{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2018:TEZHHFH3Q5DU54MTIQOUBQUH4W","short_pith_number":"pith:TEZHHFH3","schema_version":"1.0","canonical_sha256":"99327394fb87474ef193441d40c287e58e85b3b446b181b5956d6a8fbfb0d709","source":{"kind":"arxiv","id":"1802.10115","version":3},"attestation_state":"computed","paper":{"title":"Exploring the squeezed three-point galaxy correlation function with generalized halo occupation distribution models","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"astro-ph.CO","authors_text":"Daniel J. Eisenstein, Lehman H. Garrison, Sihan Yuan","submitted_at":"2018-02-27T19:04:57Z","abstract_excerpt":"We present the GeneRalized ANd Differentiable Halo Occupation Distribution (GRAND-HOD) routine that generalizes the standard 5 parameter halo occupation distribution model (HOD) with various halo-scale physics and assembly bias. We describe the methodology of 4 different generalizations: satellite distribution generalization, velocity bias, closest approach distance generalization, and assembly bias. We showcase the signatures of these generalizations in the 2-point correlation function (2PCF) and the squeezed 3-point correlation function (squeezed 3PCF). We identify generalized HOD prescripti"},"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":"1802.10115","kind":"arxiv","version":3},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"astro-ph.CO","submitted_at":"2018-02-27T19:04:57Z","cross_cats_sorted":[],"title_canon_sha256":"2ec420ba835700c9363d124f6d6578990955dea113d1b40a90c02f0f6c8e762f","abstract_canon_sha256":"00757377be0fb7f0bcf241699d684b2eda3bd41e599a9c5eefd4dfa17f7a6552"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:17:18.541971Z","signature_b64":"4qKBS4WP0IqbUgOzOya7W2nOt8gEfWPMggdkfoQnq3ZP3u8kDmryYTMnln1A/vo0tV00cVAGaaNnt0vkbTd4Dw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"99327394fb87474ef193441d40c287e58e85b3b446b181b5956d6a8fbfb0d709","last_reissued_at":"2026-05-18T00:17:18.541465Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:17:18.541465Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Exploring the squeezed three-point galaxy correlation function with generalized halo occupation distribution models","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"astro-ph.CO","authors_text":"Daniel J. Eisenstein, Lehman H. Garrison, Sihan Yuan","submitted_at":"2018-02-27T19:04:57Z","abstract_excerpt":"We present the GeneRalized ANd Differentiable Halo Occupation Distribution (GRAND-HOD) routine that generalizes the standard 5 parameter halo occupation distribution model (HOD) with various halo-scale physics and assembly bias. We describe the methodology of 4 different generalizations: satellite distribution generalization, velocity bias, closest approach distance generalization, and assembly bias. We showcase the signatures of these generalizations in the 2-point correlation function (2PCF) and the squeezed 3-point correlation function (squeezed 3PCF). We identify generalized HOD prescripti"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1802.10115","kind":"arxiv","version":3},"verdict":{"id":null,"model_set":{},"created_at":null,"strongest_claim":"","one_line_summary":"","pipeline_version":null,"weakest_assumption":"","pith_extraction_headline":""},"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":"1802.10115","created_at":"2026-05-18T00:17:18.541536+00:00"},{"alias_kind":"arxiv_version","alias_value":"1802.10115v3","created_at":"2026-05-18T00:17:18.541536+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1802.10115","created_at":"2026-05-18T00:17:18.541536+00:00"},{"alias_kind":"pith_short_12","alias_value":"TEZHHFH3Q5DU","created_at":"2026-05-18T12:32:53.628368+00:00"},{"alias_kind":"pith_short_16","alias_value":"TEZHHFH3Q5DU54MT","created_at":"2026-05-18T12:32:53.628368+00:00"},{"alias_kind":"pith_short_8","alias_value":"TEZHHFH3","created_at":"2026-05-18T12:32:53.628368+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":1,"internal_anchor_count":1,"sample":[{"citing_arxiv_id":"2606.12405","citing_title":"Bounding the Effect of HOD Assumptions on Small-Scale Clustering Constraints","ref_index":74,"is_internal_anchor":true}]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/TEZHHFH3Q5DU54MTIQOUBQUH4W","json":"https://pith.science/pith/TEZHHFH3Q5DU54MTIQOUBQUH4W.json","graph_json":"https://pith.science/api/pith-number/TEZHHFH3Q5DU54MTIQOUBQUH4W/graph.json","events_json":"https://pith.science/api/pith-number/TEZHHFH3Q5DU54MTIQOUBQUH4W/events.json","paper":"https://pith.science/paper/TEZHHFH3"},"agent_actions":{"view_html":"https://pith.science/pith/TEZHHFH3Q5DU54MTIQOUBQUH4W","download_json":"https://pith.science/pith/TEZHHFH3Q5DU54MTIQOUBQUH4W.json","view_paper":"https://pith.science/paper/TEZHHFH3","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1802.10115&json=true","fetch_graph":"https://pith.science/api/pith-number/TEZHHFH3Q5DU54MTIQOUBQUH4W/graph.json","fetch_events":"https://pith.science/api/pith-number/TEZHHFH3Q5DU54MTIQOUBQUH4W/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/TEZHHFH3Q5DU54MTIQOUBQUH4W/action/timestamp_anchor","attest_storage":"https://pith.science/pith/TEZHHFH3Q5DU54MTIQOUBQUH4W/action/storage_attestation","attest_author":"https://pith.science/pith/TEZHHFH3Q5DU54MTIQOUBQUH4W/action/author_attestation","sign_citation":"https://pith.science/pith/TEZHHFH3Q5DU54MTIQOUBQUH4W/action/citation_signature","submit_replication":"https://pith.science/pith/TEZHHFH3Q5DU54MTIQOUBQUH4W/action/replication_record"}},"created_at":"2026-05-18T00:17:18.541536+00:00","updated_at":"2026-05-18T00:17:18.541536+00:00"}