Directional Derivative at an Angle from the Gradient

In summary: Does that make sense?In summary, the conversation discusses finding the directional derivative of a function at a specific point in a given direction. The first two parts of the problem involve finding the directional derivative in a specific direction, with the second part requiring the use of the gradient vector. The final part asks for the direction in which the directional derivative is largest, which is in the direction of the gradient vector. The conversation also mentions using geometric and trigonometric methods to find the unit vector in a given direction.
  • #1
Drakkith
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Homework Statement


(a) Find the directional derivative of z = x2y at (3,4) in the direction of 3π/4 with the x-axis. Give an exact answer.

(b) Find the directional derivative of z = x2y at (3,4) in the direction that makes an angle of 3π/4 with the gradient vector at (3,4). Give an exact answer.

(c) In which direction is the directional derivative the largest? Give your answer as a vector.

Homework Equations


##F\vec u (a,b) = \nabla F(a,b) \cdot \vec u##

Found the following two equations using the one above:
##\nabla F(3,4) = \langle 24,9 \rangle##
##\frac { \vec \nabla F(3,4)} {\left\|\vec \nabla F(3,4)\right\|} = \langle \frac {8}{\sqrt{73}},\frac {3} {\sqrt {73}} \rangle ##

The Attempt at a Solution



A. I found the directional derivative as ##\frac {-15}{\sqrt{2}}##.

B. I'm stuck here. I can't seem to figure out how to get the unit vector I need to dot the gradient with.
I've tried using the geometric and algebraic definitions of the dot product and the fact that##\sqrt{{u_1}^2 + {u_2}^2} = 1## to find each component of u, but I'm just getting garbage as an answer (1 = not 1 ?:)). Part of the problem is that I'm supposed to give an exact answer, which I haven't quite figured out how to do yet.

I just tried to use some trig logic to get the angles I need, but it doesn't seem to be working either.
Since ##θ = arccos (x)##, and ##θ = arcsin (y)##, I set my unit vector to ##\vec u = \langle cos(\frac {3π}{4} + arccos\frac {8}{\sqrt{73}}), sin(\frac {3π}{4} + arcsin\frac {3}{\sqrt{73}})\rangle## and dotted it with the gradient, but that's wrong as well.

C. Haven't gotten to this part yet.

The good news is that after 6 years on PF, I've finally learned the basics of LaTeX! :rolleyes:
 
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  • #2
Drakkith said:

Homework Statement


(a) Find the directional derivative of z = x2y at (3,4) in the direction of 3π/4 with the x-axis. Give an exact answer.

Do you mean ##x^2y##?

(b) Find the directional derivative of z = x2y at (3,4) in the direction that makes an angle of 3π/4 with the gradient vector at (3,4). Give an exact answer.

(c) In which direction is the directional derivative the largest? Give your answer as a vector.

Homework Equations


##F\vec u (a,b) = \nabla F(a,b) \cdot \vec u##

Found the following two equations using the one above:
##\nabla F(3,4) = \langle 24,9 \rangle##
##\frac { \vec \nabla F(3,4)} {\left\|\vec \nabla F(3,4)\right\|} = \langle \frac {8}{\sqrt{73}},\frac {3} {\sqrt {73}} \rangle ##

The Attempt at a Solution



A. I found the directional derivative as ##\frac {-15}{\sqrt{2}}##.

B. I'm stuck here. I can't seem to figure out how to get the unit vector I need to dot the gradient with.
I've tried using the geometric and algebraic definitions of the dot product and the fact that##\sqrt{{u_1}^2 + {u_2}^2} = 1## to find each component of u, but I'm just getting garbage as an answer (1 = not 1 ?:)). Part of the problem is that I'm supposed to give an exact answer, which I haven't quite figured out how to do yet.

I just tried to use some trig logic to get the angles I need, but it doesn't seem to be working either.
Since ##θ = arccos (x)##, and ##θ = arcsin (y)##, I set my unit vector to ##\vec u = \langle cos(\frac {3π}{4} + arccos\frac {8}{\sqrt{73}}), sin(\frac {3π}{4} + arcsin\frac {3}{\sqrt{73}})\rangle## and dotted it with the gradient, but that's wrong as well.

C. Haven't gotten to this part yet.

The good news is that after 6 years on PF, I've finally learned the basics of LaTeX! :rolleyes:

I will give you a hint on how to find that vector for (b). Let's start with ##\vec v = \langle 8,3\rangle## which is in the direction of your gradient. Two vectors perpendicular to ##\vec v## are ##\langle -3,8\rangle## and ##\langle 3,-8\rangle## (obvious from the dot product = 0). Draw these three vectors and also ##-\vec v## at the origin. Do you see in that picture two vectors you could add to give you a vector in the direction ##\frac{3\pi}{4}## from ##\vec v##? If so, make it a unit vector and proceed.
 
  • #3
LCKurtz said:
Do you mean x^2y?

Indeed.

LCKurtz said:
I will give you a hint on how to find that vector for (b). Let's start with ⃗v=⟨8,3⟩v→=⟨8,3⟩\vec v = \langle 8,3\rangle which is in the direction of your gradient. Two vectors perpendicular to ⃗vv→\vec v are ⟨−3,8⟩⟨−3,8⟩\langle -3,8\rangle and ⟨3,−8⟩⟨3,−8⟩\langle 3,-8\rangle (obvious from the dot product = 0). Draw these three vectors and also −⃗v−v→-\vec v at the origin. Do you see in that picture two vectors you could add to give you a vector in the direction 3π43π4\frac{3\pi}{4} from ⃗vv→\vec v? If so, make it a unit vector and proceed.

That worked perfectly.

B. The answer is ##-\frac{657}{\sqrt{1314}}##

C. The answer is ##\left\langle 24,9\right\rangle ##

Thanks, Kurtz.
 
  • #4
Drakkith said:
Indeed.
That worked perfectly.

B. The answer is ##-\frac{657}{\sqrt{1314}}##

C. The answer is ##\left\langle 24,9\right\rangle ##

Thanks, Kurtz.

I hope you realize that for any ##f(x_1, x_2, \ldots, x_n)## the directional derivative is largest in the direction ##\nabla f##, and the proof is extremely easy.
 
  • #5
Ray Vickson said:
I hope you realize that for any ##f(x_1, x_2, \ldots, x_n)## the directional derivative is largest in the direction ##\nabla f##, and the proof is extremely easy.

Yep. There's several examples in my book that I've gone through.
 
  • #6
Drakkith said:
Indeed.
That worked perfectly.

B. The answer is ##-\frac{657}{\sqrt{1314}}##

Are you sure about that answer? What did you get for your unit vector in the new direction?
[Edit, added]: That answer is correct but it can be reduced.

Of course, the geometric trick I just showed you depended on the fact that the angle ##\frac{3\pi}{4}## is easy to construct geometrically. But what if you had wanted to rotate the vector clockwise by an arbitrary angle ##\theta##? If you have studied the complex plane, you know that if you represent a vector ##z=\langle a,b \rangle## as ##a + bi## and multiply it by the complex number ##e^{i\theta}##, the result rotates ##z## by the angle ##\theta##. In your problem you would multiply by ##e^{\frac {3\pi i} 4} = \cos(\frac {3\pi i} 4) + i \sin(\frac {3\pi i} 4) = -\frac 1 {\sqrt 2} + i\frac 1 {\sqrt 2}##. You could use this idea to check your work above.
 
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  • #7
LCKurtz said:
Are you sure about that answer?

The online program accepted it as a correct answer.

LCKurtz said:
What did you get for your unit vector in the new direction?

##\langle \frac {-33}{\sqrt{1314}}, \frac{15}{\sqrt{1314}}\rangle##

LCKurtz said:
But what if you had wanted to rotate the vector clockwise by an arbitrary angle θθ\theta? If you have studied the complex plane, you know that if you represent a vector z=⟨a,b⟩z=⟨a,b⟩z=\langle a,b \rangle as a+bia+bia + bi and multiply it by the complex number eiθeiθe^{i\theta}, the result rotates zzz by the angle θθ\theta. In your problem you would multiply by e3πi4=cos(3πi4)+isin(3πi4)=−1√2+i1√2e3πi4=cos⁡(3πi4)+isin⁡(3πi4)=−12+i12e^{\frac {3\pi i} 4} = \cos(\frac {3\pi i} 4) + i \sin(\frac {3\pi i} 4) = -\frac 1 {\sqrt 2} + i\frac 1 {\sqrt 2}. You could use this idea to check your work above.

I have not studied the complex plane but I'll try to remember this. Thanks Kurtz.
 
  • #8
I edited my answer about the same time that you replied noting that your answer is correct but that it can be reduced. You can factor a 3 out of both numerator and denominator. Ditto for your unit vector.
 
  • #9
LCKurtz said:
I edited my answer about the same time that you replied noting that your answer is correct but that it can be reduced. You can factor a 3 out of both numerator and denominator. Ditto for your unit vector.

Roger!
 

FAQ: Directional Derivative at an Angle from the Gradient

1. What is the directional derivative at an angle from the gradient?

The directional derivative at an angle from the gradient is a measure of how much a function changes in a particular direction. It takes into account both the rate of change of the function and the direction in which the change is occurring.

2. How is the directional derivative at an angle from the gradient calculated?

The directional derivative at an angle from the gradient is calculated by taking the dot product of the gradient vector and a unit vector in the desired direction. This can also be expressed as the product of the magnitude of the gradient and the cosine of the angle between the gradient and the direction vector.

3. What does the directional derivative at an angle from the gradient tell us?

The directional derivative at an angle from the gradient tells us the rate of change of a function in a specific direction. It can also indicate the direction in which the function is increasing or decreasing the most.

4. How is the directional derivative at an angle from the gradient used in real-world applications?

The directional derivative at an angle from the gradient is used in various fields of science and engineering, such as physics, economics, and computer graphics. It is particularly useful in optimization problems, where the goal is to find the maximum or minimum value of a function.

5. What happens when the direction vector is parallel to the gradient vector?

If the direction vector is parallel to the gradient vector, the directional derivative at an angle from the gradient will be equal to the magnitude of the gradient. This means that the function is changing at its maximum rate in that direction.

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