Packing in a hypergraph

In mathematics, a packing in a hypergraph is a partition of the set of the hypergraph's edges into a number of disjoint subsets such that no pair of edges in each subset share any vertex. There are two famous algorithms to achieve asymptotically optimal packing in k-uniform hypergraphs. One of them is a random greedy algorithm which was proposed by Joel Spencer. He used a branching process to formally prove the optimal achievable bound under some side conditions. The other algorithm is called the Rödl nibble and was proposed by Vojtěch Rödl et al. They showed that the achievable packing by the Rödl nibble is in some sense close to that of the random greedy algorithm.

History edit

The problem of finding the number of such subsets in a k-uniform hypergraph was originally motivated through a conjecture by Paul Erdős and Haim Hanani in 1963. Vojtěch Rödl proved their conjecture asymptotically under certain conditions in 1985. Pippenger and Joel Spencer generalized Rödl's results using a random greedy algorithm in 1989.

Definition and terminology edit

In the following definitions, the hypergraph is denoted by H=(V,E). H is called a k-uniform hypergraph if every edge in E consists of exactly k vertices.

  is a hypergraph packing if it is a subset of edges in H such that there is no pair of distinct edges with a common vertex.

  is a ( , )-good hypergraph if there exists a   such that for all   and   and both of the following conditions hold.

 
 

where the degree   of a vertex   is the number of edges that contain   and the codegree   of two distinct vertices   and   is the number of edges that contain both vertices.

Theorem edit

There exists an asymptotic packing P of size at least   for a  -uniform hypergraph under the following two conditions,

  1. All vertices have the degree of   in which   tends to infinity.
  2. For every pair of vertices shares only   common edges.

where   is the total number of vertices. This result was shown by Pippenger and was later proved by Joel Spencer. To address the asymptotic hypergraph packing problem, Joel Spencer proposed a random greedy algorithm. In this algorithm, a branching process is used as the basis and it was shown that it almost always achieves an asymptotically optimal packing under the above side conditions.

Asymptotic packing algorithms edit

There are two famous algorithms for asymptotic packing of k-uniform hypergraphs: the random greedy algorithm via branching process, and the Rödl nibble.

Random greedy algorithm via branching process edit

Every edge   is independently and uniformly assigned a distinct real "birthtime"  . The edges are taken one by one in the order of their birthtimes. The edge   is accepted and included in   if it does not overlap any previously accepted edges. Obviously, the subset   is a packing and it can be shown that its size is   almost surely. To show that, let stop the process of adding new edges at time  . For an arbitrary  , pick   such that for any  -good hypergraph   where   denotes the probability of vertex   survival (a vertex survives if it is not in any edges in  ) until time  . Obviously, in such a situation the expected number of   surviving at time   is less than  . As a result, the probability of   surviving being less than   is higher than  . In other words,   must include at least   vertices which means that  .

To complete the proof, it must be shown that  . For that, the asymptotic behavior of   surviving is modeled by a continuous branching process. Fix   and begin with Eve with the birthdate of  . Assume time goes backward so Eve gives birth in the interval of   with a unit density Poisson distribution. The probability of Eve having   birth is  . By conditioning on   the birthtimes   are independently and uniformly distributed on  . Every birth given by Eve consists of   offspring all with the same birth time say  . The process is iterated for each offspring. It can be shown that for all   there exists a   so that with a probability higher than  , Eve has at most   descendants.

A rooted tree with the notions of parent, child, root, birthorder and wombmate shall be called a broodtree. Given a finite broodtree   we say for each vertex that it survives or dies. A childless vertex survives. A vertex dies if and only if it has at least one brood all of whom survive. Let   denote the probability that Eve survives in the broodtree   given by the above process. The objective is to show   and then for any fixed  , it can be shown that  . These two relations complete our argument.

To show  , let  . For   small,   as, roughly, an Eve starting at time   might have a birth in time interval   all of whose children survive while Eve has no births in   all of whose children survive. Letting   yields the differential equation  . The initial value   gives a unique solution  . Note that indeed  .

To prove  , consider a procedure we call History which either aborts or produces a broodtree. History contains a set   of vertices, initially  .   will have a broodtree structure with   the root. The   are either processed or unprocessed,   is initially unprocessed. To each   is assigned a birthtime  , we initialize  . History is to take an unprocessed   and process it as follows. For the value of all   with   but with no   that has already been processed, if either some   has   and   with   or some   have   with   and  , then History is aborted. Otherwise for each   with   add all   to   as wombmates with parent   and common birthdate  . Now   is considered processed. History halts, if not aborted, when all   are processed. If History does not abort then root   survives broodtree   if and only if   survives at time  . For a fixed broodtree, let   denote the probability that the branching process yields broodtree  . Then the probability that History does not abort is  . By the finiteness of the branching process,  , the summation over all broodtrees   and History does not abort. The   distribution of its broodtree approaches the branching process distribution. Thus  .

The Rödl nibble edit

In 1985, Rödl proved Paul Erdős’s conjecture by a method called the Rödl nibble. Rödl's result can be formulated in form of either packing or covering problem. For   the covering number denoted by   shows the minimal size of a family   of  -element subsets of   which have the property that every  -element set is contained in at least one  . Paul Erdős et al. conjecture was

 .

where  . This conjecture roughly means that a tactical configuration is asymptotically achievable. One may similarly define the packing number   as the maximal size of a family   of  -element subsets of   having the property that every  -element set is contained in at most one  .

Packing under the stronger condition edit

In 1997, Noga Alon, Jeong Han Kim, and Joel Spencer also supply a good bound for   under the stronger codegree condition that every distinct pair   has at most one edge in common.

For a k-uniform, D-regular hypergraph on n vertices, if k > 3, there exists a packing P covering all vertices but at most  . If k = 3 there exists a packing P covering all vertices but at most  .

This bound is desirable in various applications, such as Steiner triple system. A Steiner Triple System is a 3-uniform, simple hypergraph in which every pair of vertices is contained in precisely one edge. Since a Steiner Triple System is clearly d=(n-1)/2-regular, the above bound supplies the following asymptotic improvement.

Any Steiner Triple System on n vertices contains a packing covering all vertices but at most  .

This has subsequently improved to  [1] and  [2]

See also edit

References edit

  1. ^ Keevash, Peter; Pokrovskiy, Alexey; Sudakov, Benny; Yepremyan, Liana (2022-04-15). "New bounds for Ryser's conjecture and related problems". Transactions of the American Mathematical Society, Series B. 9 (8): 288–321. doi:10.1090/btran/92. hdl:20.500.11850/592212. ISSN 2330-0000.
  2. ^ Montgomery, Richard (2023). "A proof of the Ryser-Brualdi-Stein conjecture for large even n". arXiv:2310.19779 [math.CO].