eigenvalue, 2-\sqrt{3}.
  • #1
Combinatus
42
1

Homework Statement



Determine the largest value of [tex]x_{1}^2 + x_{2}^2 + x_{3}^2[/tex] when [tex]x_{1}^2 + 2x_{2}^2 + 2x_{3}^2 + 2x_{1}x_{2} + 2x_{1}x_{3} + 2x_{2}x_{3} = 1[/tex]

Homework Equations



Not sufficiently relevant to produce the expected answer.

The Attempt at a Solution



Completing the square, we get [tex]x_{1}^2 + 2x_{2}^2 + 2x_{3}^2 + 2x_{1}x_{2} + 2x_{1}x_{3} + 2x_{2}x_{3} = (x_1 + x_2 + x_3)^2 + x_{2}^2 + x_{3}^2 = 1[/tex].

Assigning [tex]x_{1}' = x_{1} + x_{2} + x_{3}, x_{2}' = x_{2}, x_{3}' = x_{3}[/tex] as a coordinate change (and checking that the determinant of the transformation matrix is non-zero to ensure its validity), we equivalently get [tex]x_{1} = x_{1}' - x_{2}' - x_{3}', x_{2} = x_{2}', x_{3} = x_{3}'[/tex].

Consequently, the problem can be formulated as determining the largest and smallest value of

[tex]x_{1}^2 + x_{2}^2 + x_{3}^2 = (x_{1}' - x_{2}' - x_{3}')^2 + x_{2}'^2 + x_{3}'^2 = x_{1}'^2 + 2x_{2}'^2 + 2x_{3}'^2 - 2x_{1}'x_{2}' - 2x_{1}'x_{3}' + 2x_{2}'x_{3}'[/tex] (1)

when [tex]x_{1}'^2 + x_{2}'^2 + x_{3}'^2 = 1[/tex].

Rewriting (1), we get: [tex]x_{1}'^2 + 2x_{2}'^2 + 2x_{3}'^2 - 2x_{1}'x_{2}' - 2x_{1}'x_{3}' + 2x_{2}'x_{3}' =

\begin{pmatrix}x_{1}' & x_{2}' & x_{3}' \end{pmatrix}

\begin{pmatrix}

1 & -1 & -1 \\
-1 & 2 & 1 \\
-1 & 1 & 2 \end{pmatrix}

\begin{pmatrix}x_{1}' \\ x_{2}' \\ x_{3}' \end{pmatrix} = X'^tAX' = X''^tDX'' = \lambda_{1} x''_{1}^2 + \lambda_{2} x''_{2}^2 + \lambda_{3} x''_{3}^2

[/tex]

by using the spectral theorem, the relation [tex]X' = TX''[/tex] between the bases and the orthogonality of transformation matrices between orthonormal bases. (T and D are obviously the transformation matrix between the bases and the diagonalized matrix in the orthonormal eigenvector base, respectively.)

Solving the characteristic equation [tex]\begin{vmatrix} 1-\lambda & -1 & -1\\-1 & 2-\lambda & 1\\-1 & 1 & 2-\lambda \end{vmatrix} = 0 \iff (\lambda - 1)(\lambda - (2-\sqrt{3}))(\lambda-(2+\sqrt{3})) = 0[/tex]

we get that [tex]X''^t D X'' = x''_{1}^2 + (2-\sqrt{3}) x''_{2}^2 + (2+\sqrt{3}) x''_{3}^2[/tex]

Since [tex]|X'|^2 = x_{1}'^2 + x_{2}'^2 + x_{3}'^2 = x_{1}''^2 + x_{2}''^2 + x_{3}''^2 = 1[/tex] (all bases involved are orthonormal), it follows that the largest value sought is equal to the largest eigenvalue, [tex]2+\sqrt{3}[/tex], and the smallest value sought is equal to the smallest eigenvalue, [tex]2-\sqrt{3}[/tex].Turns out that the key to the problem doesn't agree. It states that the largest value is [tex]1/(2-\sqrt{3})[/tex] and the smallest is [tex]1/(2+\sqrt{3})[/tex]. If I knew where I purportedly managed to mess up, you would not be reading this sentence. Some assistance, or perhaps a suggestion for a different approach, will be appreciated.
 
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  • #2
The key to the problem should have rationalized the denominator of its answers =)
 
  • #3
UGH. http://intp.se/whoco5.gif Note to self: FFFFUUUUUUUUUUU.

Thank you.
 
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1. What is a quadratic form?

A quadratic form is a mathematical expression that includes variables raised to the second power and may also include linear and constant terms. It is often written in the form of ax^2 + bx + c, where a, b, and c are constants and x is the variable.

2. What are the maxima and minima of a quadratic form?

The maxima and minima of a quadratic form are the highest and lowest points on the graph of the function, respectively. These points are also known as the vertex or turning points of the function.

3. How do you find the maxima and minima of a quadratic form?

To find the maxima and minima of a quadratic form, you can use the formula x = -b/2a, where a and b are the coefficients of the x^2 and x terms, respectively. This will give you the x-coordinate of the vertex. To find the y-coordinate, you can substitute this value of x into the quadratic form.

4. Can a quadratic form have more than one maxima or minima?

Yes, a quadratic form can have more than one maxima or minima. This occurs when the coefficient of the x^2 term is negative, which results in a parabola opening downwards and having a maximum point, as well as a minimum point if the coefficient of the x^2 term is positive.

5. How is a quadratic form used in real-life applications?

Quadratic forms have various uses in real-life applications, such as in physics, engineering, and economics. For example, they can be used to model the trajectory of a projectile, determine the optimal production level for a business, or calculate the maximum profit for a given cost function.

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