323 citations · 2.1k across the 45 of their papers we have counts for
5 papers · 1 filter
Discovering a new well: Decaying dark matter with profile likelihoods
Emil Brinch Holm, Laura Herold, Steen Hannestad +2
A large number of studies, all using Bayesian parameter inference from Markov Chain Monte Carlo methods, have constrained the presence of a decaying dark matter component. All such…
Euclid: Modelling massive neutrinos in cosmology -- a code comparison
J. Adamek, R. E. Angulo, C. Arnold +133
The measurement of the absolute neutrino mass scale from cosmological large-scale clustering data is one of the key science goals of the Euclid mission. Such a measurement relies o…
Massive neutrino self-interactions and inflation
Shouvik Roy Choudhury, Steen Hannestad, Thomas Tram
Certain inflationary models like Natural inflation (NI) and Coleman-Weinberg inflation (CWI) are disfavoured by cosmological data in the standard model (where …
Decaying warm dark matter revisited
Emil Brinch Holm, Thomas Tram, Steen Hannestad
Decaying dark matter models provide a physically motivated way of channeling energy between the matter and radiation sectors. In principle, this could affect the predicted value of…
CONNECT: A neural network based framework for emulating cosmological observables and cosmological parameter inference
Andreas Nygaard, Emil Brinch Holm, Steen Hannestad +1
Bayesian parameter inference is an essential tool in modern cosmology, and typically requires the calculation of -- theoretical models for each inference of model param…