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Exercise 1306Combinatorics › Graph theoryM1Added 5 Nov 2026

A cut containing at least half of the edges

#probabilistic method#expectation#graph theory#local improvement

Statement

Let GG be a graph with mm edges. Prove that its vertices can be split into two sets X,YX,Y so that at least m2\frac m2 edges join XX to YY. Give two proofs: one by averaging and one by moving vertices.

Hint

(a) Assign each vertex to XX or YY by a fair coin flip and compute the expected number of crossing edges. (b) If a vertex has more neighbours on its own side than on the other, move it.

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Solution

Proof 1 (average). Put each vertex independently in XX or YY with probability 12\frac12. A fixed edge uvuv crosses iff u,vu,v land on different sides, which has probability 12\frac12. By linearity of expectation the expected number of crossing edges is m2\frac m2. A random variable cannot always be below its mean, so some choice of X,YX,Y gives at least m2\frac m2 crossing edges.

Proof 2 (local improvement). Start with any split. While some vertex vv has strictly more neighbours on its own side than on the other, move vv to the other side. This replaces the aa non-crossing edges at vv by crossing ones and the b<ab<a crossing edges by non-crossing ones, so the number of crossing edges increases by a−b≥1a-b\ge1. It cannot exceed mm, so the process stops. At the end, each vertex vv has at least half of its edges crossing; summing over all vertices, every crossing edge is counted twice: 2⋅(crossing)≥m2\cdot(\text{crossing})\ge m, so crossing ≥m2\ge\frac m2.

Remark. For KnK_n the best possible cut has ⌊n2/4⌋\lfloor n^2/4\rfloor edges, a proportion slightly above 12\frac12.

Lesson. When you need an object at least as good as average, compute the average (probabilistic method), or run a monovariant that improves a counter.