{"paper":{"title":"Towards Optimal Signal Extraction for Imaging X-ray Polarimetry","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"astro-ph.IM","authors_text":"A.L.Peirson, R.W.Romani","submitted_at":"2021-07-17T17:13:15Z","abstract_excerpt":"We describe an optimal signal extraction process for imaging X-ray polarimetry using an ensemble of deep neural networks. The initial photo-electron angle, used to recover the polarization, has errors following a von Mises distribution. This is complicated by events converting outside of the fiducial gas volume, whose tracks have little polarization sensitivity. We train a deep ensemble of convolutional neural networks to select against these events and to measure event angles and errors for the desired gas conversion tracks. We show how the expected modulation amplitude from each event gives "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2107.08289","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/2107.08289/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"}