Strongest model-independent bound on the lifetime of Dark Matter
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We study gravity coupled to scalar and fermion fields in the Einstein-Cartan framework. We discuss the most general form of the action that contains terms of mass dimension not bigger than four, leaving out only contributions quadratic in curvature. By res ...
The combination of multiple observational probes has long been advocated as a powerful technique to constrain cosmological parameters, in particular dark energy. The Dark Energy Survey has measured 207 spectroscopically confirmed type Ia supernova light cu ...
Photons traveling cosmological distances through the inhomogeneous Universe experience a great variation in their in-medium induced effective mass. Using the EAGLE suite of hydrodynamical simulations, we infer the free electron distribution and thereby the ...
We interpret the recent NANOGrav results in terms of a stochastic gravitational wave background from metastable cosmic strings. The observed amplitude of a stochastic signal can be translated into a range for the cosmic string tension and the mass of magne ...
Instead of Lorentz invariance, gravitational degrees of freedom may obey Lifshitz scaling at high energies, as it happens in Horava's proposal for quantum gravity. We study consequences of this proposal for the spectra of primordial perturbations generated ...
Most of the upcoming cosmological information will come from analyzing the clustering of the Large Scale Structures (LSS) of the universe through LSS or CMB observations. It is therefore essential to be able to understand their behavior with exquisite prec ...
We extend the formalism of time-sliced perturbation theory (TSPT) for cosmological large-scale structure to include non-Gaussian initial conditions. We show that in such a case the TSPT interaction vertices acquire new contributions whose time-dependence f ...
The expansion history of the Universe between the end of inflation and the onset of radiation-domination (RD) is currently unknown. If the equation of state during this period is stiffer than that of radiation, w > 1/3, the gravitational wave (GW) backgrou ...
Convolutional Neural Networks (CNNs) are a cornerstone of the Deep Learning toolbox and have led to many breakthroughs in Artificial Intelligence. So far, these neural networks (NNs) have mostly been developed for regular Euclidean domains such as those su ...
The stochastic gravitational wave background (SGWB) contains a wealth of information on astrophysical and cosmological processes. A major challenge of upcoming years will be to extract the information contained in this background and to disentangle the con ...