Gradient Vector: Find the Projection of Steepest Ascent Path on xy-Plane

In summary, the hiker climbs a mountain with a height function of z= 1000-2x^2-3y^2 and when at point (1,1,995), moves on the path of steepest ascent. This path is in the direction of the gradient vector, -4xi-6yj, and has a projection of y=x^(3/2) on the xy-plane.
  • #1
plexus0208
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Homework Statement


A hiker climbs a mountain whose height is given by z = 1000 - 2x2 - 3y2.

When the hiker is at point (1,1,995), she moves on the path of steepest ascent. If she continues to move on this path, show that the projection of this path on the xy-plane is y = x3/2

Homework Equations



The Attempt at a Solution


The path of steepest ascent is in the direction in which she would ascent as rapidly as possible, aka the gradient vector.

gradf = fx i + fy j = -4x i -6y j
gradf at (1,1,995) = -4 i - 6 j

What now?
 
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  • #2
Okay, since the gradient vector always points in the direction of fastest ascent, she should be moving on a curve whose tangent vector is -4xi- 6yj. That is, dx/dt is a multiple of -4x and dy/dt is the same multiple of -6y. That means that dy/dx= (-4x)/(-6y)= 2x/dy. Solve the differential equation dy/dx= (2x)/(3y) with intial value y(1)= 1.
 
  • #3
You probably mean dy/dx = 3y/2x, not 2x/3y. But thanks a lot!
 
  • #4
yes, of course. Sorry for that.
 

FAQ: Gradient Vector: Find the Projection of Steepest Ascent Path on xy-Plane

What is a gradient vector?

A gradient vector is a mathematical concept used in multivariate calculus to represent the direction and magnitude of the steepest increase of a function at a specific point. It is represented as a vector with each component representing the partial derivative of the function with respect to a specific variable.

How do you find the projection of steepest ascent path on the xy-plane?

To find the projection of steepest ascent path on the xy-plane, you first need to calculate the gradient vector of the function at a specific point. Then, you can project this vector onto the xy-plane by setting the z-component of the vector to 0. This will give you the direction of the steepest ascent on the xy-plane.

What is the significance of finding the steepest ascent path on the xy-plane?

Finding the steepest ascent path on the xy-plane is useful in optimizing functions and finding the maximum value of a function. By following the steepest ascent path, you can reach the global maximum of a function in the shortest amount of time.

Can the steepest ascent path on the xy-plane be used to find the minimum value of a function?

No, the steepest ascent path on the xy-plane can only be used to find the maximum value of a function. To find the minimum value, you would need to find the steepest descent path, which is the opposite direction of the steepest ascent path.

Are there any limitations to using the gradient vector to find the steepest ascent path on the xy-plane?

Yes, the gradient vector method assumes that the function is continuous and differentiable at the point of interest. It also assumes that the function is unimodal, meaning it only has one global maximum. If the function is not unimodal, the steepest ascent path may not lead to the global maximum.

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