Past exam of the mathematics course of the University of Cambridge 2013 iii Paper 10 3 Solution Created 2026-10-03 Updated 2026-10-07
Identify the hypercube graph with , joining two sets when their symmetric difference has size one. Write for the closed graph neighbourhood of , and for its radius- neighbourhood in Hamming distance. In the simplicial order on the discrete cube, smaller sets come first, with lexicographic order within each rank: the smallest differing coordinate belongs to the earlier set. Let be the first vertices in this order. Harper theorem isEquivalently, minimizes the external vertex boundary at fixed size. We will also obtain for every integer .
Here is a complete proof by simplicial section compression. First note two properties of the simplicial order on the discrete cube. Its restriction to either face obtained by fixing one coordinate is the corresponding order on the smaller hypercube graph. Also, the closed graph neighbourhood of an initial segment is an initial segment. To verify the latter, a nonempty initial segment contains every level below its last level , and a lexicographic prefix at level . For , its closed graph neighbourhood contains every set of size at most , and its only further members are the upper shadow of . An -set lies in this upper shadow exactly when its lexicographically earliest -subset lies in . That earliest subset is obtained by deleting the largest element. These earliest subsets vary monotonically in lexicographic order, so the upper shadow is another lexicographic prefix. For , the closed graph neighbourhood of is the union of levels zero and one. The empty initial segment causes no exception.
Induct on , with immediate. Fix a coordinate and write the sections of as , deleting from the latter section. Replace them by the initial segments with , . The sections of the old closed graph neighbourhood areBy induction their sizes are at least and , respectively. These are exactly the sizes of the new sections, because both sets in each new union are initial segments and hence nested. Thus simplicial section compression preserves size and never enlarges the closed graph neighbourhood.
Repeatedly compress any section that is not already an initial segment. Every change strictly reduces the sum of the global simplicial positions of the included vertices. This nonnegative integer decreases only finitely often, so the process ends at a family whose sections in every coordinate are initial segments. If itself is an initial segment, the induction is complete. Otherwise choose the earliest absent vertex and the latest present vertex , with . They cannot agree in any coordinate: agreement would put them in one compressed section, where an earlier absent vertex cannot precede a later present one. Hence . Nor can a vertex lie between them: if is present, pairing it with would force ; if absent, pairing it with would force . Thus are consecutive, and is obtained from by replacing its last vertex with the next vertex .
There are only two possibilities for these terminal families for simplicial section compression. If , consecutiveness makes the last -set and the first -set. Complementarity forces , and . For , the corresponding contains all sets of size at most except , and additionally . Every -set has at least two -subsets, so at least one belongs to . The missing has a -subset in . Consequently contains every set of size at most , which is exactly .
If , then . Since are complementary, the smaller one contains coordinate . Consecutiveness forces to be the last -set containing , and the first -set avoiding :The initial segment consists of all sets of size less than and all -sets containing . Its closed graph neighbourhood contains all sets of size at most and all -sets containing . For , each such -set has -subsets containing , so removing only leaves one in . All sets of size at most are still in , because all levels below belong to . Hence again . For , the two families are related by exchanging coordinates and both have the whole as their closed graph neighbourhood. These comparisons finish the induction and prove Harper theorem.
For the radius- version, repeatedly use the one-step result. At each step the comparison family remains an initial segment, and its closed graph neighbourhood is monotone in its size. If , applying Harper theorem to therefore gives . Induction on proves the asserted extension.
A Lévy family of graphs has vanishing concentration of measure functions after distances have been scaled by the graph diameter. More explicitly, for connected finite graphs of diameter , use normalized graph distance and uniform probability measure. For every fixed , requireFor this normalization is normalized Hamming distance , since its diameter is .
If , the corresponding initial segment contains the Hamming ball about of radius . The radius- version of Harper theorem impliesUse the precise Hoeffding inequality for . One can also derive this estimate directly: the moment-generating function of is ; the exponential Markov inequality followed by minimization at gives the bound. With , we have . Thus, whenever ,This proves that the hypercube graphs form a Lévy family of graphs. The stronger fixed-positive-mass formulation follows as well. For any , choose with . The Chebyshev inequality for , whose variance is , makes the Hamming ball of radius have fewer than vertices. An initial segment of size at least contains that ball. Enlarging by and using the same Hoeffding inequality gives a complement proportion tending to zero uniformly over all such . The normalization matters: with unscaled unit Hamming distance, cubes do not satisfy the metric version at every fixed radius; for a radius below one, a half-cube has no enlargement.
Equality in Harper theorem does not determine a down-set up to isomorphism. In , takeThis is a down-set of size nine. Its closed graph neighbourhood contains every set of size at most two, because all singletons belong to . Every triple contains an edge of the four-cycle among the listed pairs, so every triple also belongs to . The four-element set does not. Hence .
The size-nine simplicial order on the discrete cube initial segment is all sets of size at most one together with the pairs . Every triple contains one of these pairs, and the four-element set is again absent from its closed graph neighbourhood. Its neighbourhood therefore also has size , proving extremality of . Nevertheless the induced graphs are not isomorphic: in , the empty set has degree four, the four singletons have degree three, and the four pairs have degree two. The initial segment has two vertices of degree four, namely and . Since a graph automorphism preserves induced degree of a vertex, no automorphism of the cube can carry one family to the other. This gives nonunique down-set extremizers for Harper theorem even under the stronger test of induced graph isomorphism.
Past exam of the mathematics course of the University of Cambridge 2013 iii Paper 12 1 Solution Created 2026-10-03 Updated 2026-10-07
Write for the balanced graph blow-up of a complete graph, with classes of size ; containment here is as a subgraph, not necessarily an induced subgraph. The logarithmic form of the Erdős-Stone theorem is: for fixed and , there are and such thatThus the guaranteed balanced part size is at least , with independent of . We prove the logarithmic Erdős-Stone theorem by a density-to-cliques step and a constructive dense clique family blow-up lemma.
First choose a fixed large enough that , where is the edge count of the Turan graph. A uniformly chosen -vertex subset has expected edge count at least . If its induced graph contains no , the Turan theorem bounds that count by . Since the count is always at most , the probability that the subset contains an -clique is at least . Double counting the incidences between such subsets and their cliques gives, for ,for a fixed and all sufficiently large . Here . This is clique supersaturation by sampling.
We now prove the needed dense clique family blow-up lemma, with the following stronger induction invariant. Given any family of at least distinct -cliques, there is a complete -partite subgraph with each class of size , containing that many pairwise vertex-disjoint transversal members of , each with one vertex in every class. Extra edges within its classes can be ignored. We may suppose . For , any singletons suffice, and we may take once is large.
For , put . Repeatedly delete every member of the current family containing an -clique whose number of extensions is at most . Each such face is processed at most once, and there are at most possible faces. At most members are deleted. The remaining family has size at least , and every face that remains has more than extensions. Its family of -faces has size at least , since each face is in at most members.
Apply the induction hypothesis to these faces. It gives a complete -partite subgraph with vertices in each class and a matching of transversal -faces from the family. Form a bipartite graph whose left vertices are the and whose right vertices are the original vertices; join to when . Every left degree exceeds .
The following common neighbourhood from bipartite density estimate is elementary. In a bipartite graph with class sizes and at least edges, averaging over left subsets of size and using convexity of the integer sequence giveswhenever . The last inequality follows by comparing the factors in the two binomial coefficients; the integer convexity follows from the nondecreasing first differences .
ChooseFor large , , so . The estimate supplies selected faces with a common extension set of size at least . This extension set is disjoint from the selected faces: a vertex in any one of them cannot extend that face. Their union has vertices in each of the old classes, with all required cross edges; choose distinct common extension vertices as a new class. Attaching one different extension vertex to each selected face also gives disjoint members of . This completes the induction, with positive constants independent of . Apply it to the clique family above and take .
The logarithmic order cannot be increased in a uniform forcing result. Put , choose strictly between and one, and take a binomial random graph. Its edge density exceeds with probability tending to one, by the variance estimate for a sum of independent edge indicators. With , the expected number of ordered embeddings of is at mostFor and , the logarithm of this bound is negative of order . Markov's inequality therefore makes the probability of any such copy tend to zero. Both events hold simultaneously for some graphs of every sufficiently large order. There are graphs meeting the density hypothesis whose largest balanced blow-up has part size . This upper bound concerns what density can force; it is not an upper bound for every dense graph, since a complete graph has much larger blow-ups.
Finally, is the square of a cycle, for . Any three consecutive vertices form a triangle in a graph. In a proper three-colouring, once the first three colours are fixed, each subsequent vertex must repeat the colour three positions earlier. Closing the cycle is possible precisely when . Conversely, repeating the three colours gives such a colouring whenever . In that case embeds in , and the density exceeds the bipartite Turan theorem threshold by a fixed amount, so the theorem forces eventually. If , the balanced Turan graphs have density at least and contain no graph of chromatic number greater than three. They give a counterexample sequence. Exactly the cycle lengths divisible by three have the required property.
Past exam of the mathematics course of the University of Cambridge 2013 iii Paper 12 2 Solution Created 2026-10-03 Updated 2026-10-07
For a fixed uniform hypergraph with vertices, uniformity , and at least one edge, define its Turán density bywhere is the maximum edge count of an -free hypergraph. The limit exists: averaging the edge count over all -vertex subsets of an extremal -vertex hypergraph, with , shows that the displayed normalized extremal numbers are nonincreasing. Thus their limit is their infimum.
For hypergraph supersaturation by sampling, choose so that . The expected edge count in a uniform -vertex subset of is at least . A subset containing no copy of has at most edges, while any subset has at most . Hence at least an fraction of the subsets contain . Every particular copy of lies in exactly such subsets, so their number is at leastfor . TakeFor , the requested integer lower bound is zero; for , the calculation proves it. This positive depends only on and . If the density hypothesis is impossible there is nothing to prove. For an edgeless , every -set is already a copy and the conclusion follows directly.
For the edge-triangle objective, let be the open neighbourhood of and define its local scoreIt counts the contribution to of edges and triangles in a graph containing . If are nonadjacent, making a false twin of changes the objective by , since no edge or triangle in a graph uses both. More generally, partition vertices into false-twin classes, meaning equal open neighbourhoods. If distinct classes have no edges between them, making every vertex of a twin of a representative of changes the objective by . Choose the direction with nonnegative change.
Among graphs maximizing the objective, choose one maximizing the sum of squared false-twin class sizes. The operation cannot split any old false-twin class and merges , so it would strictly increase that secondary quantity. Therefore no two distinct classes can be nonadjacent. An objective maximizer is a complete multipartite graph. This edge-triangle symmetrization works for every real , with no assumption on its sign.
For positive part sizes , the correct multipartite formula isThe first sum in the printed intermediate formula has inconsistent indices; the edge count is the pairwise-product sum above. Fix two part sizes with sum and let be the sum of all other sizes. All terms varying with the pair have the formChoose a maximizing partition with the fewest nonempty parts. If , merging those two parts cannot decrease and reduces the number of parts, a contradiction. Therefore this coefficient is positive for every pair. If two integer sizes differ by at least two, moving one vertex from the larger to the smaller increases their product and hence , again a contradiction. All sizes differ by at most one, so a maximizer is a Turan graph. This is balancing a multipartite edge-triangle objective.
Next maximize the same polynomial on the compact simplex of nonnegative real sizes summing to , starting with at least two possible parts. Choose a maximizer with the smallest positive support. The merging argument still applies, and now varying two positive unequal sizes towards equality improves the product. Thus every positive size is for some integer . A two-part choice has value when , so . The optimum is attained at rational sizes, and thereforeOne may take the initial simplex to have coordinates, so it includes every multipartite graph obtained above; zero coordinates are discarded.
Set . Dividing the right side by givesbecause is an integer at least two. Rearranging provesEquality in the continuous calculation occurs at two or three equal parts, explaining the triangle support line between bipartite and tripartite Turan graphs.
Past exam of the mathematics course of the University of Cambridge 2013 iii Paper 12 3 Solution Created 2026-10-03 Updated 2026-10-07
We prove edit-distance stability for clique-free graphs by induction on , using the symmetric difference of edge sets as the distance. For , a -free graph is edgeless, and there is nothing to change. For , choose a vertex of maximum degree , let be its neighbourhood and put . Then is -free. WriteBoth deficits are nonnegative by the Turan theorem. Since every vertex of has degree at most ,The complete -partite graph formed from an -partite Turan graph on and the new class has at most edges. Thus , and direct subtraction givesBy induction, edit into a complete -partite graph using at most changes. Delete the edges inside , and add the missing edges between and . The resulting graph is complete -partite on the same vertex set, andwhere the inequality uses . The required edit distance is at most . Empty partition classes are allowed; a sufficiently dense nondegenerate case has the usual full complement of classes.
For the odd-cycle conclusion, use two standard consequences of the Szemerédi regularity lemma, stated explicitly. The triangle removal lemma says that for every , some ensures that a graph with at most triangles in a graph can be made triangle-free by deleting at most edges, for all sufficiently large . Also, for each fixed odd length and each , there is such that a graph with at least triangles in a graph contains at least copies of .
For clarity, the latter odd-cycle copies from positive triangle density consequence follows by applying regularity with error small relative to , removing exceptional, irregular and very sparse pairs, and retaining a triangle in a graph among the remaining regular dense pairs. The graph embedding lemma for regular pairs counts a positive constant times embeddings of any fixed graph properly three-coloured into those three clusters, including . Dividing by the fixed number of descriptions of a cycle gives the same conclusion for unlabelled copies.
Apply triangle in a graph removal with , and take the resulting . A -free graph cannot have triangles in a graph for large , by the preceding consequence. Delete at most edges to obtain a triangle-free . With ,Apply the proved stability result with . The resulting complete bipartite graph satisfiesChoose also large enough that . Then the distance is at most .
For the unheaded continuation, use the same and its associated , and set . Having at most cycles rules out triangles in a graph just as before. The identical deletion and stability calculation applies. A sufficiently small gives the same bound.