Complete graph minor density threshold 2026-10-05
The complete graph minor density threshold isThe density here is edge count divided by order, half the average degree of a vertex. For large , this threshold has order , with the logarithm taken to base .
Degree-biased vertex distribution Created 2026-09-24 Updated 2026-09-29
In a finite graph with at least one edge, the degree-biased vertex distribution assigns probability proportional to the degree of a vertex. It is the distribution of an endpoint on a specified side of a uniformly random edge.
Edge-triangle symmetrization 2026-10-05
For each real , some maximizer of among graphs on vertices is complete multipartite graph. Among maximizers maximize . Cloning either of two nonadjacent vertices preserves the objective, since maximality forces their local contributions to agree. If their vertex neighbourhoods differ, the sum of the two changes in the squared-degree of a vertex objective is twice the size of their symmetric difference, a contradiction. Nonadjacency therefore partitions the vertices into classes with identical vertex neighbourhoods.
High-minimum-degree multipartite stability subgraph Created 2026-10-05 Updated 2026-10-07
For fixed positive integers , a graph on vertices with and no balanced complete multipartite blow-up contains an -partite subgraph with vertices, balanced classes of size , and minimum degree of a graph .
One proof first removes a vanishing fraction of vertices of low degree of a vertex, finds a slowly growing by the Erdős-Stone theorem, and assigns almost every remaining vertex to a root class in which it has fewer than neighbours of a vertex. After discarding a further vanishing fraction, a inside an assigned class would extend to using the root classes. Thus internal edges and missing cross-class edges both number . Removing the vertices with unusually many missing cross-class edges gives the stated minimum degree of a graph.
Leaf of a graph Created 2026-09-24 Updated 2026-09-24
Maximum degree of a graph Created 2026-09-24 Updated 2026-09-24
Minimum degree of a graph Created 2026-09-24 Updated 2026-09-24
If a fixed graph has chromatic number , every extremal -free graph on vertices has minimum degree of a graph . Use a high-minimum-degree multipartite stability subgraph : replacing any vertex by one adjacent to all but one class of preserves -freeness. Any supposed new copy of can replace the new vertex by an unused common neighbour in the omitted class. Extremality therefore gives the lower bound on every degree of a vertex; the Erdős-Stone theorem gives the upper bound on the average degree of a vertex.
Equality in Harper theorem need not make a down-set a cube-automorphic image of a simplicial initial segment. In , take all sets of size at most one and the four two-element sets forming a four-cycle. This family has size nine and closed graph neighbourhood size fifteen, just like the size-nine simplicial order on the discrete cube initial segment. The induced degree of a vertex distributions differ, so they cannot be related by a graph automorphism.
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 2016 iii Paper 109 1 Solution Created 2026-10-03 Updated 2026-10-06
For a family , let its lower shadow consist of all -sets contained in members of . The local LYM inequality isTo prove it, use double counting on the pairs with , and . Each contributes pairs; each contributes at most . Hence , exactly the displayed Local LYM inequality after using .
To deduce the LYM inequality, start with an antichain in the Boolean lattice and assign it weight . If its largest occupied rank is , replace that whole rank by its lower shadow. The result remains an antichain: if an old lower-rank member were contained in a new shadow member, it would also be contained in an original rank- member, contradicting the original antichain property. Nor can a new member be contained in an old one, since every old member has size at most and equality would give the same contradiction. The Local LYM inequality shows that this replacement does not decrease the weight. Repeating eventually leaves an antichain on rank zero, whose weight is at most one. ThereforeFor the empty family the conclusion is immediate; the same argument includes the singleton family containing the empty set.
The antichains of maximum size are exactly the full middle levels. More precisely, for even only attains the bound in Sperner theorem; for odd either or does. To prove that there are no others, put . If , the LYM inequality and imply equality in every term's bound . Thus every member lies on a middle level. For even , there is only one such level, so it must be full.
For odd , let be the rank- members and the rank- members. Consider the bipartite graph of inclusions between those levels. Both parts have size , and the degree of a vertex is . If is the neighbourhood of , double counting gives . Since the family is an antichain, avoids ; equality forces and to be the full complement of . Equality in the degree count means that every edge into comes from , so there are no edges between and its complement.
This inclusion graph is connected: any two -sets can be joined by successively exchanging one element, and each exchange passes through their -set union. Every upper vertex has a lower neighbour. Thus must be empty or the whole lower level, proving the classification. For the graph is just one edge, and for the unique maximum family is . This establishes equality in Sperner theorem without assuming that equality in the LYM inequality alone always forces a middle level.
For the set-pair bound, choose a uniformly random permutation of , and let be the event that every element of appears before every element of . Since , their relative order is uniform, andFor distinct , choose and . These are distinct because is empty. On , precedes ; on , precedes . Thus the events are pairwise disjoint events, giving the Bollobas set-pairs inequalityThis Bollobas set-pairs inequality immediately gives another proof of the LYM inequality: enumerate the members of an antichain, and take , . For , incomparability means , while . The set-pair hypotheses therefore hold, and makes the resulting sum exactly the LYM inequality.
Past exam of the mathematics course of the University of Cambridge 2017 ib Paper 3 9H b Solution Created 2026-09-24 Updated 2026-10-05
For the usual undirected graph with at least two vertices, a simple random walk chooses a neighbor uniformly at each step, so when and are adjacent and zero otherwise, where is the degree of a vertex. The handshaking lemma gives . Thus the stationary distribution of a graph random walk isFor adjacent , , and for nonadjacent pairs both sides vanish. By detailed balance, this is an invariant distribution and the walk started from it is a reversible Markov chain. Connectedness makes the finite walk an irreducible Markov chain, giving uniqueness of its invariant distribution. No aperiodicity assumption is needed for uniqueness, so a bipartite graph is allowed.
If the connected graph has a single isolated vertex, the usual neighbor-choice formula is undefined. With the natural absorbing convention , its unique invariant distribution is and it is reversible. The degree-normalization formula presupposes at least one edge.
Past exam of the mathematics course of the University of Cambridge 2017 iii Paper 214 2 b Solution Created 2026-10-03 Updated 2026-10-06
We use planar duality for rectangle crossings, Harris-FKG inequality and the permitted exponential decay of subcritical percolation. A critical-point detail matters: uniqueness stated only for cannot by itself be applied at . We prove the Burton-Keane theorem by the boundary counting proof of percolation uniqueness, establishing at most one infinite percolation cluster at every parameter and avoiding that gap.
For , the number of infinite percolation clusters is almost surely constant by translation ergodicity of Bernoulli percolation. It cannot be a finite constant greater than one. A sufficiently large box meets two different infinite percolation clusters with positive probability; opening its finitely many interior edges joins them without creating a new infinite percolation cluster, decreasing . Finite modification of Bernoulli percolation gives positive probability to this modification, contradicting constancy.
Nor can . A finite box then meets three different infinite percolation clusters with positive probability. Select one infinite exterior branch from each. In the box and a finite collar retain just an embedded three-armed tree joining those branches and close all other incident edges there. Its branching graph vertex separates three infinite components when removed, so is a trifurcation vertex in percolation. All selections concern finitely many possible entrances and edge patterns; finite-energy property of Bernoulli percolation gives positive probability for at least one such pattern. Translation invariance then gives a common positive trifurcation probability .
Here is the counting contradiction in detail. For a finite box , contract each open component outside that touches to a boundary terminal. In each cluster, the resulting incidence graph is finite and connected. Every trifurcation in separates at least three sets of terminals, since each infinite branch must leave . A minimal subtree joining all terminals must therefore contain that graph vertex with degree of a vertex at least three. Its leaves are terminals. The tree identity bounds the number of those branching graph vertices by the terminal count. Different terminals are represented by different exterior graph neighbours of . Thus the trifurcation boundary-counting lemma givesFor , the two sizes are and . Letting contradicts . Therefore almost surely, with the same conclusion for the translated planar dual graph.
Now prove absence of percolation at by Zhang's argument. Suppose instead that . Almost surely an infinite primal cluster exists, and self-duality gives an infinite dual cluster as well. An infinite connected subgraph of this locally finite lattice contains a graph ray, by the König infinity lemma. Expanding square boxes meet the infinite percolation clusters with probability tending to one.
For , let mean that an open graph ray takes an outward edge through the indicated side and subsequently uses graph vertices outside . The union occurs whenever the box meets an infinite percolation cluster: take the last exit of an infinite graph ray from the finite box. Conversely an exterior arm supplies an infinite percolation cluster meeting its boundary. Quarter-turn symmetry makes the four probabilities equal. Their complements are decreasing events, so the square-root trick for positively associated events givesFor the planar dual graph use the box with boundary coordinates and define its exterior side-arm events in the same way. This box also has quarter-turn symmetry and meets the dual infinite percolation cluster with probability tending to one. Thus each dual side has an infinite exterior arm with probability tending to one. Primal outward edges cross this dual-box contour on the corresponding sides; their remaining graph vertices stay outside it. A union bound makes the simultaneous event of primal north/south arms and dual east/west arms have positive probability for a sufficiently large box.
The four arms alternate around the contour. Open all edges with both endpoints in , leaving all outward and exterior edges intact. This joins the two primal entrance points and preserves all four exterior arms. Finite-energy property of Bernoulli percolation keeps the event's probability positive. The primal north and south arms are now connected through the box. The two dual arms must lie in different infinite dual clusters. To see the separation, a hypothetical finite dual graph path joining the east and west arms cannot enter the dual-box interior: its boundary-crossing and interior edges cross primal edges that were just opened. Erase its loops and cut it at successive hits of the contour. A resulting exterior dual crosscut, together with the corresponding contour arc, encloses one of the two intervening primal entrance points. The infinite primal graph ray from that point would have to cross a dual-open edge, which is impossible. This is the planar separation used in the alternating arms argument at the self-dual percolation parameter. It contradicts uniqueness of the infinite dual cluster. HenceFinally suppose . At the permitted exponential decay of subcritical percolation would supply with . Use the rectangle with graph vertices , and let be its left-to-right open crossing. Planar duality for rectangle crossings identifies its complement with a dual top-to-bottom crossing of a rectangle of width and height . Rotation and translation give the same crossing law; side edges at the entrance and exit boundaries are irrelevant. Thus the exact self-dual rectangle crossing probability isBut a crossing has some starting graph vertex on its -vertex left side connected to distance . The union bound and exponential decay of subcritical percolation imply , a contradiction. ThereforeNo Russo-Seymour-Welsh theorem or continuity assertion for is being used, and critical uniqueness was proved rather than inferred from the supercritical hypothesis.
Past exam of the mathematics course of the University of Cambridge 2017 iii Paper 215 1 c Solution Created 2026-10-03 Updated 2026-10-06
Let interchange the two complete graphs, sending to and fixing . This involution preserves the transition matrix of the simple random walk. A mirror coupling under an involution starts at , keeps until the hitting time of , and then makes the two walks move identically. Each coordinate has the correct transition probabilities, and they coalesce precisely at . The coupling inequality for total variation gives
There is a genuine error in the printed expected hitting time bound, as well as an unspecified initial law. For , write and for . From every clique vertex there is a positive chance of reaching within two steps, uniformly over the finite state space for each fixed , so has finite expected value. First-step analysis, using the degree of a vertex at and at the other clique vertices, givesSolving these linear equations yieldsIn particular even the attachment vertex exceeds the printed bound by one. The valid uniform replacement is , the hitting time of the bridge vertex between two cliques formula.
We must also handle arbitrary starting states, including , before applying the mirror argument. Identify related vertices and consider the lumped Markov chain on . Its transition matrix has for , , for and , and , with all other entries zero. Here the row for only ranges over .
For and , direct two-step calculation givesAll these entries are at least . Thus for every , where is the uniform distribution on a finite set and . This is a Doeblin condition. At each two-step block couple the two quotient endpoints to the same sample from with probability , using the residual probability distributions otherwise. The first successful block has expected value at most , so the alignment time has . Lift each endpoint coupling of probability distributions to the original walks by their conditional two-step path laws; this preserves every marginal path law. The success test uses fresh block randomness and so permits restarting the walks with their original transition matrix at the aligned endpoints.
At alignment the original walks are equal or related. Use identical transitions in the first case and the mirror coupling under an involution in the second. The resulting coalescing coupling has coalescence time satisfying for every pair of initial states. Therefore Markov inequality and the pairwise mixing diameter implyFor the hint's particular starting states, the quotient one-step laws from two different clique indices have a common component of mass at least : for two ordinary indices it is ; for one attachment index it is . A maximal coupling therefore aligns those indices with probability , as suggested. The two-step argument above additionally covers .
The nonlazy walk is an aperiodic Markov chain for , because the connected graph contains a triangle. For it is a periodic Markov chain on a bipartite graph; each bipartition class has stationary mass , and the walk stays on a single class at each time. Hence and the mixing time is infinite. The asymptotic conclusion is valid for .
Past exam of the mathematics course of the University of Cambridge 2018 ib Paper 4 9H c Solution Created 2026-09-24 Updated 2026-10-03
Let be the degree of a vertex and putIf and are adjacent, then ; if they are not adjacent, both sides vanish. Thus the walk is in detailed balance, and its invariant distribution is proportional to vertex degree.
Past exam of the mathematics course of the University of Cambridge 2018 iii Paper 110 1 Solution Created 2026-10-03 Updated 2026-10-05
Write . The Erdős-Stone theorem states that, for a fixed graph with chromatic number ,Here is the extremal number, and copies are subgraphs, not necessarily induced subgraphs. We write for the balanced complete multipartite blow-up with classes of vertices each. All asymptotic errors below concern with the forbidden graphs fixed.
The stability subgraph. We prove the high-minimum-degree multipartite stability subgraph assertion directly from the Erdős-Stone theorem. For , the edgeless spanning subgraph suffices. Suppose .
First repeatedly remove a vertex whose degree of a vertex is less than times the current order, where sufficiently slowly. The Erdős-Stone theorem gives, uniformly for every -free subgraph of order at most ,Indeed, apply the asymptotic bound at large orders; the contribution from bounded or sufficiently small orders is negligible relative to . If vertices survive, the removed edges number at mostComparing with shows that , provided dominates , the initial relative error, and . Consequently . The surviving induced subgraph satisfies and .
By the Erdős-Stone theorem, contains for some as slowly as necessary. This follows because exceeds the extremal number density for each fixed by the positive gap . Choose so slowly that and , and denote its root classes by .
An outside vertex having at least neighbours of a vertex in every determines one choice of a -subset in each . At most outside vertices can determine any fixed choice, since otherwise these vertices and the chosen root sets form . Thus at most outside vertices have this property. Exclude those vertices and the root classes; put each remaining vertex in a class for which it has fewer than neighbours of a vertex in .
Write , with . Counting missing incidences with givesSince , it follows that for every . The total missing incidences from all root vertices to assigned vertices are at most . At least of them are incidences with a vertex's own assigned root class. Hence only missing incidences go to other root classes.
Choose slowly and discard the assigned vertices with more than missing incidences to other root classes. Each remaining vertex of is adjacent to all but at most vertices of every , . If its class contained a complete bipartite graph , the vertices of this copy would have at least common neighbours of a vertex in each other root class. These sets extend the copy to , a contradiction. By the bipartite case of the Erdős-Stone theorem, the number of internal edges in each surviving class is .
The surviving graph still has edges, whereas the total possible cross-class edges, with these balanced classes, is . Thus only cross-class edges are missing. Discard the vertices missing more than cross-class edges, with slowly, and delete all internal edges. The resulting -partite subgraph has classes of size andFor the lower bound, every surviving vertex misses only vertices outside its class; the upper bound follows from the class sizes. This also records the uniform cross-class error that we need next.
Minimum degree in an extremal graph. Fix with . Choose large enough that embeds in . An extremal -free graph is therefore -free, and its edge count has the required asymptotics by the Erdős-Stone theorem. For take as above.
For any vertex , remove and introduce a new vertex whose vertex neighbourhood consists precisely of the vertices in other than . The new degree of a vertex is . This new graph remains -free. Indeed, a new copy of must use , and all its neighbours of a vertex in that copy lie in the other classes of . There are only boundedly many of them. Each misses only vertices in , so an unused vertex is adjacent to all of them. Replacing by would give in , which is impossible.
Extremality now forces , uniformly in . The upper bound for the minimum degree of a graph follows from . For , already gives . ThusThis is the minimum degree of an extremal forbidden-subgraph graph principle.
The exact extremal graph for disjoint cliques. DefineThe plus sign denotes the join of graphs. The Turan graph contains no , so every such clique in uses a vertex of . Therefore contains no vertex-disjoint such cliques, and the extremal number is at least .
Induct on , with supplied by the Turan theorem, including its equality characterization. Let and let be extremal for . The preceding results give and the -partite subgraph . Keep its classes fixed and assign each of the remaining vertices to a class in which it has fewest neighbours of a vertex in . Write the resulting classes as ; all have size . Choose a positive so slowly that dominates the outside count, every cross-class error in , and every error in the minimum degree of a graph bound.
Suppose some vertex has at least internal neighbours of a vertex. If , the assignment rule shows that has at least neighbours of a vertex in every . If , it has this many in and in the other . If contained disjoint , we could choose one vertex in each , successively avoiding those copies and the missing cross-neighbours of the already chosen vertices. This produces a further through . For , this just chooses an unused neighbour of . Hence is -free, and induction givesSince the candidate attains , equality holds throughout: is a universal vertex and is the inductively unique extremal graph. Thus is isomorphic to .
It remains to show that this case must occur. Otherwise all internal vertex degrees are less than . Together with the lower bound on and , this implies that every vertex misses only vertices outside its own class. If some contains a matching in a graph of edges, extend its edges one by one to , choosing one vertex from each other class. At every step only cross-neighbours and boundedly many used vertices are excluded. This gives disjoint forbidden cliques, a contradiction.
A maximal matching in each class therefore has at most edges, and its at most endpoints form a vertex cover of the internal edges. Their internal vertex degrees are all , so the total internal edge count is . The cross-class edge count is at most , whenceBut the balanced part sizes of the Turan graph givecontradicting extremality for . This argument also works for . Consequently, for all sufficiently large ,The uniqueness is up to isomorphic graphs, as usual for an extremal graph for disjoint cliques.
Past exam of the mathematics course of the University of Cambridge 2018 iii Paper 110 4 Solution Created 2026-10-03 Updated 2026-10-05
Use natural logarithms. A graph minor is represented by disjoint nonempty branch sets of a graph minor, each inducing a connected graph, with an edge between every pair. The complete graph minor density threshold is defined over nonempty finite graphs byIt uses , half the average degree of a vertex; the nonempty convention excludes the vacuous density inequality for the empty graph. The PDF has the intended definition with a universal implication over ; the TeX transcription corrupts that definition.
Probabilistic lower bound. Put and take the binomial random graph . Its edge count has mean . The Chernoff bound impliesWe show that the probability of a graph minor tends to zero. Ignore connectedness, which only enlarges the set of possible models, and assign each of the vertices one of branch labels or an unused label. There are at most assignments.
For any assignment with nonempty branch sets, at least of them have size at most . Between any two such small sets , the probability of no edge isThe absence or presence of edges between different pairs of branch sets depends on disjoint sets of random edges, so these events are independent. For this assignment the probability that all small pairs are adjacent is at mostThe union bound over assignments is therefore at mostsince the positive term is and the negative term has order . There is consequently a graph with no graph minor and with . Any constant having the universal forcing property must exceed this ratio. Since for large ,
The auxiliary density lemma contains a typo. Both the original PDF and the TeX print in the hint. This cannot imply its conclusion: for , an edgeless graph has only edgeless graph minors, and none satisfies . We use the intended dense minor with bounded order and high minimum degree lemma with the hypothesis for nonempty . The upper-bound argument below depends on that corrected supplied lemma; the literal printed hint is false.
Probabilistic upper bound and the constant seven. Suppose is nonempty and , and setThe corrected lemma gives a graph minor of order with . Since , we also have . For large , every vertex has at most nonneighbours, counting itself, becausethe last inequality uses . Moreover any two distinct vertices have at leastcommon neighbours.
Choose disjoint random -sets from , uniformly, which is possible since for sufficiently large . For a set , let be the set of vertices having no neighbour in . For each vertex, the probability that all members of a uniformly sampled -set are its nonneighbours is at most , even when sampling without replacement. By linearity of expected value,Call good if . The Markov inequality shows that a random set is bad with probability at most . Thus the expected number of bad sets among our samples is .
Conditional on a fixed good , the marginal distribution of is uniform among -sets outside . For there to be no edge between them, all its members must lie in . HenceHere . Consequently the expected number of nonadjacent pairs of good sets is at mostsince . Applying the Markov inequality to both counts shows that there exists a choice with fewer than bad sets and at most nonadjacent pairs of good sets. Select of the good sets; they still have at most missing adjacencies.
Make each selected set connected by fixing one of its vertices as a root and, for each of its other members, adding one unused common neighbour of that member and the root. This uses at most additional vertices. Then for each pair with no original edge, choose one vertex in each set and add an unused common neighbour to one of the sets. The added vertex is joined to that set and to the other set, so it preserves connectedness and repairs their adjacency. At most such repairs are required.
Throughout this process the total number of occupied vertices is at mostSince every pair has at least common neighbours, an unused choice always exists. The final sets are disjoint connected branch sets of a graph minor with every pair adjacent. They represent in , and hence in , by transitivity of graph minors. This random branch-set construction of a complete graph minor proves
The sharp linear threshold for a four-vertex complete minor. We prove by induction that a graph on vertices with at least edges has a graph minor. The case is itself. If some edge has at most one common neighbour, an edge contraction reduces the order by one and removes exactly edges. The contracted graph has at least edges, so induction applies.
Otherwise every edge is in at least two triangles in a graph. Choose a vertex incident with an edge. Each vertex has at least two neighbours of a vertex in , since these are the common neighbours of . Thus has minimum degree of a graph at least two. A longest path in this finite graph has an endpoint adjacent to an earlier nonconsecutive path vertex, and hence contains a cycle in a graph. Together with , this cycle in a graph gives a wheel graph as a subgraph. Divide its rim into three consecutive nonempty connected arcs; these arcs and form four pairwise adjacent branch sets of a graph minor. Therefore
With edges the answer is no. Take the join of graphs of and an independent set of vertices. It has edges. Among four disjoint putative branch sets of a graph minor, at most two can contain the two vertices of . Any connected branch set avoiding them is a singleton in the independent set. At least two such singleton sets would therefore have no edge between them. This excludes a graph minor for every and proves sharpness.