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| Main Authors: | , , , , , , , , , , , , |
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| Format: | Preprint |
| Published: |
2026
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| Subjects: | |
| Online Access: | https://arxiv.org/abs/2604.18111 |
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| _version_ | 1866913047355850752 |
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| author | Loureiro, Arthur Muir, Jessica Blazek, Jonathan Chisari, Nora Elisa Ribeiro, Pedro H. Costa Georgiou, Christos Leonard, C. Danielle Moraes, Bruno Paterno, Marc Šarčević, Nikolina Tröster, Tilman Vitenti, Sandro D. P. Collaboration, the LSST Dark Energy Science |
| author_facet | Loureiro, Arthur Muir, Jessica Blazek, Jonathan Chisari, Nora Elisa Ribeiro, Pedro H. Costa Georgiou, Christos Leonard, C. Danielle Moraes, Bruno Paterno, Marc Šarčević, Nikolina Tröster, Tilman Vitenti, Sandro D. P. Collaboration, the LSST Dark Energy Science |
| contents | Smokescreen is an open-source Python library for data-vector concealment (blinding) in cosmological analyses. Data-vector blinding works by applying cosmology-dependent shifts to the observed data vector, moving it away from the true cosmological signal without affecting its statistical properties, so that analysts cannot infer the true result until the analysis is frozen and the blinding is lifted. The package computes these shifts using Firecrown likelihoods applied to data vectors stored in the SACC format, ensuring that the theoretical model used for blinding is identical to that used for inference whilst remaining agnostic to the specific observable being blinded. To prevent accidental unblinding, the original SACC file, containing the true cosmology, is encrypted. Although developed for the Vera C. Rubin Observatory Legacy Survey of Space and Time (LSST), Smokescreen is applicable to any experiment using Firecrown likelihoods and the SACC data format. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2604_18111 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | Smokescreen: A Python package for data vector blinding and encryption in cosmological analyses Loureiro, Arthur Muir, Jessica Blazek, Jonathan Chisari, Nora Elisa Ribeiro, Pedro H. Costa Georgiou, Christos Leonard, C. Danielle Moraes, Bruno Paterno, Marc Šarčević, Nikolina Tröster, Tilman Vitenti, Sandro D. P. Collaboration, the LSST Dark Energy Science Instrumentation and Methods for Astrophysics Cosmology and Nongalactic Astrophysics Smokescreen is an open-source Python library for data-vector concealment (blinding) in cosmological analyses. Data-vector blinding works by applying cosmology-dependent shifts to the observed data vector, moving it away from the true cosmological signal without affecting its statistical properties, so that analysts cannot infer the true result until the analysis is frozen and the blinding is lifted. The package computes these shifts using Firecrown likelihoods applied to data vectors stored in the SACC format, ensuring that the theoretical model used for blinding is identical to that used for inference whilst remaining agnostic to the specific observable being blinded. To prevent accidental unblinding, the original SACC file, containing the true cosmology, is encrypted. Although developed for the Vera C. Rubin Observatory Legacy Survey of Space and Time (LSST), Smokescreen is applicable to any experiment using Firecrown likelihoods and the SACC data format. |
| title | Smokescreen: A Python package for data vector blinding and encryption in cosmological analyses |
| topic | Instrumentation and Methods for Astrophysics Cosmology and Nongalactic Astrophysics |
| url | https://arxiv.org/abs/2604.18111 |