Gradient vector perpendicular to level curves?

In summary, the gradient vector is perpendicular to level curves because the directional derivative of a function in the direction of the tangent vector to the level curve is equivalent to the dot product between the gradient vector and any unit tangent vector to the level curve, and since the directional derivative is 0 in this direction, the two vectors must be perpendicular. This can be proven by understanding the definitions of the gradient, dot product, and directional derivative.
  • #1
princejan7
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Homework Statement



can anyone explain/prove why the gradient vector is perpendicular to level curves?

Homework Equations





The Attempt at a Solution

 
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  • #2
I think this could be a good exercise for you to prove yourself. I will give some pointers. You have a function ##f : \mathbb{R}^n \rightarrow \mathbb{R}## and level sets such that ##f(x_1,..., x_n) = c.##

Let ##\gamma(t) = (x_1(t),...,x_n(t))## be a curve on the level surface and consider ## g(t) = f(x_1(t),...,x_n(t))##. Now compute ##\frac{d}{dt}g(t)##.
 
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  • #3
The directional derivative DuF(P) of a function F in the direction of the unit vector u at the point P is equivalent to the dot product of the gradient vector ∇F(P) with the unit vector u (this is something you should prove if you have not already done so).
The value of F does not change in the direction of the tangent vector to the level curve that passes through P, since a level curve is a set of points where the value of F is constant. Therefore, the directional derivative of F in that direction is 0. Since this is equivalent to the dot product between ∇F(P) and any unit tangent vector to the level curve, and assuming neither vector is the zero vector, the two vectors must be perpendicular.
You can put each of these intuitive arguments into rigorous mathematical form in order to get a more rigorous picture.

Edit: I agree with Quesadilla (it looks like we posted at the same time). This is something you may like to prove rigorously yourself, if you understand the definition of the gradient, dot product, and directional derivative. It is a walk through a series of definitions.
 

Related to Gradient vector perpendicular to level curves?

1. What is a gradient vector?

A gradient vector is a mathematical object that represents the direction and magnitude of the steepest increase of a function at a given point. It is calculated by taking the partial derivatives of the function with respect to each variable and then combining them into a vector.

2. What are level curves?

Level curves, also known as contour lines, are imaginary lines on a two-dimensional graph that connect points with the same value of a given function. They represent areas on the graph where the function has a constant value.

3. How is the gradient vector related to level curves?

The gradient vector is always perpendicular to the level curves of a function. This means that at any point on a level curve, the gradient vector will be pointing directly away from the curve, in the direction of the steepest increase of the function.

4. Why is the gradient vector perpendicular to level curves?

This is because the gradient vector represents the direction of the steepest increase of the function, while the level curves represent areas where the function has a constant value. Therefore, at any point on a level curve, there is no change in the value of the function in the direction of the gradient vector, making them perpendicular to each other.

5. How can gradient vectors be used in real-world applications?

Gradient vectors are used in many fields, such as physics, engineering, and economics, to analyze and optimize various processes. For example, in physics, gradient vectors are used to calculate the force on an object in a given field. In economics, they can be used to determine the optimal direction of growth for a business.

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