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Classical and Log-Log Erdős–Hajnal Bounds
1 · Prerequisites
- Absolute and Conditional Convergence; Rearrangement; Products
- Binary Operations, Monoids, Groups and Subgroups
- Compactness in Metric Spaces
- Completeness, Completion, and Uniform Continuity
- Construction of the Natural Numbers
- Construction of the Real Numbers via Cauchy Sequences
- Construction of the Real Numbers via Dedekind Cuts
- Continuity, IVT, EVT, and Uniform Continuity
- Countability and Uncountability
- Finite Counting, Factorials and Binomial Coefficients
- Foundations of the Real Numbers for Analysis
- Graph Colouring
- Graphs, Walks and Connectivity
- Inclusion–Exclusion, the Pigeonhole Principle and Double Counting
- Induced Subgraphs and Hereditary Graph Classes
- Limits of Real Functions
- limsup, liminf, and Subsequential Limits
- Metric Spaces
- Monotone Functions, Discontinuities, and Continuity Sets
- Monotone Sequences, Bolzano-Weierstrass, and Cauchy Completeness
- Order, Zorn's Lemma, and the Axiom of Choice
- Power Series and Real-Analytic Functions
- Properties of the Integral and the Working FTC
- Regular Pairs and Induced Counting
- Relations, Functions, and Quotients
- Roots, Rational Powers, and Classical Inequalities
- Sequences and Limits
- Sequences and Series of Functions; Uniform Convergence
- Series: Convergence and the Nonnegative Tests
- Sparse Restricted Subgraphs and the Rödl–Nikiforov Theorems
- Suprema and Infima
- The Derivative and the Mean Value Theorems
- The Erdős–Hajnal Property and Homogeneous Sets
- The Exponential Function
- The Logarithm and General Powers
- The Riemann Integral: Definition and Integrability
- The ZFC Axioms and the Basic Set Constructions
- Topology of ℝ
- Vector Spaces, Linear Subspaces, Span and Direct Sums
2 · Summary
Homogeneous sets, sparse induced subgraphs, greedy colouring, the product bound , complementation, and base- logarithms are the ingredients behind the quantitative Erdős–Hajnal estimates. The page uses them in one fixed order: a density theorem isolates a large induced subgraph with few edges or few nonedges, trimming turns low density into bounded degree, colouring extracts a large stable set, and the complement turns the same argument into a clique bound.
The page then records two source-cited quantitative density inputs, one on the classical scale and one on the improved scale, and proves from them the corresponding homogeneous-set lower bounds for -free graphs. A final corollary compares the two exponents and shows that the log-log scale eventually dominates every fixed classical scale.
3 · Logical flowchart
4 · Definitions, theorems and proofs
Fox–Sudakov: a quantitative density form of Rödl's theorem
Statement
For every finite graph there exists a constant such that for every real with and every finite -free graph , there is a vertex set with such that one of the induced graphs and has at most edges.
Remarks
This page uses only that -free specialization and keeps the source's base-2 logarithm convention. A local proof belongs to the quantitative induced-density track rather than to this page, so the result is recorded here and cited by Every -free graph has a homogeneous set of size at least .
Every -free graph has a homogeneous set of size at least
Statement
Let be a finite graph. Then there exists a constant such that every nonnull finite -free graph with satisfies Equivalently, has a clique or a stable set of size at least .
Facts & Assumptions
Given: A finite graph , a nonnull finite -free graph , and .
The homogeneous number is (Homogeneous vertex sets and the homogeneous number ).
Fox-Sudakov quantitative density: there exists such that for every real with there is with and one of and has at most edges (Fox–Sudakov: a quantitative density form of Rödl's theorem ‡).
If a nonempty vertex set satisfies , then some has and is -sparse (A set of self-density at most has a subset of at least half its size that is -sparse).
A nonempty set is -sparse exactly when every vertex of has degree at most (A set is -sparse exactly when the maximum degree of the graph it induces is at most times its size).
Every nonnull finite graph satisfies (The greedy colouring bound for every nonnull finite graph).
Every finite graph satisfies (The bounds and ).
A vertex set is a clique in if and only if it is a stable set in (Complementation swaps cliques with stable sets, so ).
For nonempty , the self-density is (Edge counts and densities between nonempty vertex sets).
Proof
By [L2], choose a constant . Write and set . Since , one has , so .
Because , [L2] gives a set with , and one of and has at most edges. For that chosen graph on vertex set , [L8] gives .
If , then [L3] gives with and -sparse in . By [L4] every vertex of has degree at most , so [L5] gives , and then [L6] yields .
If , then [L3] gives with and -sparse in . Applying [L4], [L5], and [L6] inside the complement shows that has a stable set of size at least , and [L7] turns that stable set into a clique of the same size in .
Steps 3.1 and 3.2 show that has a homogeneous set with for some satisfying .
Because , choose so that whenever . For such , step 4.1 gives , hence , so .
Set . Choose so that whenever . Then step 5.1 gives for all . Shrinking if necessary handles the finitely many integers , because every nonnull graph has .
Therefore every nonnull finite -free graph with satisfies .
Bucić–Nguyen–Scott–Seymour: a log-log quantitative density theorem
Statement
For every finite graph there exists a constant such that for every real with and every finite -free graph , there is a vertex set with such that one of the induced graphs and has at most edges.
Remarks
Again the statement is recorded exactly in the paper's base-2 convention. The page uses it only as a source-cited input for Every -free graph has a homogeneous set of size at least .
Every -free graph has a homogeneous set of size at least
Statement
Let be a finite graph. Then there exists a constant such that every nonnull finite -free graph with satisfies
Facts & Assumptions
Given: A finite graph , a nonnull finite -free graph , and .
The homogeneous number is (Homogeneous vertex sets and the homogeneous number ).
Bucić-Nguyen-Scott-Seymour quantitative density: there exists such that for every real with there is with and one of and has at most edges (Bucić–Nguyen–Scott–Seymour: a log-log quantitative density theorem ‡).
If a nonempty vertex set satisfies , then some has and is -sparse (A set of self-density at most has a subset of at least half its size that is -sparse).
A nonempty set is -sparse exactly when every vertex of has degree at most (A set is -sparse exactly when the maximum degree of the graph it induces is at most times its size).
Every nonnull finite graph satisfies (The greedy colouring bound for every nonnull finite graph).
Every finite graph satisfies (The bounds and ).
A vertex set is a clique in if and only if it is a stable set in (Complementation swaps cliques with stable sets, so ).
For nonempty , the self-density is (Edge counts and densities between nonempty vertex sets).
Proof
By [L2], choose a constant . Because every nonnull graph has , it is enough to prove the bound for all sufficiently large ; assume from now on that is large enough that . Set and . Then .
For large enough , the inequality holds, so . Therefore . Using [L2], obtain with , and one of and has at most edges. For that chosen graph on vertex set , [L8] gives .
If , then [L3] gives with and -sparse in . By [L4], [L5], and [L6], .
If , then the same argument inside the complement produces a stable set of of size at least for some with , and [L7] turns it into a clique of .
Steps 3.1 and 3.2 show that has a homogeneous set with for some satisfying .
Because , choose a threshold so that whenever . For those , step 4.1 gives , hence , and therefore .
Set . For all sufficiently large , the inequality holds, so step 5.1 gives . Shrinking if necessary handles the finitely many smaller values of .
Hence every nonnull finite -free graph with satisfies .
For fixed , the log-log scale eventually exceeds every classical scale
Statement
Let . Then there exists such that for every integer , In particular, for each fixed finite graph , the log-log lower bound of Every -free graph has a homogeneous set of size at least eventually exceeds every classical scale .
Facts & Assumptions
Given: Positive reals .
For , is defined (The logarithm to a positive base other than one).
Proof
For every integer , one has .
Choose so that whenever . This is possible because tends to with .
For every , step 2.1 gives , and exponentiating base preserves the inequality.
This proves the displayed eventual inequality, and the final sentence is its application with the constant supplied by Every -free graph has a homogeneous set of size at least .
5 · Examples, counterexamples and false statements
None yet.
Sources
- Matija Bucić, Tung Nguyen, Alex Scott, and Paul Seymour, Induced subgraph density. I. A loglog step towards Erdős-Hajnal, Theorem 1.5
- Maria Chudnovsky, The Erdős-Hajnal Conjecture: A Survey, sec. 1
- Matija Bucić, Tung Nguyen, Alex Scott, and Paul Seymour, Induced subgraph density. I. A loglog step towards Erdős-Hajnal, Theorem 1.2
- Matija Bucić, Tung Nguyen, Alex Scott, and Paul Seymour, Induced subgraph density. I. A loglog step towards Erdős-Hajnal, Theorem 1.8
- Matija Bucić, Tung Nguyen, Alex Scott, and Paul Seymour, Induced subgraph density. I. A loglog step towards Erdős-Hajnal, Theorem 1.3
- Matija Bucić, Tung Nguyen, Alex Scott, and Paul Seymour, Induced subgraph density. I. A loglog step towards Erdős-Hajnal