Lagrange Multipliers with ellipse

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Homework Help Overview

The discussion revolves around finding extreme values of the function f(x,y) = xy on the constraint defined by the ellipse x² + 2y² = 1. Participants are exploring the application of Lagrange multipliers in this context.

Discussion Character

  • Exploratory, Conceptual clarification, Mathematical reasoning

Approaches and Questions Raised

  • Participants are attempting to set up the Lagrange multiplier equations and are discussing the relationships between the gradients of the functions involved. Questions arise about how to proceed after establishing initial equations and solving for variables.

Discussion Status

Some participants have provided insights into manipulating the equations to reduce the number of unknowns. Others are questioning the implications of their findings and exploring the geometric interpretations of the constraints.

Contextual Notes

There are indications of confusion regarding the setup of the equations and the implications of the values of λ. The discussion includes attempts to clarify the relationships between variables under the given constraints.

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Homework Statement



Find the points on the ellipse x2 + 2y2 = 1 where f(x,y) = xy has its extreme values.

Homework Equations





The Attempt at a Solution


f(x,y,z) = x2 + y2 + z2 -- constraint
g(x,y,z) = x2 + 2y2 -1 = 0

gradient of f = [tex]\lambda[/tex] * gradient of g

2xi + 2yj + 2zk = [tex]\lambda[/tex]2xi + [tex]\lambda[/tex]4yj

2x = [tex]\lambda[/tex]2x
2y = [tex]\lambda[/tex]4y
2z = 0

I don't know where to go from here, can someone help me out?
 
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Sorry, I made a mistake in my original post, it should be:

f(x,y,z) = xy
g(x,y,z) = x2 + 2y2 - 1

yi + xj = [tex]\lambda[/tex](2xi + 4yj)
y = 2x[tex]\lambda[/tex]
x = 4y[tex]\lambda[/tex]

y = 2(4y[tex]\lambda[/tex])[tex]\lambda[/tex] = 8y[tex]\lambda[/tex]2

[tex]\lambda[/tex] = sqrt(1/8)

where do i go from here?
 
you have three equations and three unknowns... the two gradient equations and the fact that x2+2y2=1. Now that you have solved for one unknown, can you make it two equations with two unknowns?
 
How about this one:

Find the minimum distance from the surface x2 - y2 - z2 = 1 to the origin. (function being minimized = x2 + y2 + z2)

2xi + 2yj + 2zk = [tex]\lambda[/tex](2xi - 2yj -2zk)

2x = 2x[tex]\lambda[/tex]
2y = -2y[tex]\lambda[/tex]
2z = -2z[tex]\lambda[/tex]
x2 = y2 +z2 + 1

- I can't figure out how to solve this system of equations, any tips?
 
These are pretty close to being trivial. From the first equation, if [itex]x\ne 0[/itex], [itex]\lambda[/itex] must be 1. From the second equation, if [itex]y\ne 0[/itex], [itex]\lambda[/itex] must be -1, and from the third, if [itex]z\ne 0[/itex], [itex]\lambda[/itex] must be -1.

Since [itex]\lambda[/itex] cannot be both 1 and -1, at least one of the coordinates must be 0!

Suppose x= 0. Then the constraint becomes [itex]-y^2- z^2= 1[/itex] which is impossible. If x is not 0, then [itex]\lambda[/itex] must be 1, not -1, so y and z must be 0. The constraint becomes [itex]x^2= 1[/itex].

Looking at it geometrically gives an easy check. This is a "hyperboloid of two sheets" with the x-axis as axis of symmetry.
 
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