A metric space ${\displaystyle X}$  is said to be hyperconvex if it is convex and its closed balls have the binary Helly property. That is:

1. Any two points ${\displaystyle x}$  and ${\displaystyle y}$  can be connected by the isometric image of a line segment of length equal to the distance between the points (i.e. ${\displaystyle X}$  is a path space).
2. If ${\displaystyle F}$  is any family of closed balls
   $${\displaystyle {\bar {B}}_{r}(p)=\{q\mid d(p,q)\leq r\}}$$

    
   such that each pair of balls in ${\displaystyle F}$  meets, then there exists a point ${\displaystyle x}$  common to all the balls in ${\displaystyle F}$ .

Equivalently, a metric space ${\displaystyle X}$  is hyperconvex if, for any set of points ${\displaystyle p_{i}}$  in ${\displaystyle X}$  and radii ${\displaystyle r_{i}>0}$  satisfying ${\displaystyle r_{i}+r_{j}\geq d(p_{i},p_{j})}$  for each ${\displaystyle i}$  and ${\displaystyle j}$ , there is a point ${\displaystyle q}$  in ${\displaystyle X}$  that is within distance ${\displaystyle r_{i}}$  of each ${\displaystyle p_{i}}$  (that is, ${\displaystyle d(p_{i},q)\leq r_{i}}$  for all ${\displaystyle i}$ ).

A retraction of a metric space ${\displaystyle X}$  is a function ${\displaystyle f}$  mapping ${\displaystyle X}$  to a subspace of itself, such that

1. for all ${\displaystyle x\in X}$  we have that ${\displaystyle f(f(x))=f(x)}$ ; that is, ${\displaystyle f}$  is the identity function on its image (i.e. it is idempotent), and
2. for all ${\displaystyle x,y\in X}$  we have that ${\displaystyle d(f(x),f(y))\leq d(x,y)}$ ; that is, ${\displaystyle f}$  is nonexpansive.

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

Examples of hyperconvex metric spaces include

• The real line
• ${\displaystyle \mathbb {R} ^{d}}$  with the ${\displaystyle \ell }$ ^∞ 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 complete real tree
• ${\displaystyle \operatorname {Aim} (X)}$  – see Metric space aimed at its subspace

Due to the equivalence between hyperconvexity and injectivity, these spaces are all also injective.

In an injective space, the radius of the minimum ball that contains any set ${\displaystyle S}$  is equal to half the diameter of ${\displaystyle S}$ . This follows since the balls of radius half the diameter, centered at the points of ${\displaystyle S}$ , 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 ${\displaystyle S}$ . Thus, injective spaces satisfy a particularly strong form of Jung's theorem.

Every injective space is a complete space,^[2] and every metric map (or, equivalently, nonexpansive mapping, or short map) on a bounded injective space has a fixed point.^[3] A metric space is injective if and only if it is an injective object in the category of metric spaces and metric maps.^[4]

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