Forbidden subgraph problem explained
In extremal graph theory, the forbidden subgraph problem is the following problem: given a graph
, find the maximal number of edges
an
-vertex graph can have such that it does not have a subgraph
isomorphic to
. In this context,
is called a
forbidden subgraph.
[1] An equivalent problem is how many edges in an
-vertex graph guarantee that it has a subgraph isomorphic to
?
[2] Definitions
The extremal number
is the maximum number of edges in an
-vertex graph containing no subgraph isomorphic to
.
is the
complete graph on
vertices.
is the
Turán graph: a complete
-partite graph on
vertices, with vertices distributed between parts as equally as possible. The chromatic number
of
is the minimum number of colors needed to color the vertices of
such that no two adjacent vertices have the same color.
Upper bounds
Turán's theorem
See also: Turán's theorem. Turán's theorem states that for positive integers
satisfying
,
[3] This solves the forbidden subgraph problem for
. Equality cases for Turán's theorem come from the
Turán graph
.
This result can be generalized to arbitrary graphs
by considering the chromatic number
of
. Note that
can be colored with
colors and thus has no subgraphs with chromatic number greater than
. In particular,
has no subgraphs isomorphic to
. This suggests that the general equality cases for the forbidden subgraph problem may be related to the equality cases for
. This intuition turns out to be correct, up to
error.
Erdős–Stone theorem
See also: Erdős–Stone theorem. Erdős–Stone theorem states that for all positive integers
and all graphs
,
[4] When
is not bipartite, this gives us a first-order approximation of
.
Bipartite graphs
For bipartite graphs
, the Erdős–Stone theorem only tells us that
\operatorname{ex}(n,G)=o(n2)
. The forbidden subgraph problem for bipartite graphs is known as the
Zarankiewicz problem, and it is unsolved in general.
Progress on the Zarankiewicz problem includes following theorem:
Kővári–Sós–Turán theorem. For every pair of positive integers
with
, there exists some constant
(independent of
) such that
for every positive integer
.
Another result for bipartite graphs is the case of even cycles,
. Even cycles are handled by considering a root vertex and paths branching out from this vertex. If two paths of the same length
have the same endpoint and do not overlap, then they create a cycle of length
. This gives the following theorem.
Theorem (Bondy and Simonovits, 1974). There exists some constant
such that
for every positive integer
and positive integer
.
[5] A powerful lemma in extremal graph theory is dependent random choice. This lemma allows us to handle bipartite graphs with bounded degree in one part:
Theorem (Alon, Krivelevich, and Sudakov, 2003). Let
be a bipartite graph with vertex parts
and
such that every vertex in
has degree at most
. Then there exists a constant
(dependent only on
) such that
for every positive integer
.
[6] In general, we have the following conjecture.:
Rational Exponents Conjecture (Erdős and Simonovits). For any finite family
of graphs, if there is a bipartite
, then there exists a rational
such that
\operatorname{ex}(n,l{L})=\Theta(n1+\alpha)
.
A survey by Füredi and Simonovits describes progress on the forbidden subgraph problem in more detail.[7]
Lower bounds
There are various techniques used for obtaining the lower bounds.
Probabilistic method
While this method mostly gives weak bounds, the theory of random graphs is a rapidly developing subject. It is based on the idea that if we take a graph randomly with a sufficiently small density, the graph would contain only a small number of subgraphs of
inside it. These copies can be removed by removing one edge from every copy of
in the graph, giving us a
free graph.
The probabilistic method can be used to prove
\operatorname{ex}(n,G)\ge
where
is a constant only depending on the graph
.
[8] For the construction we can take the Erdős-Rényi random graph
, that is the graph with
vertices and the edge been any two vertices drawn with probability
, independently. After computing the expected number of copies of
in
by linearity of expectation, we remove one edge from each such copy of
and we are left with a
-free graph in the end. The expected number of edges remaining can be found to be
\operatorname{ex}(n,G)\ge
for a constant
depending on
. Therefore, at least one
-vertex graph exists with at least as many edges as the expected number.
This method can also be used to find the constructions of a graph for bounds on the girth of the graph. The girth, denoted by
, is the length of the shortest cycle of the graph. Note that for
, the graph must forbid all the cycles with length less than equal to
. By linearity of expectation,the expected number of such forbidden cycles is equal to the sum of the expected number of cycles
(for
.). We again remove the edges from each copy of a forbidden graph and end up with a graph free of smaller cycles and
, giving us
edges in the graph left.
Algebraic constructions
For specific cases, improvements have been made by finding algebraic constructions. A common feature for such constructions is that it involves the use of geometry to construct a graph, with vertices representing geometric objects and edges according to the algebraic relations between the vertices. We end up with no subgraph of
, purely due to purely geometric reasons, while the graph has a large number of edges to be a strong bound due to way the incidences were defined. The following proof by Erdős, Rényi, and Sős
[9] establishing the lower bound on
\operatorname{ex}(n,K2,2)
as
, demonstrates the power of this method.
First, suppose that
for some prime
. Consider the
polarity graph
with vertices elements of
and edges between vertices
and
if and only if
in
. This graph is
-free because a system of two linear equations in
cannot have more than one solution. A vertex
(assume
) is connected to
for any
, for a total of at least
edges (subtracted 1 in case
). So there are at least
edges, as desired. For general
, we can take
with
(which is possible because there exists a prime
in the interval
for sufficiently large
) and construct a polarity graph using such
, then adding
isolated vertices, which do not affect the asymptotic value.
The following theorem is a similar result for
.
Theorem (Brown, 1966).
\operatorname{ex}(n,K3,3)\ge\left(
-o(1)\right)n5/3.
[10] Proof outline.[11] Like in the previous theorem, we can take
for prime
and let the vertices of our graph be elements of
. This time, vertices
and
are connected if and only if
in
, for some specifically chosen
. Then this is
-free since at most two points lie in the intersection of three spheres. Then since the value of
is almost uniform across
, each point should have around
edges, so the total number of edges is
-o(1)\right)p2 ⋅
-o(1)\right)n5/3
.
However, it remains an open question to tighten the lower bound for
\operatorname{ex}(n,Kt,t)
for
.
Theorem (Alon et al., 1999) For
,
\operatorname{ex}(n,Ks,t)=
).
[12] Randomized Algebraic constructions
This technique combines the above two ideas. It uses random polynomial type relations when defining the incidences between vertices, which are in some algebraic set. Using this technique to prove the following theorem.
Theorem: For every
, there exists some
such that
\operatorname{ex}(n,Ks,t)\geq\left(
-o(1)\right)
.
Proof outline: We take the largest prime power
with
. Due to the prime gaps, we have
. Let
f\inFq[x1,x2, … ,xs,y1,y2, … ,ys]\le
be a random polynomial in
with degree at most
in
and
and satisfying
. Let the graph
have the vertex set
such that two vertices
are adjacent if
.
We fix a set
, and defining a set
as the elements of
not in
satisfying
for all elements
. By the Lang–Weil bound, we obtain that for
sufficiently large enough, we have
or
for some constant
.Now, we compute the expected number of
such that
has size greater than
, and remove a vertex from each such
. The resulting graph turns out to be
free, and at least one graph exists with the expectation of the number of edges of this resulting graph.
Supersaturation
Supersaturation refers to a variant of the forbidden subgraph problem, where we consider when some
-uniform graph
contains many copies of some forbidden subgraph
. Intuitively, one would expect this to once
contains significantly more than
edges. We introduce Turán density to formalize this notion.
Turán density
The Turán density of a
-uniform graph
is defined to be
\pi(G)=\limn
| \operatorname{ex |
(n,G)}{\binom{n}{h}}. |
It is true that
| \operatorname{ex |
(n,G)}{\binom{n}{h}} |
is in fact positive and monotone decreasing, so the limit must therefore exist.
[13] As an example, Turán's Theorem gives that
, and the Erdős–Stone theorem gives that
. In particular, for bipartite
,
. Determining the Turán density
is equivalent to determining
up to an
error.
[14] Supersaturation Theorem
Consider an
-uniform hypergraph
with
vertices. The supersaturation theorem states that for every
, there exists a
such that if
is an
-uniform hypergraph on
vertices and at least
(\pi(H)+\epsilon)\binom{n}{h}
edges for
sufficiently large, then there are at least
copies of
.
[15] Equivalently, we can restate this theorem as the following: If a graph
with
vertices has
copies of
, then there are at most
edges in
.
Applications
We may solve various forbidden subgraph problems by considering supersaturation-type problems. We restate and give a proof sketch of the Kővári–Sós–Turán theorem below:
Kővári–Sós–Turán theorem. For every pair of positive integers
with
, there exists some constant
(independent of
) such that
for every positive integer
.
Proof. Let
be a
-graph on
vertices, and consider the number of copies of
in
. Given a vertex of degree
, we get exactly
copies of
rooted at this vertex, for a total of
\sumv\binom{\operatorname{deg}(v)}{s}
copies. Here,
when
. By convexity, there are at total of at least
copies of
. Moreover, there are clearly
subsets of
vertices, so if there are more than
copies of
, then by the
Pigeonhole Principle there must exist a subset of
vertices which form the set of leaves of at least
of these copies, forming a
. Therefore, there exists an occurrence of
as long as we have
n\binom{2e(G)/n}{s}>(t-1)\binom{n}{s}
. In other words, we have an occurrence if
, which simplifies to
, which is the statement of the theorem.
[16] In this proof, we are using the supersaturation method by considering the number of occurrences of a smaller subgraph. Typically, applications of the supersaturation method do not use the supersaturation theorem. Instead, the structure often involves finding a subgraph
of some forbidden subgraph
and showing that if it appears too many times in
, then
must appear in
as well. Other theorems regarding the forbidden subgraph problem which can be solved with supersaturation include:
Generalizations
The problem may be generalized for a set of forbidden subgraphs
: find the maximal number of edges in an
-vertex graph which does not have a subgraph isomorphic to any graph from
.
[17] There are also hypergraph versions of forbidden subgraph problems that are much more difficult. For instance, Turán's problem may be generalized to asking for the largest number of edges in an
-vertex 3-uniform hypergraph that contains no tetrahedra. The analog of the Turán construction would be to partition the vertices into almost equal subsets
, and connect vertices
by a 3-edge if they are all in different
s, or if two of them are in
and the third is in
(where
). This is tetrahedron-free, and the edge density is
. However, the best known upper bound is 0.562, using the technique of flag algebras.
[18] See also
Notes and References
- Combinatorics: Set Systems, Hypergraphs, Families of Vectors and Probabilistic Combinatorics, Béla Bollobás, 1986,, p. 53, 54
- "Modern Graph Theory", by Béla Bollobás, 1998,, p. 103
- Turán. Pál. 1941. On an extremal problem in graph theory. Matematikai és Fizikai Lapok. hu. 48. 436–452.
- Erdős. P.. Paul Erdős. Stone, A. H.. Arthur Stone (mathematician). 1946. On the structure of linear graphs. Bulletin of the American Mathematical Society. 52. 12. 1087–1091. 10.1090/S0002-9904-1946-08715-7. free.
- Bondy. J. A.. John Adrian Bondy. Simonovits. M.. Miklós Simonovits. Cycles of even length in graphs.. . Series B. 16. 2. April 1974. 97–105. 10.1016/0095-8956(74)90052-5. free. 340095.
- Alon. Noga. Noga Alon. Krivelevich. Michael. Michael Krivelevich. Sudakov. Benny. Benny Sudakov. Turán numbers of bipartite graphs and related Ramsey-type questions. Combinatorics, Probability and Computing. 2037065.
- Füredi. Zoltán. Simonovits. Miklós. 2013-06-21. The history of degenerate (bipartite) extremal graph problems. 1306.5167. math.CO.
- Web site: Zhao. Yufei. Graph Theory and Additive Combinatorics. 2 December 2019. 3237.
- Erdős. P.. Rényi. A.. Sós. V. T.. 1966. On a problem of graph theory. Studia Sci. Math. Hungar. 1. 215235. 223262.
- Brown. W. G.. 1966. 281285. On graphs that do not contain a Thomsen graph. . 9 . 3. 10.4153/CMB-1966-036-2 . free . 200182.
- Web site: Graph Theory and Additive Combinatorics. Zhao . Yufei . 3237. 2 December 2019.
- Alon. Noga. Rónyai. Lajos. Szabó. Tibor. 1999. 280290. Norm-graphs: variations and applications. . Series B . 76. 2. 1699238. 10.1006/jctb.1999.1906. free.
- Web site: Supersaturated Graphs and Hypergraphs. Erdős. Paul. Simonovits. Miklós. 3. 27 November 2021.
- Web site: Graph Theory and Additive Combinatorics. Zhao . Yufei . 1617. 2 December 2019.
- Web site: Extremal Graph Problems, Degenerate Extremal Problems, and Supersaturated Graphs. Simonovits . Miklós. 17. 25 November 2021.
- Web site: Extremal Graph Problems, Degenerate Extremal Problems, and Supersaturated Graphs. Simonovits. Miklós. 27 November 2021.
- Handbook of Discrete and Combinatorial Mathematics By Kenneth H. Rosen, John G. Michaels p. 590
- Web site: Hypergraph Turán Problems. Keevash . Peter. 2 December 2019.