What is the metric (distance function) on the 1-sphere and 2-sphere?

In summary: Adding those, we getds^2= d\theta^2+ sin^2(\phi)d\phi^2In summary, the distance function in S1 (1-sphere) and S2 (2-sphere) is defined by the round metric, which is based on the parametric equations of the manifold and its corresponding Jacobian matrix
  • #1
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Hi i only know the distance function in euclidean space as the standard definition involving the sqrt of the dot product of the vector connecting two points.

What is the metric (distance function) in S1 or S2 which is the 1 sphere and 2sphere respectively.
 
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  • #2
The round metric for the unit 1-sphere is (using radians), [itex]\mathbf{g} = d\theta^2[/itex], and for the unit 2-sphere, [itex]\mathbf{g} = \sin^2\theta\,d\phi^2 + d\theta^2[/itex], I think, working off of memory. It should be simple to add in the r term for arbitrary euclidean 1 and 2-spheres

In general, if J is the jacobian matrix of the manifold:
[itex]\mathbf{g} = J^T J[/itex]
 
  • #3
That's right. The 1-sphere (unit circle for us pedestrians) has parametric equations [itex]x= cos(\theta)[/itex], [itex]y= sin(\theta)[/itex] so that [itex]dx= -sin(\theta)d\theta[/itex] and [itex]dy= cos(\theta)[/itex] so that [itex]ds^2= dx^2+ dy^2= (sin^2(\theta)+ cos^2(\theta))d\theta^2= d\theta^2[/itex].

For the 2-sphere (the surface of the unit sphere), we can take [itex]x= cos(\theta)sin(\phi)[/itex], [itex]y= sin(\theta)sin(\phi)[/itex], [itex]z= cos(\phi)[/itex] (spherical coordinates with [itex]\rho= 1[/itex]). Then [itex]dx= -sin(\theta)sin(\phi)+ cos(\theta)cos(\phi)[/itex], [itex]dy= cos(\theta)sin(\phi)+ sin(\theta)cos(\phi)[/itex], and [itex]dz= -sin(\phi)d\phi[/itex].

[tex]dx^2= sin^2(\theta)sin^2(\phi)d\theta^2- 2sin(\theta)cos(\theta)sin(\phi)cos(\phi)d\theta d\phi+ cos^2(\theta)cos^2(\phi)d\phi^2[/tex]
 

FAQ: What is the metric (distance function) on the 1-sphere and 2-sphere?

What is a metric in terms of distance function?

A metric is a mathematical concept used to measure the distance between two points in a given space. It is a function that takes two points as input and outputs a non-negative value representing the distance between those points.

What are the properties of a metric?

The properties of a metric include non-negativity, symmetry, and the triangle inequality. Non-negativity means that the metric value between two points cannot be negative. Symmetry means that the distance from point A to point B is the same as the distance from point B to point A. The triangle inequality states that the distance from point A to point C must be less than or equal to the sum of the distances from point A to point B and from point B to point C.

How is a metric different from a distance function?

A metric is a type of distance function, but not all distance functions are metrics. A metric must follow the properties mentioned above, while a distance function can have different properties depending on its intended use. A distance function can also measure things other than distance, such as similarity or dissimilarity.

What are some common examples of metric distance functions?

Some common examples of metric distance functions include Euclidean distance, Manhattan distance, and Minkowski distance. Euclidean distance is the straight-line distance between two points in a two- or three-dimensional space. Manhattan distance is the sum of the absolute differences between the coordinates of two points. Minkowski distance is a generalization of both Euclidean and Manhattan distance that includes a parameter to adjust the calculation.

How is a metric used in scientific research?

A metric is used in scientific research to quantify the distance between data points, whether they are physical points in space or abstract points in a dataset. It is often used in fields such as biology, computer science, and statistics to measure the similarity or dissimilarity between objects, clusters, or groups. It is also used in optimization problems to find the shortest distance between two points.

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