Abstract: A prediction of the standard Lambda cold dark matter cosmology is that dark matter (DM) haloes are teeming with numerous self-bound substructure or subhaloes. The precise properties of these subhaloes represent important probes of the underlying cosmological model. We use data from Via Lactea II and Exploring the Local Volume in Simulations N-body simulations to learn about the structure of subhaloes with masses 10(6)-10(11) h(-1) M circle dot. Thanks to a superb subhalo statistics, we study subhalo properties as a function of distance to host halo centre and subhalo mass, and provide a set of fits that accurately describe the subhalo structure. We also investigate the role of subhaloes on the search for DM annihilation. Previous work has shown that subhaloes are expected to boost the DM signal of their host haloes significantly. Yet, these works traditionally assumed that subhaloes exhibit similar structural properties than those of field haloes, while it is known that subhaloes are more concentrated. Building upon our N-body data analysis, we refine the substructure boost model of Sanchez-Conde & Prada (2014), and find boosts that are a factor 2-3 higher. We further refine the model to include unavoidable tidal stripping effects on the subhalo population. For field haloes, this introduces a moderate (similar to 20-30 per cent) suppression. Yet, for subhaloes like those hosting dwarf galaxy satellites, tidal stripping plays a critical role, the boost being at the level of a few tens of percent at most. We provide a parametrization of the boost for field haloes that can be safely applied over a wide halo mass range.

Abstract: We present a method to minimize, or even cancel out, the nuisance parameters affecting a measurement. Our approach is general and can be applied to any experiment or observation where systematic errors are a concern e.g. are larger than statistical errors. We compare it with the Bayesian technique used to deal with nuisance parameters: marginalization, and show how the method compares and improves by avoiding biases. We illustrate the method with several examples taken from the astrophysics and cosmology world: baryonic acoustic oscillations (BAOs), cosmic clocks, Type Ia supernova (SNIa) luminosity distance, neutrino oscillations and dark matter detection. By applying the method we not only recover some known results but also find some interesting new ones. For BAO experiments we show how to combine radial and angular BAO measurements in order to completely eliminate the dependence on the sound horizon at radiation drag. In the case of exploiting SNIa as standard candles we show how the uncertainty in the luminosity distance by a second parameter modelled as a metallicity dependence can be eliminated or greatly reduced. When using cosmic clocks to measure the expansion rate of the universe, we demonstrate how a particular combination of observables nearly removes the metallicity dependence of the galaxy on determining differential ages, thus removing the agemetallicity degeneracy in stellar populations. We hope that these findings will be useful in future surveys to obtain robust constraints on the dark energy equation of state.

Abstract: We show that the effective brane-world and the loop quantum cosmology background expansion histories can be reproduced from a modified gravity perspective in terms of an f (R) gravity action plus a g(R) term non-minimally coupled with the matter Lagrangian. The reconstruction algorithm that we provide depends on a free function of the matter density that must be specified in each case and allows to obtain analytical solutions always. In the simplest cases, the function f (R) is quadratic in the Ricci scalar, R, whereas g(R) is linear. Our approach is compared with recent results in the literature. We show that working in the Palatini formalism there is no need to impose any constraint that keeps the equations second order, which is a key requirement for the successful implementation of the reconstruction algorithm.