{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2019:QTI7FVWMW5ZQEGGE2UXLNLTYWL","short_pith_number":"pith:QTI7FVWM","schema_version":"1.0","canonical_sha256":"84d1f2d6ccb7730218c4d52eb6ae78b2dc4351f15837cdb552030b3284677ce4","source":{"kind":"arxiv","id":"1909.00791","version":2},"attestation_state":"computed","paper":{"title":"The impact of braiding covariance and in-survey covariance on next-generation galaxy surveys","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"astro-ph.CO","authors_text":"Fabien Lacasa","submitted_at":"2019-09-02T16:38:14Z","abstract_excerpt":"As galaxy surveys become more precise and push to smaller scales, the need for accurate covariances beyond the classical Gaussian formula becomes more acute. Here, I investigate the analytical implementation and impact of non-Gaussian covariance terms that I previously derived for galaxy clustering. Braiding covariance is such a class of terms and it gets contribution both from in-survey and super-survey modes. I present an approximation for braiding covariance which speeds up the numerical computation. I show that including braiding covariance is a necessary condition for including other non-"},"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":"1909.00791","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"astro-ph.CO","submitted_at":"2019-09-02T16:38:14Z","cross_cats_sorted":[],"title_canon_sha256":"5642f1ac1129084e01830fe720cc30784459387de5a03e112b99e5dda8c63bb0","abstract_canon_sha256":"4622c88f8235efa9f3fbfca823eb3c64b088ec87b40edc76f3993eb33143523a"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T00:39:57.216450Z","signature_b64":"67uaanXpOc6KMI6r79pb1Uy/AZwx+VepyO9kF2M2z1pz5z4vLk+iudNUOIELXvVHdQPoEZMwN7Yb4tt8pdq9Bg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"84d1f2d6ccb7730218c4d52eb6ae78b2dc4351f15837cdb552030b3284677ce4","last_reissued_at":"2026-07-05T00:39:57.215988Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T00:39:57.215988Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"The impact of braiding covariance and in-survey covariance on next-generation galaxy surveys","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"astro-ph.CO","authors_text":"Fabien Lacasa","submitted_at":"2019-09-02T16:38:14Z","abstract_excerpt":"As galaxy surveys become more precise and push to smaller scales, the need for accurate covariances beyond the classical Gaussian formula becomes more acute. Here, I investigate the analytical implementation and impact of non-Gaussian covariance terms that I previously derived for galaxy clustering. Braiding covariance is such a class of terms and it gets contribution both from in-survey and super-survey modes. I present an approximation for braiding covariance which speeds up the numerical computation. I show that including braiding covariance is a necessary condition for including other non-"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1909.00791","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/1909.00791/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":"1909.00791","created_at":"2026-07-05T00:39:57.216043+00:00"},{"alias_kind":"arxiv_version","alias_value":"1909.00791v2","created_at":"2026-07-05T00:39:57.216043+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1909.00791","created_at":"2026-07-05T00:39:57.216043+00:00"},{"alias_kind":"pith_short_12","alias_value":"QTI7FVWMW5ZQ","created_at":"2026-07-05T00:39:57.216043+00:00"},{"alias_kind":"pith_short_16","alias_value":"QTI7FVWMW5ZQEGGE","created_at":"2026-07-05T00:39:57.216043+00:00"},{"alias_kind":"pith_short_8","alias_value":"QTI7FVWM","created_at":"2026-07-05T00:39:57.216043+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":1,"internal_anchor_count":0,"sample":[{"citing_arxiv_id":"2606.12551","citing_title":"Complex yet Hermitian: Gaussian covariance of cross-correlation and multi-tracer power spectra","ref_index":40,"is_internal_anchor":false}]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/QTI7FVWMW5ZQEGGE2UXLNLTYWL","json":"https://pith.science/pith/QTI7FVWMW5ZQEGGE2UXLNLTYWL.json","graph_json":"https://pith.science/api/pith-number/QTI7FVWMW5ZQEGGE2UXLNLTYWL/graph.json","events_json":"https://pith.science/api/pith-number/QTI7FVWMW5ZQEGGE2UXLNLTYWL/events.json","paper":"https://pith.science/paper/QTI7FVWM"},"agent_actions":{"view_html":"https://pith.science/pith/QTI7FVWMW5ZQEGGE2UXLNLTYWL","download_json":"https://pith.science/pith/QTI7FVWMW5ZQEGGE2UXLNLTYWL.json","view_paper":"https://pith.science/paper/QTI7FVWM","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1909.00791&json=true","fetch_graph":"https://pith.science/api/pith-number/QTI7FVWMW5ZQEGGE2UXLNLTYWL/graph.json","fetch_events":"https://pith.science/api/pith-number/QTI7FVWMW5ZQEGGE2UXLNLTYWL/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/QTI7FVWMW5ZQEGGE2UXLNLTYWL/action/timestamp_anchor","attest_storage":"https://pith.science/pith/QTI7FVWMW5ZQEGGE2UXLNLTYWL/action/storage_attestation","attest_author":"https://pith.science/pith/QTI7FVWMW5ZQEGGE2UXLNLTYWL/action/author_attestation","sign_citation":"https://pith.science/pith/QTI7FVWMW5ZQEGGE2UXLNLTYWL/action/citation_signature","submit_replication":"https://pith.science/pith/QTI7FVWMW5ZQEGGE2UXLNLTYWL/action/replication_record"}},"created_at":"2026-07-05T00:39:57.216043+00:00","updated_at":"2026-07-05T00:39:57.216043+00:00"}