Helly family

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In combinatorics, a Helly family of order k is a family of sets such that any minimal subfamily with an empty intersection has k or fewer sets in it. Equivalently, every finite subfamily such that every -fold intersection is non-empty has non-empty total intersection. [1] The k-Helly property is the property of being a Helly family of order k. [2]


The number k is frequently omitted from these names in the case that k = 2. Thus, a set-family has the Helly property if for every n sets in the family, if , then .

These concepts are named after Eduard Helly (1884-1943); Helly's theorem on convex sets, which gave rise to this notion, states that convex sets in Euclidean space of dimension n are a Helly family of order n + 1. [1]


Formal definition

More formally, a Helly family of order k is a set system (V, E), with E a collection of subsets of V, such that, for every finite GE with

we can find HG such that



In some cases, the same definition holds for every subcollection G, regardless of finiteness. However, this is a more restrictive condition. For instance, the open intervals of the real line satisfy the Helly property for finite subcollections, but not for infinite subcollections: the intervals (0,1/i) (for i = 0, 1, 2, ...) have pairwise nonempty intersections, but have an empty overall intersection.

Helly dimension

If a family of sets is a Helly family of order k, that family is said to have Helly numberk. The Helly dimension of a metric space is one less than the Helly number of the family of metric balls in that space; Helly's theorem implies that the Helly dimension of a Euclidean space equals its dimension as a real vector space. [4]

The Helly dimension of a subset S of a Euclidean space, such as a polyhedron, is one less than the Helly number of the family of translates of S. [5] For instance, the Helly dimension of any hypercube is 1, even though such a shape may belong to a Euclidean space of much higher dimension. [6]

Helly dimension has also been applied to other mathematical objects. For instance Domokos (2007) defines the Helly dimension of a group (an algebraic structure formed by an invertible and associative binary operation) to be one less than the Helly number of the family of left cosets of the group. [7]

The Helly property

If a family of nonempty sets has an empty intersection, its Helly number must be at least two, so the smallest k for which the k-Helly property is nontrivial is k = 2. The 2-Helly property is also known as the Helly property. A 2-Helly family is also known as a Helly family. [1] [2]

A convex metric space in which the closed balls have the 2-Helly property (that is, a space with Helly dimension 1, in the stronger variant of Helly dimension for infinite subcollections) is called injective or hyperconvex. [8] The existence of the tight span allows any metric space to be embedded isometrically into a space with Helly dimension 1. [9]

The Helly property in hypergraphs

A hypergraph is equivalent to a set-family. In hypergraphs terms, a hypergraph H = (V, E) has the Helly property if for every n hyperedges in E, if , then . [10] :467 For every hypergraph H, the following are equivalent: [10] :470-471

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  1. 1 2 3 4 Bollobás, Béla (1986), Combinatorics: Set Systems, Hypergraphs, Families of Vectors, and Combinatorial Probability, Cambridge University Press, p. 82, ISBN   9780521337038 .
  2. 1 2 3 Duchet, Pierre (1995), "Hypergraphs", in Graham, R. L.; Grötschel, M.; Lovász, L. (eds.), Handbook of combinatorics, Vol. 1, 2, Amsterdam: Elsevier, pp. 381–432, MR   1373663 . See in particular Section 2.5, "Helly Property", pp. 393–394.
  3. This is the one-dimensional case of Helly's theorem. For essentially this proof, with a colorful phrasing involving sleeping students, see Savchev, Svetoslav; Andreescu, Titu (2003), "27 Helly's Theorem for One Dimension", Mathematical Miniatures, New Mathematical Library, 43, Mathematical Association of America, pp. 104–106, ISBN   9780883856451 .
  4. Martini, Horst (1997), Excursions Into Combinatorial Geometry, Springer, pp. 92–93, ISBN   9783540613411 .
  5. Bezdek, Károly (2010), Classical Topics in Discrete Geometry, Springer, p. 27, ISBN   9781441906007 .
  6. Sz.-Nagy, Béla (1954), "Ein Satz über Parallelverschiebungen konvexer Körper", Acta Universitatis Szegediensis, 15: 169–177, MR   0065942, archived from the original on 2016-03-04, retrieved 2013-09-10.
  7. Domokos, M. (2007), "Typical separating invariants", Transformation Groups, 12 (1): 49–63, arXiv: math/0511300 , doi:10.1007/s00031-005-1131-4, MR   2308028 .
  8. Deza, Michel Marie; Deza, Elena (2012), Encyclopedia of Distances, Springer, p. 19, ISBN   9783642309588
  9. Isbell, J. R. (1964), "Six theorems about injective metric spaces", Comment. Math. Helv., 39: 65–76, doi:10.1007/BF02566944 .
  10. 1 2 Lovász, László; Plummer, M. D. (1986), Matching Theory, Annals of Discrete Mathematics, 29, North-Holland, ISBN   0-444-87916-1, MR   0859549