We present a fully computer-assisted proof system for solving a particular family of problems in Extremal Combinatorics. Existing techniques using Flag Algebras have proven powerful in the past, but have so far lacked a computational counterpart to derive matching constructive bounds. We demonstrate that common search heuristics are capable of finding constructions far beyond the reach of human intuition. Additionally, the most obvious downside of such heuristics, namely a missing guarantee of global optimality, can often be fully eliminated in this case through lower bounds and stability results coming from the Flag Algebra approach. To illustrate the potential of this approach, we study two related and well-known problems in Extremal Graph Theory that go back to questions of Erdős from the 60s. Most notably, we present the first major improvement in the upper bound of the Ramsey multiplicity of K_4 in 25 years, precisely determine the first off-diagonal Ramsey multiplicity number, and settle the minimum number of independent sets of size four in graphs with clique number strictly less than five.

In the max-min allocation problem a set P of players are to be allocated disjoint subsets of a set R of indivisible resources, such that the minimum utility among all players is maximized. We study the restricted variant, also known as the Santa Claus problem, where each resource has an intrinsic positive value, and each player covets a subset of the resources. Bezáková and Dani [15] showed that this problem is NP-hard to approximate within a factor less than 2, consequently a great deal of work has focused on approximate solutions. The principal approach for obtaining approximation algorithms has been via the Configuration LP (CLP) of Bansal and Sviridenko [12]. Accordingly, there has been much interest in bounding the integrality gap of this CLP. The existing algorithms and integrality gap estimations are all based one way or another on the combinatorial augmenting tree argument of Haxell [26] for finding perfect matchings in certain hypergraphs. Our main innovation in this paper is to introduce the use of topological methods, to replace the combinatorial argument of [26] for the restricted max-min allocation problem. This approach yields substantial improvements in the integrality gap of the CLP. In particular we improve the previously best known bound of 3.808 to 3.534. We also study the (1, ε)-restricted version, in which resources can take only two values, and improve the integrality gap in most cases. Our approach applies a criterion of Aharoni and Haxell, and Meshulam, for the existence of independent transversals in graphs, which involves the connectedness of the independence complex. This is complemented by a graph process of Meshulam that decreases the connectedness of the independence complex in a controlled fashion and hence, tailored appropriately to the problem, can verify the criterion. In our applications we aim to establish the flexibility of the approach and hence argue for it to be a potential asset in other optimization problems involving hypergraph matchings.

Abstract Two $$n \times n$$ n × n Latin squares $$L_1, L_2$$ L 1 , L 2 are said to be orthogonal if, for every ordered pair (x, y) of symbols, there are coordinates (i, j) such that $$L_1(i,j) = x$$ L 1 ( i , j ) = x and $$L_2(i,j) = y$$ L 2 ( i , j ) = y . A k-MOLS is a sequence of k pairwise-orthogonal Latin squares, and the existence and enumeration of these objects has attracted a great deal of attention. Recent work of Keevash and Luria provides, for all fixed k, log-asymptotically tight bounds on the number of k-MOLS. To study the situation when k grows with n, we bound the number of ways a k-MOLS can be extended to a $$(k+1)$$ ( k + 1 ) -MOLS. These bounds are again tight for constant k, and allow us to deduce upper bounds on the total number of k-MOLS for all k. These bounds are close to tight even for k linear in n, and readily generalise to the broader class of gerechte designs, which include Sudoku squares.

We investigate the smallest possible minimum degree of $r$-color minimal Ramsey graphs for the $k$-clique. In particular, we obtain a bound of the form $O(k^2\log^2 k\big)$, which is tight up to a $(\log^2 k)$-factor whenever the number $r\geq2$ of colors is fixed. This extends the work of Burr, Erdös, and Lovász, who determined this extremal value for two colors and any clique size, and complements that of Fox, Grinshpun, Liebenau, Person, and Szabó, who gave essentially tight bounds when the order $k$ of the clique is fixed. As a side product our result also yields an improved upper bound on the vertex Folkman number $F(r,k, k+1)$ of the $k$-clique. The proof relies on a reformulation of the corresponding extremal function by Fox et al. and combines and refines methods used by Dudek, Eaton, and Rödl.

The Local Lemma is a fundamental tool of probabilistic combinatorics and theoretical computer science, yet there are hardly any natural problems known where it provides an asymptotically tight answer. The main theme of our article is to identify several of these problems, among them a couple of widely studied extremal functions related to certain restricted versions of the k -SAT problem, where the Local Lemma does give essentially optimal answers. As our main contribution, we construct unsatisfiable k -CNF formulas where every clause has k distinct literals and every variable appears in at most 2/e + o (1)) 2 k / k clauses. The Lopsided Local Lemma, applied with an assignment of random values according to counterintuitive probabilities, shows that this is asymptotically best possible. The determination of this extremal function is particularly important, as it represents the value where the corresponding k -SAT problem exhibits a complexity hardness jump: From having every instance being a YES-instance it becomes NP-hard just by allowing each variable to occur in one more clause. The construction of our unsatisfiable CNF formulas is based on the binary tree approach of Gebauer [2012], and thus the constructed formulas are in the class MU(1) of minimal unsatisfiable formulas having one more clause than variables. The main novelty of our approach here comes in setting up an appropriate continuous approximation of the problem. This leads us to a differential equation, the solution of which we are able to estimate. The asymptotically optimal binary trees are then obtained through a discretization of this solution. The importance of the binary trees constructed is also underlined by their appearance in many other scenarios. In particular, they give asymptotically precise answers for seemingly unrelated problems like the European Tenure Game introduced by Doerr [2004] and a search problem allowing a limited number of consecutive lies. As yet another consequence, we slightly improve the best-known bounds on the maximum degree and maximum edge-degree of a k -uniform Maker’s win hypergraph in the Neighborhood Conjecture of Beck.

In this paper we study the behavior of the domination number of the Erdös--Rényi random graph $\mathcal{G}(n,p)$. Extending a result of Wieland and Godbole we show that the domination number of $\mathcal{G}(n,p)$ is equal to one of two values asymptotically almost surely whenever $p \gg \frac{\ln^2n}{\sqrt{n}}$. The explicit values are exactly at the first moment threshold, that is, where the expected number of dominating sets starts to tend to infinity. For small $p$ we also provide various nonconcentration results which indicate why some sort of lower bound on the probability $p$ is necessary in our first theorem. Concentration, though not on a constant length interval, is proven for every $p\gg 1/n$. These results show that unlike in the case of $p \gg \frac{\ln^2n}{\sqrt{n}}$, where concentration of the domination number happens around the first moment threshold, for $p = O( \ln n/n)$ it does so around the median. In particular, in this range the two are far apart from each other.

We study the impact of metric constraints on the realizability of planar graphs. Let G be a subgraph of a planar graph H (where H is the "host" of G). The graph G is free in H if for every choice of positive lengths for the edges of G, the host H has a planar straight-line embedding that realizes these lengths; and G is extrinsically free in H if all constraints on the edge lengths of G depend on G only, irrespective of additional edges of the host H.

We construct unsatisfiable k-CNF formulas where every clause has k distinct literals and every variable appears in at most clauses. The lopsided Local Lemma shows that our result is asymptotically best possible: every k-CNF formula where every variable appears in at most clauses is satisfiable. The determination of this extremal function is particularly important as it represents the value where the k-SAT problem exhibits its complexity hardness jump: from having every instance being a YES-instance it becomes NP-hard just by allowing each variable to occur in one more clause. The asymptotics of other related extremal functions are also determined. Let l(k) denote the maximum number, such that every k-CNF formula with each clause containing k distinct literals and each clause having a common variable with at most l(k) other clauses, is satisfiable. We establish that the bound on l(k) obtained from the Local Lemma is asymptotically optimal, i.e., . The constructed formulas are all in the class MU(1) of minimal unsatisfiable formulas having one more clause than variables and thus they resolve these asymptotic questions within that class as well. The SAT-formulas are constructed via the binary trees of [10]. In order to construct the trees a continuous setting of the problem is defined, giving rise to a differential equation. The solution of the equation diverges at 0, which in turn implies that the binary tree obtained from the discretization of this solution has the required properties.

Let m and b be positive integers, and let F be a hypergraph. In an $(m,b)$ Maker-Breaker game F two players, called Maker and Breaker, take turns selecting previously unclaimed vertices of F. Maker selects m vertices per move, and Breaker selects b vertices per move. The game ends when every vertex has been claimed by one of the players. Maker wins if he claims all of the vertices of some hyperedge of F; otherwise Breaker wins. An $(m,b)$ Avoider-Enforcer game F is played in a similar way. The only difference is in the determination of the winner: Avoider loses if he claims all of the vertices of some hyperedge of F; otherwise Enforcer loses. In this paper we consider the Maker-Breaker and Avoider-Enforcer versions of the planarity game, the k-colorability game, and the $K_t$-minor game.

We are motivated by the analogue of Turán’s theorem in the hypercube $Q_n$: How many edges can a $Q_d$‐free subgraph of $Q_n$ have? We study this question through its Ramsey‐type variant and obtain asymptotic results. We show that for every odd d it is possible to color the edges of $Q_n$ with $\frac{(d+1)^2}{4}$ colors such that each subcube $Q_d$ is polychromatic, that is, contains an edge of each color. The number of colors is tight up to a constant factor, as it turns out that a similar coloring with ${d+1\choose 2} +1$ colors is not possible. The corresponding question for vertices is also considered. It is not possible to color the vertices of $Q_n$ with $d+2$ colors such that any $Q_d$ is polychromatic, but there is a simple $d+1$ coloring with this property. A relationship to anti‐Ramsey colorings is also discussed. We discover much less about the Turán‐type question which motivated our investigations. Numerous problems and conjectures are raised.

We prove that random edge, the simplex algorithm that always chooses a random improving edge to proceed on, can take a mildly exponential number of steps in the model of abstract objective functions (introduced by K. W. Hoke (1998) and by G. Kalai (1988) under different names). We define an abstract objective function on the n-dimensional cube for which the algorithm, started at a random vertex, needs at least exp(const /spl middot/ n/sup 1/3/) steps with high probability. The best previous lower bound was quadratic. So in order for random edge to succeed in polynomial time, geometry must help.

Suppose we are given (the edge graph of) an n-dimensional hypercube with its edges oriented so that every face has a unique sink. Such an orientation is called a unique sink orientation, and we are interested in finding the unique sink of the whole cube, when the orientation is given implicitly. The basic operation available is the so-called vertex evaluation, where we can access an arbitrary vertex of the cube, for which we obtain the orientations of the incident edges. Unique sink orientations occur when the edges of a deformed geometric n-dimensional cube (i.e., a polytope with the combinatorial structure of a cube) are oriented according to some generic linear function. These orientations are easily seen to be acyclic. The main motivation for studying unique sink orientations are certain linear complementarity problems, which allow this combinatorial abstraction (due to Stickney and Watson, 1978), where orientations with cycles can arise. Similarly, some quadratic optimization problems, like computing the smallest enclosing ball of a finite point set, can be formulated as finding a sink in a unique sink orientation (with cycles possible). For acyclic unique sink orientations, randomized procedures due to Bernd Gartner (1998, 2001) with an expected number of at Most e/sup 2/spl radic/n/ vertex evaluations have been known. For the general case, a simple randomized (3/2)/sup n/ procedure exists (without explicit mention in the literature). We present new algorithms, a deterministic O(1.61/sup n/) procedure and a randomized O((43/20)/sup n/2/)=O(1.47/sup n/) procedure for unique sink orientations. An interesting aspect of these algorithms is that they do not proceed on a path to the sink (in a simplex-like fashion), but they exploit the potential of random access (in the sense of arbitrary access) to any vertex of the cube. We consider this feature the main contribution of the paper. We believe that unique sink orientations have a rich structure, and there is ample space for improvement on the bounds given above.

This paper contains two main results. The first is an explicit construction of bipartite graphs which do not contain certain complete bipartite subgraphs and have maximal density, up to a constant factor, under this constraint. This construction represents the first significant progress in three decades on this old problem in extremal graph theory. The construction beats the previously known probabilistic lower bound on density. The proof uses the elements of commutative algebra and algebraic geometry (theory of ideals, integral extensions, valuation rings). The second result concerns monotone span programs. We obtain the first superpolynomial lower bounds for explicit functions in this model. The best previous lower bound was $\Omega(n^{5/2})$ by Beimel, Gal, Paterson (FOCS’95); our analysis exploits a general combinatorial lower bound criterion from that paper. We give two proofs of superpolynomial lower bounds; one based on an analysis of Paley-type bipartitie graphs via Weil’s character sum estimates. A third result demonstrates the power of monotone span programs by exhibiting a function computable in this model in linear size while requiring superpolynomial size monotone circuits and exponential size monotone formulae.