Calculating the Gradient of f at (4,5)

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In summary, to find the gradient f at point (4,5), we need to use the formula D_u f = grad f (dot) u = |grad f| |u| cos theta. Using the given directional derivatives and unit vectors, we can set up two equations and solve for the two components of grad f.
  • #1
Juntao
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Consider the function z=f(x,y). If you start at the point (4,5) and move toward the point (5,6), the direction derivative is sqrt(2). Starting at (4,5) and moving toward (6,6), the directional derivative is sqrt(5). Find gradient f at (4,5).

Okay, this is probably a simple problem, but I don't know how to start it. Help appreciated.
 
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  • #2
Do you know a formula that relates gradients and directional derivatives?

What do you get when you plug what you know into that formula? (represent unknowns with variables)
 
  • #3
Forumula...*scratches head*

Um, I think this is the one, hopefully:
The derivative of f at Po in the direction of u= gradient f dot with u = magnitude grad f * magnitude u * cos theta = magnitude grad f * cos theta.

Or like D_u f= grad f (dot) u = |grad f| |u| cos theta = |grad f| cos theta

Maybe that'll help me out?
 
  • #4
D_u f= grad f (dot) u
Yes, that's true as long as u is a unit vector (has length 1).

Another way of saying this is that the directional derivative is
f_x u_x+ f_y u_y where f_x is the partial derivative and u_x is the x component of unit vector u.

Find unit vectors in both the given directions and write out
f_x u_x+ f_y u_y= √(2) and
f_x v_x+ f_y v_y= √(5).

That gives you two equations for f_x and f_y.
 
  • #5
D_u f= grad f (dot) u

That's the one of which I was thinking.

You know two instances of D_u f and u. (don't forget that u is a unit vector!), so grad f is the unknown. You have two equations, so you should be able to solve for the two components of grad f.
 

1. What is the formula for calculating the gradient of f at (4,5)?

The formula for calculating the gradient of f at a point (a,b) is:
Gradient = (change in y/change in x) = (f(b) - f(a)) / (b-a)

2. Why is it important to calculate the gradient of a function at a specific point?

The gradient at a specific point gives us information about the rate of change of the function at that point. This can be useful in many applications, such as optimization problems, finding the direction of steepest ascent or descent, and identifying critical points.

3. How do you interpret the gradient of f at (4,5)?

The gradient of f at (4,5) represents the slope of the tangent line to the function at that point. It tells us how much the function is changing in the x direction for a given change in the y direction.

4. Can the gradient of f at (4,5) be negative?

Yes, the gradient of f at (4,5) can be negative. A negative gradient indicates that the function is decreasing in the x direction at that point.

5. Are there any shortcuts or tricks for calculating the gradient of f at (4,5)?

There are no shortcuts or tricks for calculating the gradient of f at (4,5). However, if f is a multivariable function, we can use partial derivatives to calculate the gradient at a point.

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