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An -vertex graph of minimum degree has a dominating set of size at most
Statement
Let be an -vertex graph with minimum degree . Then
Facts & Assumptions
Given: An -vertex graph of minimum degree .
A dominating set contains or neighbours every vertex (Dominating sets in a finite graph).
Independent Bernoulli coordinate choices form a finite product space (Product weights normalize, and coordinate events are mutually independent).
Expectation is linear and some outcome is at most its expectation (Expectation is linear for every finite family of random variables, without any independence hypothesis, Expectation preserves pointwise order and lies between the minimum and maximum attained values).
for ( for every real , hence ).
The natural logarithm is increasing and satisfies its inverse and product laws (The natural logarithm as the inverse of the exponential function, Order, continuity, range, and the product, quotient, and reciprocal laws for the natural logarithm).
Proof
Put . Since and the logarithm is increasing with , one has . Applying [L4] at is not needed here: applying its first inequality at gives , hence .
Select every vertex independently with probability , obtaining , and let be the vertices neither in nor adjacent to a member of . Then is dominating.
A fixed vertex belongs to only if none of at least vertices in its closed neighbourhood is selected, so .
By linearity, .
Some outcome has at most this expectation, and its is a dominating set by step 1.2.
Depends on
- Dominating sets in a finite graph
- Product weights normalize, and coordinate events are mutually independent
- Expectation is linear for every finite family of random variables, without any independence hypothesis
- Expectation preserves pointwise order and lies between the minimum and maximum attained values
- $1+x\le\exp(x)$ for every real $x$, hence $(1-p)^m\le\exp(-mp)$
- The natural logarithm as the inverse of the exponential function
- Order, continuity, range, and the product, quotient, and reciprocal laws for the natural logarithm
Used by
Nothing in the library uses this result yet.
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Sources
- Y. Zhao, MIT 18.218 Probabilistic Method in Combinatorics, Theorem 6.1 (standard reference, not scraped)