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IMC / 2007 / Problems / Day 1, P4

IMC 2007 · Day 1 · P4

hard

Let GG be a finite group. For arbitrary sets U,V,WGU, V, W \subset G, denote by NUVWN_{UVW} the number of triples (x,y,z)U×V×W(x, y, z) \in U \times V \times W for which xyzxyz is the unity.

Suppose that GG is partitioned into three sets AA, BB and CC (i.e. sets A,B,CA, B, C are pairwise disjoint and G=ABCG = A \cup B \cup C). Prove that NABC=NCBAN_{ABC} = N_{CBA}.

Solution (official)

We start with three preliminary observations.

Let U,VU, V be two arbitrary subsets of GG. For each xUx \in U and yVy \in V there is a unique zGz \in G for which xyz=exyz = e. Therefore, NUVG=U×V=UV.(1)\tag{1} N_{UVG} = |U \times V| = |U| \cdot |V|. Second, the equation xyz=exyz = e is equivalent to yzx=eyzx = e and zxy=ezxy = e. For arbitrary sets U,V,WGU, V, W \subset G, this implies {(x,y,z)U×V×W:xyz=e}={(x,y,z)U×V×W:yzx=e}={(x,y,z)U×V×W:zxy=e}\{ (x,y,z) \in U \times V \times W : xyz = e \} = \{ (x,y,z) \in U \times V \times W : yzx = e \} = \{ (x,y,z) \in U \times V \times W : zxy = e \} and therefore NUVW=NVWU=NWUV.(2)\tag{2} N_{UVW} = N_{VWU} = N_{WUV}. Third, if U,VGU, V \subset G and W1,W2,W3W_1, W_2, W_3 are disjoint sets and W=W1W2W3W = W_1 \cup W_2 \cup W_3 then, for arbitrary U,VGU, V \subset G, {(x,y,z)U×V×W:xyz=e}={(x,y,z)U×V×W1:xyz=e}{(x,y,z)U×V×W2:xyz=e}{(x,y,z)U×V×W3:xyz=e}\begin{align*} \{ (x,y,z) \in U \times V \times W : xyz = e \} &= \{ (x,y,z) \in U \times V \times W_1 : xyz = e \} \cup \\ &\quad \cup \{ (x,y,z) \in U \times V \times W_2 : xyz = e \} \cup \{ (x,y,z) \in U \times V \times W_3 : xyz = e \} \end{align*} so NUVW=NUVW1+NUVW2+NUVW3.(3)\tag{3} N_{UVW} = N_{UVW_1} + N_{UVW_2} + N_{UVW_3}. Applying these observations, the statement follows as NABC=NABGNABANABB=ABNBAANBAB==NBAGNBAANBAB=NBAC=NCBA.\begin{align*} N_{ABC} &= N_{ABG} - N_{ABA} - N_{ABB} = |A| \cdot |B| - N_{BAA} - N_{BAB} = \\ &= N_{BAG} - N_{BAA} - N_{BAB} = N_{BAC} = N_{CBA}. \end{align*}

How the field did

contestants scored
242
average (of 20)
4.02
solved (≥ 80%)
16.1%
near-0 (≤ 10%)
69.0%
discrimination
0.61

Score distribution (field cohort)

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

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