Minimizing Magnetic Field Intensity: Solving for the Directional Derivative

  • Thread starter Lancen
  • Start date
  • Tags
    Derivative
In summary, the conversation discusses finding the curve that minimizes the magnetic field intensity at a given point. This can be achieved by finding the parametrized curve with a speed equal to the negative directional derivative of the magnetic field, or by finding a function that gives a constant value when the magnetic field is plotted as a level curve. The derivative of the curve, noted as \dot{\gamma}, gives the tangent to the curve and guides its direction. While there may be confusion about the specific method suggested, the overall goal is to find the curve that decreases the magnetic field intensity the fastest.
  • #1
Lancen
17
0
This is a problem that's been bugging me. Suppose you are on the surface M(x,y)=3*x^2+y^2+5000 that describes a magnetic field, you are at the point (8,6), what is the curve along which you should travel so as to minimize field intensity as rapidly as possible? I am told I need to solve a differential equation, I am thinking I need to find the minimal directional derivative and somehow from that find the equation of the line that represents, and integrate it to get a curve. But I am at a loss as to how to start. Someone help?
 
Physics news on Phys.org
  • #2
You know that [itex]-\nabla M(x,y)[/itex] is the direction you need to go into in order for your field to decrease the most rapidly. And given a parametrized curve [itex]\gamma (t) = (x(t),y(t))[/itex], the speed [itex]\dot{\gamma}[/itex], is the direction in which the curve is "going". So if you'd have a curve whose speed is [itex]-\nabla M(x,y)[/itex], you'd have a curve that follows the path of fastest decrease, would you not?
 
  • #3
Sorry I don't quite follow, the negative of the directional derivative is the directional I need to go, but what is the parametrized curve? Is the equation of setting up -M(x,y)=(x(t),y(t))?
 
  • #4
A curve and a "parametrized curve" are practically the same thing. A curve is a function (typically smooth) [itex]\gamma : (t_1, t_2)\rightarrow \mathbb{R}^2[/itex], [itex]\gamma(t)=(x(t),y(t))[/itex].

This is a what a curve is. The other way to define a curve is as a "level curve", i.e. by finding a function f(x,y) such that f(x,y)=constant gives a certain relation btw x and y.
 
  • #5
And just as the derivative of a single valued function f(x) gives the tangant to the curve, the derivative of the curve, typically noted [itex]\dot{\gamma}[/itex]*, gives the tangeant to the curve, i.e. the direction where the curve is "heading".*[tex]\dot{\gamma} =\frac{d}{dt}\gamma(t) = \left(\frac{dx(t)}{dt},\frac{dy(t)}{dt} \right)[/tex]
 
Last edited:
  • #6
I am still a bit confused but I have something like this - (xn,yn) = (8,6)+[(-3x,2y)/sqrt(36x^2+4y^2)]*[v,w] where (xn,yn) is the new point after moving some distance, [v,w] the unit vector and [(-3x,2y)/sqrt(36x^2+4y^2)] the gradient divided by its length to give you the unit gradient, but how do I solve this?
 
  • #7
I don't understand what you've done here. What do you not understand about the method I suggested?
 

What is a directional derivative?

A directional derivative is a measure of the rate of change of a function in a particular direction. It indicates how fast a function changes at a given point in the direction of a specified vector.

How is a directional derivative calculated?

The directional derivative is calculated by taking the dot product of the gradient of the function and the unit vector representing the direction in which the derivative is being evaluated.

What is the significance of the directional derivative?

The directional derivative is important in multivariable calculus as it allows us to understand how a function changes in a specific direction. It is used in optimization problems, where we need to find the direction of steepest ascent or descent.

Can the directional derivative be negative?

Yes, the directional derivative can be negative. It depends on the direction in which the derivative is being evaluated. A negative directional derivative indicates a decrease in the function in that direction.

What is the relationship between the directional derivative and the gradient?

The directional derivative is closely related to the gradient of a function. The gradient is a vector that points in the direction of steepest ascent, and its magnitude is equal to the directional derivative in that direction. The directional derivative can be thought of as the rate of change of the function in the direction of the gradient.

Similar threads

  • Calculus and Beyond Homework Help
Replies
3
Views
953
  • Calculus and Beyond Homework Help
Replies
4
Views
555
  • Calculus and Beyond Homework Help
Replies
5
Views
1K
Replies
9
Views
703
  • Calculus and Beyond Homework Help
Replies
8
Views
455
  • Calculus and Beyond Homework Help
Replies
7
Views
498
  • Calculus and Beyond Homework Help
Replies
23
Views
1K
  • Calculus and Beyond Homework Help
Replies
7
Views
1K
  • Calculus and Beyond Homework Help
Replies
6
Views
643
  • Calculus and Beyond Homework Help
Replies
3
Views
814
Back
Top