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If and , an -vertex tournament with property exists
Statement
Let and . Then there exists a tournament on vertices with property .
Facts & Assumptions
Given: Naturals and .
Property means every set of at most vertices has an outside vertex directing an arc to each of its members (Tournament property : every set of at most vertices is dominated by one vertex).
Independent edge orientations form a product probability space (Product weights normalize, and coordinate events are mutually independent).
Probability of a finite union is at most the sum of its event probabilities, and an event and its complement have probabilities summing to (The finite union bound, Normalization, nonnegativity, monotonicity, complements, and differences in a finite probability space).
For every real , ; consequently for ( for every real , hence ).
The number of -subsets is , and is its usual finite product (The set of -element subsets and the binomial coefficient , for ; hence , the quotient is a natural number, and , The factorial and the falling factorial , defined by recursion in ).
is the sum of its nonnegative exponential series; ; natural powers obey their product laws; and is the increasing inverse of with (The real exponential function and the number by a power series, A series of nonnegative terms converges iff its partial sums are bounded, and then the sum is their supremum, The exponential addition formula , Integer powers , Laws of integer exponents, Monotonicity of and of , The natural logarithm as the inverse of the exponential function, Order, continuity, range, and the product, quotient, and reciprocal laws for the natural logarithm).
A positive-probability event in a finite probability space is nonempty (An event of positive probability in a finite probability space is nonempty).
Proof
Orient every edge independently and fairly. For a fixed -set , each outside vertex dominates all of with probability , independently across outside vertices; hence the failure probability is .
The union bound gives total failure probability at most .
The ratio is at most whenever . Thus is nonincreasing throughout the stated range.
Suppose . At , .
Suppose . At , . Since , one has , and ; hence .
Suppose and put . The th nonnegative term of the exponential series gives , so . With [L4], .
Since , [L4] applied at gives for . Hence the exponent in step 3.4 is at most , using , , and . Thus .
Monotonicity from step 3.1, together with the initial bounds in steps 3.2, 3.3, and 4.1, shows in every case. Since step 2.1 bounds the failure union by , [L3] makes its complement positive; that event is nonempty by [L7].
In the resulting tournament every set of size exactly has a dominator. Any smaller set extends to a -set because , and the same dominator works; hence [L1] gives property .
Depends on
- Tournament property $S_k$: every set of at most $k$ vertices is dominated by one vertex
- Product weights normalize, and coordinate events are mutually independent
- Normalization, nonnegativity, monotonicity, complements, and differences in a finite probability space
- The finite union bound
- $1+x\le\exp(x)$ for every real $x$, hence $(1-p)^m\le\exp(-mp)$
- The set $[A]^{k}$ of $k$-element subsets and the binomial coefficient $\binom{n}{k} := \lvert [n]^{k}\rvert$
- $\binom{n}{k}\,k!\,(n-k)! = n!$ for $k \le n$; hence $\binom{n}{k}\,k! = n^{\underline{k}}$, the quotient $n!/(k!(n-k)!)$ is a natural number, and $\binom{n}{k} = \binom{n}{n-k}$
- The factorial $n!$ and the falling factorial $n^{\underline{k}}$, defined by recursion in $\mathbb{N}$
- The real exponential function and the number $e$ by a power series
- A series of nonnegative terms converges iff its partial sums are bounded, and then the sum is their supremum
- The exponential addition formula $\exp(x+y)=\exp(x)\exp(y)$
- Integer powers $a^m$
- Laws of integer exponents
- Monotonicity of $x \mapsto x^n$ and of $n \mapsto a^n$
- The natural logarithm as the inverse of the exponential function
- Order, continuity, range, and the product, quotient, and reciprocal laws for the natural logarithm
- An event of positive probability in a finite probability space is nonempty
Used by
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Sources
- M. Bucic, Probabilistic Method, Theorem 1.5 (standard reference, not scraped)