组合数学 (Fall 2011)/Ramsey theory: Difference between revisions

Latest revision as of 11:53, 21 November 2011

Ramsey's Theorem

Ramsey's theorem for graph

Ramsey's Theorem

Let [math]\displaystyle{ k,\ell }[/math] be positive integers. Then there exists an integer [math]\displaystyle{ R(k,\ell) }[/math] satisfying:

If [math]\displaystyle{ n\ge R(k,\ell) }[/math], for any coloring of edges of [math]\displaystyle{ K_n }[/math] with two colors red and blue, there exists a red [math]\displaystyle{ K_k }[/math] or a blue [math]\displaystyle{ K_\ell }[/math].

Proof.

We show that [math]\displaystyle{ R(k,\ell) }[/math] is finite by induction on [math]\displaystyle{ k+\ell }[/math]. For the base case, it is easy to verify that

[math]\displaystyle{ R(k,1)=R(1,\ell)=1 }[/math].

For general [math]\displaystyle{ k }[/math] and [math]\displaystyle{ \ell }[/math], we will show that

[math]\displaystyle{ R(k,\ell)\le R(k,\ell-1)+R(k-1,\ell) }[/math].

Suppose we have a two coloring of [math]\displaystyle{ K_n }[/math], where [math]\displaystyle{ n=R(k,\ell-1)+R(k-1,\ell) }[/math]. Take an arbitrary vertex [math]\displaystyle{ v }[/math], and split [math]\displaystyle{ V\setminus\{v\} }[/math] into two subsets [math]\displaystyle{ S }[/math] and [math]\displaystyle{ T }[/math], where

[math]\displaystyle{ \begin{align} S&=\{u\in V\setminus\{v\}\mid uv \text{ is blue }\}\\ T&=\{u\in V\setminus\{v\}\mid uv \text{ is red }\} \end{align} }[/math]

Since

[math]\displaystyle{ |S|+|T|+1=n=R(k,\ell-1)+R(k-1,\ell) }[/math],

we have either [math]\displaystyle{ |S|\ge R(k,\ell-1) }[/math] or [math]\displaystyle{ |T|\ge R(k-1,\ell) }[/math]. By symmetry, suppose [math]\displaystyle{ |S|\ge R(k,\ell-1) }[/math]. By induction hypothesis, the complete subgraph defined on [math]\displaystyle{ S }[/math] has either a red [math]\displaystyle{ K_k }[/math], in which case we are done; or a blue [math]\displaystyle{ K_{\ell-1} }[/math], in which case the complete subgraph defined on [math]\displaystyle{ S\cup{v} }[/math] must have a blue [math]\displaystyle{ K_\ell }[/math] since all edges from [math]\displaystyle{ v }[/math] to vertices in [math]\displaystyle{ S }[/math] are blue.

[math]\displaystyle{ \square }[/math]

Ramsey's Theorem (graph, multicolor)

Let [math]\displaystyle{ r, k_1,k_2,\ldots,k_r }[/math] be positive integers. Then there exists an integer [math]\displaystyle{ R(r;k_1,k_2,\ldots,k_r) }[/math] satisfying:

For any [math]\displaystyle{ r }[/math]-coloring of a complete graph of [math]\displaystyle{ n\ge R(r;k_1,k_2,\ldots,k_r) }[/math] vertices, there exists a monochromatic [math]\displaystyle{ k_i }[/math]-clique with the [math]\displaystyle{ i }[/math]th color for some [math]\displaystyle{ i\in\{1,2,\ldots,r\} }[/math].

Lemma (the "mixing color" trick)

[math]\displaystyle{ R(r;k_1,k_2,\ldots,k_r)\le R(r-1;k_1,k_2,\ldots,k_{r-2},R(2;k_{r-1},k_r)) }[/math]

Proof.

We transfer the [math]\displaystyle{ r }[/math]-coloring to [math]\displaystyle{ (r-1) }[/math]-coloring by identifying the [math]\displaystyle{ (r-1) }[/math]th and the [math]\displaystyle{ r }[/math]th colors.

If [math]\displaystyle{ n\ge R(r-1;k_1,k_2,\ldots,k_{r-2},R(2;k_{r-1},k_r)) }[/math], then for any [math]\displaystyle{ r }[/math]-coloring of [math]\displaystyle{ K_n }[/math], there either exist an [math]\displaystyle{ i\in\{1,2,\ldots,r-2\} }[/math] and a [math]\displaystyle{ k_i }[/math]-clique which is monochromatically colored with the [math]\displaystyle{ i }[/math]th color; or exists clique of [math]\displaystyle{ R(2;k_{r-1},k_r) }[/math] vertices which is monochromatically colored with the mixed color of the original [math]\displaystyle{ (r-1) }[/math]th and [math]\displaystyle{ r }[/math]th colors, which again implies that there exists either a [math]\displaystyle{ k }[/math]-clique which is monochromatically colored with the original [math]\displaystyle{ (r-1) }[/math]th color, or a [math]\displaystyle{ \ell }[/math]-clique which is monochromatically colored with the original [math]\displaystyle{ r }[/math]th color. This implies the recursion.

[math]\displaystyle{ \square }[/math]

Ramsey number

The smallest number [math]\displaystyle{ R(k,\ell) }[/math] satisfying the condition in the Ramsey theory is called the Ramsey number.

Alternatively, we can define [math]\displaystyle{ R(k,\ell) }[/math] as the smallest [math]\displaystyle{ N }[/math] such that if [math]\displaystyle{ n\ge N }[/math], for any 2-coloring of [math]\displaystyle{ K_n }[/math] in red and blue, there is either a red [math]\displaystyle{ K_k }[/math] or a blue [math]\displaystyle{ K_\ell }[/math]. The Ramsey theorem is stated as:

"[math]\displaystyle{ R(k,\ell) }[/math] is finite for any positive integers [math]\displaystyle{ k }[/math] and [math]\displaystyle{ \ell }[/math]."

The core of the inductive proof of the Ramsey theorem is the following recursion

[math]\displaystyle{ \begin{align} R(k,1) &=R(1,\ell)=1\\ R(k,\ell) &\le R(k,\ell-1)+R(k-1,\ell). \end{align} }[/math]

From this recursion, we can deduce an upper bound for the Ramsey number.

Theorem

[math]\displaystyle{ R(k,\ell)\le{k+\ell-2\choose k-1} }[/math].

Proof.

It is easy to verify the bound by induction.

[math]\displaystyle{ \square }[/math]

The following theorem is due to Spencer in 1975, which is the best known lower bound for diagonal Ramsey number.

Theorem (Spencer 1975)

[math]\displaystyle{ R(k,k)\ge Ck2^{k/2} }[/math] for some constant [math]\displaystyle{ C\gt 0 }[/math].

Its proof uses the Lovász local lemma in the probabilistic method.

Lovász Local Lemma (symmetric case)

Let [math]\displaystyle{ A_1,A_2,\ldots,A_n }[/math] be a set of events, and assume that the following hold:

for all [math]\displaystyle{ 1\le i\le n }[/math], [math]\displaystyle{ \Pr[A_i]\le p }[/math];
each event [math]\displaystyle{ A_i }[/math] is independent of all but at most [math]\displaystyle{ d }[/math] other events, and

[math]\displaystyle{ ep(d+1)\le 1 }[/math].

Then

[math]\displaystyle{ \Pr\left[\bigwedge_{i=1}^n\overline{A_i}\right]\gt 0 }[/math].

We can use the local lemma to prove a lower bound for the diagonal Ramsey number.

Proof.

To prove a lower bound [math]\displaystyle{ R(k,k)\gt n }[/math], it is sufficient to show that there exists a 2-coloring of [math]\displaystyle{ K_n }[/math] without a monochromatic [math]\displaystyle{ K_k }[/math]. We prove this by the probabilistic method.

Pick a random 2-coloring of [math]\displaystyle{ K_n }[/math] by coloring each edge uniformly and independently with one of the two colors. For any set [math]\displaystyle{ S }[/math] of [math]\displaystyle{ k }[/math] vertices, let [math]\displaystyle{ A_S }[/math] denote the event that [math]\displaystyle{ S }[/math] forms a monochromatic [math]\displaystyle{ K_k }[/math]. It is easy to see that [math]\displaystyle{ \Pr[A_s]=2^{1-{k\choose 2}}=p }[/math].

For any [math]\displaystyle{ k }[/math]-subset [math]\displaystyle{ T }[/math] of vertices, [math]\displaystyle{ A_S }[/math] and [math]\displaystyle{ A_T }[/math] are dependent if and only if [math]\displaystyle{ |S\cap T|\ge 2 }[/math]. For each [math]\displaystyle{ S }[/math], the number of [math]\displaystyle{ T }[/math] that [math]\displaystyle{ |S\cap T|\ge 2 }[/math] is at most [math]\displaystyle{ {k\choose 2}{n\choose k-2} }[/math], so the max degree of the dependency graph is [math]\displaystyle{ d\le{k\choose 2}{n\choose k-2} }[/math].

Take [math]\displaystyle{ n=Ck2^{k/2} }[/math] for some appropriate constant [math]\displaystyle{ C\gt 0 }[/math].

[math]\displaystyle{ \begin{align} \mathrm{e}p(d+1) &\le \mathrm{e}2^{1-{k\choose 2}}\left({k\choose 2}{n\choose k-2}+1\right)\\ &\le 2^{3-{k\choose 2}}{k\choose 2}{n\choose k-2}\\ &\le 1 \end{align} }[/math]

Applying the local lemma, the probability that there is no monochromatic [math]\displaystyle{ K_k }[/math] is

[math]\displaystyle{ \Pr\left[\bigwedge_{S\in{[n]\choose k}}\overline{A_S}\right]\gt 0 }[/math].

Therefore, there exists a 2-coloring of [math]\displaystyle{ K_n }[/math] which has no monochromatic [math]\displaystyle{ K_k }[/math], which means

[math]\displaystyle{ R(k,k)\gt n=Ck2^{k/2} }[/math].

[math]\displaystyle{ \square }[/math]

Theorem

[math]\displaystyle{ \Omega\left(k2^{k/2}\right)\le R(k,k)\le{2k-2\choose k-1}=O\left(k^{-1/2}4^{k}\right) }[/math].

[math]\displaystyle{ k }[/math],[math]\displaystyle{ l }[/math]	1	2	3	4	5	6	7	8	9	10
1	1	1	1	1	1	1	1	1	1	1
2	1	2	3	4	5	6	7	8	9	10
3	1	3	6	9	14	18	23	28	36	40–43
4	1	4	9	18	25	35–41	49–61	56–84	73–115	92–149
5	1	5	14	25	43–49	58–87	80–143	101–216	125–316	143–442
6	1	6	18	35–41	58–87	102–165	113–298	127–495	169–780	179–1171
7	1	7	23	49–61	80–143	113–298	205–540	216–1031	233–1713	289–2826
8	1	8	28	56–84	101–216	127–495	216–1031	282–1870	317–3583	317-6090
9	1	9	36	73–115	125–316	169–780	233–1713	317–3583	565–6588	580–12677
10	1	10	40–43	92–149	143–442	179–1171	289–2826	317-6090	580–12677	798–23556

Ramsey's theorem for hypergraph

Ramsey's Theorem (hypergraph, multicolor)

Let [math]\displaystyle{ r, t, k_1,k_2,\ldots,k_r }[/math] be positive integers. Then there exists an integer [math]\displaystyle{ R_t(r;k_1,k_2,\ldots,k_r) }[/math] satisfying:

For any [math]\displaystyle{ r }[/math]-coloring of [math]\displaystyle{ {[n]\choose t} }[/math] with [math]\displaystyle{ n\ge R_t(r;k_1,k_2,\ldots,k_r) }[/math], there exist an [math]\displaystyle{ i\in\{1,2,\ldots,r\} }[/math] and a subset [math]\displaystyle{ X\subseteq [n] }[/math] with [math]\displaystyle{ |X|\ge k_i }[/math] such that all members of [math]\displaystyle{ {X\choose t} }[/math] are colored with the [math]\displaystyle{ i }[/math]th color.

[math]\displaystyle{ n\rightarrow(k_1,k_2,\ldots,k_r)^t }[/math]

Lemma (the "mixing color" trick)

[math]\displaystyle{ R_t(r;k_1,k_2,\ldots,k_r)\le R_t(r-1;k_1,k_2,\ldots,k_{r-2},R_t(2;k_{r-1},k_r)) }[/math]

It is then sufficient to prove the Ramsey's theorem for the two-coloring of a hypergraph, that is, to prove [math]\displaystyle{ R_t(k,\ell)=R_t(2;k,\ell) }[/math] is finite.

Lemma

[math]\displaystyle{ R_t(k,\ell)\le R_{t-1}(R_t(k-1,\ell),R_t(k,\ell-1))+1 }[/math]

Proof.

Let [math]\displaystyle{ n=R_{t-1}(R_t(k-1,\ell),R_t(k,\ell-1))+1 }[/math]. Denote [math]\displaystyle{ [n]=\{1,2,\ldots,n\} }[/math].

Let [math]\displaystyle{ f:{[n]\choose t}\rightarrow\{{\color{red}\text{red}},{\color{blue}\text{blue}}\} }[/math] be an arbitrary 2-coloring of [math]\displaystyle{ {[n]\choose t} }[/math]. It is then sufficient to show that there either exists an [math]\displaystyle{ X\subseteq[n] }[/math] with [math]\displaystyle{ |X|=k }[/math] such that all members of [math]\displaystyle{ {X\choose t} }[/math] are colored red by [math]\displaystyle{ f }[/math]; or exists an [math]\displaystyle{ X\subseteq[n] }[/math] with [math]\displaystyle{ |X|=\ell }[/math] such that all members of [math]\displaystyle{ {X\choose t} }[/math] are colored blue by [math]\displaystyle{ f }[/math].

We remove [math]\displaystyle{ n }[/math] from [math]\displaystyle{ [n] }[/math] and define a new coloring [math]\displaystyle{ f' }[/math] of [math]\displaystyle{ {[n-1]\choose t-1} }[/math] by

[math]\displaystyle{ f'(A)=f(A\cup\{n\}) }[/math] for any [math]\displaystyle{ A\in{[n-1]\choose t-1} }[/math].

By the choice of [math]\displaystyle{ n }[/math] and by symmetry, there exists a subset [math]\displaystyle{ S\subseteq[n-1] }[/math] with [math]\displaystyle{ |X|=R_t(k-1,\ell) }[/math] such that all members of [math]\displaystyle{ {S\choose t-1} }[/math] are colored with red by [math]\displaystyle{ f' }[/math]. Then there either exists an [math]\displaystyle{ X\subseteq S }[/math] with [math]\displaystyle{ |X|=\ell }[/math] such that [math]\displaystyle{ {X\choose t} }[/math] is colored all blue by [math]\displaystyle{ f }[/math], in which case we are done; or exists an [math]\displaystyle{ X\subseteq S }[/math] with [math]\displaystyle{ |X|=k-1 }[/math] such that [math]\displaystyle{ {X\choose t} }[/math] is colored all red by [math]\displaystyle{ f }[/math]. Next we prove that in the later case [math]\displaystyle{ {X\cup{n}\choose t} }[/math] is all red, which will close our proof. Since all [math]\displaystyle{ A\in{S\choose t-1} }[/math] are colored with red by [math]\displaystyle{ f' }[/math], then by our definition of [math]\displaystyle{ f' }[/math], [math]\displaystyle{ f(A\cup\{n\})={\color{red}\text{red}} }[/math] for all [math]\displaystyle{ A\in {X\choose t-1}\subseteq{S\choose t-1} }[/math]. Recalling that [math]\displaystyle{ {X\choose t} }[/math] is colored all red by [math]\displaystyle{ f }[/math], [math]\displaystyle{ {X\cup\{n\}\choose t} }[/math] is colored all red by [math]\displaystyle{ f }[/math] and we are done.

[math]\displaystyle{ \square }[/math]

Applications of Ramsey Theorem

The "Happy Ending" problem

The happy ending problem

Any set of 5 points in the plane, no three on a line, has a subset of 4 points that form the vertices of a convex quadrilateral.

See the article [1] for the proof.

We say a set of points in the plane in general positions if no three of the points are on the same line.

Theorem (Erdős-Szekeres 1935)

For any positive integer [math]\displaystyle{ m\ge 3 }[/math], there is an [math]\displaystyle{ N(m) }[/math] such that any set of at least [math]\displaystyle{ N(m) }[/math] points in general position in the plane (i.e., no three of the points are on a line) contains [math]\displaystyle{ m }[/math] points that are the vertices of a convex [math]\displaystyle{ m }[/math]-gon.

Proof.

Let [math]\displaystyle{ N(m)=R_3(m,m) }[/math]. For [math]\displaystyle{ n\ge N(m) }[/math], let [math]\displaystyle{ X }[/math] be an arbitrary set of [math]\displaystyle{ n }[/math] points in the plane, no three of which are on a line. Define a 2-coloring of the 3-subsets of points [math]\displaystyle{ f:{X\choose 3}\rightarrow\{0,1\} }[/math] as follows: for any [math]\displaystyle{ \{a,b,c\}\in{X\choose 3} }[/math], let [math]\displaystyle{ \triangle_{abc}\subset X }[/math] be the set of points covered by the triangle [math]\displaystyle{ abc }[/math]; and [math]\displaystyle{ f(\{a,b,c\})=|\triangle_{abc}|\bmod 2 }[/math], that is, [math]\displaystyle{ f(\{a,b,c\}) }[/math] indicates the oddness of the number of points covered by the triangle [math]\displaystyle{ abc }[/math].

Since [math]\displaystyle{ |X|\ge R_3(m,m) }[/math], there exists a [math]\displaystyle{ Y\subseteq X }[/math] such that [math]\displaystyle{ |Y|=m }[/math] and all members of [math]\displaystyle{ {Y\choose 3} }[/math] are colored with the same value by [math]\displaystyle{ f }[/math].

We claim that the [math]\displaystyle{ m }[/math] points in [math]\displaystyle{ Y }[/math] are the vertices of a convex [math]\displaystyle{ m }[/math]-gon. If otherwise, by the definition of convexity, there exist [math]\displaystyle{ \{a,b,c,d\}\subseteq Y }[/math] such that [math]\displaystyle{ d\in\triangle_{abc} }[/math]. Since no three points are in the same line,

[math]\displaystyle{ \triangle_{abc}=\triangle_{abd}\cup\triangle_{acd}\cup\triangle_{bcd}\cup\{d\} }[/math],

where all unions are disjoint. Then [math]\displaystyle{ |\triangle_{abc}|=|\triangle_{abd}|+|\triangle_{acd}|+|\triangle_{bcd}|+1 }[/math], which implies that [math]\displaystyle{ f(\{a,b,c\}), f(\{a,b,d\}), f(\{a,c,d\}), f(\{b,c,d\})\, }[/math] cannot be equal, contradicting that all members of [math]\displaystyle{ {Y\choose 3} }[/math] have the same color.

[math]\displaystyle{ \square }[/math]

Yao's lower bound on implicit data structures

Lemma

Let [math]\displaystyle{ n\ge 2 }[/math] be a power of 2 and [math]\displaystyle{ N\ge 2n }[/math]. Suppose the universe is [math]\displaystyle{ [N] }[/math] and the size of the data set is [math]\displaystyle{ n }[/math].

If the data structure is a sorted table, any search algorithm requires at least [math]\displaystyle{ \log n }[/math] accesses to the data structure in the worst case.

Proof.

We will show by an adversarial argument that [math]\displaystyle{ \log n }[/math] accesses are required to search for the key value [math]\displaystyle{ x=n }[/math] from the universe [math]\displaystyle{ [N]=\{1,2,\ldots,N\} }[/math]. The construction of the adversarial data set [math]\displaystyle{ S }[/math] is by induction on [math]\displaystyle{ n }[/math].

For [math]\displaystyle{ n=2 }[/math] and [math]\displaystyle{ N\ge 2n-1=3 }[/math] it is easy to see that two accesses are necessary.

Let [math]\displaystyle{ n\gt 2 }[/math]. Assume the induction hypothesis to be true for all smaller [math]\displaystyle{ n }[/math]; we will prove it for the size of data set [math]\displaystyle{ n }[/math], size of universe [math]\displaystyle{ N\ge 2n }[/math] and the search key [math]\displaystyle{ x=n }[/math].

Suppose that the first access position is [math]\displaystyle{ k }[/math]. The adversary chooses the table content [math]\displaystyle{ T[k] }[/math]. The adversary's strategy is:

[math]\displaystyle{ \begin{align} T[k]= \begin{cases} k & k\le \frac{n}{2},\\ N-(n-k) & k\gt \frac{n}{2}. \end{cases} \end{align} }[/math]

By symmetry, suppose it is the first case that [math]\displaystyle{ k\le \frac{n}{2} }[/math]. Then the key [math]\displaystyle{ x=n }[/math] may be in any position [math]\displaystyle{ i }[/math], where [math]\displaystyle{ n/2+1\le i\le n }[/math]. In fact, [math]\displaystyle{ T[ n/2+1] }[/math] through [math]\displaystyle{ T[n] }[/math] is a sorted table of size [math]\displaystyle{ n'=n/2 }[/math] which may contain any [math]\displaystyle{ n' }[/math]-subset of [math]\displaystyle{ \{n/2+1, n/2+2,\ldots,N\} }[/math], and hence, in particular, any [math]\displaystyle{ n' }[/math]-subset of the universe

[math]\displaystyle{ U'=\{n/2+1, n/2+2,\ldots,N-n/2\} }[/math].

The size [math]\displaystyle{ N' }[/math] of [math]\displaystyle{ U' }[/math] satisfies

[math]\displaystyle{ N'=N-n/2-n/2\ge 2n-n\ge 2n' }[/math],

and the desired key [math]\displaystyle{ n }[/math] has the relative value [math]\displaystyle{ x'=n- n/2=n' }[/math] in the universe [math]\displaystyle{ U' }[/math].

By the induction hypothesis, [math]\displaystyle{ \log n'=-1+\log n }[/math] more accesses will be required. Hence the total number of accesses is at least [math]\displaystyle{ 1+\log n'=\log n }[/math].

If the first access is [math]\displaystyle{ k\gt \frac{n}{2} }[/math], we symmetrically get that [math]\displaystyle{ T[1] }[/math] through [math]\displaystyle{ T[n/2] }[/math] is a sorted table of size [math]\displaystyle{ n'=n/2 }[/math] which may contain any [math]\displaystyle{ n' }[/math]-subset of the universe

[math]\displaystyle{ U'=\{n/2+1, n/2+2,\ldots,N-n/2\} }[/math].

The rest is the same.

[math]\displaystyle{ \square }[/math]

We have seen that on a sorted table, there is no search algorithm outperforming the binary search in the worst case. Our question is:

Is there any other order than the increasing order, on which there is a better search algorithm?

An implicit data structure use no extra space in addition to the original data set, thus a data structure can only be represented implicitly by the order of the data items in the table. That is, each data set is stored as a permutation of the set. Formally, an implicit data structure is a function

[math]\displaystyle{ f:{U\choose n}\rightarrow[n!] }[/math],

where each [math]\displaystyle{ \pi\in[n!] }[/math] specify a permutation of the sorted table. Thus, the sorted table is the simplest implicit data structure, in which [math]\displaystyle{ f(S) }[/math] is the identity for all [math]\displaystyle{ S\in{U\choose n} }[/math].

Ramsey Theory

Van der Waerden's Theorem

Theorem (Van der Waerden 1927)

For every choice of positive integers [math]\displaystyle{ r }[/math] and [math]\displaystyle{ t }[/math], there exists an integer [math]\displaystyle{ W(r,t) }[/math] such that for every [math]\displaystyle{ r }[/math]-coloring of [math]\displaystyle{ [n] }[/math] where [math]\displaystyle{ n\ge W(r,t) }[/math], there exists a monochromatic arithmetic progression of length [math]\displaystyle{ t }[/math].

Hales–Jewett Theorem

Theorem (Hales-Jewett 1963)

Let [math]\displaystyle{ A }[/math] be a finte alphabet of [math]\displaystyle{ t }[/math] symbols and let [math]\displaystyle{ r }[/math] be a positive integer. Then there exists an integer [math]\displaystyle{ \mathrm{HJ}(r,t) }[/math] such that for every [math]\displaystyle{ r }[/math]-coloring of the cube [math]\displaystyle{ A^n }[/math] where [math]\displaystyle{ n\ge \mathrm{HJ}(r,t) }[/math], there exists a combinatorial line, which is monochromatic.

Theorem (Hales-Jewett 1963)

Let [math]\displaystyle{ A }[/math] be a finte alphabet of [math]\displaystyle{ t }[/math] symbols and let [math]\displaystyle{ m,r }[/math] be positive integers. Then there exists an integer [math]\displaystyle{ \mathrm{HJ}(m,r,t) }[/math] such that for every [math]\displaystyle{ r }[/math]-coloring of the cube [math]\displaystyle{ A^n }[/math] where [math]\displaystyle{ n\ge \mathrm{HJ}(r,t) }[/math], there exists a combinatorial [math]\displaystyle{ m }[/math]-space, which is monochromatic.

@@ Line 53: / Line 53: @@
 }}
-=== Lovász local lemma===
+------
-Consider a set of "bad" events <math>A_1,A_2,\ldots,A_n</math>. Suppose that <math>\Pr[A_i]\le p</math> for all <math>1\le i\le n</math>. We want to show that there is a situation that none of the bad events occurs. Due to the probabilistic method, we need to prove that
-:<math>
-\Pr\left[\bigwedge_{i=1}^n\overline{A_i}\right]>0.
-</math>
-;Case 1<nowiki>: mutually independent events.</nowiki>
-If all the bad events <math>A_1,A_2,\ldots,A_n</math> are mutually independent, then
-:<math>
-\Pr\left[\bigwedge_{i=1}^n\overline{A_i}\right]\ge(1-p)^n>0,
-</math>
-for any <math>p<1</math>.
-;Case 2<nowiki>: arbitrarily dependent events.</nowiki>
-On the other hand, if we put no assumption on the dependencies between the events, then by the union bound (which holds unconditionally),
-:<math>
-\Pr\left[\bigwedge_{i=1}^n\overline{A_i}\right]=1-\Pr\left[\bigvee_{i=1}^n A_i\right]\ge 1-np,
-</math>
-which is not an interesting bound for <math>p\ge\frac{1}{n}</math>. We cannot improve bound without further information regarding the dependencies between the events.
-----
+The following theorem is due to Spencer in 1975, which is the best known lower bound for diagonal Ramsey number.
-We would like to know what is going on between the two extreme cases: mutually independent events, and arbitrarily dependent events. The Lovász local lemma provides such a tool.
+{{Theorem|Theorem (Spencer 1975)|
+:<math>R(k,k)\ge Ck2^{k/2}</math> for some constant <math>C>0</math>.
-The local lemma is powerful tool for showing the possibility of rare event under ''limited dependencies''. The structure of dependencies between a set of events is described by a '''dependency graph'''.
-{{Theorem
-|Definition|
-:Let <math>A_1,A_2,\ldots,A_n</math> be a set of events. A graph <math>D=(V,E)</math> on the set of vertices <math>V=\{1,2,\ldots,n\}</math> is called a '''dependency graph''' for the events <math>A_1,\ldots,A_n</math> if for each <math>i</math>, <math>1\le i\le n</math>, the event <math>A_i</math> is mutually independent of all the events <math>\{A_j\mid (i,j)\not\in E\}</math>.
 }}
-;Example
+Its proof uses the Lovász local lemma in the probabilistic method.
-:Let <math>X_1,X_2,\ldots,X_m</math> be a set of ''mutually independent'' random variables. Each event <math>A_i</math> is a predicate defined on a number of variables among <math>X_1,X_2,\ldots,X_m</math>. Let <math>v(A_i)</math> be the unique smallest set of variables which determine <math>A_i</math>. The dependency graph <math>D=(V,E)</math> is defined by
-:::<math>(i,j)\in E</math> iff <math>v(A_i)\cap v(A_j)\neq \emptyset</math>.
-The following lemma, known as the Lovász local lemma, first proved by Erdős and Lovász in 1975, is an extremely powerful tool, as it supplies a way for dealing with rare events.
 {{Theorem
 |Lovász Local Lemma (symmetric case)|
 :Let <math>A_1,A_2,\ldots,A_n</math> be a set of events, and assume that the following hold:
 :#for all <math>1\le i\le n</math>, <math>\Pr[A_i]\le p</math>;
-:#the maximum degree of the dependency graph for the events <math>A_1,A_2,\ldots,A_n</math> is <math>d</math>, and
+:# each event <math>A_i</math> is independent of all but at most <math>d</math> other events, and
 :::<math>ep(d+1)\le 1</math>.
 :Then
@@ Line 99: / Line 72: @@
 }}
-We will prove a general version of the local lemma, where the events <math>A_i</math> are not symmetric. This generalization is due to Spencer.
-{{Theorem
-|Lovász Local Lemma (general case)|
-:Let <math>D=(V,E)</math> be the dependency graph of events <math>A_1,A_2,\ldots,A_n</math>. Suppose there exist real numbers <math>x_1,x_2,\ldots, x_n</math> such that <math>0\le x_i<1</math> and for all <math>1\le i\le n</math>,
-::<math>\Pr[A_i]\le x_i\prod_{(i,j)\in E}(1-x_j)</math>.
-:Then
-::<math>\Pr\left[\bigwedge_{i=1}^n\overline{A_i}\right]\ge\prod_{i=1}^n(1-x_i)</math>.
-}}
-{{Proof|
-We can use the following probability identity to compute the probability of the intersection of events:
-{{Theorem|Lemma 1|
-:<math>\Pr\left[\bigwedge_{i=1}^n\overline{A_i}\right]=\prod_{i=1}^n\Pr\left[\overline{A_i}\mid \bigwedge_{j=1}^{i-1}\overline{A_{j}}\right]</math>.
-}}
-{{Proof|
-By definition of conditional probability,
-:<math>
-\Pr\left[\overline{A_n}\mid\bigwedge_{i=1}^{n-1}\overline{A_{i}}\right]
-=\frac{\Pr\left[\bigwedge_{i=1}^n\overline{A_{i}}\right]}
-{\Pr\left[\bigwedge_{i=1}^{n-1}\overline{A_{i}}\right]}</math>,
-so we have
-:<math>\Pr\left[\bigwedge_{i=1}^n\overline{A_{i}}\right]=\Pr\left[\bigwedge_{i=1}^{n-1}\overline{A_{i}}\right]\Pr\left[\overline{A_n}\mid\bigwedge_{i=1}^{n-1}\overline{A_{i}}\right]</math>.
-The lemma is proved by recursively applying this equation.
-}}
-Next we prove by induction on <math>m</math> that for any set of <math>m</math> events <math>i_1,\ldots,i_m</math>,
-:<math>\Pr\left[A_{i_1}\mid \bigwedge_{j=2}^m\overline{A_{i_j}}\right]\le x_{i_1}</math>.
-The local lemma is a direct consequence of this by applying Lemma 1.
-For <math>m=1</math>, this is obvious. For general <math>m</math>, let <math>i_2,\ldots,i_k</math> be the set of vertices adjacent to  <math>i_1</math> in the dependency graph. Clearly <math>k-1\le d</math>. And it holds that
-:<math>
-\Pr\left[A_{i_1}\mid \bigwedge_{j=2}^m\overline{A_{i_j}}\right]
-=\frac{\Pr\left[ A_i\wedge \bigwedge_{j=2}^k\overline{A_{i_j}}\mid \bigwedge_{j=k+1}^m\overline{A_{i_j}}\right]}
-{\Pr\left[\bigwedge_{j=2}^k\overline{A_{i_j}}\mid \bigwedge_{j=k+1}^m\overline{A_{i_j}}\right]}
-</math>,
-which is due to the basic conditional probability identity
-:<math>\Pr[A\mid BC]=\frac{\Pr[AB\mid C]}{\Pr[B\mid C]}</math>.
-We bound the numerator
-:<math>
-\begin{align}
-\Pr\left[ A_{i_1}\wedge \bigwedge_{j=2}^k\overline{A_{i_j}}\mid \bigwedge_{j=k+1}^m\overline{A_{i_j}}\right]
-&\le\Pr\left[ A_{i_1}\mid \bigwedge_{j=k+1}^m\overline{A_{i_j}}\right]\\
-&=\Pr[A_{i_1}]\\
-&\le x_{i_1}\prod_{(i_1,j)\in E}(1-x_j).
-\end{align}
-</math>
-The equation is due to the independence between <math>A_{i_1}</math> and <math>A_{i_k+1},\ldots,A_{i_m}</math>.
-The denominator can be expanded using Lemma 1 as
-:<math>
-\Pr\left[\bigwedge_{j=2}^k\overline{A_{i_j}}\mid \bigwedge_{j=k+1}^m\overline{A_{i_j}}\right]
-=\prod_{j=2}^k\Pr\left[\overline{A_{i_j}}\mid \bigwedge_{\ell=j+1}^m\overline{A_{i_\ell}}\right]
-</math>
-which by the induction hypothesis, is at least
-:<math>
-\prod_{j=2}^k(1-x_{i_j})=\prod_{\{i_1,i_j\}\in E}(1-x_j)
-</math>
-where <math>E</math> is the edge set of the dependency graph.
-Therefore,
-:<math>
-\Pr\left[A_{i_1}\mid \bigwedge_{j=2}^m\overline{A_{i_j}}\right]
-\le\frac{x_{i_1}\prod_{(i_1,j)\in E}(1-x_j)}{\prod_{\{i_1,i_j\}\in E}(1-x_j)}\le x_{i_1}.
-</math>
-Applying Lemma 1,
-:<math>
-\begin{align}
-\Pr\left[\bigwedge_{i=1}^n\overline{A_i}\right]
-&=\prod_{i=1}^n\Pr\left[\overline{A_i}\mid \bigwedge_{j=1}^{i-1}\overline{A_{j}}\right]\\
-&=\prod_{i=1}^n\left(1-\Pr\left[A_i\mid \bigwedge_{j=1}^{i-1}\overline{A_{j}}\right]\right)\\
-&\ge\prod_{i=1}^n\left(1-x_i\right).
-\end{align}
-</math>
-}}
-To prove the symmetric case. Let <math>x_i=\frac{1}{d+1}</math> for all <math>i=1,2,\ldots,n</math>. Note that <math>\left(1-\frac{1}{d+1}\right)^d>\frac{1}{\mathrm{e}}</math>.
-If the following conditions are satisfied:
-:#for all <math>1\le i\le n</math>, <math>\Pr[A_i]\le p</math>;
-:#<math>ep(d+1)\le 1</math>;
-then for all <math>1\le i\le n</math>,
-:<math>\Pr[A_i]\le p\le\frac{1}{e(d+1)}<\frac{1}{d+1}\left(1-\frac{1}{d+1}\right)^d\le x_i\prod_{(i,j)\in E}(1-x_j)</math>.
-Due to the local lemma for general cases, this implies that
-:<math>\Pr\left[\bigwedge_{i=1}^n\overline{A_i}\right]\ge\prod_{i=1}^n(1-x_i)=\left(1-\frac{1}{d+1}\right)^n>0</math>.
-This gives the symmetric version of local lemma.
-=== Ramsey number (continued)===
 We can use the local lemma to prove a lower bound for the diagonal Ramsey number.
-{{Theorem|Theorem|
-:<math>R(k,k)\ge Ck2^{k/2}</math> for some constant <math>C>0</math>.
-}}
 {{Proof|
 To prove a lower bound <math>R(k,k)>n</math>, it is sufficient to show that there exists a 2-coloring of <math>K_n</math> without a monochromatic <math>K_k</math>. We prove this by the probabilistic method.
@@ Line 443: / Line 327: @@
 where each <math>\pi\in[n!]</math> specify a permutation of the sorted table. Thus, the sorted table is the simplest implicit data structure, in which <math>f(S)</math> is the identity for all <math>S\in{U\choose n}</math>.
-== Ramsey-like Theorems ==
+== Ramsey Theory==
 === Van der Waerden's Theorem ===
 {{Theorem|Theorem (Van der Waerden 1927)|

组合数学 (Fall 2011)/Ramsey theory: Difference between revisions

Latest revision as of 11:53, 21 November 2011

Contents

Ramsey's Theorem

Ramsey's theorem for graph

Ramsey number

Ramsey's theorem for hypergraph

Applications of Ramsey Theorem

The "Happy Ending" problem

Yao's lower bound on implicit data structures

Ramsey Theory

Van der Waerden's Theorem

Hales–Jewett Theorem

Navigation menu

组合数学 (Fall 2011)/Ramsey theory: Difference between revisions

Latest revision as of 11:53, 21 November 2011

Ramsey's Theorem

Ramsey's theorem for graph

Ramsey number

Ramsey's theorem for hypergraph

Applications of Ramsey Theorem

The "Happy Ending" problem

Yao's lower bound on implicit data structures

Ramsey Theory

Van der Waerden's Theorem

Hales–Jewett Theorem

Navigation menu

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