What is the relationship between the gradient and the normal vector?

In summary, the gradient vector of a function, at a given point, is normal to the tangent plane of the surface defined by the function. The directional derivative of the function can be written as the dot product of the gradient vector and a unit vector in the given direction. The gradient vector is normal to any surface where the function is constant.
  • #1
jaguar7
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is the normal just grad(f(x0,y0,z0))? If so, how exactly does this work out to be so? Explain? Thanks... :D

& is the calculus section the most appropriate place to put this question? thanks again. :)
 
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  • #2
The tangent plane is defined to be the plane of all points (x,y,z) the equation

[tex] \nabla f(x_0,y_0,z_0) \cdot (x,y,z)=\nabla f(x_0,y_0,z_0) \cdot (x_0, y_0, z_0) [/tex]
(you may not have seen it written down this way, but look at what your definition of the tangent plane and make sure you understand that you can write it in this form).

From this equation, what can you say about a vector lying along the tangent plane (this is different from picking a point in the plane) when compared to the gradient?
 
  • #3
jaguar7 said:
is the normal just grad(f(x0,y0,z0))? If so, how exactly does this work out to be so? Explain? Thanks... :D

& is the calculus section the most appropriate place to put this question? thanks again. :)
This question is poorly phrased. The normal to what? A normal is a vector perpendicular to some surface and just the function, f(x, y, z), does not determine any surface. The gradient vector, of a function, at a given point, is, as Office Shredder says, normal to the tangent plane of the graph of the surface defined by f(x, y, z)= constant.

We can write the "directional derivative", the rate of change of the function f in the direction that makes angles [itex]\theta[/itex], [itex]\phi[/itex], and [itex]\psi[/itex] with the positive x, y, and z axes, respectively, as
[tex]\frac{\partial f}{\partial x}cos(\theta)+ \frac{\partial f}{\partial y}cos(\phi)+ \frac{\partial f}{\partial z}cos(\psi)[/tex]
which is exactly the same as the dot product
[tex]\nabla f\cdot cos(\theta)\vec{i}+ cos(\phi)\vec{j}+ cos(\psi)\vec{k}[/tex]
and now [itex]cos(\theta)\vec{i}+ cos(\phi)\vec{j}+ cos(\psi)\vec{k}[/itex] is the unit vector in the given direction.
If f(x,y,z) is a constant on a given surface, the derivative in any direction tangent to that surface must be 0. That is, [itex]\nabla f[/itex] has 0 dot product with any vector tangent to the surface and so is normal to the surface.
 

1. What is a gradient?

A gradient is a vector that represents the rate of change of a variable in a particular direction. It is often used in mathematics and physics to describe how a quantity changes over a given distance or time.

2. How is the gradient related to the normal vector?

The gradient and the normal vector are closely related, as they both represent the direction of steepest ascent or descent of a function. The gradient is perpendicular to the level curves of a function, while the normal vector is perpendicular to the surface of a function.

3. What does the magnitude of the gradient represent?

The magnitude of the gradient represents the rate of change or steepness of a function in a particular direction. A larger magnitude indicates a steeper slope, while a smaller magnitude indicates a gentler slope.

4. How is the gradient used in real-world applications?

The gradient is used in a variety of real-world applications, such as in computer graphics, machine learning, and optimization problems. It is also used in fields like geology and meteorology to analyze changes in physical quantities.

5. Can the gradient and normal vector be used interchangeably?

No, the gradient and normal vector cannot be used interchangeably. They have different mathematical definitions and represent different concepts. However, they are closely related and can be used together to solve various mathematical and physical problems.

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