Smokescreen is a Python package that blinds cosmological data vectors using Firecrown likelihoods on SACC files while encrypting the true data to avoid premature unblinding.
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Blue galaxy selection in DES Y3 cosmic shear mitigates IA effects, producing stable parameters with 1.5x smaller S8 uncertainty and improved CMB agreement versus the full sample.
Bulk flow measurements from Hawai`i Supernova Flows SNe Ia yield speeds of 100-400 km/s consistent with ΛCDM expectations at z ≲ 0.1.
Lensing amplitude A_L deviates from 1 at up to 3.06 sigma in combined datasets while other phenomenological amplitudes remain consistent with Lambda CDM or are poorly constrained.
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Smokescreen: A Python package for data vector blinding and encryption in cosmological analyses
Smokescreen is a Python package that blinds cosmological data vectors using Firecrown likelihoods on SACC files while encrypting the true data to avoid premature unblinding.