Four parameters suffice to describe dust attenuation curve diversity in TNG simulations, yielding a new symbolic-regression model that recovers curves and fluxes better than existing parameterizations while linking parameters to SFR surface density, metallicity, and geometry.
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New observations of SN 2024dy show carbon dust formation with mass ~10^{-5} M_sun inferred from NIR excess and asymmetric H-alpha profile in a long-lived Type IIn supernova.
CARMApy provides a Python interface to the ExoCARMA microphysics code, enabling simulation of cloud particle size distributions and rates in exoplanet atmospheres with claimed consistency to prior versions and speed gains of 1.9x single-threaded and 3.8x multithreaded.
citing papers explorer
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Learning the Universe: The Structure of Dust Attenuation Curves in Galaxy Simulations
Four parameters suffice to describe dust attenuation curve diversity in TNG simulations, yielding a new symbolic-regression model that recovers curves and fluxes better than existing parameterizations while linking parameters to SFR surface density, metallicity, and geometry.
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SN 2024dy: Dust formation in a long-lived Type IIn supernova and constraints on the dust mass
New observations of SN 2024dy show carbon dust formation with mass ~10^{-5} M_sun inferred from NIR excess and asymmetric H-alpha profile in a long-lived Type IIn supernova.
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CARMApy: An Open-Source Python Framework for Simulating Microphysical Clouds in Planetary Atmospheres
CARMApy provides a Python interface to the ExoCARMA microphysics code, enabling simulation of cloud particle size distributions and rates in exoplanet atmospheres with claimed consistency to prior versions and speed gains of 1.9x single-threaded and 3.8x multithreaded.