Directional derivative of vector valued functions?

In summary, the directional derivative of a vector valued function is calculated as Lu, where L is the Frechet derivative and u is the unit vector in the direction. There are not many sources on this topic, but it can be represented as a linear function using matrix multiplication. In the case of a scalar field, a unit vector must be used to define the direction, while in the case of a vector field, any vector can be used. However, for consistency, it is recommended to use a unit vector.
  • #1
chy1013m1
15
0
Just to confirm, is the directional derivative of a vector valued function calculated as Lu ? where L is the Frechet derivative , and u is the unit vector in the direction.

There seem to be a lot of sources for a real valued function's directional derivative, but very little on vector valued function in Rm.

it says DuF(directional derivative) = lim (F(x + tu) - F(x)) / t as t->0
if F is diff'ble, then -] L , then just set h = tu, we get the desired result?..
 
Physics news on Phys.org
  • #2
There's a reason why you find "very little on vector valued function in Rm"!

If f is a differentiable function from Rm to Rn, then the derivative of f is a linear function from Rm to Rn which can be represented by a n by m matrix. In particular, the directional derivative of a n dimensional vector valued function on Rm in the direction of vector m dimensional vector v, is an n dimensional vector given by the product of the matrix representing the derivative and the vector v, represented as a column matrix.
 
  • #3
so that means, if the Fretchet derivative is L, and the directional vector is u, it is just Lu.
 
  • #4
Sorry for bringing this thread back from the dead, but I would like to clarify a doubt, if possible.

In order to calculate the directional derivative of a scalar field, we must use a unit vector to define the direction.

What happens in the case of a vector field? Does the direction also have to be defined by a unit vector, or we can use any vector?

If anyone could help, I would appreciate.
 
  • #5
Consider the derivative operator [tex]D_v[/tex]. We require it to be linear in the direction of integration, v. So [tex]D_{2v} = 2 D_v[/tex] and [tex]D_{u+v} = D_u + D_v[/tex]. In fact, this correspondence is taken to be an isomorphism in differential geometry, where tangent vectors are defined to be directional derivative operators.
 
  • #6
Thanks for your reply, but my doubt remains. :blushing:

I'll use 2 examples:


Scalar field

f(x,y)=x[tex]^{3}[/tex]y[tex]^{2}[/tex]

To find the directional derivative for this function in the point P(-1,2), in the direction of the vector a=4i-3j, we must start by finding a unit vector, u, with the same direction as a.

u=[tex]\frac{1}{\left\right\|a\|}[/tex]a = [tex]\frac{1}{5}[/tex] (4i-3j) = [tex]\frac{4}{5}[/tex]i - [tex]\frac{3}{5}[/tex]j

The result is:

Du f(x,y) = 3x[tex]^{2}[/tex]y[tex]^{2}[/tex] ([tex]\frac{4}{5}[/tex]) + 2x[tex]^{3}[/tex]y ([tex]\frac{-3}{5}[/tex])

For P(-1,2)

Du f(-1,2) = 12


Vector field

f(x,y)= (y logx, x[tex]^{3}[/tex] - 3y)

Suppose we want to find the directional derivative for this function in the point P(1,2), in the direction of the vector v=1i+4j.

My doubt is: do we need to find a unit vector or we simply use v=(1,4).

I solved it like this (but I'm not sure it's right):

Dv f(x,y) = [[y/x, logx][3x[tex]^{2}[/tex], -3]]*[[1][4]]
Dv f(1,2) = [[2][-9]]

Sorry for the matrix notation, but I couldn't get it right with LaTeX.
 
Last edited:

1. What is the definition of the directional derivative of a vector valued function?

The directional derivative of a vector valued function at a point is the rate of change of the function in the direction of a unit vector at that point.

2. How is the directional derivative of a vector valued function calculated?

The directional derivative can be calculated using the dot product between the gradient of the function and the unit vector in the desired direction. It can also be expressed using partial derivatives.

3. What is the significance of the directional derivative in vector calculus?

The directional derivative is an important concept in vector calculus as it allows us to measure the rate of change of a function in a specific direction. It is particularly useful in optimization problems and in understanding the behavior of vector fields.

4. Can the directional derivative of a vector valued function be negative?

Yes, the directional derivative can be negative if the function is decreasing in the chosen direction. It can also be zero if the function is constant in the chosen direction.

5. Are there any applications of the directional derivative in real-world problems?

Yes, the directional derivative has many applications in physics, engineering, and economics. For example, it can be used to calculate the velocity and acceleration of a moving object, determine the direction of maximum change in a physical system, and optimize production processes in industries.

Similar threads

  • Calculus and Beyond Homework Help
Replies
7
Views
1K
Replies
9
Views
703
  • Calculus and Beyond Homework Help
Replies
8
Views
454
  • Calculus and Beyond Homework Help
Replies
4
Views
1K
  • Calculus and Beyond Homework Help
Replies
2
Views
652
  • Calculus and Beyond Homework Help
Replies
2
Views
1K
  • Calculus and Beyond Homework Help
Replies
11
Views
1K
  • Calculus and Beyond Homework Help
Replies
6
Views
1K
  • Calculus and Beyond Homework Help
Replies
27
Views
708
  • Calculus and Beyond Homework Help
Replies
7
Views
963
Back
Top