Forcing graph

Summary

In graph theory, a forcing graph is one whose density determines whether a graph sequence is quasi-random. The term was first coined by Chung, Graham, and Wilson in 1989.,[1] and forcing graphs play an important role in the study of pseudorandomness in graph sequences.

Definitions edit

Let t(H, G) = # labeled copies of H in G/v(G)v(H), known as the subgraph density (in particular, t(K2, G) is the edge density of G). A sequence of graphs {Gn} is called quasi-random if, for all graphs H, the edge density t(K2, Gn) approaches some p and t(H, Gn) approaches pe(H) as n increases, where e(H) is the number of edges in H. Intuitively, this means that a graph sequence with a given edge density has the number of graph homomorphisms that one would expect in a random graph sequence. A graph F is called forcing if for all graph sequences {Gn} where t(K2, Gn) approaches p as n goes to infinity, {Gn} is quasi-random if t(F, Gn) approaches pe(F). In other words, one can verify that a sequence of graphs is quasi-random by just checking the homomorphism density of a single graph.[2]

There is a second definition of forcing graphs using the language of graphons. Formally, a graph is called forcing if every graphon W such that t(F, W) = t(K2, W)e(F) is constant. Intuitively, it makes sense that these definitions are related. The constant graphon W(x, y) = p represents the Erdős–Rényi random graph G(n, p), so one could expect it to have a close relationship with quasi-random graphs. In fact, these definitions are equivalent.[citation needed]

Examples edit

The first forcing graph to be considered is the 4-cycle C4, as it bears a close relationship with other conditions of quasi-randomness. It was shown in the same paper by Chung, Graham, and Wilson that every even cycle C2t and complete bipartite graphs of the form K2,t with t ≥ 2 are forcing.[1] Conlon, Fox, and Sudakov expanded this last result to include all bipartite graphs with two vertices in one part that are complete to the other part[2]

Forcing families edit

Forcing families provide a natural generalization of forcing graphs. A family of graphs F is forcing {Gn} is quasi-random whenever t(F, Gn) approaches pe(F) for all FF. Characterizing forcing families is much more challenging than characterizing forcing graphs, so there are few that are known. Known forcing families include:

  • {K2, C2t}, where t is a positive integer;
  • {C2s, C2t}, where s and t are positive integers with st;
  • {K2, K2,t}, where t ≥ 2; and
  • {K2,s, K2,t}, where st and s, t ≥ 2.[1]

Forcing conjecture edit

The forcing conjecture was posed by Skokan and Thoma in 2004[3] and formalized by Conlon, Fox, and Sudakov in 2010.[2] It provides a characterization for forcing graphs, formalized as follows:

A graph is forcing if and only if it is bipartite and contains a cycle.

One direction of this claim is well-known. Chung, Graham, and Wilson showed that if a graph has an odd cycle, it cannot be forcing,[1] so if a graph is forcing, then it must be bipartite. Also, Conlon, Fox, and Sudakov argued that t(H, Gn) approaches pe(H) for every forest H when {Gn} is a nearly regular (and not necessarily quasi-random) graph sequences.[2] Thus, a forcing graph must be bipartite and have at least one cycle. The other direction is yet to be proven, but no forcing graph that does not have both of these properties has been found.

The forcing conjecture also implies Sidorenko's conjecture, a long-standing conjecture in the field. It is known that all forcing graphs are Sidorenko, so if the forcing conjecture is true, then all bipartite graphs with at least one cycle would be Sidorenko.[2] Since trees are Sidorenko,[4] all bipartite graphs would be Sidorenko.

References edit

  1. ^ a b c d Chung, F. R. K.; Graham, R. L.; Wilson, R. M. (1989-12-01). "Quasi-random graphs". Combinatorica. 9 (4): 345–362. doi:10.1007/BF02125347. ISSN 1439-6912. S2CID 17166765.
  2. ^ a b c d e Conlon, David; Fox, Jacob; Sudakov, Benny (2010-10-20). "An Approximate Version of Sidorenko's Conjecture". Geometric and Functional Analysis. 20 (6): 1354–1366. arXiv:1004.4236. doi:10.1007/s00039-010-0097-0. ISSN 1016-443X. S2CID 1872674.
  3. ^ Skokan, Jozef; Thoma, Lubos (2004-06-01). "Bipartite Subgraphs and Quasi-Randomness". Graphs and Combinatorics. 20 (2): 255–262. doi:10.1007/s00373-004-0556-1. ISSN 0911-0119. S2CID 2154492.
  4. ^ SIDORENKO, A. F. (1992). "Inequalities for functionals generated by bipartite graphs". Discrete Mathematics and Applications. 2 (5). doi:10.1515/dma.1992.2.5.489. ISSN 0924-9265. S2CID 117471984.