On the Power of Las Vegas for One-Way Communication Complexity, OBDDs, and Finite Automata

The study of the computational power of randomized computations is one of the central tasks of complexity theory. The main goal of this paper is the comparison of the power of Las Vegas computation and deterministic respectively nondeterministic computation. We investigate the power of Las Vegas computation for the complexity measures of one-way communication, ordered binary decision diagrams, and finite automata.(i) For the one-way communication complexity of two-party protocols we show that Las Vegas communication can save at most one half of the deterministic one-way communication complexity. We also present a language for which this gap is tight.(ii) The result (i) is applied to show an at most polynomial gap between determinism and Las Vegas for ordered binary decision diagrams.(iii) For the size (i.e., the number of states) of finite automata we show that the size of Las Vegas finite automata recognizing a language L is at least the square root of the size of the minimal deterministic finite automaton recognizing L. Using a specific language we verify the optimality of this lower bound.     

Fast Minor Testing in Planar Graphs

Minor Containment is a fundamental problem in Algorithmic Graph Theory used as a subroutine in numerous graph algorithms. A model of a graph H in a graph G is a set of disjoint connected subgraphs of G indexed by the vertices of H, such that if {u,v} is an edge of H, then there is an edge of G between components C _u and C _v . A graph H is a minor of G if G contains a model of H as a subgraph. We give an algorithm that, given a planar n-vertex graph G and an h-vertex graph H, either finds in time $\mathcal{O}(2^{\mathcal{O}(h)} \cdot n +n^{2}\cdot\log n)$ a model of H in G, or correctly concludes that G does not contain H as a minor. Our algorithm is the first single-exponential algorithm for this problem and improves all previous minor testing algorithms in planar graphs. Our technique is based on a novel approach called partially embedded dynamic programming.     

Production and Emulsifying Effect of Polyglycerol and Fatty Acid Esters with Varying Degrees of Esterification

Esters with acyl groups can be formed by the esterification of polyglycerol. The purpose of the present study was to produce fatty acid esters [hexanoic (caproic), octanoic (caprylic), decanoic (capric), dodecanoic (lauric), tetradecanoic (myristic), hexadecanoic (palmitic), octadecanoic (stearic)] and polyglycerol (average number‐of degrees of polymerization of 5) with varying degrees of esterification and to examine their emulsifying properties. A number of fundamental catalysts of polyglycerol acylation reactions by methyl esters of carboxylic acid were studied, and sodium methoxide was found to be the best choice. The temperature rate of transesterification increased from 180 to 220 °C with the fatty acid chain alkyl residue. Synthesized mono‐, di‐, tri‐, tetra‐, and heptaesters of various fatty acids and polyglycerol provided the highest hydroxyl values from 15 to 815 mg KOH g^?1 and saponification values from 82 to 321 mg KOH g^?1. The emulsifying properties were assessed for all polyglycerol and fatty acid esters, with results showing maximum emulsifying effect for tri‐ and tetraesters of capric, lauric, and caprylic acids. Regardless of the hydrophilic–lipophilic balance value (HLB) of polyglycerol esters and carboxylic acid, a 4:1 ratio of sunflower oil to water formed a water‐in‐oil type emulsion. When mixing oil and water in a 1:1 ratio, mono‐ and diesters of polyglycerol formed an oil‐in‐water type emulsion, heptaesters formed a water‐in‐oil type emulsion, and tri‐ and tetraesters formed both of types of emulsions, depending on the length of the acid hydrocarbon radicals.     

Graph Searching, Elimination Trees, and a Generalization of Bandwidth

The bandwidth minimization problem has a long history and a number of practical applications. In this paper we introduce a natural extension of bandwidth to partially ordered layouts. We consider this extension from three main viewpoints: graph searching, tree decompositions, and elimination orderings. The three graph parameters pathwidth, profile, and bandwidth related to linear layouts can be defined by variants of graph searching using a standard fugitive. Switching to an inert fugitive, the two former parameters are extended to treewidth and fill-in, and our first viewpoint considers the analogous tree-like extension that arises from the bandwidth variant. Bandwidth also has a definition in terms of ordered path decompositions, and our second viewpoint extends this in a natural way to ordered tree decompositions. In showing that both extensions are equivalent we employ the third viewpoint of elimination trees, as used in the field of sparse matrix computations. We call the resulting parameter the treespan of a graph and prove some of its combinatorial and algorithmic properties.     

Approximating minimum cocolorings

A cocoloring of a graph G is a partition of the vertex set of G such that each set of the partition is either a clique or an independent set in G. Some special cases of the minimum cocoloring problem are of particular interest.We provide polynomial-time algorithms to approximate a minimum cocoloring on graphs, partially ordered sets and sequences. In particular, we obtain an efficient algorithm to approximate within a factor of 1.71 a minimum partition of a partially ordered set into chains and antichains, and a minimum partition of a sequence into increasing and decreasing subsequences.     

The Power of Nondeterminism and Randomness for Oblivious Branching Programs

Abstract. This paper abstracts and generalizes the known approaches for proving lower bounds on the size of various variants of oblivious branching programs (oblivious BPs for short), providing an easy-to-use technique which works for all nondeterministic and randomized modes of acceptance. The technique is applied to obtain the following results concerning the power of nondeterminism and randomness for oblivious BPs: <p>— Oblivious read-once BPs, better known as OBDDs (ordered binary decision diagrams), are used in many applications and their structure is well understood in the deterministic case. It has been open so far to compare the power of nondeterministic OBDDs with so-called partitioned BDDs which are a variant of nondeterministic branching programs also used in practice. A k -partitioned BDD has a nondeterministic node at the top by which one out of k deterministic OBDDs with possibly different variable orders is chosen. It is proven here that the two models are incomparable as long as k is bounded by a logarithmic function in the input length. <p>— It is shown that deterministic oblivious read-k -times BPs for an explicitly defined function require superpolynomial size, for k logarithmic in the input length, while there are Las Vegas oblivious read-twice BPs of linear size for this function. This is in contrast to the situation for OBDDs, for which the respective size measures are polynomially related. <p>— Furthermore, an explicitly defined function is presented for which randomized oblivious read-k -times BPs with bounded error require exponential size, while the function as well as its complement can be represented in polynomial size by nondeterministic oblivious read-k -times BPs and deterministic oblivious read-(k+1) -times BPs, where k=o(log n) .     

Computing Optimal Steiner Trees in Polynomial Space

Given an n-node edge-weighted graph and a subset of k terminal nodes, the NP-hard (weighted) Steiner tree problem is to compute a minimum-weight tree which spans the terminals. All the known algorithms for this problem which improve on trivial O(1.62 ⁿ )-time enumeration are based on dynamic programming, and require exponential space. Motivated by the fact that exponential-space algorithms are typically impractical, in this paper we address the problem of designing faster polynomial-space algorithms. Our first contribution is a simple O((27/4) ^k n ^O(logk))-time polynomial-space algorithm for the problem. This algorithm is based on a variant of the classical tree-separator theorem: every Steiner tree has a node whose removal partitions the tree in two forests, containing at most 2k/3 terminals each. Exploiting separators of logarithmic size which evenly partition the terminals, we are able to reduce the running time to $O(4^{k}n^{O(\log^{2} k)})$ . This improves on trivial enumeration for roughly k<n/3, which covers most of the cases of practical interest. Combining the latter algorithm (for small k) with trivial enumeration (for large k) we obtain a O(1.59 ⁿ )-time polynomial-space algorithm for the weighted Steiner tree problem. As a second contribution of this paper, we present a O(1.55 ⁿ )-time polynomial-space algorithm for the cardinality version of the problem, where all edge weights are one. This result is based on a improved branching strategy. The refined branching is based on a charging mechanism which shows that, for large values of k, convenient local configurations of terminals and non-terminals exist. The analysis of the algorithm relies on the Measure & Conquer approach: the non-standard measure used here is a linear combination of the number of nodes and number of non-terminals. Using a recent result in Nederlof (International colloquium on automata, languages and programming (ICALP), pp. 713–725, 2009), the running time can be reduced to O(1.36 ⁿ ). The previous best algorithm for the cardinality case runs in O(1.42 ⁿ ) time and exponential space.