We prove the existence conjecture for combinatorial designs, answering a question of Steiner from 1853. More generally, we show that the natural divisibility conditions are sufficient for clique decompositions of simplicial complexes that satisfy a certain pseudorandomness condition. As a further generalisation, we obtain the same conclusion only assuming an extendability property and the existence of a robust fractional clique decomposition.
As a weaker version of the Existence Conjecture, Erd o s and Hanani @cite_6 posed the question of the existence of asymptotically optimal Steiner systems; equivalently, finding @math edge-disjoint @math 's in @math . This was proved by R "odl @cite_3 , by developing a new semi-random construction method known as the nibble', which has since had a great impact on Combinatorics (see e.g. @cite_15 @cite_1 @cite_10 @cite_12 @cite_46 @cite_19 @cite_33 @cite_25 @cite_28 for related results and improved bounds). It will also play an important role in this paper.
@cite_33 @cite_46 @cite_28 @cite_1 @cite_3 @cite_6 @cite_19 @cite_15 @cite_10 @cite_25 @cite_12
1991434971 2530299459 2949560198 2963702702
A partial Steiner system Sp(t, k, n) is a collection of k-subsets (i.e. subsets of size k) of n element set such that every t-subset is contained in at most one k-subset. To avoid trivial cases, we assume 2 ⩾ t < k < n. It is easy to see that the size of a partial Steiner system Sp(t, k, n) is at most (tn) (kt). Confirming a conjecture of Erdos and Hanani [5], Rodl [19] proved that for fixed positive integers t and k, there is a partial Steiner system Sp(t, k, n) of size at least (1 − o(1)) ( nt)( kt) where o(1) goes to 0 as n goes to infinity. Grable [7] found an explicit bound of the o(1) term above and it was improved by Kostochka and Rodl [15] to n−1 ((kt)+o(1)−1). All proofs used Rodl's nibble method. We also use the method to improve the bound to O(( log nn) k − t(( kt)−1) for 2 ⩾ t < k — 2. (For t = k — 1, slightly better bounds were already known. See [2].) We believe that the nibble method gives no better bound up to a logarithmic factor. Recently, in [Random Struct Algorithm 41 2012, 441-450] we adapted exploration and martingale arguments of Nachmias and Peres [ALEA Lat Am J Probab Math Stat 3 2007, 133-142], in turn based on ideas of Martin-Lof [J Appl Probab 23 1986, 265-282], Karp [Random Struct Alg 1 1990, 73-93] and Aldous [Ann Probab 25 1997, 812-854], to prove asymptotic normality of the number L1 of vertices in the largest component L1 of the random r-uniform hypergraph in the supercritical regime. In this paper we take these arguments further to prove two new results: strong tail bounds on the distribution of L1, and joint asymptotic normality of L1 and the number M1 of edges of L1 in the sparsely supercritical case. These results are used in [Combin Probab Comput 25 2016, 21-75], where we enumerate sparsely connected hypergraphs asymptotically. © 2016 Wiley Periodicals, Inc. Random Struct. Alg., 50, 325-352, 2017 We initiate the probabilistic analysis of linear programming (LP) decoding of low-density parity-check (LDPC) codes. Specifically, we show that for a random LDPC code ensemble, the linear programming decoder of Feldman succeeds in correcting a constant fraction of errors with high probability. The fraction of correctable errors guaranteed by our analysis surpasses previous nonasymptotic results for LDPC codes, and in particular, exceeds the best previous finite-length result on LP decoding by a factor greater than ten. This improvement stems in part from our analysis of probabilistic bit-flipping channels, as opposed to adversarial channels. At the core of our analysis is a novel combinatorial characterization of LP decoding success, based on the notion of a flow on the Tanner graph of the code. An interesting by-product of our analysis is to establish the existence of ldquoprobabilistic expansionrdquo in random bipartite graphs, in which one requires only that almost every (as opposed to every) set of a certain size expands, for sets much larger than in the classical worst case setting. We prove tight upper bounds on the logarithmic derivative of the independence and matching polynomials of d-regular graphs. For independent sets, this theorem is a strengthening of Kahn's result that a disjoint union of copies of Kd;d maximizes the number of independent sets of a bipartite d-regular graph, Galvin and Tet ali's result that the independence polynomial is maximized by the same, and Zhao's extension of both results to all d-regular graphs. For matchings, this shows that the matching polynomial and the total number of matchings of a d-regular graph are maximized by a union of copies of Kd;d. Using this we prove the asymptotic upper matching conjecture of Friedland, Krop, Lundow, and Markstrom. In probabilistic language, our main theorems state that for all d-regular graphs and all �, the occupancy fraction of the hard-core model and the edge occupancy fraction of the monomer-dimer model with fugacity � are maximized by Kd;d. Our method involves constrained optimization problems over distributions of random variables and applies to all d-regular graphs directly, without a reduction to the bipartite case. Using a variant of the method we prove a lower bound on the occupancy fraction of the hard-core model on any d-regular, vertex-transitive, bipartite graph: the occupancy fraction of such a graph is strictly greater than the occupancy fraction of the unique translationinvariant hard-core measure on the infinite d-regular tree