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Induced Subgraphs and Hereditary Graph Classes
1 · Prerequisites
- Construction of the Natural Numbers
- Construction of the Real Numbers via Cauchy Sequences
- Construction of the Real Numbers via Dedekind Cuts
- Countability and Uncountability
- Finite Counting, Factorials and Binomial Coefficients
- Foundations of the Real Numbers for Analysis
- Graphs, Walks and Connectivity
- Relations, Functions, and Quotients
- Roots, Rational Powers, and Classical Inequalities
- The ZFC Axioms and the Basic Set Constructions
2 · Summary
Published finite-simple-graph, induced-subgraph, graph-isomorphism, complementation, connectivity, and finite-counting definitions provide the setting. An induced embedding preserves both adjacency and nonadjacency, so its image is stricter than an ordinary subgraph copy; the induced-copy number counts such injective maps rather than unlabelled vertex subsets.
Composition of induced embeddings makes -freeness hereditary, and every hereditary class is characterized by its possibly infinite minimal forbidden induced subgraphs. Complementation transports classes, bases, cliques and stable sets. Connectedness and anticonnectedness then organize component decompositions, while complete, anticomplete, pure and mixed disjoint vertex-set pairs record their cross-edge patterns.
3 · Logical flowchart
4 · Definitions, theorems and proofs
Induced embeddings and induced copies of a graph
Definition
Let and be finite simple graphs (A finite simple graph is a finite vertex set together with a set of two-element vertex subsets). An induced embedding of in is an injection such that, for all distinct ,
Thus preserves both adjacency and nonadjacency (Injection, surjection, bijection). Its image is an induced copy of in : the restricted map is an isomorphism from onto that induced subgraph (Subgraphs, induced subgraphs and spanning subgraphs, Graph isomorphisms, automorphisms and graph complements).
We say that is an induced subgraph of up to isomorphism when such an embedding exists.
Induced embeddings compose, and the induced-subgraph relation is transitive up to isomorphism
Statement
If and , then . Consequently, being an induced subgraph up to isomorphism is transitive.
Facts & Assumptions
Given: Induced embeddings and .
An induced embedding is injective and preserves adjacency in both directions (Induced embeddings and induced copies of a graph).
A composite of injections is injective (Injection, surjection, bijection).
Graph isomorphism is compatible with composition (Graph isomorphisms, automorphisms and graph complements).
Proof
The composite is injective.
For distinct , one has if and only if , if and only if .
Hence is an induced embedding. Replacing induced copies by their isomorphic representatives gives the stated transitivity up to isomorphism.
The induced-embedding count
Definition
For finite graphs and , define the induced-embedding count
The set inside the cardinality is a subset of the finite function set , so the displayed natural number is well defined (The set of functions between finite sets is finite, with , A subset of a finite set is finite, with , and equality holds if and only if , The cardinality of a finite set).
This convention counts labelled embeddings, not vertex subsets. An induced copy with image contributes one embedding for each isomorphism (Induced embeddings and induced copies of a graph).
is isomorphism-invariant and equals
Statement
If and , then
Moreover,
Facts & Assumptions
Given: Finite graphs with isomorphisms and .
is the finite cardinality of the induced-embedding set (The induced-embedding count ).
Isomorphisms and induced embeddings preserve adjacency and nonadjacency in both directions (Induced embeddings and induced copies of a graph, Graph isomorphisms, automorphisms and graph complements).
Proof
The assignment sends induced embeddings to induced embeddings .
The same vertex map is an induced embedding exactly when it is an induced embedding , because complementation reverses both adjacency tests simultaneously.
Its inverse is , so it is a bijection and the first equality follows.
The identity on maps is therefore a bijection between these embedding sets, proving the complement equality.
-free and -free graphs under the induced-subgraph convention
Definition
For finite graphs and , the graph is -free when has no induced copy of (Induced embeddings and induced copies of a graph). Equivalently,
(The induced-embedding count ).
For a family of finite graphs, a finite graph is -free when it is -free for every . Throughout this page, “free” always refers to induced subgraphs. It does not merely prohibit ordinary subgraph copies.
Every induced subgraph of an -free graph is -free
Statement
If is -free and is an induced subgraph of , then is -free.
Facts & Assumptions
Given: An -free graph and an induced embedding .
-free means that no has an induced embedding into (-free and -free graphs under the induced-subgraph convention).
Induced embeddings compose (Induced embeddings compose, and the induced-subgraph relation is transitive up to isomorphism).
Proof
Suppose is not -free. Then some has an induced embedding .
The composite is an induced embedding.
This contradicts that is -free. Hence is -free.
Hereditary graph classes
Definition
A class of finite simple graphs is a hereditary graph class when:
- it is closed under isomorphism; and
- whenever and has an induced embedding into , one has .
The second clause is closure under taking induced subgraphs (Induced embeddings and induced copies of a graph). Isomorphism closure makes membership depend only on graph structure, not on the chosen vertex labels (Graph isomorphisms, automorphisms and graph complements).
Every class defined by forbidden induced subgraphs is hereditary
Statement
For every family of finite graphs, the class of all -free finite graphs is hereditary.
Facts & Assumptions
Given: A family of finite graphs.
Induced subgraphs of an -free graph remain -free (Every induced subgraph of an -free graph is -free).
-freeness is invariant under graph isomorphism (-free and -free graphs under the induced-subgraph convention).
Heredity means closure under isomorphism and induced subgraphs (Hereditary graph classes).
Proof
The class of -free graphs is closed under isomorphism because an isomorphism transports every induced copy in both directions.
It is closed under induced subgraphs by L1.
These are exactly the two requirements for a hereditary class.
Minimal forbidden induced subgraphs and forbidden bases
Definition
Let be a hereditary class. A finite graph is a minimal forbidden induced subgraph for when
but every proper induced subgraph with belongs to (Subgraphs, induced subgraphs and spanning subgraphs).
The minimal forbidden basis is the class of all such graphs, understood up to isomorphism. More generally, a family is a forbidden induced-subgraph basis for when exactly when is -free (-free and -free graphs under the induced-subgraph convention). Minimality here concerns proper induced subgraphs, not ordinary subgraphs (Induced embeddings and induced copies of a graph, Hereditary graph classes).
Every hereditary graph class is determined by its unique minimal forbidden induced subgraphs
Statement
For every hereditary graph class and every finite graph ,
If is any forbidden induced-subgraph basis for , then for every , the family contains a graph isomorphic to . Consequently, is, up to isomorphism, the unique inclusion-minimal forbidden basis for .
Facts & Assumptions
Given: A hereditary class and a finite graph .
Membership in passes to induced subgraphs and is invariant under graph isomorphism (Hereditary graph classes).
consists exactly of graphs outside all of whose proper induced subgraphs lie in (Minimal forbidden induced subgraphs and forbidden bases).
A finite vertex set has finitely many subsets, whose cardinalities are natural numbers; every nonempty set of natural numbers has a least element (The cardinality of a finite set, for finite , The well-ordering principle).
-free means containing no induced member of (-free and -free graphs under the induced-subgraph convention).
Proof
If , then no induced subgraph of lies outside , so in particular contains no member of .
Suppose . Among vertex sets for which , choose one of least cardinality; it exists because is available.
Let be any forbidden induced-subgraph basis for . Every lies outside : otherwise would contain itself as an induced copy of a member of , contradicting the defining equivalence for .
Every proper induced subgraph of lies in by minimality of . Hence .
Fix . Since , it is not -free, so some occurs as an induced subgraph of . If that copy were proper, then it would lie in by the minimality of ; closure under isomorphism would give , contradicting step 1.3. Thus the copy uses all vertices of , and .
Thus is not -free. Together with step 1.1 this proves the equivalence.
Hence every forbidden basis for contains, up to isomorphism, every member of . Since is itself a basis by step 3.1, it is inclusion-minimal, and any inclusion-minimal forbidden basis has no additional members. This proves uniqueness up to isomorphism.
Every nonempty hereditary graph class contains the null graph
Statement
Every nonempty hereditary class of finite graphs contains the null graph .
Facts & Assumptions
Given: A nonempty hereditary graph class .
Choose .
The induced subgraph is the null graph (Subgraphs, induced subgraphs and spanning subgraphs, Empty and complete graphs, complete bipartite graphs, and the convention that and have vertices).
A hereditary class contains every induced subgraph of each member (Hereditary graph classes).
Proof
Since , heredity gives .
Since , the null graph belongs to .
The complement of a graph class
Definition
For a graph class , its complement class is
It consists exactly of those graphs whose complements belong to . If is isomorphism-closed, this is equivalently the isomorphism-closed class of complements of members of (Graph isomorphisms, automorphisms and graph complements). The notation does not mean set-theoretic complement inside the class of all graphs.
When is isomorphism-closed, so is , because an isomorphism of graphs induces an isomorphism of their complements.
for every vertex set
Statement
For every finite graph and every ,
as graphs on vertex set .
Facts & Assumptions
Given: A graph and .
retains exactly the edges of with both endpoints in (Subgraphs, induced subgraphs and spanning subgraphs).
Complementation replaces adjacency by nonadjacency between distinct vertices (Graph isomorphisms, automorphisms and graph complements).
Proof
Both displayed graphs have vertex set .
For distinct , is an edge of if and only if it is not an edge of , if and only if it is not an edge of , if and only if it is an edge of .
Their vertex and edge sets are equal, so the graphs are equal.
Complementation preserves hereditary classes and complements their minimal forbidden bases
Statement
If is hereditary, then is hereditary and
up to isomorphism.
Facts & Assumptions
Given: A hereditary graph class .
exactly when (The complement of a graph class).
Complementation commutes with taking induced subgraphs ( for every vertex set ).
A minimal forbidden graph lies outside the class while all its proper induced subgraphs lie inside (Minimal forbidden induced subgraphs and forbidden bases).
A hereditary class is determined by its unique minimal forbidden basis (Every hereditary graph class is determined by its unique minimal forbidden induced subgraphs).
Proof
Let and . Then , so by heredity.
Let . Then , while for every proper , and therefore .
Since , one has . Isomorphism closure is likewise preserved, so is hereditary.
Hence . Applying the same argument to the involution of complementation gives the reverse inclusion.
Therefore the minimal bases are complementary as claimed.
is -free if and only if is -free
Statement
For finite graphs and ,
Facts & Assumptions
Given: Finite graphs and .
-free means containing no induced copy of (-free and -free graphs under the induced-subgraph convention).
Complementation commutes with induced subgraphs ( for every vertex set ).
Complementation carries isomorphisms to isomorphisms (Graph isomorphisms, automorphisms and graph complements).
Proof
For every , one has if and only if .
Thus contains an induced if and only if contains an induced . Negating both sides gives the claimed equivalence.
Cliques, stable sets, the clique number and stability number
Definition
Let be a finite simple graph. A set is a clique when every two distinct vertices of are adjacent, equivalently when is complete. It is a stable set, or independent set, when no two distinct vertices of are adjacent, equivalently when is edgeless (Subgraphs, induced subgraphs and spanning subgraphs, Empty and complete graphs, complete bipartite graphs, and the convention that and have vertices).
The clique number and stability number are
Both maxima exist because the families are nonempty, containing , and lie inside the finite power set of (The cardinality of a finite set, for finite , A subset of a finite set is finite, with , and equality holds if and only if , The well-ordering principle). In particular, .
Complementation swaps cliques with stable sets, so
Statement
For every finite graph , a vertex set is a clique in if and only if it is a stable set in . Consequently,
Facts & Assumptions
Given: A finite graph and .
A clique has all possible edges among its vertices, while a stable set has none (Cliques, stable sets, the clique number and stability number ).
Distinct vertices are adjacent in exactly when they are nonadjacent in (Graph isomorphisms, automorphisms and graph complements).
Proof
Every pair of distinct vertices in is adjacent in if and only if no such pair is adjacent in .
Thus is a clique in if and only if it is stable in , and symmetrically is stable in if and only if it is a clique in .
The same vertex sets occur in the paired maximizations and retain their cardinalities, so the two displayed equalities follow.
Anticonnected graphs and anticonnected components
Definition
A graph is anticonnected, or co-connected, when its complement is connected (Connected graphs and connected components defined by the existence of vertex paths, Graph isomorphisms, automorphisms and graph complements).
An anticonnected component, or anticomponent, of is a vertex set that is the vertex set of a connected component of . Equivalently, is anticonnected and is inclusion-maximal with that property (Subgraphs, induced subgraphs and spanning subgraphs).
Under the library convention, the null graph is not anticonnected, while a one-vertex graph is anticonnected.
The anticonnected components of are exactly the connected components of
Statement
For every graph , its anticomponents are exactly the vertex sets of the connected components of . In particular, they partition .
Facts & Assumptions
Given: A finite graph .
Anticomponents are defined to be the component vertex sets of (Anticonnected graphs and anticonnected components).
Connected components partition a graph's vertex set (The connected components of a graph partition its vertex set and are its maximal connected subgraphs).
( for every vertex set ).
Proof
By F1, a set is an anticomponent of exactly when it is the vertex set of a connected component of .
Equivalently, is connected and is maximal with this property.
The component partition theorem applied to shows that these sets partition .
Every graph with at least two vertices is connected or anticonnected
Statement
Every finite graph with at least two vertices is connected or anticonnected. Equivalently, if is disconnected and nontrivial, then is connected.
Facts & Assumptions
Given: A finite graph with .
is anticonnected exactly when is connected (Anticonnected graphs and anticonnected components).
If is disconnected, its connected components partition into at least two nonempty parts (The connected components of a graph partition its vertex set and are its maximal connected subgraphs, Connected graphs and connected components defined by the existence of vertex paths).
Vertices in different components of are nonadjacent in and hence adjacent in (Graph isomorphisms, automorphisms and graph complements).
Proof
If is connected, the first alternative holds. Suppose instead that is disconnected.
Let . If , the length-zero path joins them. If they are distinct and lie in different components, then .
If and they lie in the same component, choose a vertex in a different component. Then , so is an - path in .
Every two vertices are therefore joined in , so is connected and is anticonnected.
Edges between disjoint vertex sets; complete, anticomplete, pure and mixed pairs
Definition
Let be a finite simple graph and let be disjoint. An edge between and is an edge with and .
The pair is:
- complete when every is adjacent to every ;
- anticomplete when no is adjacent to any ;
- pure when it is complete or anticomplete; and
- mixed when it is neither complete nor anticomplete.
Adjacency is the symmetric edge relation of (A finite simple graph is a finite vertex set together with a set of two-element vertex subsets, Adjacency, incidence, open and closed neighbourhoods, vertex degree, minimum degree and maximum degree). If or , the pair is both complete and anticomplete, hence pure and not mixed.
Purity is symmetric; complementation swaps complete and anticomplete pairs and preserves mixed pairs
Statement
For disjoint vertex sets in a graph :
- is complete, anticomplete, pure or mixed exactly when has the same property;
- complementation swaps complete pairs with anticomplete pairs; and
- complementation preserves pure pairs and mixed pairs.
Facts & Assumptions
Given: A graph and disjoint sets .
Complete, anticomplete, pure and mixed pairs are defined by the cross-pair adjacency pattern (Edges between disjoint vertex sets; complete, anticomplete, pure and mixed pairs).
Graph adjacency is symmetric, and complementation exchanges adjacency with nonadjacency between distinct vertices (Graph isomorphisms, automorphisms and graph complements).
Proof
Since and describe the same edge, reversing the ordered pair of sets changes none of the four properties.
Every cross pair is an edge of exactly when no cross pair is an edge of ; likewise, no cross pair is an edge of exactly when every cross pair is an edge of .
Hence complementation swaps complete and anticomplete pairs. It therefore preserves their union, the pure pairs, and its complement, the mixed pairs.
Together with symmetry from step 1.1, this proves all assertions.
Distinct connected components are anticomplete, and distinct anticonnected components are complete
Statement
Distinct connected components of a graph are anticomplete to one another. Distinct anticomponents are complete to one another.
Facts & Assumptions
Given: A finite graph .
Connected components partition the vertices into maximal connected parts (The connected components of a graph partition its vertex set and are its maximal connected subgraphs).
Anticomponents of are connected components of (The anticonnected components of are exactly the connected components of ).
Complementation swaps anticomplete pairs with complete pairs (Purity is symmetric; complementation swaps complete and anticomplete pairs and preserves mixed pairs).
Anticomplete and complete pairs have respectively no and all cross edges (Edges between disjoint vertex sets; complete, anticomplete, pure and mixed pairs).
Proof
No edge joins two distinct connected components, since such an edge would connect them into one component. Thus distinct components are anticomplete.
Distinct anticomponents of are distinct connected components of , so they are anticomplete in by step 1.1 applied there.
Complementing back makes those two sets complete in .
5 · Examples, counterexamples and false statements
None yet.
Sources
Standard references
Recommended treatments; not extraction sources.