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The sterile neutrino is a viable dark matter candidate that can be produced in the early Universe via non-equilibrium processes, and would therefore possess a highly non-thermal spectrum of primordial velocities. In this paper we analyse the process of structure formation with this class of dark matter particles. To this end we construct primordial dark matter power spectra as a function of the lepton asymmetry, $L_6$, that is present in the primordial plasma and leads to resonant sterile neutrino production. We compare these power spectra with those of thermally produced dark matter particles and show that resonantly produced sterile neutrinos are much colder than their thermal relic counterparts. We also demonstrate that the shape of these power spectra is not determined by the free-streaming scale alone. We then use the power spectra as an input for semi-analytic models of galaxy formation in order to predict the number of luminous satellite galaxies in a Milky Way-like halo. By assuming that the mass of the Milky Way halo must be no more than $2\times10^{12}M_{\odot}$ (the adopted upper bound based on current astronomical observations) we are able to constrain the value of $L_6$ for $M_s\le 8$~keV. We also show that the range of $L_6$ that is in best agreement with the 3.5~keV line (if produced by decays of 7~keV sterile neutrino) requires that the Milky Way halo has a mass no smaller than $1.5\times10^{12}M_{\odot}$. Finally, we compare the power spectra obtained by direct integration of the Boltzmann equations for a non-resonantly produced sterile neutrino with the fitting formula of Viel~et~al. and find that the latter significantly underestimates the power amplitude on scales relevant to satellite galaxies., Comment: Accepted by MNRAS, 15 pages 14 Figures

We present a new technique for creating mock catalogues of the individual stars that make up the accreted component of stellar haloes in cosmological simulations and show how the catalogues can be used to test and interpret observational data. The catalogues are constructed from a combination of methods. A semi-analytic galaxy formation model is used to calculate the star formation history in haloes in an N-body simulation and dark matter particles are tagged with this stellar mass. The tags are converted into individual stars using a stellar population synthesis model to obtain the number density and evolutionary stage of the stars, together with a phase-space sampling method that distributes the stars while ensuring that the phase-space structure of the original N-body simulation is maintained. A set of catalogues based on the $\Lambda$CDM Aquarius simulations of Milky Way mass haloes have been created and made publicly available on a website. Two example applications are discussed that demonstrate the power and flexibility of the mock catalogues. We show how the rich stellar substructure that survives in the stellar halo precludes a simple measurement of its density profile and demonstrate explicitly how pencil-beam surveys can return almost any value for the slope of the profile. We also show that localized variations in the abundance of particular types of stars, a signature of differences in the composition of stellar populations, allow streams to be easily identified., Comment: 19 pages, 13 figures, accepted by MNRAS

Well-motivated particle physics theories predict the existence of particles (such as sterile neutrinos) which acquire non-negligible thermal velocities in the early universe. These particles could behave as warm dark matter (WDM) and generate a small-scale cutoff in the linear density power spectrum which scales approximately inversely with the particle mass. If this mass is of order a keV, the cutoff occurs on the scale of dwarf galaxies. Thus, in WDM models the abundance of small galaxies, such as the satellites that orbit in the halo of the Milky Way, depends on the mass of the warm particle. The abundance also scales with the mass of the host galactic halo. We use the \galform semi-analytic model of galaxy formation to calculate the properties of galaxies in universes in which the dark matter is warm. Using this method, we can compare the predicted satellite luminosity functions to the observed data for the Milky Way dwarf spheroidals, and determine a lower bound on the thermally produced WDM particle mass. This depends strongly on the value of the Milky Way halo mass and, to some extent, on the baryonic physics assumed; we examine both of these dependencies. For our fiducial model we find that for a particle mass of 3.3 keV (the 2$\sigma$ lower limit found by Viel et al. from a recent analysis of the Lyman-$\alpha$ forest) the Milky Way halo mass is required to be $> 1.4 \times 10^{12}$ \msun. For this same fiducial model, we also find that all WDM particle masses are ruled out (at 95% confidence) if the halo of the Milky Way has a mass smaller than $1.1 \times 10^{12}$ \msun, while if the mass of the Galactic halo is greater than 1.8 $\times 10^{12}$ \msun, only WDM particle masses larger than 2 keV are allowed., Comment: 9 pages, 4 figures, submitted to MNRAS

We describe a methodology to accurately compute halo mass functions, progenitor mass functions, merger rates and merger trees in non-cold dark matter universes using a self-consistent treatment of the generalized extended Press-Schechter formalism. Our approach permits rapid exploration of the subhalo population of galactic halos in dark matter models with a variety of different particle properties or universes with rolling, truncated, or more complicated power spectra. We make detailed comparisons of analytically derived mass functions and merger histories with recent warm dark matter cosmological N-body simulations, and find excellent agreement. We show that, once the accretion of smoothly distributed matter is accounted for, coarse-grained statistics such as the mass accretion history of halos can be almost indistinguishable between cold and warm dark matter cases. However, the halo mass function and progenitor mass functions differ significantly, with the warm dark matter cases being strongly suppressed below the free-streaming scale of the dark matter. We demonstrate the importance of using the correct solution for the excursion set barrier first-crossing distribution in warm dark matter - if the solution for a flat barrier is used instead the truncation of the halo mass function is much slower, leading to an overestimate of the number of low mass halos., Comment: 19 pages, 14 figures, MNRAS in press. Comments welcome

With the coming data deluge from synoptic surveys, there is a growing need for frameworks that can quickly and automatically produce calibrated classification probabilities for newly-observed variables based on a small number of time-series measurements. In this paper, we introduce a methodology for variable-star classification, drawing from modern machine-learning techniques. We describe how to homogenize the information gleaned from light curves by selection and computation of real-numbered metrics ("feature"), detail methods to robustly estimate periodic light-curve features, introduce tree-ensemble methods for accurate variable star classification, and show how to rigorously evaluate the classification results using cross validation. On a 25-class data set of 1542 well-studied variable stars, we achieve a 22.8% overall classification error using the random forest classifier; this represents a 24% improvement over the best previous classifier on these data. This methodology is effective for identifying samples of specific science classes: for pulsational variables used in Milky Way tomography we obtain a discovery efficiency of 98.2% and for eclipsing systems we find an efficiency of 99.1%, both at 95% purity. We show that the random forest (RF) classifier is superior to other machine-learned methods in terms of accuracy, speed, and relative immunity to features with no useful class information; the RF classifier can also be used to estimate the importance of each feature in classification. Additionally, we present the first astronomical use of hierarchical classification methods to incorporate a known class taxonomy in the classifier, which further reduces the catastrophic error rate to 7.8%. Excluding low-amplitude sources, our overall error rate improves to 14%, with a catastrophic error rate of 3.5%., Comment: 23 pages, 9 figures

We present the first spectroscopic images of solar radio transients from the prototype for the Murchison Widefield Array (MWA), observed on 2010 March 27. Our observations span the instantaneous frequency band 170.9-201.6 MHz. Though our observing period is characterized as a period of `low' to `medium' activity, one broadband emission feature and numerous short-lived, narrowband, non-thermal emission features are evident. Our data represent a significant advance in low radio frequency solar imaging, enabling us to follow the spatial, spectral, and temporal evolution of events simultaneously and in unprecedented detail. The rich variety of features seen here reaffirms the coronal diagnostic capability of low radio frequency emission and provides an early glimpse of the nature of radio observations that will become available as the next generation of low frequency radio interferometers come on-line over the next few years., Comment: 15 pages, 5 figures, accepted for publication in Astrophysical Journal Letters. Movies for figures 4 and 5 available at http://www.mwatelescope.org/info/mwa_proto.html