Euclidean minimum spanning trees and bichromatic closest pairs

We present an algorithm to compute a Euclidean minimum spanning tree of a given setS ofN points inE ^d in timeO(F _d (N,N) log ^d N), whereF _d (n,m) is the time required to compute a bichromatic closest pair amongn red andm green points inE ^d . IfF _d (N,N)=Ω(N ^1+ε), for some fixed ɛ>0, then the running time improves toO(F _d (N,N)). Furthermore, we describe a randomized algorithm to compute a bichromatic closest pair in expected timeO((nm logn logm)^2/3+m log² n+n log² m) inE ₃, which yields anO(N ^4/3 log^4/3 N) expected time, algorithm for computing a Euclidean minimum spanning tree ofN points inE ³. Ind≥4 dimensions we obtain expected timeO((nm)^{1−1/([d/2]+1)+ε}+m logn+n logm) for the bichromatic closest pair problem andO(N ^{2−2/([d/2]+1)ε}) for the Euclidean minimum spanning tree problem, for any positive ɛ. The first, second, and fourth authors acknowledge support from the Center for Discrete Mathematics and Theoretical Computer Science (DIMACS), a National Science Foundation Science and Technology Center under NSF Grant STC 88-09648. The second author's work was supported by the National Science Foundation under Grant CCR-8714565. The third author's work was supported by the Deutsche Forschungsgemeinschaft under Grant A1 253/1-3, Schwerpunktprogramm “Datenstrukturen und effiziente Algorithmen”. The last two authors' work was also partially supported by the ESPRIT II Basic Research Action of the EC under Contract No. 3075 (project ALCOM).     

On partitions of {1,…,2m + 1}\{k} into differences d,…,d + m − 1: Extended Langford sequences of large defect

It is shown that for m = 2d ? 1, 2d, 2d + 1, and d ≥ 1, the set {1, 2,…, 2m + 2}, ? {2,k} can be partitioned into differences d,d + 1,…,d + m ? 1 whenever (m,k) ≡ (0,0), (1,d + 1), (2, 1), (3,d) (mod (4,2)) and (d,m,k) ≠ (1,1,3), (2,3,7) (where (x,y) ≡ (u,ν) mod (m,n) iff x ≡ u (mod m) and y ≡ ν (mod n)). It is also shown that if m ≥ 2d ? 1 and m ? [2d + 2, 8d ? 5], then the set {1, 2, …, 2m + 1} ? {k} can be partitioned into differences d,d + 1,…,d + m ? 1 whenever (m,k) ≡ (0, 1), (1,d), (2,0), (3,d + 1) mod (4,2). Finally, for d = 4 we obtain a complete result for when {1,…,2m + 1} ? {k} can be partitioned into differences 4,5,…,m + 3. © 2004 Wiley Periodicals, Inc.     

Randomly coloring constant degree graphs

We study a simple Markov chain, known as the Glauber dynamics, for generating a random k ‐coloring of an n ‐vertex graph with maximum degree Δ. We prove that, for every ε > 0, the dynamics converges to a random coloring within O(nlog n) steps assuming k ≥ k₀(ε) and either: (i) k/Δ > α* + ε where α*≈? 1.763 and the girth g ≥ 5, or (ii) k/Δ >β * + ε where β*≈? 1.489 and the girth g ≥ 7. Our work improves upon, and builds on, previous results which have similar restrictions on k/Δ and the minimum girth but also required Δ = Ω (log n). The best known result for general graphs is O(nlog n) mixing time when k/Δ > 2 and O(n²) mixing time when k/Δ > 11/6. Related results of Goldberg et al apply when k/Δ > α* for all Δ ≥ 3 on triangle‐free “neighborhood‐amenable” graphs.© 2012 Wiley Periodicals, Inc. Random Struct. Alg., 2013     

Genus of cartesian products of regular bipartite graphs

Let G(n, d) denote a connected regular bipartite graph on 2n vertices and of degree d. It is proved that any Cartesian product G(n, d) × G₁(n₁, d₁) × G₂(n₂, d₂) × ? × G_m(n_m, d_m), such that max {d₁, d₂,…, d_m} ≤ d ≤ d₁ + d₂ + ? + d_m, has a quadrilateral embedding, thereby establishing its genus, and thereby generalizing a result of White. It is also proved that if G is any connected bipartite graph of maximum degree D, if Q_m is the m-cube graph, and if m ≥ D then G × Q_m has a quadrilateral embedding.     

All cycle‐complete graph Ramsey numbers r(Cm,K6)

The cycle‐complete graph Ramsey number r(C_m, K_n) is the smallest integer N such that every graph G of order N contains a cycle C_m on m vertices or has independence number α(G) ≥ n. It has been conjectured by Erd?s, Faudree, Rousseau and Schelp that r(C_m, K_n) = (m ? 1) (n ? 1) + 1 for all m ≥ n ≥ 3 (except r(C₃, K₃) = 6). This conjecture holds for 3 ≤ n ≤ 5. In this paper we will present a proof for n = 6 and for all n ≥ 7 with m ≥ n² ? 2n. © 2003 Wiley Periodicals, Inc. J Graph Theory 44: 251–260, 2003     

On Hamilton cycles in Erdős‐Rényi subgraphs of large graphs

Given a graph Γ_n=(V,E) on n vertices and m edges, we define the Erd?s‐Rényi graph process with host Γ_n as follows. A permutation e₁,…,e_m of E is chosen uniformly at random, and for t ≤ m we let Γ_n,t=(V,{e₁,…,e_t}). Suppose the minimum degree of Γ_n is δ(Γ_n) ≥ (1/2+ε)n for some constant ε>0. Then with high probability (An event holds with high probability (whp) if as n→∞.), Γ_n,t becomes Hamiltonian at the same moment that its minimum degree reaches 2. Given 0 ≤ p ≤ 1 let Γ_n,p be the Erd?s‐Rényi subgraph of Γ_n, obtained by retaining each edge independently with probability p. When δ(Γ_n) ≥ (1/2+ε)n, we provide a threshold for Hamiltonicity in Γ_n,p.     

Decreasing the diameter of bounded degree graphs

Let f_d (G) denote the minimum number of edges that have to be added to a graph G to transform it into a graph of diameter at most d. We prove that for any graph G with maximum degree D and n > n₀ (D) vertices, f₂(G) = n − D − 1 and f₃(G) ≥ n − O(D³). For d ≥ 4, f_d (G) depends strongly on the actual structure of G, not only on the maximum degree of G. We prove that the maximum of f_d (G) over all connected graphs on n vertices is n/⌊d/2 ⌋ − O(1). As a byproduct, we show that for the n‐cycle C_n, f_d (C_n) = n/(2⌊d/2 ⌋ − 1) − O(1) for every d and n, improving earlier estimates of Chung and Garey in certain ranges. © 2000 John Wiley & Sons, Inc. J Graph Theory 35: 161–172, 2000     

The Ramsey number for a cycle of length five vs. a complete graph of order six

It has been conjectured that r(C_m, K_n) = (m − 1)(n − 1) + 1 for all m ≥ n ≥ 4. This has been proved recently for n = 4 and n = 5. In this paper, we prove that r(C₅, K₆) = 21. This raises the possibility that r(C_m, K₆) = 5m − 4 for all m ≥ 5. © 2000 John Wiley & Sons, Inc. J Graph Theory 35: 99–108, 2000     

Zero-sum delta-systems and multiple copies of graphs

A main result proved in this paper is the following. Theorem. Let G be a noncomplete graph on n vertices with degree sequence d₁ ≥ d₂ ≥ · · · ≥ d_n and t ≥ 2 be a prime. Let m = gcd{t, d_i − d_j: 1 ≤ i < j ≤ n} and set Then R(tG, ℤ_t) = t(n + d) − d, where R is the zero-sum Ramsey number. This settles, almost completely, problems raised in [Bialostocki & Dierker, J Graph Theory, 1994; Y. Caro, J Graph Theory, 1991]. © 1999 John Wiley & Sons, Inc. J Graph Theory 32: 207–216, 1999     

Some arrowing results for trees versus complete graphs

For an arbitrary tree T of order m and an arbitrary positive integer n, Chvátal proved that the Ramsey number r(T, K_n) = 1 + (m ? 1) (n ? 1). for graphs G, G₁, and G₂, we say that G arrows G₁ and G₂, written G → (G₁, G₂), if for every factorization G = R ⊕ B, either G₁ is a subgraph of R or G₂ is a subgraph of B. it is shown that (i) for each l ≥ 2, K₁+ (m?1)(n?1) ?E(K₁) → (T, K_n) for m ≥ 2/ ? 1 and n ≥ 2; (ii) K₁ +,(m ?1)(n ?1) ? E(H) → (T, K_n), where H is any tree of order m ? 1, m ≥ 3 and n ≥ 2. It is further shown that result (i) is sharp with respect to the inequality m ≥ 2/? 1; in particular, examples are given to show that K1 + (2l?3)(n?1) E(K₁) ? (P_21?2, K_n) for all n ≥ 2, where P_21?2 denotes the path of order 21 ? 2. Also result (ii) is sharp with respect to the order of H; examples aregiven to show that K₁ + _(m?1)(n?1)? E(K(1, m ? 1)) ?(T, K_n)for any tree T of order m and any n ≥ 2.     

Component structure of the vacant set induced by a random walk on a random graph

We consider random walks on several classes of graphs and explore the likely structure of the vacant set, i.e. the set of unvisited vertices. Let Γ(t) be the subgraph induced by the vacant set of the walk at step t. We show that for random graphs G_n,p (above the connectivity threshold) and for random regular graphs G_r,r ≥ 3, the graph Γ(t) undergoes a phase transition in the sense of the well‐known ErdJW‐RSAT1100590x.png ‐Renyi phase transition. Thus for t ≤ (1 ‐ ε)t^*, there is a unique giant component, plus components of size O(log n), and for t ≥ (1 + ε)t^* all components are of size O(log n). For G_n,p and G_r we give the value of t^*, and the size of Γ(t). For G_r, we also give the degree sequence of Γ(t), the size of the giant component (if any) of Γ(t) and the number of tree components of Γ(t) of a given size k = O(log n). We also show that for random digraphs D_n,p above the strong connectivity threshold, there is a similar directed phase transition. Thus for t ≤ (1 ‐ ε)t^*, there is a unique strongly connected giant component, plus strongly connected components of size O(log n), and for t ≥ (1 + ε)t^* all strongly connected components are of size O(log n). © 2012 Wiley Periodicals, Inc. Random Struct. Alg., 2012     

Transfer theorems and asymptotic distributional results for m‐ary search trees

We derive asymptotics of moments and identify limiting distributions, under the random permutation model on m‐ary search trees, for functionals that satisfy recurrence relations of a simple additive form. Many important functionals including the space requirement, internal path length, and the so‐called shape functional fall under this framework. The approach is based on establishing transfer theorems that link the order of growth of the input into a particular (deterministic) recurrence to the order of growth of the output. The transfer theorems are used in conjunction with the method of moments to establish limit laws. It is shown that: (i) for small toll sequences (t_n) [roughly, t_n = O(n^1/2)] we have asymptotic normality if m ≤ 26 and typically periodic behavior if m ≥ 27; (ii) for moderate toll sequences [roughly, t_n = ω(n^1/2) but t_n = o(n)] we have convergence to nonnormal distributions if m ≤ m₀ (where m₀ ≥ 26) and typically periodic behavior if m ≥ m₀ + 1; and (iii) for large toll sequences [roughly, t_n = ω(n)] we have convergence to nonnormal distributions for all values of m. © 2004 Wiley Periodicals, Inc. Random Struct. Alg., 2005     

On the minimum number of edge-disjoint complete m-partite subgraphs into which Kn can be decomposed

Let α_m(n) denote the minimum number of edge-disjoint complete m-partite subgraphs into which K_n can be decomposed. In [2] the author proved that when m ≥ 3, if (i) n ≡ m and n ≡ m (mod m ?1), or (ii) b ∈ [2, m ?1], n ≥ b(m ?1) + m ? (b ?1), and n ≡ b(m ?1) + m ? (b ?1) (mod m? 1), then α_m(n) = ?(n + m ?3)/(m ?1)? (= ?(n ?1)/(m ?1)?), and that for every integer n, if K_n has an edge-disjoint complete m-partite subgraph decomposition, then α_m(n) ≥ ?(n? 1)/(m? 1)?. In this paper we generally discuss the question as to which integers n's satisfy (or do not) α_m(n) = ?(n ?1)/(m ?1)?. Here we also study the methods to find these integers; the methods are themselves interesting. Our main results are Theorem 2.11, 2.12, and 2.16. Besides, Theorem 2.4 and 2.6 are interesting results too. © 1993 John Wiley & Sons, Inc.     

Edge disjoint Hamilton cycles in graphs

Let G be a graph of order n and k ≥ 0 an integer. It is conjectured in [8] that if for any two vertices u and v of a 2(k + 1)‐connected graph G,d _G (u,v) = 2 implies that max{d(u;G), d(v;G)} ≥ (n/2) + 2k, then G has k + 1 edge disjoint Hamilton cycles. This conjecture is true for k = 0, 1 (see cf. [3] and [8]). It will be proved in this paper that the conjecture is true for every integer k ≥ 0. © 2000 John Wiley & Sons, Inc. J Graph Theory 35: 8–20, 2000     

The critical behavior of random digraphs

We study the critical behavior of the random digraph D(n,p) for np = 1 + ε, where ε = ε(n) = o(1). We show that if ε³n →—∞, then a.a.s. D(n,p) consists of components which are either isolated vertices or directed cycles, each of size O_p(|ε|^?1). On the other hand, if ε³n →∞, then a.a.s. the structure of D(n,p) is dominated by the unique complex component of size (4 + o(1))ε²n, whereas all other components are of size O_p(ε^?1). © 2009 Wiley Periodicals, Inc. Random Struct. Alg., 2009     

Testing monotonicity over graph products

We consider the problem of monotonicity testing over graph products. Monotonicity testing is one of the central problems studied in the field of property testing. We present a testing approach that enables us to use known monotonicity testers for given graphs G₁, G₂, to test monotonicity over their product G₁ × G₂. Such an approach of reducing monotonicity testing over a graph product to monotonicity testing over the original graphs, has been previously used in the special case of monotonicity testing over [n]^d for a limited type of testers; in this article, we show that this approach can be applied to allow modular design of testers in many interesting cases: this approach works whenever the functions are boolean, and also in certain cases for functions with a general range. We demonstrate the usefulness of our results by showing how a careful use of this approach improves the query complexity of known testers. Specifically, based on our results, we provide a new analysis for the known tester for [n]^d which significantly improves its query complexity analysis in the low‐dimensional case. For example, when d = O(1), we reduce the best known query complexity from O(log ²n/ε) to O(log n/ε). © 2008 Wiley Periodicals, Inc. Random Struct. Alg., 2008     

Vertices of given degree in a random graph

This paper concerns the degree sequence d₁ ≥ d₂ ≥ … ≥ d_n of a randomly labeled graph of order n in which the probability of an edge is p(n) ≦ 1/2. Among other results the following questions are answered. What are the values of p(n) for which d₁, the maximum degree, is the same for almost every graph? For what values of p(n) is it true that d₂ > d₂ for almost every graph, that is, there is a unique vertex of maximum degree? The answers are (essentially) p(n) = o(logn/n/n) and p(n)n/logn → ∞. Also included is a detailed study of the distribution of degrees when 0 < lim n p(n)/log n ≦ lim n p(n)/log n < ∞.     

On cliques and bicliques

For integers m, n ≥ 2, let g(m, n) be the minimum order of a graph, where every vertex belongs to both a clique K_m of order m and a biclique K(n, n). We show that g(m, n) = 2(m + n − 2) if m ≤ n − 2. Furthermore, for m ≥ n − 1, we establish that ≡ 0 mod(n − 1) or, if m is sufficiently large and is not an integer. © 2000 John Wiley & Sons, Inc. J Graph Theory 34: 60–66, 2000     

On stable range conditions

In this paper, we show that a ring R satisfies unit 1-stable range if and only if a₁R + ? + a_mR = dR with m ≥ 2,a ₁, ?a_m ?R implies that there exist u₁ , ?u_m ? U(R) such that a₁u₁ +?+a_mu_m = d and an exchange ring R has stable range one if and only if a₁R+?+a_mR = dR with m ≥ 2,a ₁,?,a_m ? R implies that there exist unit-regular w ₁,?,w_m ? R such that a₁w₁ +?+ a_mw_m = d. Also we show that an exchange ring R satisfies the n-stable range condition if and only if a( ⁿR)+bR = dR with a ? Rⁿ,b,d ? R implies that there exist unimodular regular w ? ⁿ R and: y ? R such that aw+by = d.     

A fast and simple randomized parallel algorithm for the maximal independent set problem

A simple parallel randomized algorithm to find a maximal independent set in a graph G = (V, E) on n vertices is presented. Its expected running time on a concurrent-read concurrent-write PRAM with O(|E|d_max) processors is O(log n), where d_max denotes the maximum degree. On an exclusive-read exclusive-write PRAM with O(|E|) processors the algorithm runs in O(log²n). Previously, an O(log⁴n) deterministic algorithm was given by Karp and Wigderson for the EREW-PRAM model. This was recently (independently of our work) improved to O(log²n) by M. Luby. In both cases randomized algorithms depending on pairwise independent choices were turned into deterministic algorithms. We comment on how randomized combinatorial algorithms whose analysis only depends on d-wise rather than fully independent random choices (for some constant d) can be converted into deterministic algorithms. We apply a technique due to A. Joffe (1974) and obtain deterministic construction in fast parallel time of various combinatorial objects whose existence follows from probabilistic arguments.