How statement and proof provenance work
The first chip identifies the source of the statement or construction; the second identifies the source of its local proof or verification.
- Literature-sourced: the exact statement appears in a cited source; only wording and notation differ.
- AI-adapted: a semantically identical restatement of literature-sourced material, modulo indexing, notation, and boundary cases adopted by the library.
- AI-generated: a genuinely novel statement formulated by AI, with no source for the claim itself.
These labels describe origin, not correctness: citations and verification chips remain separate evidence.
A parameter ledger for the high-girth, high-chromatic alteration proof
Example
For the targets and , choose These parameters make both failure probabilities in the alteration proof less than .
Facts & Assumptions
Given: The explicit parameters in the Example.
The expected number of cycles of length at most is at most (The expected number of cycles of length at most in ).
( for ).
The exponential is strictly increasing and positive, , , and the logarithm is the increasing inverse of the exponential with its product law (The real exponential function and the number by a power series, The natural logarithm as the inverse of the exponential function, Order, continuity, range, and the product, quotient, and reciprocal laws for the natural logarithm, for every real , hence , The exponential is positive and satisfies , The exponential function is strictly increasing).
Markov bounds nonnegative upper tails; the union bound controls finite unions; complements have complementary probabilities; and positive probability gives a witness (Markov's inequality on a finite probability space, The finite union bound, Normalization, nonnegativity, monotonicity, complements, and differences in a finite probability space, An event of positive probability in a finite probability space is nonempty).
The high-girth alteration deletes one vertex per short cycle and compares the surviving order with the independence number (For all positive , some finite graph has girth greater than and chromatic number greater than ).
Verification
Here , so [L4] at the threshold bounds the short-cycle failure probability by .
Since , while [L3] gives , one has . Thus [L2] and [L3] bound the independence failure probability by a number less than .
By [L4], the union of the two failure events has probability less than , so its complement has positive probability and contains a graph with fewer than triangles and independence number below . Delete one vertex per triangle. More than vertices survive, no triangle survives, and any two-colouring would have an independent colour class larger than .
Hence the survivor has girth greater than and chromatic number greater than , with every integrality and strict inequality explicit.
Depends on
- The real exponential function and the number $e$ by a power series
- The natural logarithm as the inverse of the exponential function
- Order, continuity, range, and the product, quotient, and reciprocal laws for the natural logarithm
- $1+x\le\exp(x)$ for every real $x$, hence $(1-p)^m\le\exp(-mp)$
- The exponential is positive and satisfies $\exp(-x)=1/\exp(x)$
- The exponential function is strictly increasing
- Normalization, nonnegativity, monotonicity, complements, and differences in a finite probability space
- Markov's inequality on a finite probability space
- The finite union bound
- An event of positive probability in a finite probability space is nonempty
- The expected number of cycles of length at most $\ell$ in $G(n,p)$
- $\mathbb P(\alpha(G(n,p))\ge s)\le\binom ns(1-p)^{\binom s2}\le n^s\exp(-p\binom s2)$ for $s\le n$
- For all positive $k,\ell$, some finite graph has girth greater than $\ell$ and chromatic number greater than $k$
Used by
Nothing in the library uses this result yet.
Dependency tree · next 3 levels
Direct dependencies and their dependencies through the next three levels: 144 results over 27 levels. An arrow runs from a result to what uses it, and this result sits at the bottom with a heavier outline. Click the chart to enlarge it.
Sources
- Y. Zhao, MIT 18.218 Probabilistic Method in Combinatorics, proof of Theorem 6.3 (standard reference, not scraped)