Finding gradient vector

In summary, we are asked to find the angle between (grad)u and (grad)v at all points where x is not equal to 0 and y is not equal to 0. The equations for x and y are given in terms of u and v, and we are asked to write u and v in terms of x and y. A hint is given to start with, and the answer is determined to be pi/2.
  • #1
oahsen
59
0

Homework Statement


Find the angle between (grad)u and (grad)v at all points with x!=0 and y!= 0 if
x =( e^u)*(cos v) and y = (e^u) (sinv) .


The Attempt at a Solution



is not here x and y a function of u and v? How are we going to find grad of u and v? Should we pull out u and y from the equations (I mean if x =( e^u)*(cos v)) then u=ln(x/cosv) etc. )
 
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  • #2
No, you write u and v in terms of x and y. Here's a hint to start with: sin2x + cos2x = 1
 
  • #3
neutrino said:
No, you write u and v in terms of x and y. Here's a hint to start with: sin2x + cos2x = 1

thank you very much, ı understand. (ı found the answer as pi/2. I hope it is true)
 
  • #4
oahsen said:
ı found the answer as pi/2. I hope it is true
It's certainly true.
 

What is a gradient vector?

A gradient vector is a vector that represents the direction and magnitude of the steepest increase of a scalar field. It is perpendicular to the level curves of the scalar field.

How do you find the gradient vector?

To find the gradient vector, you take the partial derivatives of the scalar field with respect to each variable, and then combine them into a vector. This vector will point in the direction of the steepest increase of the scalar field.

What is the significance of the gradient vector in science?

The gradient vector is important in science because it helps us understand how a scalar field is changing and in which direction it is changing. This information is useful in fields such as physics, engineering, and meteorology.

What is the relationship between the gradient vector and the directional derivative?

The gradient vector and the directional derivative are closely related. The directional derivative is a scalar value that represents the rate of change of a function in a specific direction. The gradient vector points in the direction of the steepest increase of the function, so the directional derivative in that direction will be equal to the magnitude of the gradient vector.

Can the gradient vector have a negative magnitude?

Yes, the gradient vector can have a negative magnitude. This indicates that the scalar field is decreasing in that direction. However, the direction of the vector will still point in the direction of the steepest decrease of the scalar field.

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