The temperature on a unit sphere, x 2 + y 2 + z 2 = 1 , is given by a temperature distribution T ( x , y , z ) = 5 0 ∘ C ⋅ ( x ⋅ y + y ⋅ z ) What is the temperature difference between the coldest and warmest point on the sphere (in celsius)?
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Rotating the coordinate system ( X = 2 1 ( x + z ) , Y = y , Z = 2 1 ( x − z ) ), ...
How are you immediately able to rotate the Cartesian plane so effortlessly? Is there some linear algebra trick involved?
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We are, essentially, being asked to extremize ( x + z ) y over a sphere. When extremizing over a sphere, considering rotated coordinates is always worth a shot. The necessary coordinates tend to leap out at you (the vectors ( 1 0 1 ) T and ( 0 1 0 ) T are orthogonal, so it is easy to scale them to make them part of an orthonormal triad, which is what is needed to rotate coordinates).
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Thanks. I knew I just barely scratched the surface when I learned about rotating the coordinate system in precalculus.
How can I upvote a comment? No seriously, I know it's impossible for you to see this, but I've been printing and collating a lot of what you've written on this site, even when I'm NOT inside the conversation. I couldn't thank you enough.
The task is:
maximize/minimize f ( x , y , z ) under the constrain g ( x , y , z ) = 0
where f ( x , y , z ) = x y + y z and g ( x , y , z ) = x 2 + y 2 + z 2 − 1 .
To solve this, we use the method of Lagrange multipliers. Thus, stationary points of the function f ( x , y , z ) on the spherical surface satisfy the equation ∇ f ( x , y , z ) = λ ⋅ ∇ g ( x , y , z ) with some constant λ ∈ R (Lagrange multiplier). So we get the equation system ⇒ ⇒ ⎝ ⎛ y x + z y ⎠ ⎞ x = z ( λ 1 − 2 λ ) y = 2 λ ⎝ ⎛ x y z ⎠ ⎞ = 2 λ y = 0 The last equation can be solved with y = 0 or λ = ± 1 / 2 . The fact that we also choose an additional sign freely, results in a total of 6 different stationary points: ⎝ ⎛ x y z ⎠ ⎞ = ⎝ ⎛ ± 1 / 2 0 ± 1 / 2 ⎠ ⎞ , ⎝ ⎛ ± 1 / 2 ± 1 / 2 ± 1 / 2 ⎠ ⎞ , ⎝ ⎛ ∓ 1 / 2 ± 1 / 2 ∓ 1 / 2 ⎠ ⎞ with the functional values f ( x , y , z ) = 0 , 2 1 , − 2 1 corresponding to a saddle point, maximum and a minimum. The temperature difference between the coldest and the warmest point results accordingly T hot − T cold = 5 0 ∘ C ⋅ ( 2 1 − ( − 2 1 ) ) = 2 ⋅ 5 0 ∘ C ≈ 7 0 . 7 1 ∘ C
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Rotating the coordinate system ( X = 2 1 ( x + z ) , Y = y , Z = 2 1 ( x − z ) ), this problem is equivalent to that of maximizing/minimizing f ( X , Y , Z ) = 5 0 2 X Y subject to X 2 + Y 2 + Z 2 = 1 . Now 2 ∣ X Y ∣ ≤ X 2 + Y 2 ≤ X 2 + Y 2 + Z 2 = 1 and hence − 2 5 2 ≤ f ( X , Y , Z ) ≤ 2 5 2 subject to the constraint. The maximum is achieved with X = Y = 2 1 , Z = 0 , while the minimum is achieved with X = − Y = 2 1 , Z = 0 . Thus the required temperature difference is 5 0 2 ∘ C.