Existence by Probability
∃x,A(x)⇐P(A(x))>0
∃x,A(x)⇐P(¬A(x))<1
P(A)=P(∧i=1nAi)>0⇐P(∨i=1nAi)<1⇐∑i=1nP(Ai)
Lower Bound for Ramsey's Number
- R(k,k),∀ two coloring of Kn,n>R(k,k),∃ a monochromactic Kk
- Erdős Theorem(1947): (kn)21−Ck2<1 then it is possible to color the edges of Kn with two colors so that there is no monochromatic Kk subgraph
Paradoxical Tournament
- orientation of the edges of the complete graph on set of vertices V
- k-paradoxical: ∀V,∣V∣=k,∃v beats them all
- Theorem (Erdős 1963): if (kn)(1−2−k)n−k<1, there is a tournament on n vertices that is k-paradoxical
The Averaging principle
∃x,A(x)≥t⇐E(x)≥t
Hamilton Path in Tournament
- Theorem (Szele 1943): There is a tournament on n players with at least n!2−(n−1) Hamiltonian paths
Independent sets
- independent set: a set of vertices with no edges between them
- Theorem: G has an independent set with at least 4mn2 vertices
Coloring large-girth graphs
- G(n,p): graph of n vertices and each edge occurs at probability p
- girth: g(G) is the length of the shortest cycle in G
- χ(G)=min(C∈N∣∃:V→[C],∀uv∈E,f(u)=f(v))
- Independent number: α(G)=max{∣S∣∣S⊆V and ∀u,v∈S,uv∈E}
- Lemma: χ(G)≥α(G)n
- Theorem (Erdős 1959): ∀k,ℓ,∃G,g(G)>ℓ,χ(G)>k
Lovász Local Lemma
Consider a set of "bad" events A1,A2,⋯,An, suppose P(Ai)≤p,1≤i≤n
- Mutually independent events: P(∧i=1nAi)≥(1−p)n
- Arbirarily dependent events: P(∧i=1nAi)=1−P(∨i=1n)≥1−np
- dependency graph: D(V,E)
- ij∈E⟺Ai and Aj are dependent
- d=max{deg(i)}
- Lovasz Local Lemma
- ∀i,P(Ai)≤p
- ep(d+1)≤1 or 4dp≤1
- Then P(∧i=1nAi)>0
- General Lovasz Local Lemma
- ∃x1,⋯,xn∈[0,1),∀i,P(Ai)≤xi∏(j,i)∈E(1−xj)
- Then P(∧i=1nAi)≥∏i=1n(1−xi)