32 citations · 120 across the 11 of their papers we have counts for
7 papers · 1 filter
The colour variability of low-z SNe Ia is entirely explained by dust
Marco Giunta, Konstantin Karchev, Roberto Trotta
The relative importance of intrinsic colour variability of supernovae type Ia (SN Ia) versus dust-induced reddening remains an open question with important ramifications for unders…
CIGaRS I: Combined simulation-based inference from type Ia supernovae and host photometry
Konstantin Karchev, Roberto Trotta, Raul Jimenez
Using type Ia supernovae as cosmological probes requires empirical corrections that are correlated with their host environment. Here we present a unified Bayesian hierarchical mode…
SIDE-real: Supernova Ia Dust Extinction with truncated marginal neural ratio estimation applied to real data
Konstantin Karchev, Matthew Grayling, Benjamin M. Boyd +3
We present the first fully simulation-based hierarchical analysis of the light curves of a population of low-redshift type Ia supernovae (SNae Ia). Our hardware-accelerated forward…
SimSIMS: Simulation-based Supernova Ia Model Selection with thousands of latent variables
Konstantin Karchev, Roberto Trotta, Christoph Weniger
We present principled Bayesian model comparison through simulation-based neural classification applied to SN Ia analysis. We validate our approach on realistically simulated SN Ia…
One never walks alone: the effect of the perturber population on subhalo measurements in strong gravitational lenses
Adam Coogan, Noemi Anau Montel, Konstantin Karchev +3
Analyses of extended arcs in strong gravitational lensing images to date have constrained the properties of dark matter by measuring the parameters of one or two individual subhalo…
SICRET: Supernova Ia Cosmology with truncated marginal neural Ratio EsTimation
Konstantin Karchev, Roberto Trotta, Christoph Weniger
Type Ia supernovae (SNae Ia), standardisable candles that allow tracing the expansion history of the Universe, are instrumental in constraining cosmological parameters, particularl…
Estimating the warm dark matter mass from strong lensing images with truncated marginal neural ratio estimation
Noemi Anau Montel, Adam Coogan, Camila Correa +2
Precision analysis of galaxy-galaxy strong gravitational lensing images provides a unique way of characterizing small-scale dark matter halos, and could allow us to uncover the fun…