Gravity Effects on Information Filtering and Network Evolving

In this paper, based on the gravity principle of classical physics, we propose a tunable gravity-based model, which considers tag usage pattern to weigh both the mass and distance of network nodes. We then apply this model in solving the problems of information filtering and network evolving. Experimental results on two real-world data sets, \emph{Del.icio.us} and \emph{MovieLens}, show that it can not only enhance the algorithmic performance, but can also better characterize the properties of real networks. This work may shed some light on the in-depth understanding of the effect of gravity model

Physics, Astrophysics and Cosmology with Gravitational Waves

Gravitational wave detectors are already operating at interesting sensitivity levels, and they have an upgrade path that should result in secure detections by 2014. We review the physics of gravitational waves, how they interact with detectors (bars and interferometers), and how these detectors operate. We study the most likely sources of gravitational waves and review the data analysis methods that are used to extract their signals from detector noise. Then we consider the consequences of gravitational wave detections and observations for physics, astrophysics, and cosmology.Comment: 137 pages, 16 figures, Published version <http://www.livingreviews.org/lrr-2009-2

Intrinsic selection biases of ground-based gravitational wave searches for high-mass BH-BH mergers

The next generation of ground-based gravitational wave detectors may detect a few mergers of comparable-mass M\simeq 100-1000 Msun ("intermediate-mass'', or IMBH) spinning black holes. Black hole spin is known to have a significant impact on the orbit, merger signal, and post-merger ringdown of any binary with non-negligible spin. In particular, the detection volume for spinning binaries depends significantly on the component black hole spins. We provide a fit to the single-detector and isotropic-network detection volume versus (total) mass and arbitrary spin for equal-mass binaries. Our analysis assumes matched filtering to all significant available waveform power (up to l=6 available for fitting, but only l<= 4 significant) estimated by an array of 64 numerical simulations with component spins as large as S_{1,2}/M^2 <= 0.8. We provide a spin-dependent estimate of our uncertainty, up to S_{1,2}/M^2 <= 1. For the initial (advanced) LIGO detector, our fits are reliable for $M\in[100,500]M_\odot$ ($M\in[100,1600]M_\odot$). In the online version of this article, we also provide fits assuming incomplete information, such as the neglect of higher-order harmonics. We briefly discuss how a strong selection bias towards aligned spins influences the interpretation of future gravitational wave detections of IMBH-IMBH mergers.Comment: 18 pages, 15 figures, accepted by PRD. v2 is version accepted for publication, including minor changes in response to referee feedback and updated citation

On Discovering Electromagnetic Emission from Neutron Star Mergers: The Early Years of Two Gravitational Wave Detectors

We present the first simulation addressing the prospects of finding an electromagnetic (EM) counterpart to gravitational wave detections (GW) during the early years of only two advanced interferometers. The perils of such a search may have appeared insurmountable when considering the coarse ring-shaped GW localizations spanning thousands of deg^2 using time-of-arrival information alone. We show that leveraging the amplitude and phase information of the predicted GW signal narrows the localization to arcs with a median area of only ~250 deg^2, thereby making an EM search tractable. Based on the locations and orientations of the two LIGO detectors, we find that the GW sensitivity is limited to one polarization and thus to only two sky quadrants. Thus, the rates of GW events with two interferometers is only ~40% of the rate with three interferometers of similar sensitivity. Another important implication of the sky quadrant bias is that EM observatories in North America and Southern Africa would be able to systematically respond to GW triggers several hours sooner than Russia and Chile. Given the larger sky areas and the relative proximity of detected mergers, 1m-class telescopes with very wide-field cameras are well positioned for the challenge of finding an EM counterpart. Identification of the EM counterpart amidst the even larger numbers of false positives further underscores the importance of building a comprehensive catalog of foreground stellar sources, background AGN and potential host galaxies in the local universe.Comment: Submitted to ApJL, 8 pages, 4 figures, 1 tabl

Bayesian Dynamic Modeling and Monitoring of Network Flows

In the context of a motivating study of dynamic network flow data on a large-scale e-commerce web site, we develop Bayesian models for on-line/sequential analysis for monitoring and adapting to changes reflected in node-node traffic. For large-scale networks, we customize core Bayesian time series analysis methods using dynamic generalized linear models (DGLMs). These are integrated into the context of multivariate networks using the concept of decouple/recouple that was recently introduced in multivariate time series. This method enables flexible dynamic modeling of flows on large-scale networks and exploitation of partial parallelization of analysis while maintaining coherence with an over-arching multivariate dynamic flow model. This approach is anchored in a case-study on internet data, with flows of visitors to a commercial news web site defining a long time series of node-node counts on over 56,000 node pairs. Central questions include characterizing inherent stochasticity in traffic patterns, understanding node-node interactions, adapting to dynamic changes in flows and allowing for sensitive monitoring to flag anomalies. The methodology of dynamic network DGLMs applies to many dynamic network flow studies.Comment: 34 pages, 24 figure