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IMC / 2022 / Problems / Day 1, P4

IMC 2022 · Day 1 · P4

killer

Let n>3n > 3 be an integer. Let Ω\Omega be the set of all triples of distinct elements of {1,2,,n}\{1, 2, \dots, n\}. Let mm denote the minimal number of colours which suffice to colour Ω\Omega so that whenever 1a<b<c<dn1 \le a < b < c < d \le n, the triples {a,b,c}\{a, b, c\} and {b,c,d}\{b, c, d\} have different colours. Prove that 1100loglognm100loglogn.\frac{1}{100} \log\log n \leqslant m \leqslant 100 \log\log n. (proposed by Danila Cherkashin, St. Petersburg)

Solution (official)

Hint: Define two graphs, one on Ω\Omega and another graph on pairs (2-element sets).

For k=1,2,,nk = 1, 2, \dots, n denote by Ωk\Omega_k the set of all (nk)\binom{n}{k} kk-subsets of [n][n]. For each k=1,2,,n1k = 1, 2, \dots, n-1 define a directed graph GkG_k whose vertices are elements of Ωk\Omega_k, and edges correspond to elements of Ωk+1\Omega_{k+1} as follows: if 1a1<a2<<ak+1n1 \leqslant a_1 < a_2 < \dots < a_{k+1} \leqslant n, then the edge of GkG_k corresponding to (a1,,ak+1)(a_1, \dots, a_{k+1}) goes from (a1,,ak)(a_1, \dots, a_k) to (a2,,ak+1)(a_2, \dots, a_{k+1}).

For a directed graph G=(V,E)G = (V, E) we call a subset E1EE_1 \subset E admissible, if E1E_1 does not contain a directed path abca - b - c of length 2. Define b-index b(G)b(G) of the GG as the minimal number of admissible sets which cover EE. As usual, a subset V1VV_1 \subset V is called independent, if there are no edges with both endpoints in V1V_1; a chromatic number of GG is defined as the minimal number of independent sets which cover VV.

A straightforward but crucial observation is the following

Lemma. For all k=2,3,,nk = 2, 3, \dots, n a subset AΩkA \subset \Omega_k is independent in GkG_k if and only if it is admissible as a set of edges of Gk1G_{k-1}.

Corollary. χ(Gk)=b(Gk1)\chi(G_k) = b(G_{k-1}) for all k=2,3,,nk = 2, 3, \dots, n.

Now the bounds for numbers χ(Gk)\chi(G_k) follow by induction using the following general

Lemma. For a directed graph G=(V,E)G = (V, E) we have log2χ(G)b(G)2log2χ(G).\log_2 \chi(G) \leqslant b(G) \leqslant 2 \lceil \log_2 \chi(G) \rceil. Proof. 1) Denote b(G)=mb(G) = m and prove that log2χ(G)m\log_2 \chi(G) \leqslant m. For this we take a covering of EE by mm admissible subsets E1,,EmE_1, \dots, E_m and define a color c(v)c(v) of a vertex vVv \in V as the following subset of [m][m]: c(v):={i[m]:vwEi}c(v) := \{ i \in [m] : \exists vw \in E_i \}. Note that for any edge vwEvw \in E there exists ii such that vwEivw \in E_i which yields ic(v)i \in c(v) and ic(w)i \notin c(w), therefore c(v)c(w)c(v) \ne c(w). So, each color class is an independent set and we get χ(G)2m\chi(G) \leqslant 2^m as needed.

2) Denote χ(G)=k\chi(G) = k and prove that b(G)2log2kb(G) \leqslant 2 \lceil \log_2 k \rceil. Take a proper coloring τ:V{0,1,,k1}\tau : V \to \{0, 1, \dots, k-1\} (that means that τ(u)τ(v)\tau(u) \ne \tau(v) for all edges vuEvu \in E). For an integer x{0,1,,k1}x \in \{0, 1, \dots, k-1\} take a binary representation x=i=0r1εi(x)2ix = \sum_{i=0}^{r-1} \varepsilon_i(x) 2^i, εi(x){0,1}\varepsilon_i(x) \in \{0, 1\}, where r=log2kr = \lceil \log_2 k \rceil. Consider the following 2r2r subsets of EE, two subsets Ei,+E_{i,+} and Ei,E_{i,-} for each i{0,1,,k1}i \in \{0, 1, \dots, k-1\}: Ei,+={vuE:εi(τ(v))=0,εi(τ(u))=1},Ei,={vuE:εi(τ(v))=1,εi(τ(u))=0}.\begin{gather*} E_{i,+} = \{ vu \in E : \varepsilon_i(\tau(v)) = 0, \varepsilon_i(\tau(u)) = 1 \}, \\ E_{i,-} = \{ vu \in E : \varepsilon_i(\tau(v)) = 1, \varepsilon_i(\tau(u)) = 0 \}. \end{gather*} Each of them is admissible, and they cover EE, thus b(G)2rb(G) \leqslant 2r.

Note that χ(G1)=n\chi(G_1) = n, thus b(G1)log2nb(G_1) \geqslant \log_2 n. Actually we have b(G1)=log2nb(G_1) = \lceil \log_2 n \rceil: indeed, if we define τ(v)=v1\tau(v) = v - 1 for all v[n]=Ω1v \in [n] = \Omega_1, then the above sets Ei,+E_{i,+} cover all edges of G1G_1.

The Lemma above now yields for our number m=χ(G3)=b(G2)m = \chi(G_3) = b(G_2) the following bounds, which are better than required: b(G2)log2χ(G2)=log2b(G1)=log2log2nb(G2)2log2χ(G2)=2log2b(G1)=2log2log2n.\begin{gather*} b(G_2) \geqslant \log_2 \chi(G_2) = \log_2 b(G_1) = \log_2 \lceil \log_2 n \rceil \\ b(G_2) \leqslant 2 \lceil \log_2 \chi(G_2) \rceil = 2 \lceil \log_2 b(G_1) \rceil = 2 \lceil \log_2 \lceil \log_2 n \rceil \rceil. \end{gather*}

Remark. Actually the upper bound in the Lemma may be improved to (1+o(1))log2χ(G)(1 + o(1)) \log_2 \chi(G) that yields m=(1+o(1))log2log2nm = (1 + o(1)) \log_2 \log_2 n.

How the field did

contestants scored
589
average (of 10)
0.24
solved (≥ 80%)
1.2%
near-0 (≤ 10%)
95.9%
discrimination
0.43

Score distribution (field cohort)

Computed on contestants with a meaningful total (field cohort); discrimination is the corrected item–total correlation.

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