How do you define the distance between two points in a non-flat 2-D space?

In summary, the distance between two points in a 2-dimensional space is defined as the length of the shortest path lying in the space, which is measured by 2-dimensional beings. This can be calculated by finding the infimum of the set of all smooth curves between the two points. The infimum may not be an element of this set, meaning that the distance may not be realized by any particular curve. A geodesic is a curve whose acceleration is 0 and can serve as a generalization of a "straight line" in the plane. However, in some spaces, there may not be a distance-minimizing curve, and a geodesic may not minimize distance. It is necessary to start with a choice of metric to
  • #1
gikiian
98
0
Is it the shortest distance thru the non-flat space; or is it the simple displacement a middle-school student would imagine?
 
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  • #2
It's the length of the shortest path lying in the space (so option #1). In other words, the distance between two points in a 2-d space is defined as the distance "as measured by 2d beings whose universe is said space".
 
  • #3
Oh, alright! I need one more clarification. Is this the same thing as geodesic?
 
  • #4
We measure the distance between two points P and Q like so:
1) We consider consider all the smooth curves between P and Q.
2) We record their length and put them in a set S.
3) We say that the distance d(P,Q) between P and Q is the infimum of that set (i.e. the largest number that is smaller than all the numbers in S).

The infimum of a set is not necessarily an element of that set (for instance, the infimum of the set S={all real numbers >0} is 0 but 0 is not in S).

What this means for our definition is that the distance between P and Q might not be realized by any particular curve (there might not be a curve c between P and Q whose length is d(P,Q)). This is the case for instance in the space obtained from the plane by removing a point, say the origin, (0,0). Then, in cartesian coordinates, the distance between the points P=(0,-1) and Q=(1,0) is 2 but there are no curves of length 2 joining P and Q: there is only a sequence of curves whose length is arbitrarily close to 2.)

If is a fact however that if the distance is realized by some curve c, then c is a "geodesic". A geodesic is defined as a curve whose acceleration is 0. So it serves as generalization to the notion of a "straight line" in the plane.
 
  • #5
that is the intrinsic approach, but for an embedded space, like a sphere in three space, it seems acceptable also to use the restriction of the 3 space metric. I think quasar is giving you the preferable way, but maybe not the only way. ?

sometimes the ambient space is easier to deal with than the intrinsic manifold.
e.g. the whitney embedding theorem tells you that you can embed manifolds in euclidean space. this has as a useful corollary that you can also define a metric on the manifold, and even a triangulation.
 
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  • #6
gikiian said:
Oh, alright! I need one more clarification. Is this the same thing as geodesic?

If there is a distance minimizing curve between two points then it will be a geodesic. But in some spaces there is no distance minimizing curve.

Also a geodesic may not minimize distance. It will do so locally, that is for small enough distances, but not necessarily for large distances. Although it is true that a distance minimizing curve is a geodesic, a geodesic may not be a distance minimizing curve.
 
  • #8
Quasar:

Don't you need to start with a choice of metric so that you can select the infimum over the collection of all curves? i.e., in order to define d_L:=inf{d(x,y)} over all rectifiable curves joining x and y, we must start with a notion of d .

To add to your and Mathwonk's example, (example is also given in above Wikipedia link), the circle with the subspace metric does not generate an intrinsic metric, since the Euclidean distance between any x,y on the circle does not equal the arc-length distance, i.e., there are no arc-length paths of length equal to the Euclidean length between points, say, for (-1,0) and (1,0), there are no arc-length paths of length 2 in S^1 between those two points.
 
  • #9
Indeed.
 

Related to How do you define the distance between two points in a non-flat 2-D space?

1. How do you measure distance in a non-flat 2-D space?

The most common method for measuring distance in a non-flat 2-D space is by using the Pythagorean theorem. This theorem states that the square of the hypotenuse (the longest side) of a right triangle is equal to the sum of the squares of the other two sides. In other words, you can find the distance between two points in a non-flat 2-D space by drawing a straight line between them and using this formula.

2. What is the difference between Euclidean distance and non-Euclidean distance?

Euclidean distance is the distance between two points in a flat, 2-D space. It follows the Pythagorean theorem and is the most commonly used method for measuring distance. Non-Euclidean distance, on the other hand, refers to any other method of measuring distance in a non-flat 2-D space, such as using the Great Circle Distance formula for measuring distances on a sphere.

3. Can you use Euclidean distance to measure distances in a non-flat 2-D space?

No, Euclidean distance is only applicable in flat, 2-D spaces. In a non-flat 2-D space, the Pythagorean theorem does not hold true, and thus Euclidean distance cannot be used. Other methods, such as the Great Circle Distance formula or the Haversine formula, must be used instead.

4. How does the curvature of a space affect the distance between two points?

The curvature of a space affects the distance between two points by altering the geometry of the space. In a flat space, the distance between two points can be measured using the Pythagorean theorem. However, in a curved space, the distance between two points can only be measured using non-Euclidean methods, as the Pythagorean theorem does not apply.

5. What is the significance of measuring distances in a non-flat 2-D space?

Measuring distances in a non-flat 2-D space is important because it allows us to accurately represent and understand the geometry of our world. Many real-world applications, such as navigation or astronomy, require the use of non-Euclidean distance formulas to accurately measure distances on curved surfaces, such as the Earth or the celestial sphere.

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