Calculating Gradient Vector at Point S: x=4, y=8, z=-6

It might be worth double checking your calculations for any errors. In summary, the problem involves calculating the gradient vector at a given point for a function that includes a square root. The attempt at a solution reveals that the scalar field becomes imaginary at the given point, which may indicate a mistake in the calculations. It is recommended to double check the problem and calculations for accuracy.
  • #1
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Homework Statement


Calculate the gradient vector at the point [tex]S[/tex] for the function, [tex]f(x,y,z)=x-\sqrt{z^2 - y^2}; S(x,y,z)=(4, 8, -6)[/tex].


2. The attempt at a solution
[tex]\frac{\partial f}{\partial x} = 1[/tex]
[tex]\frac{\partial f}{\partial y} = \frac{y}{\sqrt{z^2-y^2}}[/tex]
[tex]\frac{\partial f}{\partial z} = -\frac{z}{\sqrt{z^2-y^2}}[/tex]
Therefore at Point [tex]S[/tex]:
[tex]\frac{\partial f}{\partial x} = 1[/tex]
[tex]\frac{\partial f}{\partial y} = \frac{-6}{\sqrt{36-64}} = \frac{-6}{\sqrt{-28}}[/tex]


3. The problem that I'm having
When I put the point values of Point [tex]S[/tex] into the equation, I get a negative square root in the denominator. Where am I going wrong? Thanks in advance.
 
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  • #2
Indeed, this is weird. Have you double checked you copied the problem down right?

We can see that the scalar field becomes imaginary at that point as well (you will also get a negative sign under the square root).
 

Related to Calculating Gradient Vector at Point S: x=4, y=8, z=-6

1) What is the formula for calculating the gradient vector at a given point?

The formula for calculating the gradient vector at a point is ∇f(x,y,z) = (∂f/∂x, ∂f/∂y, ∂f/∂z).

2) How do you find the partial derivatives in the gradient vector formula?

To find the partial derivatives, you take the derivative of the function with respect to each variable and plug in the values of the given point.

3) Can you explain the concept of the gradient vector in simpler terms?

The gradient vector represents the direction and magnitude of the steepest increase of a function at a given point. It points towards the direction of greatest change in the function.

4) What does the gradient vector tell us about the function at a specific point?

The gradient vector tells us the direction in which the function is increasing the fastest at the given point and the rate of change in that direction.

5) Why is calculating the gradient vector important in scientific research?

Calculating the gradient vector is important in scientific research because it helps us understand the behavior and properties of functions in three-dimensional space. It is also essential in optimizing functions and solving problems in fields such as physics, engineering, and economics.

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