Math Problem Statement

Find the minimum and maximum values of 𝑄(π‘₯)=2π‘₯2+2𝑦2+𝑧2 subject to the constraint 𝑋𝑇𝑋=𝐼.

Solution

To find the minimum and maximum values of the function Q(x,y,z)=2x2+2y2+z2Q(x, y, z) = 2x^2 + 2y^2 + z^2 subject to the constraint XTX=IX^T X = I, we can interpret XX as a vector in R3\mathbb{R}^3, i.e., X=[xyz]X = \begin{bmatrix} x \\ y \\ z \end{bmatrix}. The constraint XTX=IX^T X = I implies that the vector XX has a unit length, i.e., x2+y2+z2=1x^2 + y^2 + z^2 = 1.

Given this setup, we need to find the extrema of Q(x,y,z)=2x2+2y2+z2Q(x, y, z) = 2x^2 + 2y^2 + z^2 subject to x2+y2+z2=1x^2 + y^2 + z^2 = 1. This is a problem that can be solved using the method of Lagrange multipliers.

Step 1: Set up the Lagrangian

The Lagrangian function is given by:

L(x,y,z,Ξ»)=2x2+2y2+z2+Ξ»(1βˆ’x2βˆ’y2βˆ’z2)\mathcal{L}(x, y, z, \lambda) = 2x^2 + 2y^2 + z^2 + \lambda(1 - x^2 - y^2 - z^2)

Step 2: Find the Partial Derivatives

To find the extrema, we take partial derivatives of L\mathcal{L} with respect to xx, yy, zz, and Ξ»\lambda and set them equal to zero:

  1. Partial derivative with respect to xx: βˆ‚Lβˆ‚x=4xβˆ’2Ξ»x=0β€…β€ŠβŸΉβ€…β€Šx(4βˆ’2Ξ»)=0\frac{\partial \mathcal{L}}{\partial x} = 4x - 2\lambda x = 0 \implies x(4 - 2\lambda) = 0

  2. Partial derivative with respect to yy: βˆ‚Lβˆ‚y=4yβˆ’2Ξ»y=0β€…β€ŠβŸΉβ€…β€Šy(4βˆ’2Ξ»)=0\frac{\partial \mathcal{L}}{\partial y} = 4y - 2\lambda y = 0 \implies y(4 - 2\lambda) = 0

  3. Partial derivative with respect to zz: βˆ‚Lβˆ‚z=2zβˆ’2Ξ»z=0β€…β€ŠβŸΉβ€…β€Šz(2βˆ’2Ξ»)=0\frac{\partial \mathcal{L}}{\partial z} = 2z - 2\lambda z = 0 \implies z(2 - 2\lambda) = 0

  4. Partial derivative with respect to Ξ»\lambda: βˆ‚Lβˆ‚Ξ»=1βˆ’x2βˆ’y2βˆ’z2=0\frac{\partial \mathcal{L}}{\partial \lambda} = 1 - x^2 - y^2 - z^2 = 0

Step 3: Solve the Equations

From the first three equations, we get two possibilities for Ξ»\lambda:

  1. If Ξ»=2\lambda = 2:

    • From the equations x(4βˆ’2Ξ»)=0x(4 - 2\lambda) = 0 and y(4βˆ’2Ξ»)=0y(4 - 2\lambda) = 0, both xx and yy must be 00.
    • The constraint x2+y2+z2=1x^2 + y^2 + z^2 = 1 implies z=Β±1z = \pm 1.

    Substituting these into QQ: Q=2(02)+2(02)+12=1Q = 2(0^2) + 2(0^2) + 1^2 = 1

    So, Q=1Q = 1 in this case.

  2. If Ξ»=4\lambda = 4:

    • From z(2βˆ’2Ξ»)=0z(2 - 2\lambda) = 0, z=0z = 0.
    • Then x2+y2=1x^2 + y^2 = 1.

    Substituting these into QQ: Q=2x2+2y2+02=2(x2+y2)=2β‹…1=2Q = 2x^2 + 2y^2 + 0^2 = 2(x^2 + y^2) = 2 \cdot 1 = 2

    So, Q=2Q = 2 in this case.

Step 4: Conclusion

  • The minimum value of QQ is 1, occurring when (x,y,z)=(0,0,Β±1)(x, y, z) = (0, 0, \pm 1).
  • The maximum value of QQ is 2, occurring when (x,y,z)=(Β±1,0,0)(x, y, z) = (\pm 1, 0, 0) or (0,Β±1,0)(0, \pm 1, 0).

Would you like more details or have any questions about these steps?

Related Questions:

  1. How does the method of Lagrange multipliers work for finding extrema of functions?
  2. Can this method be used for functions with more than three variables?
  3. What are some practical applications of Lagrange multipliers?
  4. How would the solution change if the constraint were different, like x2+y2+z2=cx^2 + y^2 + z^2 = c for some c≠1c \neq 1?
  5. How would we approach this problem if the objective function had additional terms involving x,y,x, y, and zz?

Tip:

When dealing with optimization problems, always ensure the constraints are correctly interpreted and applied, as they define the feasible region where the extrema need to be found.

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Math Problem Analysis

Mathematical Concepts

Optimization
Lagrangian mechanics
Constraint optimization

Formulas

Lagrangian function

Theorems

Lagrange multipliers

Suitable Grade Level

Advanced undergraduate