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Search Results: 1 - 10 of 222346 matches for " Christian L. Staudt "
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Engineering Parallel Algorithms for Community Detection in Massive Networks
Christian L. Staudt,Henning Meyerhenke
Computer Science , 2013, DOI: 10.1109/TPDS.2015.2390633
Abstract: The amount of graph-structured data has recently experienced an enormous growth in many applications. To transform such data into useful information, fast analytics algorithms and software tools are necessary. One common graph analytics kernel is disjoint community detection (or graph clustering). Despite extensive research on heuristic solvers for this task, only few parallel codes exist, although parallelism will be necessary to scale to the data volume of real-world applications. We address the deficit in computing capability by a flexible and extensible community detection framework with shared-memory parallelism. Within this framework we design and implement efficient parallel community detection heuristics: A parallel label propagation scheme; the first large-scale parallelization of the well-known Louvain method, as well as an extension of the method adding refinement; and an ensemble scheme combining the above. In extensive experiments driven by the algorithm engineering paradigm, we identify the most successful parameters and combinations of these algorithms. We also compare our implementations with state-of-the-art competitors. The processing rate of our fastest algorithm often reaches 50M edges/second. We recommend the parallel Louvain method and our variant with refinement as both qualitatively strong and fast. Our methods are suitable for massive data sets with billions of edges.
NetworKit: A Tool Suite for Large-scale Complex Network Analysis
Christian L. Staudt,Aleksejs Sazonovs,Henning Meyerhenke
Computer Science , 2014,
Abstract: We introduce NetworKit, an open-source software package for analyzing the structure of large complex networks. Appropriate algorithmic solutions are required to handle increasingly common large graph data sets containing up to billions of connections. We describe the methodology applied to develop scalable solutions to network analysis problems, including techniques like parallelization, heuristics for computationally expensive problems, efficient data structures, and modular software architecture. Our goal for the software is to package results of our algorithm engineering efforts and put them into the hands of domain experts. NetworKit is implemented as a hybrid combining the kernels written in C++ with a Python front end, enabling integration into the Python ecosystem of tested tools for data analysis and scientific computing. The package provides a wide range of functionality (including common and novel analytics algorithms and graph generators) and does so via a convenient interface. In an experimental comparison with related software, NetworKit shows the best performance on a range of typical analysis tasks.
Approximating Betweenness Centrality in Large Evolving Networks
Elisabetta Bergamini,Henning Meyerhenke,Christian L. Staudt
Computer Science , 2014,
Abstract: Betweenness centrality ranks the importance of nodes by their participation in all shortest paths of the network. Therefore computing exact betweenness values is impractical in large networks. For static networks, approximation based on randomly sampled paths has been shown to be significantly faster in practice. However, for dynamic networks, no approximation algorithm for betweenness centrality is known that improves on static recomputation. We address this deficit by proposing two incremental approximation algorithms (for weighted and unweighted connected graphs) which provide a provable guarantee on the absolute approximation error. Processing batches of edge insertions, our algorithms yield significant speedups up to a factor of $10^4$ compared to restarting the approximation. This is enabled by investing memory to store and efficiently update shortest paths. As a building block, we also propose an asymptotically faster algorithm for updating the SSSP problem in unweighted graphs. Our experimental study shows that our algorithms are the first to make in-memory computation of a betweenness ranking practical for million-edge semi-dynamic networks. Moreover, our results show that the accuracy is even better than the theoretical guarantees in terms of absolutes errors and the rank of nodes is well preserved, in particular for those with high betweenness.
Fast generation of complex networks with underlying hyperbolic geometry
Moritz von Looz,Christian L. Staudt,Henning Meyerhenke,Roman Prutkin
Computer Science , 2015,
Abstract: Complex networks have become increasingly popular for modeling various real-world phenomena. Realistic generative network models are important in this context as they avoid privacy concerns of real data and simplify complex network research regarding data sharing, reproducibility, and scalability studies. \emph{Random hyperbolic graphs} are a well-analyzed family of geometric graphs. Previous work provided empirical and theoretical evidence that this generative graph model creates networks with non-vanishing clustering and other realistic features. However, the investigated networks in previous applied work were small, possibly due to the quadratic running time of a previous generator. In this work we provide the first generation algorithm for these networks with subquadratic running time. We prove a time complexity of $O((n^{3/2}+m) \log n)$ with high probability for the generation process. This running time is confirmed by experimental data with our implementation. The acceleration stems primarily from the reduction of pairwise distance computations through a polar quadtree, which we adapt to hyperbolic space for this purpose. In practice we improve the running time of a previous implementation by at least two orders of magnitude this way. Networks with billions of edges can now be generated in a few minutes. Finally, we evaluate the largest networks of this model published so far. Our empirical analysis shows that important features are retained over different graph densities and degree distributions.
Structure-Preserving Sparsification of Social Networks
Gerd Lindner,Christian L. Staudt,Michael Hamann,Henning Meyerhenke,Dorothea Wagner
Computer Science , 2015,
Abstract: Sparsification reduces the size of networks while preserving structural and statistical properties of interest. Various sparsifying algorithms have been proposed in different contexts. We contribute the first systematic conceptual and experimental comparison of \textit{edge sparsification} methods on a diverse set of network properties. It is shown that they can be understood as methods for rating edges by importance and then filtering globally by these scores. In addition, we propose a new sparsification method (\textit{Local Degree}) which preserves edges leading to local hub nodes. All methods are evaluated on a set of 100 Facebook social networks with respect to network properties including diameter, connected components, community structure, and multiple node centrality measures. Experiments with our implementations of the sparsification methods (using the open-source network analysis tool suite NetworKit) show that many network properties can be preserved down to about 20\% of the original set of edges. Furthermore, the experimental results allow us to differentiate the behavior of different methods and show which method is suitable with respect to which property. Our Local Degree method is fast enough for large-scale networks and performs well across a wider range of properties than previously proposed methods.
Monoterpene and sesquiterpene emissions from Quercus coccifera exhibit interacting responses to light and temperature
M. Staudt,L. Lhoutellier
Biogeosciences (BG) & Discussions (BGD) , 2011,
Abstract: Light and temperature are known to be the most important environmental factors controlling biogenic volatile organic compound (BVOC) emissions from plants, but little is known about their interdependencies especially for BVOCs other than isoprene. We studied light responses at different temperatures and temperature responses at different light levels of foliar BVOC emissions, photosynthesis and chlorophyll fluorescence on Quercus coccifera, an evergreen oak widespread in Mediterranean shrublands. More than 50 BVOCs were detected in the emissions from Q. coccifera leaves most of them being isoprenoids plus a few green leaf volatiles (GLVs). Under standard conditions non-oxygenated monoterpenes (MT-hc) accounted for about 90% of the total BVOC release (mean ± SD: 738 ± 378 ng m 2 projected leaf area s 1 or 13.1 ± 6.9 μg g 1 leaf dry weight h 1) and oxygenated monoterpenes (MT-ox) and sesquiterpenes (SQTs) accounted for the rest in about equal proportions. Except GLVs, emissions of all BVOCs responded positively to light and temperature. The light responses of MT and SQT emissions resembled that of CO2-assimilation and were little influenced by the assay temperature: at high assay temperature, MT-hc emissions saturated at lower light levels than at standard assay temperature and tended even to decrease in the highest light range. The emission responses to temperature showed mostly Arrhenius-type response curves, whose shapes in the high temperature range were clearly affected by the assay light level and were markedly different between isoprenoid classes: at non-saturating light, all isoprenoids showed a similar temperature optimum (~43 °C), but, at higher temperatures, MT-hc emissions decreased faster than MT-ox and SQT emissions. At saturating light, MT-hc emissions peaked around 37 °C and rapidly dropped at higher temperatures, whereas MT-ox and SQT emissions strongly increased between 40 and 50 °C accompanied by a burst of GLVs. In all experiments, decreases of MT-hc emissions under high temperatures were correlated with decreases in CO2-assimilation and/or photosynthetic electron transport. We conclude that light and temperature can have interactive short-term effects on the quantity and quality of BVOC emissions from Q. coccifera through substrate limitations of MT biosynthesis occurring at temperatures supraoptimal for photosynthetic processes that are exacerbated by oxidative stress and membrane damages. Such interactive effects are likely to occur frequently during hot and dry summers and simulations made in this work showed that they may have important consequences for emission predictions.
Monoterpene and sesquiterpene emissions from Quercus coccifera exhibit interacting responses to light and temperature
M. Staudt,L. Lhoutellier
Biogeosciences (BG) & Discussions (BGD) , 2011, DOI: 10.5194/bg-8-2757-2011
Abstract: Light and temperature are known to be the most important environmental factors controlling biogenic volatile organic compound (BVOC) emissions from plants, but little is known about their interdependencies especially for BVOCs other than isoprene. We studied light responses at different temperatures and temperature responses at different light levels of foliar BVOC emissions, photosynthesis and chlorophyll fluorescence on Quercus coccifera, an evergreen oak widespread in Mediterranean shrublands. More than 50 BVOCs were detected in the emissions from Q. coccifera leaves most of them being isoprenoids plus a few green leaf volatiles (GLVs). Under standard conditions non-oxygenated monoterpenes (MT-hc) accounted for about 90% of the total BVOC release (mean ± SD: 738 ± 378 ng m 2 projected leaf area s 1 or 13.1 ± 6.9 μg g 1 leaf dry weight h 1) and oxygenated monoterpenes (MT-ox) and sesquiterpenes (SQTs) accounted for the rest in about equal proportions. Except GLVs, emissions of all BVOCs responded positively to light and temperature. The light responses of MT and SQT emissions resembled that of CO2-assimilation and were little influenced by the assay temperature: at high assay temperature, MT-hc emissions saturated at lower light levels than at standard assay temperature and tended even to decrease in the highest light range. The emission responses to temperature showed mostly Arrhenius-type response curves, whose shapes in the high temperature range were clearly affected by the assay light level and were markedly different between isoprenoid classes: at non-saturating light, all isoprenoids showed a similar temperature optimum (~43 °C), but, at higher temperatures, MT-hc emissions decreased faster than MT-ox and SQT emissions. At saturating light, MT-hc emissions peaked around 37 °C and rapidly dropped at higher temperatures, whereas MT-ox and SQT emissions strongly increased between 40 and 50 °C accompanied by a burst of GLVs. In all experiments, decreases of MT-hc emissions under high temperatures were correlated with decreases in CO2-assimilation and/or photosynthetic electron transport. We conclude that light and temperature can have interactive short-term effects on the quantity and quality of BVOC emissions from Q. coccifera through substrate limitations of MT biosynthesis occurring at temperatures supraoptimal for photosynthetic processes that are exacerbated by oxidative stress and membrane damages. Such interactive effects are likely to occur frequently during hot and dry summers and simulations made in this work showed that they may have imp
Monoterpene and sesquiterpene emissions from Quercus coccifera exhibit interacting responses to light and temperature
M. Staudt,L. Lhoutellier
Biogeosciences Discussions , 2011, DOI: 10.5194/bgd-8-5691-2011
Abstract: Light and temperature are known to be the most important environmental factors controlling biogenic volatile organic compound (BVOC) emissions from plants, but little is known about their interdependencies especially for BVOCs other than isoprene. We studied light responses at different temperatures and temperature responses at different light levels of foliar BVOC emissions, photosynthesis and chlorophyll fluorescence on Quercus coccifera, an evergreen oak widespread in Mediterranean shrublands. More than 50 BVOCs were detected in the emissions from Q. coccifera leaves most of them being isoprenoids plus a few green leaf volatiles (GLVs). Under standard conditions non-oxygenated monoterpenes (MT-hc) accounted for about 90 % of the total BVOC release (mean ± SD: 738 ± 378 ng m 2 projected leaf area s 1 or 13.1 ± 6.9 μg g 1 leaf dry weight h 1) and oxygenated monoterpenes (MT-ox) and sesquiterpenes (SQTs) accounted for the rest in about equal proportions. Except GLVs, emissions of all BVOCs responded positively to light and temperature. The light responses of MT and SQT emissions resembled that of CO2-assimilation and were little influenced by the assay temperature: at high assay temperature, MT-hc emissions saturated at lower light levels than at standard assay temperature and tended even to decrease in the highest light range. The emission responses to temperature showed mostly Arrhenius-type response curves, whose shapes in the high temperature range were clearly affected by the assay light level and were markedly different between isoprenoid classes: at non-saturating light, all isoprenoids showed a similar temperature optimum (~43 °C), but, at higher temperatures, MT-hc emissions decreased faster than MT-ox and SQT emissions. At saturating light, MT-hc emissions peaked already around 37 °C and rapidly dropped at higher temperatures, whereas MT-ox and SQT emissions strongly increased between 40 and 50 °C accompanied by a burst of GLVs. In all experiments, decreases of MT-hc emissions under high temperatures were correlated with decreases in CO2-assimilation and/or photosynthetic electron transport. We conclude that light and temperature can have interactive short-term effects on the quantity and quality of BVOC emissions from Q. coccifera through substrate limitations of MT biosynthesis occurring at temperatures supraoptimal for photosynthetic processes that are exacerbated by oxidative stress and membrane damages. Such interactive effects are likely to occur frequently during hot and dry summers and simulations made in this work showed that they may
Moisture harvesting and water transport through specialized micro-structures on the integument of lizards
Philipp Comanns,Christian Effertz,Florian Hischen,Konrad Staudt
Beilstein Journal of Nanotechnology , 2011, DOI: 10.3762/bjnano.2.24
Abstract: Several lizard species that live in arid areas have developed special abilities to collect water with their bodies' surfaces and to ingest the so collected moisture. This is called rain- or moisture-harvesting. The water can originate from air humidity, fog, dew, rain or even from humid soil. The integument (i.e., the skin plus skin derivatives such as scales) has developed features so that the water spreads and is soaked into a capillary system in between the reptiles' scales. Within this capillary system the water is transported to the mouth where it is ingested. We have investigated three different lizard species which have developed the ability for moisture harvesting independently, viz. the Australian thorny devil (Moloch horridus), the Arabian toadhead agama (Phrynocephalus arabicus) and the Texas horned lizard (Phrynosoma cornutum). All three lizards have a honeycomb like micro ornamentation on the outer surface of the scales and a complex capillary system in between the scales. By investigation of individual scales and by producing and characterising polymer replicas of the reptiles' integuments, we found that the honeycomb like structures render the surface superhydrophilic, most likely by holding a water film physically stable. Furthermore, the condensation of air humidity is improved on this surface by about 100% in comparison to unstructured surfaces. This allows the animals to collect moisture with their entire body surface. The collected water is transported into the capillary system. For Phrynosoma cornutum we found the interesting effect that, in contrast to the other two investigated species, the water flow in the capillary system is not uniform but directed to the mouth. Taken together we found that the micro ornamentation yields a superhydrophilic surface, and the semi-tubular capillaries allow for an efficient passive – and for Phrynosoma directed – transport of water.
Predictivity of models with spontaneously broken non-Abelian discrete flavor symmetries
Chen, Mu-Chun;Fallbacher, Maximilian;Omura, Yuji;Ratz, Michael;Staudt, Christian
High Energy Physics - Phenomenology , 2013,
Abstract: In a class of supersymmetric flavor models predictions are based on residual symmetries of some subsectors of the theory such as those of the charged leptons and neutrinos. However, the vacuum expectation values of the so-called flavon fields generally modify the K\"ahler potential of the setting, thus changing the predictions. We derive simple analytic formulae that allow us to understand the impact of these corrections on the predictions for the masses and mixing parameters. Furthermore, we discuss the effects on the vacuum alignment and on flavor changing neutral currents. Our results can also be applied to non--supersymmetric flavor models.
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