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Injective metric space

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In metric geometry, an injective metric space, or equivalently a hyperconvex metric space, is a metric space with certain properties generalizing those of the real line and of L distances in higher-dimensional vector spaces. These properties can be defined in two seemingly different ways: hyperconvexity involves the intersection properties of closed balls in the space, while injectivity involves the isometric embeddings of the space into larger spaces. However it is a theorem of Aronszajn and Panitchpakdi (1956; see e.g. Chepoi 1997) that these two different types of definitions are equivalent.

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Hyperconvexity

A metric space X is said to be hyperconvex if it is convex and its closed balls have the binary Helly property. That is,

  1. any two points x and y can be connected by the isometric image of a line segment of length equal to the distance between the points (i.e. X is a path space), and
  2. if F is any family of closed balls
such that each pair of balls in F meet, then there exists a point x common to all the balls in F.

Equivalently, if a set of points pi and radii ri > 0 satisfies ri + rjd(pi,pj) for each i and j, then there is a point q of the metric space that is within distance ri of each pi.

Injectivity

A retraction of a metric space X is a function ƒ mapping X to a subspace of itself, such that

  1. for all x, ƒ(ƒ(x)) = ƒ(x); that is, ƒ is the identity function on its image (i. e. it is idempotent), and
  2. for all x and y, d(ƒ(x), ƒ(y)) ≤ d(xy); that is, ƒ is nonexpansive.

A retract of a space X is a subspace of X that is an image of a retraction. A metric space  X is said to be injective if, whenever X is isometric to a subspace Z of a space Y, that subspace Z is a retract of Y.

Examples

Examples of hyperconvex metric spaces include

  • The real line
  • Any vector space Rd with the L distance
  • Manhattan distance (L1) in the plane (which is equivalent up to rotation and scaling to the L), but not in higher dimensions
  • The tight span of a metric space
  • Any real tree
  • Aim(X) – see Metric space aimed at its subspace
  • Due to the equivalence between hyperconvexity and injectivity, these spaces are all also injective.

    Properties

    In an injective space, the radius of the minimum ball that contains any set S is equal to half the diameter of S. This follows since the balls of radius half the diameter, centered at the points of S, intersect pairwise and therefore by hyperconvexity have a common intersection; a ball of radius half the diameter centered at a point of this common intersection contains all of S. Thus, injective spaces satisfy a particularly strong form of Jung's theorem.

    Every injective space is a complete space (Aronszajn & Panitchpakdi 1956), and every metric map (or, equivalently, nonexpansive mapping, or short map) on a bounded injective space has a fixed point (Sine 1979; (Soardi 1979)). A metric space is injective if and only if it is an injective object in the category of metric spaces and metric maps. For additional properties of injective spaces see Espínola & Khamsi (2001).

    References

    Injective metric space Wikipedia


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