What are the closest points to the origin on the level surface xy2z4=1?

In summary, the task is to find the points on the level surface xy^2z^4=1 that are closest to the origin. This can be done by using Lagrange's method for finding extrema and setting up a system of equations. By simplifying the equations and setting them equal to each other, it is determined that x= z^2/2 and y= +/- √(z^4/2). Plugging these values into the constraint xy^2z^4=1, it is found that z= (1/4)^{1/10}. This gives the point (z^2/2, +/-
  • #1
Jamin2112
986
12

Homework Statement



Find the points on the level surface xy2z4=1 that are closest to the origin.

Homework Equations



Lagrange's method for finding extrema

The Attempt at a Solution



If I have a level surface F(x,y,z)=c, it's points closest to the origin will be the ones in which the gradient vector points to the origin. A generic vector pointing to/from the origin is G=<x,y,z>, so F must be a scalar multiple of G.

I come up with a system of equations

ßx=y2z4
ßy=2xyz4
ßz=4x2z3
xy2z4=1.

I can first simplify a little bit.

ßx=y2z4
ß=2xz4
ß=4x2z2


I can set the 2nd and 3rd equations equal.

2xz4=4x2z2
----> x= z2/2

I can plug that x into the first 2 equations.

(y2z4)/[z2/2]=2[z2/2]z4
----> y = +/- √(z4/2)

Plugging those into the constraint xy2z4=1

----> z=4(1/10).

Am I right? What is the most straight-forward way of solving such a problem?
 
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  • #2
looking at [itex] xy^2z^4=1 [/itex] can make the following observations that may help later
[itex] x =\frac{1}{y^2z^4} [/itex]
so x > 1 and [itex] x,y,z \neq 0[/itex]
 
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  • #3
then i think you're doing the correct thing with the lagrange multipliers

the gradient point to the origin comes from minimising [itex] g(x,y,z) = x^2 + y^2 + z ^2 [/itex] subject to the constraint [itex] f(x,y,z) = xy^2z^4 = 1[/itex]

then taking the gradient
[tex] \nabla g(x,y,z) = \nabla(x^2 + y^2 + z ^2) = 2(x,y,z) [/tex]
note is teh direction from the origin to the point as you say

[tex] \nablaf(x,y,z) = \nabla(xy^2z^4) = (y^2z^4 ,2xyz^4 ,4xy^2z^3 )[/tex]

so i think your 3rd equation is missing a y^2
 
  • #4
Since the value of the lagrange multiplier, [itex]\beta[/itex], is not necessary to the solution, I often find it simplest to start by dividing equations to eliminate the multiplier.

Dividing [itex]\beta x= y^2z^4[/itex] by [itex]\beta y= 2xyz^4[/itex] gives
[tex]\frac{x}{y}= \frac{y^2z^4}{2xyz^4}= \frac{y}{2x}[/tex]
so that [itex]2x^2= y^2[/itex] and [itex]y= \sqrt{2}x[/itex].

Dividing [itex]\beta y= 2xyz^4[/itex] by [itex]\beta z= 4x^2z^3[/itex] gives
[tex]\frac{y}{z}= \frac{2xyz^4}{4x^2z^3}= \frac{yz}{2x}[/tex]
so that [itex]2x= z^2[/itex] and [itex]x= z^2/2[/itex] and then [itex]y= \sqrt{2}{x}= z^2/\sqrt{z}[/itex].

Putting those into the equation of the surface, [itex]xy^2z^4= 1[/itex] gives [itex](z^2/2)(z^4/2)(z^4)= z^10/4= 1[/itex] so that [itex]z= (1/4)^{1/10}[/itex].

Check my arithmetic.
 
  • #5
i don't think equation 3 is correct - shouldn't the equation set be
[tex]\beta x= y^2z^4[/tex]
[tex]\beta y = 2xyz^4 [/tex]
[tex]\beta z= 4xy^2z^3 [/tex]
[tex]1= xy^2z^4 [/tex]
 
  • #6
also as the surface is symmetric about the xy and xz axes, i'd think there should be at least 2 points... if not 4...
 
Last edited:
  • #7
1 div 2
[itex]2x^2= y^2[/itex]

1 div 3
[tex]\frac{x}{z}= \frac{y^2z^4}{4xy^2z^3 }= \frac{z}{4x}[/tex]
[tex]4x^2 = z^2[/tex]
 

Related to What are the closest points to the origin on the level surface xy2z4=1?

1. What is a Lagrange multiplier?

A Lagrange multiplier is a mathematical concept used in optimization problems to find the maximum or minimum value of a function subject to constraints.

2. When is a Lagrange multiplier used?

A Lagrange multiplier is used when a function needs to be optimized while satisfying one or more constraints.

3. How does a Lagrange multiplier work?

A Lagrange multiplier works by introducing a new variable, known as the multiplier, into the equation to represent the constraint. This variable is then used to find the extreme values of the function.

4. What is the formula for calculating a Lagrange multiplier?

The formula for calculating a Lagrange multiplier is:
λ = (gradient of the function / gradient of the constraint).

5. Can a Lagrange multiplier be used for non-linear constraints?

Yes, a Lagrange multiplier can be used for both linear and non-linear constraints. However, the process may be more complex for non-linear constraints.

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