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Philippe Flajolet, mathematician and computer scientist extraordinaire, the father of analytic combinatorics, suddenly passed away on 22 March 2011, at the prime of his career. He is celebrated for opening new lines of research in the analysis of algorithms, developing powerful new methods, and solving difficult open problems. His research contributions will have an impact for generations, and his approach to research, based on curiosity, discriminating taste, broad knowledge and interests, intellectual integrity, and a genuine sense of camaraderie, will serve as an inspiration to those who knew him, for years to come.
A set of reals A = {a1,. . .,an} is called convex if ai+1 − ai > ai − ai−1 for all i. We prove, among other results, that for some c > 0 every convex A satisfies |A−A| ≥ c|A|8/5log−2/5|A|.
A unit disk graph is the intersection graphof a family of unit disks in the plane.If the disks do not overlap, it is also a unit coin graph or penny graph.It is known that finding a maximum independent setin a unit disk graph is a NP-hard problem.In this work we extend this result to penny graphs.Furthermore, we prove that finding a minimum clique partitionin a penny graph is also NP-hard, and presenttwo linear-time approximation algorithms for the computation of clique partitions:a 3-approximation algorithm for unit disk graphsand a 2-approximation algorithm for penny graphs.
We prove that the Fibonacci morphism is an automorphism of infinite order of free Burnside groups for all odd $n\geq 665$ and even $n = 16k \geq 8000$.
Since recognizable tree languages are closed under the rational operations, every regular tree expression denotes a recognizable tree language. We provide an alternative proof to this fact that results in smaller tree automata. To this aim, we transfer Antimirov's partial derivatives from regular word expressions to regular tree expressions. For an analysis of the size of the resulting automaton as well as for algorithmic improvements, we also transfer the methods of Champarnaud and Ziadi from words to trees.
Motivated by striking properties of the well known Fibonacci wordwe consider pictures which are defined by this word and itsvariants via so-called turtle graphics. Such a picture can bebounded or unbounded. We characterize when the picture defined bynot only the Fibonacci recurrence, but also by a generalrecurrence formula, is bounded, the characterization beingcomputable.
In the last decade, formal methods have proved their interest whenanalyzing security protocols. Security protocols require inparticular to reason about the attacker knowledge. Two standardnotions are often considered in formal approaches: deducibility andindistinguishability relations. The first notion states whether anattacker can learn the value of a secret, while the latter stateswhether an attacker can notice some difference between protocol runswith different values of the secret. Several decision procedureshave been developed so far for both notions but none of them can beapplied in the context of e-voting protocols, which requirededicated cryptographic primitives. In this work, we show that bothdeduction and indistinguishability are decidable in polynomial timefor two theories modeling the primitives of e-voting protocols.
The tools of zero biasing are adapted to yield a general result suitable for analysing the behaviour of certain growth processes. The main theorem is applied to prove a central limit theorem, with explicit error terms in the L1 metric, for a natural statistic of the Jack measure on partitions.
An old result by Shearer relates the Lovász local lemma with the independent set polynomial on graphs, and consequently, as observed by Scott and Sokal, with the partition function of the hard-core lattice gas on graphs. We use this connection and a recent result on the analyticity of the logarithm of the partition function of the abstract polymer gas to get an improved version of the Lovász local lemma. As an application we obtain tighter bounds on conditions for the existence of Latin transversal matrices.
Let Δ ≥ 3 be an integer. Given a fixed z ∈ +Δ such that zΔ > 0, we consider a graph Gz drawn uniformly at random from the collection of graphs with zin vertices of degree i for i = 1,. . .,Δ. We study the performance of the Karp–Sipser algorithm when applied to Gz. If there is an index δ > 1 such that z1 = . . . = zδ−1 = 0 and δzδ,. . .,ΔzΔ is a log-concave sequence of positive reals, then with high probability the Karp–Sipser algorithm succeeds in finding a matching with n ∥ z ∥ 1/2 − o(n1−ε) edges in Gz, where ε = ε (Δ, z) is a constant.
In this paper we explore first passage percolation (FPP) on the Erdős–Rényi random graph Gn(pn), where we assign independent random weights, having an exponential distribution with rate 1, to the edges. In the sparse regime, i.e., when npn → λ > 1, we find refined asymptotics both for the minimal weight of the path between uniformly chosen vertices in the giant component, as well as for the hopcount (i.e., the number of edges) on this minimal weight path. More precisely, we prove a central limit theorem for the hopcount, with asymptotic mean and variance both equal to (λ log n)/(λ − 1). Furthermore, we prove that the minimal weight centred by (log n)/(λ − 1) converges in distribution.
We also investigate the dense regime, where npn → ∞. We find that although the base graph is ultra-small (meaning that graph distances between uniformly chosen vertices are o(log n)), attaching random edge weights changes the geometry of the network completely. Indeed, the hopcount Hn satisfies the universality property that whatever the value of pn, Hn/log n → 1 in probability and, more precisely, (Hn − βn log n)/, where βn = λn/(λn − 1), has a limiting standard normal distribution. The constant βn can be replaced by 1 precisely when λn ≫ , a case that has appeared in the literature (under stronger conditions on λn) in [4, 13]. We also find lower bounds for the maximum, over all pairs of vertices, of the optimal weight and hopcount.
This paper continues the investigation of FPP initiated in [4] and [5]. Compared to the setting on the configuration model studied in [5], the proofs presented here are much simpler due to a direct relation between FPP on the Erdős–Rényi random graph and thinned continuous-time branching processes.
The classical Erdős–Pósa theorem states that for each positive integer k there is an f(k) such that, in each graph G which does not have k + 1 disjoint cycles, there is a blocker of size at most f(k); that is, a set B of at most f(k) vertices such that G−B has no cycles. We show that, amongst all such graphs on vertex set {1,. . .,n}, all but an exponentially small proportion have a blocker of size k. We also give further properties of a random graph sampled uniformly from this class, concerning uniqueness of the blocker, connectivity, chromatic number and clique number.
A key step in the proof of the main theorem is to show that there must be a blocker as in the Erdős–Pósa theorem with the extra ‘redundancy’ property that B–v is still a blocker for all but at most k vertices v ∈ B.
Games provide mathematical models for interaction. Numerous tasks in computer science can be formulated in game-theoretic terms. This fresh and intuitive way of thinking through complex issues reveals underlying algorithmic questions and clarifies the relationships between different domains. This collection of lectures, by specialists in the field, provides an excellent introduction to various aspects of game theory relevant for applications in computer science that concern program design, synthesis, verification, testing and design of multi-agent or distributed systems. Originally devised for a Spring School organised by the GAMES Networking Programme in 2009, these lectures have since been revised and expanded, and range from tutorials concerning fundamental notions and methods to more advanced presentations of current research topics. This volume is a valuable guide to current research on game-based methods in computer science for undergraduate and graduate students. It will also interest researchers working in mathematical logic, computer science and game theory.
We prove that the maximum degree Δn of a random series-parallel graph with n vertices satisfies Δn/logn → c in probability, and Δn ~ c logn for a computable constant c > 0. The same kind of result holds for 2-connected series-parallel graphs, for outerplanar graphs, and for 2-connected outerplanar graphs.
Let G be a graph with m edges, and let k be a positive integer. We show that V(G) admits a k-partition V1, . . . Vk such that for i ∈ {1, 2, . . . k}, and , where e(Vi) denotes the number of edges with both ends in Vi and . This answers a problem of Bollobás and Scott [2] in the affirmative. Moreover, for i ∈ {1, 2, . . ., k}, which is close to being best possible and settles another problem of Bollobás and Scott [2].
Dynamic programming is a standard technique in algorithm design in which an optimal solution for a problem is built up from optimal solutions for a number of subproblems, normally stored in a table or multidimensional array. Approximation algorithms can be designed using dynamic programming in a variety of ways, many of which involve rounding the input data in some way.
For instance, sometimes weakly NP-hard problems have dynamic programming algorithms that run in time polynomial in the input size if the input is represented in unary rather than in binary (so, for example, the number 7 would be encoded as 1111111). If so, we say that the algorithm is pseudopolynomial. Then by rounding the input values so that the number of distinct values is polynomial in the input size and an error parameter ε > 0, this pseudopolynomial algorithm can be made to run in time polynomial in the size of the original instance. We can often show that the rounding does not sacrifice too much in the quality of the solution produced. We will use this technique in discussing the knapsack problem in Section 3.1.
For other problems, such as scheduling problems, we can often make distinctions between “large” and “small” parts of the input instance; for instance, in scheduling problems, we distinguish between jobs that have large and small processing times. We can then show that by rounding the sizes of the large inputs so that, again, the number of distinct, large input values is polynomial in the input size and an error parameter, we can use dynamic programming to find an optimal solution on just the large inputs.