2,226 research outputs found

    Coarse Graining for Synchronization in Directed Networks

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    Coarse graining model is a promising way to analyze and visualize large-scale networks. The coarse-grained networks are required to preserve the same statistical properties as well as the dynamic behaviors as the initial networks. Some methods have been proposed and found effective in undirected networks, while the study on coarse graining in directed networks lacks of consideration. In this paper, we proposed a Topology-aware Coarse Graining (TCG) method to coarse grain the directed networks. Performing the linear stability analysis of synchronization and numerical simulation of the Kuramoto model on four kinds of directed networks, including tree-like networks and variants of Barab\'{a}si-Albert networks, Watts-Strogatz networks and Erd\"{o}s-R\'{e}nyi networks, we find our method can effectively preserve the network synchronizability.Comment: 9 pages, 7 figure

    Significance analysis and statistical mechanics: an application to clustering

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    This paper addresses the statistical significance of structures in random data: Given a set of vectors and a measure of mutual similarity, how likely does a subset of these vectors form a cluster with enhanced similarity among its elements? The computation of this cluster p-value for randomly distributed vectors is mapped onto a well-defined problem of statistical mechanics. We solve this problem analytically, establishing a connection between the physics of quenched disorder and multiple testing statistics in clustering and related problems. In an application to gene expression data, we find a remarkable link between the statistical significance of a cluster and the functional relationships between its genes.Comment: to appear in Phys. Rev. Let

    A New Approach to Time Domain Classification of Broadband Noise in Gravitational Wave Data

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    Broadband noise in gravitational wave (GW) detectors, also known as triggers, can often be a deterrant to the efficiency with which astrophysical search pipelines detect sources. It is important to understand their instrumental or environmental origin so that they could be eliminated or accounted for in the data. Since the number of triggers is large, data mining approaches such as clustering and classification are useful tools for this task. Classification of triggers based on a handful of discrete properties has been done in the past. A rich information content is available in the waveform or 'shape' of the triggers that has had a rather restricted exploration so far. This paper presents a new way to classify triggers deriving information from both trigger waveforms as well as their discrete physical properties using a sequential combination of the Longest Common Sub-Sequence (LCSS) and LCSS coupled with Fast Time Series Evaluation (FTSE) for waveform classification and the multidimensional hierarchical classification (MHC) analysis for the grouping based on physical properties. A generalized k-means algorithm is used with the LCSS (and LCSS+FTSE) for clustering the triggers using a validity measure to determine the correct number of clusters in absence of any prior knowledge. The results have been demonstrated by simulations and by application to a segment of real LIGO data from the sixth science run.Comment: 16 pages, 16 figure

    Exploring The Frequency Of Close-In Jovian Planets Around M Dwarfs

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    We discuss our high precision radial velocity results of a sample of 90 M dwarfs observed with the Hobby-Eberly Telescope and the Harlan J. Smith 2.7 m Telescope at McDonald Observatory, as well as the ESO VLT and the Keck I telescopes, within the context of the overall frequency of Jupiter-mass planetary companions to main sequence stars. None of the stars in our sample show variability indicative of a giant planet in a short period orbit, with a 3.8 M_Jup and a 3.5 M_Jup and a < 0.7 AU. Our results point toward a generally lower frequency of close-in Jovian planets for M dwarfs as compared to FGK-type stars. This is an important piece of information for our understanding of the process of planet formation as a function of stellar mass

    Seven Years of SN 2014C: A Multiwavelength Synthesis of an Extraordinary Supernova

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    SN 2014C was originally classified as a Type Ib supernova, but at phase ϕ = 127 days, post-explosion strong Hα emission was observed. SN 2014C has since been observed in radio, infrared, optical and X-ray bands. Here we present new optical spectroscopic and photometric data spanning ϕ = 947–2494 days post-explosion. We address the evolution of the broadened Hα emission line, as well as broad [O iii] emission and other lines. We also conduct a parallel analysis of all publicly available multiwavelength data. From our spectra, we find a nearly constant Hα FWHM velocity width of ∼2000 km s−1 that is significantly lower than that of other broadened atomic transitions (∼3000–7000 km s−1) present in our spectra ([O i] λ6300; [O iii] λλ4959, 5007; He i λ7065; [Ca ii] λλ7291, 7324). The late radio data demand a fast forward shock (∼10,000 km s−1 at ϕ = 1700 days) in rarified matter that contrasts with the modest velocity of the Hα. We propose that the infrared flux originates from a toroidal-like structure of hydrogen surrounding the progenitor system, while later emission at other wavelengths (radio, X-ray) likely originates predominantly from the reverse shock in the ejecta and the forward shock in the quasi-spherical progenitor He-wind. We propose that the Hα emission arises in the boundary layer between the ejecta and torus. We also consider the possible roles of a pulsar and a binary companion

    Maintenance treatment of adolescent bipolar disorder: open study of the effectiveness and tolerability of quetiapine

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    <p>Abstract</p> <p>Background</p> <p>The purpose of the study was to determine the effectiveness and tolerability of quetiapine as a maintenance treatment preventing against relapse or recurrence of acute mood episodes in adolescent patients diagnosed with bipolar disorder.</p> <p>Methods</p> <p>Consenting patients meeting DSM-IV lifetime criteria for a bipolar disorder and clinically appropriate for maintenance treatment were enrolled in a 48-week open prospective study. After being acutely stabilized (CGI-S ≤ 3 for 4 consecutive weeks), patients were started or continued on quetiapine and other medications were weaned off over an 8-week period. Quetiapine monotherapy was continued for 40-weeks and other mood stabilizers or antidepressants were added if clinically indicated. A neurocognitive test battery assessing the most reliable findings in adult patients was administered at fixed time points throughout the study to patients and matched controls.</p> <p>Results</p> <p>Of the 21 enrolled patients, 18 completed the 48-week study. Thirteen patients were able to be maintained without relapse or recurrence in good quality remission on quetiapine monotherapy, while 5 patients required additional medication to treat impairing residual depressive and/or anxiety symptoms. According to symptom ratings and global functioning scores, the quality of remission for all patients was very good.</p> <p>Neurocognitive test performance over treatment was equivalent to that of a matched control group of never ill adolescents. Quetiapine was generally well tolerated with no serious adverse effects.</p> <p>Conclusion</p> <p>This study suggests that a proportion of adolescent patients diagnosed with bipolar disorder can be successfully maintained on quetiapine monotherapy. The good quality of clinical remission and preserved neurocognitive functioning underscores the importance of early diagnosis and effective stabilization.</p> <p>Clinical Trials Registry</p> <p>D1441L00024</p

    Autonomous clustering using rough set theory

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    This paper proposes a clustering technique that minimises the need for subjective human intervention and is based on elements of rough set theory. The proposed algorithm is unified in its approach to clustering and makes use of both local and global data properties to obtain clustering solutions. It handles single-type and mixed attribute data sets with ease and results from three data sets of single and mixed attribute types are used to illustrate the technique and establish its efficiency

    The Role of Pressure in Inverse Design for Assembly

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    Isotropic pairwise interactions that promote the self assembly of complex particle morphologies have been discovered by inverse design strategies derived from the molecular coarse-graining literature. While such approaches provide an avenue to reproduce structural correlations, thermodynamic quantities such as the pressure have typically not been considered in self-assembly applications. In this work, we demonstrate that relative entropy optimization can be used to discover potentials that self-assemble into targeted cluster morphologies with a prescribed pressure when the iterative simulations are performed in the isothermal-isobaric ensemble. By tuning the pressure in the optimization, we generate a family of simple pair potentials that all self-assemble the same structure. Selecting an appropriate simulation ensemble to control the thermodynamic properties of interest is a general design strategy that could also be used to discover interaction potentials that self-assemble structures having, for example, a specified chemical potential.Comment: 29 pages, 8 figure

    The Kepler Follow-up Observation Program

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    The Kepler Mission was launched on March 6, 2009 to perform a photometric survey of more than 100,000 dwarf stars to search for terrestrial-size planets with the transit technique. Follow-up observations of planetary candidates identified by detection of transit-like events are needed both for identification of astrophysical phenomena that mimic planetary transits and for characterization of the true planets and planetary systems found by Kepler. We have developed techniques and protocols for detection of false planetary transits and are currently conducting observations on 177 Kepler targets that have been selected for follow-up. A preliminary estimate indicates that between 24% and 62% of planetary candidates selected for follow-up will turn out to be true planets.Comment: 12 pages, submitted to the Astrophysical Journal Letter
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