Milky Way dwarf spheroidal galaxies (dSphs) are among the best candidates to search for signals of dark matter annihilation with Imaging Atmospheric Cherenkov Telescopes, given their high mass-to-light ratios and the fact that they are free of astrophysical gamma-ray emitting sources. Since 2011, MAGIC has performed a multi-year observation program

We compare the surface brightness profile and morphology of the Galactic Centre Excess (GCE) identified in wide-angle γ-ray maps from the Fermi-Large Area Telescope (LAT) to dark matter annihilation predictions derived from high-resolution Λ cold dark matter magnetohydrodynamic simulations of galaxy formation. These simulations produce isolated

We report the discovery of a sub-Jovian-mass planet, OGLE-2014-BLG-0319Lb. The characteristics of this planet will be added into a future extended statistical analysis of the Microlensing Observations in Astrophysics (MOA) collaboration. The planetary anomaly of the light curve is characterized by MOA and OGLE survey observations and results in

Giant planets on short-period orbits are predicted to be inflated and eventually engulfed by their host stars. However, the detailed timescales and stages of these processes are not well known. Here, we present the discovery of three hot Jupiters (P < 10 days) orbiting evolved, intermediate-mass stars (M ⋆ ≍ 1.5 M ⊙, 2 R ⊙ < R ⋆ < 5 R ⊙). By

We present a one-dimensional, local thermodynamic equilibrium homogeneous analysis of 132 stars observed at high resolution with ESPaDOnS. This represents the largest sample observed at high resolution (R ~ 40 000) from the Pristine survey. This sample is based on the first version of the Pristine catalogue and covers the full range of

Cosmological information from weak lensing surveys is maximized by sorting source galaxies into tomographic redshift subsamples. Any uncertainties on these redshift distributions must be correctly propagated into the cosmological results. We present HYPERRANK, a new method for marginalizing over redshift distribution uncertainties, using discrete