JWST nebular spectra detect cooling ~400 K carbonaceous dust emission in normal SN Ia 2023qov at +276 and +363 days, modeled as pre-existing circumstellar dust with mass ~10^{-4} M_sun located within ~1 light year.
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5 Pith papers cite this work. Polarity classification is still indexing.
5
Pith papers citing it
representative citing papers
BayeSN analysis of ZTF Type Ia supernovae confirms a ~0.1 mag intrinsic environmental step in standardized brightness that is not explained by differences in dust extinction properties.
Calibration uncertainties during supernova light-curve fitting cause roughly 50% degradation in dark energy figure of merit for Stage IV surveys, dominating over 13% degradation from model training errors and showing near-degeneracy with cosmology.
GIGA-Lens 2.0 scales strong gravitational lens modeling across up to 128 GPU nodes and demonstrates it on 100 simulated systems plus one real DESI lens.
Union3 compilation of 2087 SNe Ia with UNITY1.5 framework shows 1.7-2.6 sigma tension with LambdaCDM and possible thawing dark energy.
citing papers explorer
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JWST Nebular Spectroscopy of SN 2023qov: Circumstellar Dust Emission in a Normal Type Ia Supernova
JWST nebular spectra detect cooling ~400 K carbonaceous dust emission in normal SN Ia 2023qov at +276 and +363 days, modeled as pre-existing circumstellar dust with mass ~10^{-4} M_sun located within ~1 light year.
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On the origin of the environmental step: A BayeSN view of the ZTF SN Ia DR2
BayeSN analysis of ZTF Type Ia supernovae confirms a ~0.1 mag intrinsic environmental step in standardized brightness that is not explained by differences in dust extinction properties.
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GIGA-Lens 2.0: Strong-Lens Modeling on Multiple GPU Nodes
GIGA-Lens 2.0 scales strong gravitational lens modeling across up to 128 GPU nodes and demonstrates it on 100 simulated systems plus one real DESI lens.