49 citations · 112 across the 13 of their papers we have counts for
13 papers
Fast and efficient nested sampling with BEST
Andreas Nygaard
Nested sampling is widely used for Bayesian evidence computation, but its intrinsically sequential structure limits how efficiently it can exploit modern vectorised likelihoods and…
Posterior sampling in the Age of Emulators
Andreas Nygaard, Luca Janken, Steen Hannestad +1
We investigate posterior sampling strategies for cosmological parameter inference using fully differentiable neural-network likelihood emulators, which provide both rapid likelihoo…
CosmoSlider: An educational tool for cosmology
Andreas Nygaard, Steen Hannestad, Thomas Tram
Understanding how cosmological parameters influence the cosmic microwave background (CMB) power spectra is a central component of modern cosmology education, but interactive explor…
CLiENT: A new tool for emulating cosmological likelihoods using deep neural networks
Luca Janken, Steen Hannestad, Thomas Tram +1
Cosmological emulation of observables such as the Cosmic Microwave Background (CMB) spectra and matter power spectra have become increasingly common in recent years because of the…
Calculating Bayesian evidence for inflationary models using CONNECT
Camilla T. G. Sørensen, Steen Hannestad, Andreas Nygaard +1
Bayesian evidence is a standard tool used for comparing the ability of different models to fit available data and is used extensively in cosmology. However, since the evidence calc…
Cutting corners: Hypersphere sampling as a new standard for cosmological emulators
Andreas Nygaard, Emil Brinch Holm, Steen Hannestad +1
Cosmological emulators of observables such as the Cosmic Microwave Background (CMB) spectra and matter power spectra commonly use training data sampled from a Latin hypercube. This…
Circular reasoning: Solving the Hubble tension with a non- value of
Jonas El Gammal, Sven Günther, Emil Brinch Holm +1
Recently, cosmology has seen a surge in alternative models that purport to solve the discrepancy between the values of the Hubble constant as measured by cosmological microwa…
PROSPECT: A profile likelihood code for frequentist cosmological parameter inference
Emil Brinch Holm, Andreas Nygaard, Jeppe Dakin +2
Cosmological parameter inference has been dominated by the Bayesian approach for the past two decades, primarily due to its computational efficiency. However, the Bayesian approach…
Fast and effortless computation of profile likelihoods using CONNECT
Andreas Nygaard, Emil Brinch Holm, Steen Hannestad +1
The frequentist method of profile likelihoods has recently received renewed attention in the field of cosmology. This is because the results of inferences based on the latter may d…
Decaying Dark Matter and the Hubble Tension
Andreas Nygaard, Emil Brinch Holm, Thomas Tram +1
Decaying dark matter models generically modify the equation of state around the time of dark matter decay, and this in turn modifies the expansion rate of the Universe through the…
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…
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…
Updated constraints on decaying cold dark matter
Andreas Nygaard, Thomas Tram, Steen Hannestad
In this paper we update the constraints on the simple decaying cold dark matter (DCDM) model with dark radiation (DR) as decay product. We consider two different regimes of the lif…