Tight span

Last updated

In metric geometry, the metric envelope or tight span of a metric space M is an injective metric space into which M can be embedded. In some sense it consists of all points "between" the points of M, analogous to the convex hull of a point set in a Euclidean space. The tight span is also sometimes known as the injective envelope or hyperconvex hull of M. It has also been called the injective hull, but should not be confused with the injective hull of a module in algebra, a concept with a similar description relative to the category of R-modules rather than metric spaces.


The tight span was first described by Isbell (1964), and it was studied and applied by Holsztyński in the 1960s. It was later independently rediscovered by Dress (1984) and Chrobak & Larmore (1994); see Chepoi (1997) for this history. The tight span is one of the central constructions of T-theory.


The tight span of a metric space can be defined as follows. Let (X,d) be a metric space, and let T(X) be the set of extremal functions on X, where we say an extremal function on X to mean a function f from X to R such that

  1. For any x, y in X, d(x,y) ≤ f(x) + f(y), and
  2. For each x in X, f(x) = sup{d(x,y) - f(y):y in X}. [1] :124

In particular (taking x = y in property 1 above) f(x) ≥ 0 for all x. One way to interpret the first requirement above is that f defines a set of possible distances from some new point to the points in X that must satisfy the triangle inequality together with the distances in (X,d). The second requirement states that none of these distances can be reduced without violating the triangle inequality.

The tight span of (X,d) is the metric space (T(X),δ), where

is analogous to the metric induced by the norm. (If d is bounded, then δ is the subspace metric induced by the metric induced by the norm. If d is not bounded, then every extremal function on X is unbounded and so Regardless, it will be true that for any f,g in T(X), the difference belongs to , i.e., is bounded.)

Equivalent definitions of extremal functions

For a function f from X to R satisfying the first requirement, the following versions of the second requirement are equivalent:

Basic properties and examples

Hyperconvexity properties


If a set of points in the plane, with the Manhattan metric, has a connected orthogonal convex hull, then that hull coincides with the tight span of the points. Orthogonal-convex-hull.svg
If a set of points in the plane, with the Manhattan metric, has a connected orthogonal convex hull, then that hull coincides with the tight span of the points.

Dimension of the tight span when X is finite

The definition above embeds the tight span T(X) of a set of n () points into RX, a real vector space of dimension n. On the other hand, if we consider the dimension of T(X) as a polyhedral complex, Develin (2006) showed that, with a suitable general position assumption on the metric, this definition leads to a space with dimension between n/3 and n/2.

Alternative definitions

An alternative definition based on the notion of a metric space aimed at its subspace was described by Holsztyński (1968), who proved that the injective envelope of a Banach space, in the category of Banach spaces, coincides (after forgetting the linear structure) with the tight span. This theorem allows to reduce certain problems from arbitrary Banach spaces to Banach spaces of the form C(X), where X is a compact space.

Develin & Sturmfels (2004) attempted to provide an alternative definition of the tight span of a finite metric space as the tropical convex hull of the vectors of distances from each point to each other point in the space. However, later the same year they acknowledged in an Erratum Develin & Sturmfels (2004a) that, while the tropical convex hull always contains the tight span, it may not coincide with it.


See also


  1. Dress, Huber & Moulton (2001).
  2. 1 2 3 4 5 6 7 8 Khamsi, Mohamed A.; Kirk, William A. (2001). An Introduction to Metric Spaces and Fixed Point Theory. Wiley.
  3. 1 2 3 Dress, Andreas; Huber, Katharina T.; Koolen, Jacobus; Moulton, Vincent; Spillner, Andreas (2012). Basic Phylogenetic Combinatorics. Cambridge University Press. ISBN   978-0-521-76832-0.
  4. 1 2 3 Huson, Daniel H.; Rupp, Regula; Scornavacca, Celine (2010). Phylogenetic Networks: Conceps, Algorithms and Applications. Cambridge University Press. ISBN   978-0-521-75596-2.
  5. Deza, Michel Marie; Deza, Elena (2014). Encyclopedia of Distances (Third ed.). Springer. p. 47. ISBN   978-3-662-44341-5.
  6. Melleray, Julien (2008). "Some geometric and dynamical properties of the Urysohn space". Topology and Its Applications. 155 (14): 1531–1560. doi: 10.1016/j.topol.2007.04.029 .
  7. Benyamini, Yoav; Lindenstrauss, Joram (2000). Geometric Nonlinear Functional Analysis. American Mathematical Society. p. 32. ISBN   978-0-8218-0835-1.
  8. In two dimensions, the Manhattan distance is isometric after rotation and scaling to the distance, so with this metric the plane is itself injective, but this equivalence between 1 and does not hold in higher dimensions.
  9. Chrobak & Larmore (1994).
  1. Khamsi and Kirk use this condition in their definition.
  2. Khamsi and Kirk's proof shows one implication of the equivalence to the condition immediately above. The other implication is not difficult to show.
  3. I.e., the Kuratowski map We will introduce the Kuratowski map below.
  4. The supremum is achieved with y=x.
  5. The supremum is achieved with y=x.

Related Research Articles

<span class="mw-page-title-main">Continuous function</span> Mathematical function with no sudden changes

In mathematics, a continuous function is a function such that a continuous variation of the argument induces a continuous variation of the value of the function. This means that there are no abrupt changes in value, known as discontinuities. More precisely, a function is continuous if arbitrarily small changes in its value can be assured by restricting to sufficiently small changes of its argument. A discontinuous function is a function that is not continuous. Up until the 19th century, mathematicians largely relied on intuitive notions of continuity, and considered only continuous functions. The epsilon–delta definition of a limit was introduced to formalize the definition of continuity.

In mathematics, the Lp spaces are function spaces defined using a natural generalization of the p-norm for finite-dimensional vector spaces. They are sometimes called Lebesgue spaces, named after Henri Lebesgue, although according to the Bourbaki group they were first introduced by Frigyes Riesz.

Distributions, also known as Schwartz distributions or generalized functions, are objects that generalize the classical notion of functions in mathematical analysis. Distributions make it possible to differentiate functions whose derivatives do not exist in the classical sense. In particular, any locally integrable function has a distributional derivative.

<span class="mw-page-title-main">Harmonic function</span> Functions in mathematics

In mathematics, mathematical physics and the theory of stochastic processes, a harmonic function is a twice continuously differentiable function where U is an open subset of that satisfies Laplace's equation, that is,

In mathematics, a self-adjoint operator on an infinite-dimensional complex vector space V with inner product is a linear map A that is its own adjoint. If V is finite-dimensional with a given orthonormal basis, this is equivalent to the condition that the matrix of A is a Hermitian matrix, i.e., equal to its conjugate transpose A. By the finite-dimensional spectral theorem, V has an orthonormal basis such that the matrix of A relative to this basis is a diagonal matrix with entries in the real numbers. This article deals with applying generalizations of this concept to operators on Hilbert spaces of arbitrary dimension.

In differential geometry, the Ricci curvature tensor, named after Gregorio Ricci-Curbastro, is a geometric object which is determined by a choice of Riemannian or pseudo-Riemannian metric on a manifold. It can be considered, broadly, as a measure of the degree to which the geometry of a given metric tensor differs locally from that of ordinary Euclidean space or pseudo-Euclidean space.

In mathematics, Fatou's lemma establishes an inequality relating the Lebesgue integral of the limit inferior of a sequence of functions to the limit inferior of integrals of these functions. The lemma is named after Pierre Fatou.

In mathematics, the Hodge star operator or Hodge star is a linear map defined on the exterior algebra of a finite-dimensional oriented vector space endowed with a nondegenerate symmetric bilinear form. Applying the operator to an element of the algebra produces the Hodge dual of the element. This map was introduced by W. V. D. Hodge.

In the mathematical field of measure theory, an outer measure or exterior measure is a function defined on all subsets of a given set with values in the extended real numbers satisfying some additional technical conditions. The theory of outer measures was first introduced by Constantin Carathéodory to provide an abstract basis for the theory of measurable sets and countably additive measures. Carathéodory's work on outer measures found many applications in measure-theoretic set theory, and was used in an essential way by Hausdorff to define a dimension-like metric invariant now called Hausdorff dimension. Outer measures are commonly used in the field of geometric measure theory.

<span class="mw-page-title-main">Barycentric subdivision</span>

In mathematics, the barycentric subdivision is a standard way to subdivide a given simplex into smaller ones. Its extension on simplicial complexes is a canonical method to refine them. Therefore, the barycentric subdivision is an important tool in algebraic topology.

The Arzelà–Ascoli theorem is a fundamental result of mathematical analysis giving necessary and sufficient conditions to decide whether every sequence of a given family of real-valued continuous functions defined on a closed and bounded interval has a uniformly convergent subsequence. The main condition is the equicontinuity of the family of functions. The theorem is the basis of many proofs in mathematics, including that of the Peano existence theorem in the theory of ordinary differential equations, Montel's theorem in complex analysis, and the Peter–Weyl theorem in harmonic analysis and various results concerning compactness of integral operators.

In mathematics, the Fubini–Study metric is a Kähler metric on projective Hilbert space, that is, on a complex projective space CPn endowed with a Hermitian form. This metric was originally described in 1904 and 1905 by Guido Fubini and Eduard Study.

In mathematics, the Wasserstein distance or Kantorovich–Rubinstein metric is a distance function defined between probability distributions on a given metric space . It is named after Leonid Vaseršteĭn.

In mathematics, uniform integrability is an important concept in real analysis, functional analysis and measure theory, and plays a vital role in the theory of martingales.

In mathematics, a filter on a set is a family of subsets such that:

  1. and
  2. if and , then
  3. If , and , then

In mathematics, a space, where is a real number, is a specific type of metric space. Intuitively, triangles in a space are "slimmer" than corresponding "model triangles" in a standard space of constant curvature . In a space, the curvature is bounded from above by . A notable special case is ; complete spaces are known as "Hadamard spaces" after the French mathematician Jacques Hadamard.

In geometry, the Chebyshev center of a bounded set having non-empty interior is the center of the minimal-radius ball enclosing the entire set , or alternatively the center of largest inscribed ball of .

<span class="mw-page-title-main">Distance correlation</span>

In statistics and in probability theory, distance correlation or distance covariance is a measure of dependence between two paired random vectors of arbitrary, not necessarily equal, dimension. The population distance correlation coefficient is zero if and only if the random vectors are independent. Thus, distance correlation measures both linear and nonlinear association between two random variables or random vectors. This is in contrast to Pearson's correlation, which can only detect linear association between two random variables.

In functional analysis and related areas of mathematics, a complete topological vector space is a topological vector space (TVS) with the property that whenever points get progressively closer to each other, then there exists some point towards which they all get closer. The notion of "points that get progressively closer" is made rigorous by Cauchy nets or Cauchy filters, which are generalizations of Cauchy sequences, while "point towards which they all get closer" means that this Cauchy net or filter converges to The notion of completeness for TVSs uses the theory of uniform spaces as a framework to generalize the notion of completeness for metric spaces. But unlike metric-completeness, TVS-completeness does not depend on any metric and is defined for all TVSs, including those that are not metrizable or Hausdorff.

In mathematics, a diversity is a generalization of the concept of metric space. The concept was introduced in 2012 by Bryant and Tupper, who call diversities "a form of multi-way metric". The concept finds application in nonlinear analysis.