Directional Derivative and unit vectors

In summary, a directional derivative is a measure of the rate of change of a function in a specific direction. It is calculated by taking the dot product of the gradient of the function and a unit vector in the desired direction, and can be negative, indicating a decrease in the function. Unit vectors are important in directional derivatives as they represent the direction of the change. The direction of maximum change can be determined by finding the unit vector that gives the maximum value for the directional derivative, which will be parallel to the gradient vector of the function.
  • #1
Gott_ist_tot
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What happens if a unit vector is not used in calculating the directional derivative. From when I worked it out the directional derivative is multiplied by a scalar if a unit vector is not used. So I gather that the directional derivative must be calculated by a unit vector. Because it is still calculating a rate of change and a rate of change multiplied by a number is not the same answer. I was just curious if my answer was on the right track or way off. Thanks.
 
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  • #2
Here's a more useful interpretation IMO.

In the same way as [itex] f(x+a) \approx f(x) + af'(x)[/itex] (sometimes known as Euler's approximation) in single variable calculus,

[tex]f(\vec{r}+\vec{A}) \approx f(\vec{r}) + \nabla f (\vec{r}) \cdot \vec{A}[/tex]

gives a first order approximation of the value of f(r+A).
 
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  • #3
Gott_ist_tot said:
What happens if a unit vector is not used in calculating the directional derivative. From when I worked it out the directional derivative is multiplied by a scalar if a unit vector is not used. So I gather that the directional derivative must be calculated by a unit vector. Because it is still calculating a rate of change and a rate of change multiplied by a number is not the same answer. I was just curious if my answer was on the right track or way off. Thanks.

A directional derivative is just the projection of a function's gradient along some direction. To get the projection of a vector in a particular direction you take the dot product of the vector with a unit vector in the direction you're looking at.

If you don't use a unit vector, then your directional derivative will be multiplied by the length of the vector that you do use.

quasar, I think you need to fix a few errors in your post

[tex]f(x+a) \approx f(x) + af^\prime (x)[/tex]

[tex]f(\vec{r}+\vec{A}) \approx f(\vec{r})+\vec{A} \cdot \nabla f(\vec{r})[/tex]

(note, this is basically just taking a Taylor expansion up to first-order)
 
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  • #4
Data said:
If you don't use a unit vector, then your directional derivative will be multiplied by the length of the vector that you do use.

So, in other words, if your original vector wasn't a unit vector, just divide your answer by its length:
[tex]D_{\vec{v}}f= \frac{\vec{v}\cdot\del f}{|\vec{v}|}[/itex]

Of course, since [itex]\frac{\vec{v}}{|\vec{v}|}[/itex] is the unit vector in the direction of [itex]\vec{v}[/itex], that is exactly the same as reducing to a unit vector in the first place.
 
  • #5
Strangely, \del doesn't do anything in Latex afaik. [itex]\nabla[/itex] is \nabla and [itex]\partial[/itex] is \partial. I'm sure everyone knew, but here it is anyway,

[tex]D_{\vec{v}}f= \frac{\vec{v}\cdot\nabla f}{|\vec{v}|}[/tex]
 

FAQ: Directional Derivative and unit vectors

1. What is a directional derivative?

A directional derivative is a measure of the rate of change of a function in a specific direction. It tells us how much the function is changing at a particular point along a specific direction.

2. How is a directional derivative calculated?

The directional derivative is calculated by taking the dot product of the gradient of the function and a unit vector in the desired direction. This can be represented mathematically as Duf(x,y) = ∇f(x,y) · u, where ∇f(x,y) is the gradient and u is the unit vector.

3. What is the significance of unit vectors in directional derivatives?

Unit vectors are important in directional derivatives because they represent the direction in which we want to calculate the rate of change. They have a magnitude of 1 and indicate the direction of the change.

4. Can the directional derivative be negative?

Yes, the directional derivative can be negative. A negative value indicates that the function is decreasing in the direction of the unit vector, while a positive value indicates an increase. A value of 0 indicates that there is no change in that direction.

5. How is the direction of maximum change determined using directional derivatives?

The direction of maximum change can be determined by finding the unit vector that gives the maximum value for the directional derivative. This unit vector will be parallel to the gradient vector of the function, pointing in the direction of steepest ascent.

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