Calculus of Variations: Shortest distance between two points in 3D space

In summary, the shortest distance between two points in three dimensional space can be found by minimizing the functional L[x(t), y(t), z(t)] = \int_{t_{0}}^{t_{1}}{\sqrt{\dot{x}^{2} + \dot{y}^{2} + \dot{z}^{2}} \, dt} and using the Euler equations for each of the functions x(t), y(t), z(t). This involves finding the derivative of each function with respect to time and setting it equal to zero. The final equation for the straight line is d/dt [ x' / (x' + y'² + z'²)^(1/2) ].
  • #1
Esran
73
0

Homework Statement



Show that the shortest distance between two points in three dimensional space is a straight line.

Homework Equations



Principally, the Euler Lagrange equation.

The Attempt at a Solution



I understand how to do this for a plane, but when we move into three dimensions, our distance element is then ds=(dx2+dy2+dz2)(1/2), which throws me off with the added variable. How do I handle calculus of variation problems like this in more than two variables? What will be my functional?
 
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  • #2
If I remember correctly, the procedure should be essentially identical whether you're working with two or three (or more) coordinates. What problem specifically did you run into that is caused by the third variable?
 
  • #3
Ah, never mind. I got it.
 
  • #4
I came across this question myself. I used the constrained Euler equation and solved for two dependent variables i.e. y and z.

The functional I need to solve is (1 + y'² + z'²)^(1/2)

I can't seem to get the equation for the straight line, what is its form?
 
  • #5
Minimize the functional:

[tex]
L[x(t), y(t), z(t)] = \int_{t_{0}}^{t_{1}}{\sqrt{\dot{x}^{2} + \dot{y}^{2} + \dot{z}^{2}} \, dt}
[/tex]

What are the Euler equations for each of the functions [itex]x(t), y(t), z(t)[/itex]?
 
  • #6
Aha, I tried this and I got the Euler equation to be:

d/dt [ x' / (x' + y'² + z'²)^(1/2) ] for the function x(t) I also got it for y(t) and z(t) the same way.


I tried differentiating w.r.t 't' for all x, y and z, but I don't think I got it right.
 
  • #7
hhhmortal said:
Aha, I tried this and I got the Euler equation to be:

d/dt [ x' / (x' + y'² + z'²)^(1/2) ]

Since there is no equality sign, this is not an equation.
 

1. What is the concept behind the calculus of variations?

The calculus of variations is a mathematical field that deals with finding the optimal solution to a function, typically involving minimizing or maximizing a certain quantity. In other words, it involves finding the path or function that minimizes or maximizes a given functional.

2. How does the calculus of variations relate to finding the shortest distance between two points in 3D space?

The calculus of variations can be applied to finding the shortest distance between two points in 3D space by treating the distance as a functional to be optimized. This involves finding the path or curve that minimizes the distance between the two points.

3. What are the main steps involved in solving for the shortest distance between two points using the calculus of variations?

The main steps involved in solving for the shortest distance between two points using the calculus of variations are: defining the functional to be optimized, setting up the Euler-Lagrange equation, solving the Euler-Lagrange equation, and applying boundary conditions to find the optimal path or curve.

4. Can the calculus of variations be applied to finding shortest distance in higher dimensions?

Yes, the calculus of variations can be applied to finding shortest distance in higher dimensions. The concept and steps involved remain the same, but the calculations become more complex as the dimensionality increases.

5. What are some real-world applications of the calculus of variations in finding shortest distance?

The calculus of variations has various applications in fields such as physics, engineering, and economics. Some examples include finding the optimal path for a rocket to travel from one point to another in space, finding the path of least resistance for a river to flow, and optimizing the shape of a bridge to withstand maximum weight while using minimal materials.

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