A non-parametric method for measuring the local dark matter density

We present a new method for determining the local dark matter density using kinematic data for a population of tracer stars. The Jeans equation in the $z$-direction is integrated to yield an equation that gives the velocity dispersion as a function of the total mass density, tracer density, and the tilt term that describes the coupling of vertical and radial motions. We then fit a dark matter mass profile to tracer density and velocity dispersion data to derive credible regions on the vertical dark matter density profile. Our method avoids numerical differentiation, leading to lower numerical noise, and is able to deal with the tilt term while remaining one dimensional. In this study we present the method and perform initial tests on idealised mock data. We also demonstrate the importance of dealing with the tilt term for tracers that sample $\gtrsim 1$ kpc above the disc plane. If ignored, this results in a systematic underestimation of the dark matter density.Comment: V2: Improved tracer density description; increased number of mocks to explore outliers; corrected sign error in the (R, z) velocity dispersion; main conclusions unchanged. 19 pages, 14 figure

The Local Dark Matter Density from SDSS-SEGUE G-dwarfs

We derive the local dark matter density by applying the integrated Jeans equation method from Silverwood et al. (2016) to SDSS-SEGUE G-dwarf data processed and presented by B\"udenbender et al. (2015). We use the MultiNest Bayesian nested sampling software to fit a model for the baryon distribution, dark matter and tracer stars, including a model for the 'tilt term' that couples the vertical and radial motions, to the data. The $\alpha$-young population from B\"udenbender et al. (2015) yields the most reliable result of $\rho_{\rm DM} = 0.46^{+0.07}_{-0.09}\, {{\rm GeV\, cm}^{-3}} = 0.012^{+0.001}_{-0.002}\, {{\rm M}_\odot \, {\rm pc}^{-3}}$. Our analyses yield inconsistent results for the $\alpha$-young and $\alpha$-old data, pointing to problems in the tilt term and its modelling, the data itself, the assumption of a flat rotation curve, or the effects of disequilibria.Comment: 17 pages, 10 figures, submitted to MNRA

PAMELA's cosmic positron from decaying LSP in SO(10) SUSY GUT

We propose two viable scenarios explaining the recent observations on cosmic positron excess. In both scenarios, the present relic density in the Universe is assumed to be still supported by thermally produced WIMP or LSP (\chi). One of the scenarios is based on two dark matter (DM) components (\chi,X) scenario, and the other is on SO(10) SUSY GUT. In the two DM components scenario, extremely small amount of non-thermally produced meta-stable DM component [O(10^{-10}) < n_X /n_\chi] explains the cosmic positron excess. In the SO(10) model, extremely small R-parity violation for LSP decay to e^\pm is naturally achieved with a non-zero VEV of the superpartner of one right-handed neutrino (\tilde{\nu}^c) and a global symmetry.Comment: 6 pages, Talks presented in PASCOS, SUSY, and COSMO/CosPA in 201

The impact of heavy quark mass effects in the NNPDF global analysis

We discuss the implementation of the FONLL general-mass scheme for heavy quarks in deep-inelastic scattering in the FastKernel framework, used in the NNPDF series of global PDF analysis. We present the general features of FONLL and benchmark the accuracy of its implementation in FastKernel comparing with the Les Houches heavy quark benchmark tables. We then show preliminary results of the NNPDF2.1 analysis, in which heavy quark mass effects are included following the FONLL-A GM scheme.Comment: 5 pages, 3 figures; to appear in the proceedings of DIS 2010, Firenz

Progress in the Neural Network Determination of Polarized Parton Distributions

We review recent progress towards a determination of a set of polarized parton distributions from a global set of deep-inelastic scattering data based on the NNPDF methodology, in analogy with the unpolarized case. This method is designed to provide a faithful and statistically sound representation of parton distributions and their uncertainties. We show how the FastKernel method provides a fast and accurate method for solving the polarized DGLAP equations. We discuss the polarized PDF parametrizations and the physical constraints which can be imposed. Preliminary results suggest that the uncertainty on polarized PDFs, most notably the gluon, has been underestimated in previous studies.Comment: 5 pages, 2 figures; to appear in the proceedings of DIS 2010, Firenz

Solar Seismic Model as a New Constraint on Supersymmetric Dark Matter

If the Milky Way is populated by WIMPs as predicted by cosmological models of the large-scale structure of the universe and as motivated by SUSY, the capture of high-mass WIMPs by the Sun would affect the temperature, density and chemical composition of the solar core. We use the sound speed and the density profiles inferred from the helioseismic instruments on the Solar and Heliospheric Observatory (SOHO) to discuss the effect of WIMP accretion and annihilation on the evolution of the Sun. The WIMP transport of energy inside the Sun is not negligible for WIMPs with a mass smaller than 60 GeV and annihilating WIMPs with ~ 10^{-27}cm^3/sec. WIMP-accreting models with WIMP masses smaller than 30 GeV are in conflict with the most recent seismic data. We combine our new constraints with the analysis of predicted neutrino fluxes from annihilating WIMPs in the solar core. Working in the framework of the Minimal Supersymmetric Standard Model and considering the neutralino as the best dark matter particle candidate, we find that supersymmetric models, consistent with solar seismic data and with recent measurements of dark matter relic density, lead to a measured muon flux on Earth in the range of 1 to 10^4 km^{-2} yr^{-1}, for neutralino masses between 30 and 400 GeV.Comment: Accepeted for publication in MNRA

Parton distributions: determining probabilities in a space of functions

We discuss the statistical properties of parton distributions within the framework of the NNPDF methodology. We present various tests of statistical consistency, in particular that the distribution of results does not depend on the underlying parametrization and that it behaves according to Bayes' theorem upon the addition of new data. We then study the dependence of results on consistent or inconsistent datasets and present tools to assess the consistency of new data. Finally we estimate the relative size of the PDF uncertainty due to data uncertainties, and that due to the need to infer a functional form from a finite set of data.Comment: 11 pages, 8 figures, presented by Stefano Forte at PHYSTAT 2011 (to be published in the proceedings

Evaluation report of demonstrator

No abstract availabl