381 research outputs found
Event Stream Processing with Multiple Threads
Current runtime verification tools seldom make use of multi-threading to
speed up the evaluation of a property on a large event trace. In this paper, we
present an extension to the BeepBeep 3 event stream engine that allows the use
of multiple threads during the evaluation of a query. Various parallelization
strategies are presented and described on simple examples. The implementation
of these strategies is then evaluated empirically on a sample of problems.
Compared to the previous, single-threaded version of the BeepBeep engine, the
allocation of just a few threads to specific portions of a query provides
dramatic improvement in terms of running time
Parallel Evaluation of Multi-join Queries
A number of execution strategies for parallel evaluation of multi-join queries have been proposed in the literature. In this paper we give a comparative performance evaluation of four execution strategies by implementing all of them on the same parallel database system, PRISMA/DB. Experiments have been done up to 80 processors. These strategies, coming from the literature, are named: Sequential Parallel, Synchronous Execution, Segmented Right-Deep, and Full Parallel. Based on the experiments clear guidelines are given when to use which strategy.
This is an extended abstract; the full paper appeared in Proc. ACM SIGMOD'94, Minneapolis, Minnesota, May 24–27, 199
On analog quantum algorithms for the mixing of Markov chains
The problem of sampling from the stationary distribution of a Markov chain
finds widespread applications in a variety of fields. The time required for a
Markov chain to converge to its stationary distribution is known as the
classical mixing time. In this article, we deal with analog quantum algorithms
for mixing. First, we provide an analog quantum algorithm that given a Markov
chain, allows us to sample from its stationary distribution in a time that
scales as the sum of the square root of the classical mixing time and the
square root of the classical hitting time. Our algorithm makes use of the
framework of interpolated quantum walks and relies on Hamiltonian evolution in
conjunction with von Neumann measurements.
There also exists a different notion for quantum mixing: the problem of
sampling from the limiting distribution of quantum walks, defined in a
time-averaged sense. In this scenario, the quantum mixing time is defined as
the time required to sample from a distribution that is close to this limiting
distribution. Recently we provided an upper bound on the quantum mixing time
for Erd\"os-Renyi random graphs [Phys. Rev. Lett. 124, 050501 (2020)]. Here, we
also extend and expand upon our findings therein. Namely, we provide an
intuitive understanding of the state-of-the-art random matrix theory tools used
to derive our results. In particular, for our analysis we require information
about macroscopic, mesoscopic and microscopic statistics of eigenvalues of
random matrices which we highlight here. Furthermore, we provide numerical
simulations that corroborate our analytical findings and extend this notion of
mixing from simple graphs to any ergodic, reversible, Markov chain.Comment: The section concerning time-averaged mixing (Sec VIII) has been
updated: Now contains numerical plots and an intuitive discussion on the
random matrix theory results used to derive the results of arXiv:2001.0630
A Unified Framework of Quantum Walk Search
The main results on quantum walk search are scattered over different, incomparable frameworks, most notably the hitting time framework, originally by Szegedy, the electric network framework by Belovs, and the MNRS framework by Magniez, Nayak, Roland and Santha. As a result, a number of pieces are currently missing. For instance, the electric network framework allows quantum walks to start from an arbitrary initial state, but it only detects marked elements. In recent work by Ambainis et al., this problem was resolved for the more restricted hitting time framework, in which quantum walks must start from the stationary distribution.
We present a new quantum walk search framework that unifies and strengthens these frameworks. This leads to a number of new results. For instance, the new framework not only detects, but finds marked elements in the electric network setting. The new framework also allows one to interpolate between the hitting time framework, which minimizes the number of walk steps, and the MNRS framework, which minimizes the number of times elements are checked for being marked. This allows for a more natural tradeoff between resources. Whereas the original frameworks only rely on quantum walks and phase estimation, our new algorithm makes use of a technique called quantum fast-forwarding, similar to the recent results by Ambainis et al. As a final result we show how in certain cases we can simplify this more involved algorithm to merely applying the quantum walk operator some number of times. This answers an open question of Ambainis et al
Quantum complexity of minimum cut
The minimum cut problem in an undirected and weighted graph G is to find the minimum total weight of a set of edges whose removal disconnects G. We completely characterize the quantum query and time complexity of the minimum cut problem in the adjacency matrix model. If G has n vertices and edge weights at least 1 and at most τ, we give a quantum algorithm to solve the minimum cut problem using Õ(n3/2√τ) queries and time. Moreover, for every integer 1 ≤ τ ≤ n we give an example of a graph G with edge weights 1 and τ such that solving the minimum cut problem on G requires Ω(n3/2√τ) queries to the adjacency matrix of G. These results contrast with the classical randomized case where Ω(n2) queries to the adjacency matrix are needed in the worst case even to decide if an unweighted graph is connected or not. In the adjacency array model, when G has m edges the classical randomized complexity of the minimum cut problem is Θ̃(m). We show that the quantum query and time complexity are Õ(√mnτ) and Õ(√mnτ + n3/2), respectively, where again the edge weights are between 1 and τ. For dense graphs we give lower bounds on the quantum query complexity of Ω(n3/2) for τ > 1 and Ω(τn) for any 1 ≤ τ ≤ n. Our query algorithm uses a quantum algorithm for graph sparsification by Apers and de Wolf (FOCS 2020) and results on the structure of near-minimum cuts by Kawarabayashi and Thorup (STOC 2015) and Rubinstein, Schramm and Weinberg (ITCS 2018). Our time efficient implementation builds on Karger's tree packing technique (STOC 1996)
Contracting Public Transport Infrastructure: Recent experience with the Dutch High Speed Line and the Amsterdam North-South Metro Line
Institute of Transport and Logistics Studies. Faculty of Economics and Business. The University of Sydne
Finding the KT partition of a weighted graph in near-linear time
In a breakthrough work, Kawarabayashi and Thorup (J.~ACM'19) gave a
near-linear time deterministic algorithm for minimum cut in a simple graph . A key component is finding the -KT partition of ,
the coarsest partition of such that for every
non-trivial -near minimum cut with sides it
holds that is contained in either or , for .
Here we give a near-linear time randomized algorithm to find the
-KT partition of a weighted graph. Our algorithm is quite
different from that of Kawarabayashi and Thorup and builds on Karger's
framework of tree-respecting cuts (J.~ACM'00).
We describe applications of the algorithm. (i) The algorithm makes progress
towards a more efficient algorithm for constructing the polygon representation
of the set of near-minimum cuts in a graph. This is a generalization of the
cactus representation initially described by Bencz\'ur (FOCS'95). (ii) We
improve the time complexity of a recent quantum algorithm for minimum cut in a
simple graph in the adjacency list model from to
. (iii) We describe a new type of randomized algorithm
for minimum cut in simple graphs with complexity . For
slightly dense graphs this matches the complexity of the current best algorithm which uses a different approach based on random
contractions.
The key technical contribution of our work is the following. Given a weighted
graph with edges and a spanning tree , consider the graph whose
nodes are the edges of , and where there is an edge between two nodes of
iff the corresponding 2-respecting cut of is a non-trivial near-minimum cut
of . We give a time deterministic algorithm to compute a
spanning forest of
A sublinear time quantum algorithm for s-t minimum cut on dense simple graphs
An minimum cut in a graph corresponds to a minimum
weight subset of edges whose removal disconnects vertices and . Finding
such a cut is a classic problem that is dual to that of finding a maximum flow
from to . In this work we describe a quantum algorithm for the minimum
cut problem on undirected graphs. For an undirected
graph with vertices, edges, and integral edge weights bounded by ,
the algorithm computes with high probability the weight of a minimum
cut in time , given adjacency list access to . For simple graphs this
bound is always , even in the dense case when . In contrast, a randomized algorithm must make queries
to the adjacency list of a simple graph even to decide whether and
are connected
Influence of sense of coherence on adolescents' self-perceived dental aesthetics:a cross-sectional study
Background
Sense of coherence (SOC) is a psychosocial factor capable of influencing perception of health, improving one’s ability to manage life. It is the central construct of salutogenesis. SOC allows for identification and mobilization of resources to effectively manage or solve problems, promoting health and quality of life. Using Wilson-Cleary’s conceptual model we hypothesized that SOC might contribute to self-perception of dental aesthetics. The aim of this study was to investigate whether SOC levels were related to self-perception of dental aesthetics against assessed normative orthodontic treatment need among adolescents.
Methods
A cross-sectional study was conducted with 615 male and female adolescents aged 12 to 15 years. Data collection comprised socio-demographic and socio-economic characteristics, SOC (SOC 13), self-perceived dental aesthetics (Oral Aesthetic Subjective Impact Scale), and assessment of orthodontic treatment need (Dental Aesthetic Index). Statistical analysis involved Pearson’s chi-square test, Kruskal-Wallis test, Mann-Whitney test and multiple linear regression. Spearman’s correlation coefficient was calculated for the determination of the strength of correlations among the numerical variables. The level of significance was set at 5% (p < 0.05).
Results
50.1% of the participants were classified as having a high SOC (≥ median). Overall, SOC was associated with self-perceived dental aesthetics (p = 0.048). In the adolescents with no orthodontic treatment need, those with a low SOC perceived their dental aesthetics more negatively than those with high levels of SOC. The multiple regression analysis demonstrated an inverse relationship between SOC and: 1) age (p = 0.007), SOC being higher in the younger age group; 2) self-perceived dental aesthetics (p = 0.001), a higher SOC being associated with those who had a positive dental self-perception.
Conclusions
SOC was associated with self-perceived dental aesthetics and adolescents with a high SOC were more likely to perceive their dental aesthetics more positively. SOC did not seem to influence self-perception of dental aesthetics in adolescents who were clinically assessed as having an orthodontic treatment need, however, in those where there was no orthodontic treatment need, a low SOC was associated with a negative self-perception of dental appearance
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