A simulation-based inference framework that jointly models type Ia supernovae brightness dependences, host galaxy evolution, and cosmology from photometric observations.
The Astrophysical Journal 975:5
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Swampland-motivated priors on the slope and field range of an exponential quintessence potential in a curved universe produce a mild shift in the best-fit value of spatial curvature Ω_k from Planck, DESI BAO, and supernova observations.
Bayesian constraints on seven w(a) parameterizations with CMB+BAO+SNIa datasets favor the logarithmic model over LambdaCDM in several combinations and show modest sigma8 relief.
citing papers explorer
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CIGaRS I: Combined simulation-based inference from type Ia supernovae and host photometry
A simulation-based inference framework that jointly models type Ia supernovae brightness dependences, host galaxy evolution, and cosmology from photometric observations.
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Constraining Spatial Curvature with Priors from Swampland Conjectures
Swampland-motivated priors on the slope and field range of an exponential quintessence potential in a curved universe produce a mild shift in the best-fit value of spatial curvature Ω_k from Planck, DESI BAO, and supernova observations.
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Constraints of dynamical dark energy models from different observational datasets
Bayesian constraints on seven w(a) parameterizations with CMB+BAO+SNIa datasets favor the logarithmic model over LambdaCDM in several combinations and show modest sigma8 relief.