Newly discovered brown dwarfs not seen in microlensing time scale frequency distribution?

The 2-Micron All Sky Survey (2MASS) (Skrutskie et al. 1997) and the DEep Near Infrared Survey of the southern sky (DENIS) (Epchtein et al. 1997) have revealed a heretofore unknown population of free brown dwarfs that has extended the local mass function down to as small as 0.01M_sun (Reid et al. 1999). If this local proportion of brown dwarfs extends throughout the Galaxy---in particular in the Galactic bulge---one expects an increase in the predicted fraction of short time scale microlensing events in directions toward the Galactic bulge. Zhao et al.(1996) have indicated that a mass function with 30-60% of the lens mass in brown dwarfs is not consistent with empirical microlensing data. Here we show that even the much lower mass fraction (~ 10%) of brown dwarfs inferred from the new discoveries appears inconsistent with the data. The added brown dwarfs do indeed increase the expected number of short time scale events, but they appear to drive the peak in the time scale frequency distribution to time scales smaller than that observed, and do not otherwise match the observed distribution. A reasonably good match to the empirical data (Alcock et al. 1996) is obtained by increasing the fraction of stars in the range 0.08<m<0.7M_sun considerably above that deduced from several star counts. However, all inferences from microlensing about the appropriate stellar mass function must be qualified by the meagerness of the microlensing data and the uncertainties in the Galactic model.Comment: 5 pages, 1 figure. PS file using aas2pp4.sty. To appear in ApJ Letter

Probability of Detecting a Planetary Companion during a Microlensing Event

The probability of detecting a planetary companion of a lensing star during a microlensing event toward the Galactic center, averaged over all relevant event and galactic parameters, when the planet-star mass ratio $q=0.001$ has a maximum exceeding 10% at an orbit semimajor axis $a$ near 1.5 AU for a uniform distribution of impact parameters. The maximum probability is raised to more than 20% for a distribution of source-lens impact parameters that is determined by the efficiency of event detection. The averaging procedures are carefully defined, and they determinine the dependence of the detection probabilities on several properties of the Galaxy. The probabilities scale approximately as $\sqrt{q}$. A planet is assumed detectable if the perturbation of the single lens light curve exceeds $2/(S/N)$ for at least 20 consecutive photometric points sometime during the event. Two meter telescopes with 60 second integrations in I-band with high time resolution photometry throughout the duration of an ongoing event are assumed. The probabilities are derived as a function of $a$, where they remain significant for $0.6<a<10$ AU. Dependence of the detection probabilities on the lens mass function, luminosity function of the source stars as modified by extinction, distribution of source-lens impact parameters, and the line of sight to the source are also determined, and the probabilities are averaged over the distribution of the projected planet position, the lens mass function, the distribution of impact parameters, the lens and source distances as weighted by their distributions along the line of sight and over the $I$-band apparent luminosity function of the sources. The extraction of the probabilility as a function of $a$ for a particular $q$ from empirical data is indicated.Comment: 32 pages, 20 figures, In Press, ApJ, Latex format with aas2pp4 forma

Coherent Graphene Devices: Movable Mirrors, Buffers and Memories

We theoretically report that, at a sharp electrostatic step potential in graphene, massless Dirac fermions can obtain Goos-H\"{a}nchen-like shifts under total internal reflection. Based on these results, we study the coherent propagation of the quasiparticles along a sharp graphene \emph{p-n-p} waveguide and derive novel dispersion relations for the guided modes. Consequently, coherent graphene devices (e.g. movable mirrors, buffers and memories) induced only by the electric field effect can be proposed.Comment: 12 pages, 5 figure

Exploring the rationale of enlightened shareholder value in the realm of UK company law – the path dependence perspective

Despite conventional beliefs in the predominance of shareholder value, a broader agenda of stakeholder consideration has been advocated in the UK by the recently-introduced ESV principle – the overriding corporate objective in the new company law regime. In this paper, the efficiency of this principle in terms of stakeholder enhancement is challenged through an interdisciplinary analysis. Through a critical review of the ESV principle, it is discovered that stakeholder enhancement practices in the context of the 2006 company law regime are still for the fundamental goal of shareholder value maximisation, and that their enlightened impact has been fairly limited in practice. Furthermore, by revisiting the interrelationships between UK economic, political and cultural factors with the predominance objective of shareholder value maximisation in the Companies Act 2006, it is discovered that the enlightened effect of this new approach in the company law regime is in fact impeded by strong, persistent forces deriving from shareholder-oriented particulars. Providing insight into the future direction of corporate governance practice, the paper concludes the rationale behind the shareholder-oriented ESV principle, and further suggests the continuing predominance of shareholder value in UK corporate governance

Estimating the characteristics of runoff inflow into Lake Gojal in ungauged, highly glacierized upper Hunza River Basin, Pakistan

Motivated by the potential flood outburst of Lake Gojal in the ungauged highly glacierized (27%) upper Hunza River Basin (HRB) in Pakistan that was dammed by a massive landslide on 4 January 2010, we attempt to analyze the characteristics of water inflow to the lake employing remote sensing data, two hydrological models, and sparsely observed data. One of the models (Model I) is a monthly degree-day model, while another (Model II) is the variable infiltration capacity (VIC) model. The mixture of glacier runoff output from Model I and runoff over unglacierized areas calculated by Model II has a similar seasonal variation pattern as that estimated from data recorded at a downstream station. This suggests that glacier runoff is the main source (87%) of runoff inflow into the lake. A sensitivity analysis suggests that the water inflow to the lake is highly sensitive to an increase in air temperature. Runoff in May is predicted to sharply increase by 15% to more than two-fold if the air temperature increases by 1 to 7, but it is predicted to increase only from 9% to 34% if the precipitation increases by 10% to 40%. The results suggested that the water inflow into Lake Gojal will not sharply rise even if there is heavy rain, and it needs to be in caution if the air temperature sharply increases. Analysis on long-term air temperature record indicates that the water inflow into the lake in May 2010 was probably less than average owing to the relatively low air temperature. Consequently, the flood outburst did not occur before the completion of the spillway on 29 May 2010. © 2013 China University of Geosciences and Springer-Verlag Berlin Heidelberg

Self-consistent models of triaxial galaxies in MOND gravity

The Bekenstein-Milgrom gravity theory with a modified Poisson equation is tested here for the existence of triaxial equilibrium solutions. Using the non-negative least square method, we show that self-consistent triaxial galaxies exist for baryonic models with a mild density cusp $\rho \sim {\Sigma \over r}$. Self-consistency is achieved for a wide range of central concentrations, $\Sigma \sim 10-1000\mathrm{M_{\odot}pc^{-2}}$, representing low-to-high surface brightness galaxies. Our results demonstrate for the first time that the orbit superposition technique is fruitful for constructing galaxy models beyond Newtonian gravity, and triaxial cuspy galaxies might exist without the help of Cold dark Matter.Comment: 19 pages, 1 table, 7 figures, Accepted for publication in Ap

Multi-view Regularized Gaussian Processes

Gaussian processes (GPs) have been proven to be powerful tools in various areas of machine learning. However, there are very few applications of GPs in the scenario of multi-view learning. In this paper, we present a new GP model for multi-view learning. Unlike existing methods, it combines multiple views by regularizing marginal likelihood with the consistency among the posterior distributions of latent functions from different views. Moreover, we give a general point selection scheme for multi-view learning and improve the proposed model by this criterion. Experimental results on multiple real world data sets have verified the effectiveness of the proposed model and witnessed the performance improvement through employing this novel point selection scheme

Exact heat kernel on a hypersphere and its applications in kernel SVM

Many contemporary statistical learning methods assume a Euclidean feature space. This paper presents a method for defining similarity based on hyperspherical geometry and shows that it often improves the performance of support vector machine compared to other competing similarity measures. Specifically, the idea of using heat diffusion on a hypersphere to measure similarity has been previously proposed, demonstrating promising results based on a heuristic heat kernel obtained from the zeroth order parametrix expansion; however, how well this heuristic kernel agrees with the exact hyperspherical heat kernel remains unknown. This paper presents a higher order parametrix expansion of the heat kernel on a unit hypersphere and discusses several problems associated with this expansion method. We then compare the heuristic kernel with an exact form of the heat kernel expressed in terms of a uniformly and absolutely convergent series in high-dimensional angular momentum eigenmodes. Being a natural measure of similarity between sample points dwelling on a hypersphere, the exact kernel often shows superior performance in kernel SVM classifications applied to text mining, tumor somatic mutation imputation, and stock market analysis

On Graph Stream Clustering with Side Information

Graph clustering becomes an important problem due to emerging applications involving the web, social networks and bio-informatics. Recently, many such applications generate data in the form of streams. Clustering massive, dynamic graph streams is significantly challenging because of the complex structures of graphs and computational difficulties of continuous data. Meanwhile, a large volume of side information is associated with graphs, which can be of various types. The examples include the properties of users in social network activities, the meta attributes associated with web click graph streams and the location information in mobile communication networks. Such attributes contain extremely useful information and has the potential to improve the clustering process, but are neglected by most recent graph stream mining techniques. In this paper, we define a unified distance measure on both link structures and side attributes for clustering. In addition, we propose a novel optimization framework DMO, which can dynamically optimize the distance metric and make it adapt to the newly received stream data. We further introduce a carefully designed statistics SGS(C) which consume constant storage spaces with the progression of streams. We demonstrate that the statistics maintained are sufficient for the clustering process as well as the distance optimization and can be scalable to massive graphs with side attributes. We will present experiment results to show the advantages of the approach in graph stream clustering with both links and side information over the baselines.Comment: Full version of SIAM SDM 2013 pape