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Generalized Niceness and Reduction Outcomes -- Examples
1 · Prerequisites
- Absolute and Conditional Convergence; Rearrangement; Products
- Binary Operations, Monoids, Groups and Subgroups
- Blockades, Combs and Pattern Graphs
- 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
- Finite Probability and the Probabilistic Method
- Finite Probability Spaces and Random Variables
- Foundations of the Real Numbers for Analysis
- Generalized Niceness and Reduction Outcomes
- Graph Colouring
- Graphs, Walks and Connectivity
- Inclusion–Exclusion, the Pigeonhole Principle and Double Counting
- Induced Subgraphs and Hereditary Graph Classes
- Iterative Restriction and Comb-Extraction Lemmas
- Leaf Reducibility and Wonderful Families
- 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
- Polynomial Rödl, Virality and Erdős–Hajnal Equivalence
- Power Series and Real-Analytic Functions
- Properties of the Integral and the Working FTC
- Regular Pairs and Induced Counting
- Relations, Functions, and Quotients
- Rings, Subrings, Integral Domains and Fields
- 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
- Trees, Forests and Spanning Trees
- Vector Spaces, Linear Subspaces, Span and Direct Sums
2 · Summary
These examples check the batch-15 mechanisms on explicit finite data. The first shows how a weakly sparse four-block configuration can be thinned to equal subblocks with directional sparsity. The second shows the maximal-blockade extension step behind the pure-pair extraction lemma. The third records the numerical exponent choice used in the final iterative restricted-sparsification argument.
3 · Logical flowchart
4 · Definitions, theorems and proofs
None yet.
5 · Examples, counterexamples and false statements
Thinning a four-block weakly sparse blockade to directional sparse subblocks
Example
Let have four pairwise disjoint blocks
and suppose the only cross-edges between noncomplete pairs are
Then is a blockade of width , every noncomplete pair is weakly -sparse, and the subblocks
are pairwise complete or pairwise anticomplete. In particular every formerly weakly sparse pair becomes directionally -sparse after thinning.
Facts & Assumptions
Given: The graph and the four blocks described in the example.
A blockade is an ordered sequence of pairwise disjoint nonempty vertex sets, and its width is the minimum block size (Blockades, their length, their width, and their support).
A weakly -sparse pair satisfies , while directional sparsity bounds the neighbours of each single vertex into the opposite set (Sparsity of one vertex set to another, and weak sparsity of a pair).
Verification
The four blocks are pairwise disjoint and nonempty, each has size , so is a blockade of width by [L1]. Every noncomplete pair listed in the example has exactly one cross-edge, hence at most cross-edges. Therefore each such pair is weakly -sparse by [L2].
None of the vertices appears in any of the six displayed cross-edges. Hence every noncomplete pair among has no cross-edge at all, so each vertex in one chosen subblock has neighbours in the other. By [L2], those pairs are directionally -sparse.
Therefore the thinning exhibits exactly the weak-to-directional sparsity conversion claimed in the example.
A large almost-pure pair extends an anticomplete blockade
Example
Let
and assume:
- is anticomplete to ;
- is anticomplete to ;
- inside there are disjoint subsets with anticomplete to .
Then is an anticomplete blockade, and replacing the last block by the pair produces the longer anticomplete blockade .
Facts & Assumptions
Given: The blocks and the subsets with the adjacency relations stated in the example.
A blockade is an ordered sequence of pairwise disjoint nonempty vertex sets (Blockades, their length, their width, and their support).
A pair of disjoint vertex sets is anticomplete exactly when there are no edges between them (Edges between disjoint vertex sets; complete, anticomplete, pure and mixed pairs).
Verification
The sets are pairwise disjoint and nonempty, so is a blockade by [L1]. Hypotheses 1 and 2 say that each earlier block is anticomplete to every later block, so [L2] makes it an anticomplete blockade.
The sets and are disjoint nonempty subsets of , and hypothesis 3 says that is anticomplete to . Hypothesis 2 also implies that both and are anticomplete to . Therefore every earlier block in is anticomplete to every later block.
By steps 1.1 and 1.2, replacing the last block by the anticomplete pair extends the original anticomplete blockade by one step.
A numeric run of the Lemma 3.3 exponent choice
Example
Suppose the three-outcome constants for a generalized nice, leaf-reducible, wonderful family satisfy
Then the exponent choices in the final restricted-sparsification step become
so
Let be a -restricted -free graph satisfying the two global failure hypotheses of the helper lemma. If , then the helper asks for a -restricted induced subgraph of size at least and returns a -restricted induced subgraph of size at least . The iterative lemma then yields an -restricted induced subgraph of size at least .
Facts & Assumptions
Given: The numerical choices , , and , and a graph satisfying the conditional hypotheses in the Example.
The helper claim uses the substitutions , , and (A large cy-restricted subgraph in the three-outcome theorem forces a smaller-scale restricted subgraph).
The iterative restricted-sparsification lemma concludes with an -restricted induced subgraph of size at least (Iterated restricted sparsification reaches the target scale).
The final generalized-niceness lemma is obtained by exactly this choice of (Constant-scale restricted generalized niceness yields an x-scale restricted subgraph, a polynomial clique or stable set, or a blockade).
Verification
Substituting the given values into [L1] gives , , and . Therefore , so the numerical inequality required by the iterative lemma holds exactly.
The graph itself supplies the starting -restricted subgraph required by [L2], because . For every , write . The helper [L1], under the two global failure hypotheses in the Given data, sends each -restricted with to a -restricted subgraph of size at least . Thus both hypotheses of [L2] hold with starting constant , and it gives an -restricted induced subgraph of size at least .
This is exactly the numerical exponent pattern used again in [L3].
Sources
- Shenwei Huang, Yiao Ju, and Yidong Zhou, Erdos-Hajnal beyond the five-vertex path, Lemma 2.6
- Shenwei Huang, Yiao Ju, and Yidong Zhou, Erdos-Hajnal beyond the five-vertex path, proof of Lemma 2.8
- Shenwei Huang, Yiao Ju, and Yidong Zhou, Erdos-Hajnal beyond the five-vertex path, Claim 3.3.1 and Lemma 3.3