Dust grain size distributions evolve from large-grain dominated at high redshift to MRN-like at low redshift, driven primarily by shattering and ISM accretion after stars supply initial large grains, reproducing z=0 dust masses and Milky Way extinction properties.
Parente,Modeling Dust in Galaxy Evolution Simulations, arXiv:2504.10585
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New SMICA formalism and binned bispectrum estimator jointly recover power spectra, spectral parameters, foreground 3-point correlators, and primordial non-Gaussianity constraints from multi-frequency polarization maps tested on LiteBIRD simulations.
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Dust and Grain Size Evolution in Galaxy Simulations: What Matters and What Does Not
Dust grain size distributions evolve from large-grain dominated at high redshift to MRN-like at low redshift, driven primarily by shattering and ISM accretion after stars supply initial large grains, reproducing z=0 dust masses and Milky Way extinction properties.
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Non-Gaussianity in SMICA
New SMICA formalism and binned bispectrum estimator jointly recover power spectra, spectral parameters, foreground 3-point correlators, and primordial non-Gaussianity constraints from multi-frequency polarization maps tested on LiteBIRD simulations.