Max rate of descent , gradient?

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Homework Help Overview

The discussion revolves around finding the path of steepest descent along the surface defined by the equation z=x^3 + 3y^2, specifically from the point (1, -2, 13) to (0, 0, 0). The context involves concepts from multivariable calculus, particularly the gradient and directional derivatives.

Discussion Character

  • Exploratory, Conceptual clarification, Mathematical reasoning, Assumption checking

Approaches and Questions Raised

  • Participants discuss the relationship between the gradient and the direction of steepest descent, with some expressing confusion about how to apply this to the given points and the provided differential equation. There are inquiries about the directional derivative and its relevance to the problem.

Discussion Status

Some participants have suggested researching the directional derivative, while others have provided expressions for the gradient and unit vector along the path. However, there is a lack of clarity on how these elements connect to the original problem, and no consensus has been reached regarding the next steps.

Contextual Notes

Participants are grappling with the implications of the two points in the context of the problem and how the hint about the differential equation relates to finding the path of steepest descent.

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Can anyone help me with the following question?
Find the path of the steepest descent along the surface z=x^3 + 3y^2 from the point (1, -2, 13) to (0,0,0)
Note: the general solution of the differential equation f ' (t)-kf(t) =0 is
f(t) = ce^kt, where c is an arbitary number
______________________________________…


I understand that max rate of change occurs in the direction of the gradient, and max descent occurs in the -gradient(f) direction

But I don't know what to do with the 2 points..and how it has anything to do with the formula given as a hint..

Can anyone help
Thanks so much
 
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Research something called directional derivative.
 
viscousflow said:
Research something called directional derivative.

I do know what that directional derivative is, but can u give a more concrete suggestion?
 
[tex]\nabla{f}= \frac{\partial f}{\partial x} \hat{i}+\frac{\partial f}{\partial y} \hat{j}[/tex], and [tex]\hat{u}=-\frac{1}{\sqrt{5}}\hat{i}+\frac{2}{\sqrt{5}}\hat{j}[/tex] for all values along the path.
 
zcd said:
[tex]\nabla{f}= \frac{\partial f}{\partial x} \hat{i}+\frac{\partial f}{\partial y} \hat{j}[/tex], and [tex]\hat{u}=-\frac{1}{\sqrt{5}}\hat{i}+\frac{2}{\sqrt{5}}\hat{j}[/tex] for all values along the path.

thanks , but how did you get the answer??

I don't undestand it...
 
That's not the answer, but you can get direction by subtracting P-P0 and dividing by its magnitude (to make it a unit vector).
 

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