{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2022:2RNFOQNHY7MN5UJOFP7WM6ITWQ","short_pith_number":"pith:2RNFOQNH","schema_version":"1.0","canonical_sha256":"d45a5741a7c7d8ded12e2bff667913b42e272cfe28dee3626561036d1decc9e1","source":{"kind":"arxiv","id":"2210.13260","version":2},"attestation_state":"computed","paper":{"title":"Almanac: Weak Lensing power spectra and map inference on the masked sphere","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"astro-ph.CO","authors_text":"A. F. Heavens, A. H. Jaffe, A. Loureiro, E. Sellentin, J. S. Lafaurie, L. Whiteway","submitted_at":"2022-10-24T14:00:13Z","abstract_excerpt":"We present a field-based signal extraction of weak lensing from noisy observations on the curved and masked sky. We test the analysis on a simulated Euclid-like survey, using a Euclid-like mask and noise level. To make optimal use of the information available in such a galaxy survey, we present a Bayesian method for inferring the angular power spectra of the weak lensing fields, together with an inference of the noise-cleaned tomographic weak lensing shear and convergence (projected mass) maps. The latter can be used for field-level inference with the aim of extracting cosmological parameter i"},"verification_status":{"content_addressed":true,"pith_receipt":true,"author_attested":false,"weak_author_claims":0,"strong_author_claims":0,"externally_anchored":false,"storage_verified":false,"citation_signatures":0,"replication_records":0,"graph_snapshot":true,"references_resolved":false,"formal_links_present":false},"canonical_record":{"source":{"id":"2210.13260","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"astro-ph.CO","submitted_at":"2022-10-24T14:00:13Z","cross_cats_sorted":[],"title_canon_sha256":"8e48a3b7247208622619cd67105879ae0bbff5cbdefccdd8fcfd6a238ab8a5ec","abstract_canon_sha256":"07ef62c75aba3393edc13e50ebd22b669f7b35f2702713ee920fd6c86a060fa1"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T05:39:54.010602Z","signature_b64":"BJY/Ftn/upPoaP9otg1ezfKmNiC40Oemhuy+OWbX7sb1l/dJq43Dqt095ZWOSdhnjY4H/CsbWEViX3x2q6sEAw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"d45a5741a7c7d8ded12e2bff667913b42e272cfe28dee3626561036d1decc9e1","last_reissued_at":"2026-07-05T05:39:54.010131Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T05:39:54.010131Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Almanac: Weak Lensing power spectra and map inference on the masked sphere","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"astro-ph.CO","authors_text":"A. F. Heavens, A. H. Jaffe, A. Loureiro, E. Sellentin, J. S. Lafaurie, L. Whiteway","submitted_at":"2022-10-24T14:00:13Z","abstract_excerpt":"We present a field-based signal extraction of weak lensing from noisy observations on the curved and masked sky. We test the analysis on a simulated Euclid-like survey, using a Euclid-like mask and noise level. To make optimal use of the information available in such a galaxy survey, we present a Bayesian method for inferring the angular power spectra of the weak lensing fields, together with an inference of the noise-cleaned tomographic weak lensing shear and convergence (projected mass) maps. The latter can be used for field-level inference with the aim of extracting cosmological parameter i"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2210.13260","kind":"arxiv","version":2},"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/2210.13260/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"},"aliases":[{"alias_kind":"arxiv","alias_value":"2210.13260","created_at":"2026-07-05T05:39:54.010187+00:00"},{"alias_kind":"arxiv_version","alias_value":"2210.13260v2","created_at":"2026-07-05T05:39:54.010187+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2210.13260","created_at":"2026-07-05T05:39:54.010187+00:00"},{"alias_kind":"pith_short_12","alias_value":"2RNFOQNHY7MN","created_at":"2026-07-05T05:39:54.010187+00:00"},{"alias_kind":"pith_short_16","alias_value":"2RNFOQNHY7MN5UJO","created_at":"2026-07-05T05:39:54.010187+00:00"},{"alias_kind":"pith_short_8","alias_value":"2RNFOQNH","created_at":"2026-07-05T05:39:54.010187+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":1,"internal_anchor_count":0,"sample":[{"citing_arxiv_id":"2606.12255","citing_title":"Towards Practical Field-Level Inference for Weak Lensing","ref_index":66,"is_internal_anchor":false}]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/2RNFOQNHY7MN5UJOFP7WM6ITWQ","json":"https://pith.science/pith/2RNFOQNHY7MN5UJOFP7WM6ITWQ.json","graph_json":"https://pith.science/api/pith-number/2RNFOQNHY7MN5UJOFP7WM6ITWQ/graph.json","events_json":"https://pith.science/api/pith-number/2RNFOQNHY7MN5UJOFP7WM6ITWQ/events.json","paper":"https://pith.science/paper/2RNFOQNH"},"agent_actions":{"view_html":"https://pith.science/pith/2RNFOQNHY7MN5UJOFP7WM6ITWQ","download_json":"https://pith.science/pith/2RNFOQNHY7MN5UJOFP7WM6ITWQ.json","view_paper":"https://pith.science/paper/2RNFOQNH","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2210.13260&json=true","fetch_graph":"https://pith.science/api/pith-number/2RNFOQNHY7MN5UJOFP7WM6ITWQ/graph.json","fetch_events":"https://pith.science/api/pith-number/2RNFOQNHY7MN5UJOFP7WM6ITWQ/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/2RNFOQNHY7MN5UJOFP7WM6ITWQ/action/timestamp_anchor","attest_storage":"https://pith.science/pith/2RNFOQNHY7MN5UJOFP7WM6ITWQ/action/storage_attestation","attest_author":"https://pith.science/pith/2RNFOQNHY7MN5UJOFP7WM6ITWQ/action/author_attestation","sign_citation":"https://pith.science/pith/2RNFOQNHY7MN5UJOFP7WM6ITWQ/action/citation_signature","submit_replication":"https://pith.science/pith/2RNFOQNHY7MN5UJOFP7WM6ITWQ/action/replication_record"}},"created_at":"2026-07-05T05:39:54.010187+00:00","updated_at":"2026-07-05T05:39:54.010187+00:00"}