Calculating Gradient of ln(r) in 3D Space

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In summary, the formula for calculating the gradient of ln(r) in 3D space is ∇ln(r) = (1/r)∇r = (1/r)(∂r/∂x, ∂r/∂y, ∂r/∂z). The gradient represents the rate of change or slope of the natural logarithm of the distance from the origin in 3D space. The partial derivatives in the formula can be calculated using basic calculus rules. The gradient can be negative, indicating a decrease in ln(r) as we move in a certain direction. It has various real-world applications in physics, engineering, and computer graphics.
  • #1
brentd49
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So, the question is: find the gradient of f=ln(r), where r=sqrt(x^2+y^2+z^2)^(1/2).

For the partial with respect to x, I use the chain rule: df/dr*dr/dx.

df/dr=1/r
dr/dx=(1/2)*(2x)=x

Which would give df/dx = x/r.

But the book gets x/r^2

Where does the extra 1/r come from?
 
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  • #2
brentd49 said:
So, the question is: find the gradient of f=ln(r), where r=sqrt(x^2+y^2+z^2)^(1/2).
...
dr/dx=(1/2)*(2x)=x
...
This isn't right. Remember to use the chain rule here as well.
 
  • #3
hah. of course. thanks
 

1. What is the formula for calculating the gradient of ln(r) in 3D space?

The formula for calculating the gradient of ln(r) in 3D space is:
∇ln(r) = (1/r)∇r = (1/r)(∂r/∂x, ∂r/∂y, ∂r/∂z)

2. What does the gradient of ln(r) represent in 3D space?

The gradient of ln(r) represents the rate of change or the slope of the natural logarithm of the distance from the origin in 3D space. It tells us how quickly the value of ln(r) changes as we move in the x, y, and z directions.

3. How do you calculate the partial derivatives in the formula for the gradient of ln(r) in 3D space?

The partial derivatives in the formula for the gradient of ln(r) in 3D space can be calculated using basic calculus rules. The derivative of ln(r) with respect to x is ∂ln(r)/∂x = 1/r * ∂r/∂x. Similarly, the derivatives with respect to y and z can be calculated in the same way.

4. Can the gradient of ln(r) in 3D space be negative?

Yes, the gradient of ln(r) in 3D space can be negative. This indicates that the value of ln(r) decreases as we move in that particular direction. However, the magnitude of the gradient is more important than its sign, as it tells us about the rate of change or slope of ln(r).

5. How is the gradient of ln(r) used in real-world applications?

The gradient of ln(r) has many real-world applications, such as in physics, engineering, and computer graphics. It is used to calculate the electric field and gravitational potential in 3D space, and also to create 3D terrain maps in computer graphics. In physics, it is used to calculate the force and torque on an object in a 3D space.

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