975 research outputs found
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
-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 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 -young
population from B\"udenbender et al. (2015) yields the most reliable result of
. Our analyses yield
inconsistent results for the -young and -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
Imaging and genetic investigations of neural tube defect in a calf: case report and review of the literature
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