{"paper":{"title":"BeyondPlanck X. Planck LFI frequency maps with sample-based error propagation","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"astro-ph.CO","authors_text":"A. Basyrov, A. Karakci, A.-S. Suur-Uski, A. Zacchei, B. Hensley, B. Partridge, C. Franceschet, D. Herman, D. J. Watts, D. Maino, D. Tavagnacco, E. Gjerl{\\o}w, E. Keih\\\"anen, G. Maggio, H. K. Eriksen, H. Thommesen, H. T. Ihle, I. K. Wehus, J. B. Jewell, J. R. Eskilt, K. J. Andersen, L. P. L. Colombo, M. Bersanelli, M. Brilenkov, M. Carbone, M. Galloway, M. Iacobellis, M. Ieronymaki, M. K. Foss, M. Maris, M. Reinecke, R. Aurlien, R. Banerji, R. Keskitalo, S. Bertocco, S. Galeotta, S. Gerakakis, S. Paradiso, T. L. Svalheim, U. Fuskeland","submitted_at":"2022-08-30T14:22:23Z","abstract_excerpt":"We present Planck LFI frequency sky maps derived within the BeyondPlanck framework. This framework draws samples from a global posterior distribution that includes instrumental, astrophysical and cosmological parameters, and the main product is an entire ensemble of frequency sky map samples. This ensemble allows for computationally convenient end-to-end propagation of low-level instrumental uncertainties into higher-level science products. We show that the two dominant sources of LFI instrumental systematic uncertainties are correlated noise and gain fluctuations, and the products presented h"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2208.14293","kind":"arxiv","version":1},"verdict":{"id":null,"model_set":{},"created_at":null,"strongest_claim":"","one_line_summary":"","pipeline_version":null,"weakest_assumption":"","pith_extraction_headline":""},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/2208.14293/integrity.json","findings":[],"available":true,"detectors_run":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938"},"references":{"count":0,"sample":[],"resolved_work":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","internal_anchors":0},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"author_claims":{"count":0,"strong_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"builder_version":"pith-number-builder-2026-05-17-v1"}