{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2013:ESG4M6TFPTAARTZZMBSKKDRFX4","short_pith_number":"pith:ESG4M6TF","schema_version":"1.0","canonical_sha256":"248dc67a657cc008cf396064a50e25bf0c2c1dab1db6ed7341fe9479e5cc7de7","source":{"kind":"arxiv","id":"1309.1477","version":2},"attestation_state":"computed","paper":{"title":"Observational Requirements for Lyman-alpha Forest Tomographic Mapping of Large-Scale Structure at z ~ 2","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"astro-ph.CO","authors_text":"Joseph F. Hennawi, Khee-Gan Lee, Martin White, Melih Ozbek, Rupert Croft","submitted_at":"2013-09-05T20:05:11Z","abstract_excerpt":"The z > 2 Lyman-alpha (Lya) forest traces the underlying dark-matter distribution on large scales and, given sufficient sightlines, can be used to create 3D maps of large-scale structure. We examine the observational requirements to construct such maps and estimate the signal-to-noise as a function of exposure time and sightline density. Sightline densities at z = 2.25 are n_los = [360, 1200,3300] deg^{-2} at limiting magnitudes of g =[24.0, 24.5,25.0], resulting in transverse sightline separations of d_perp = [3.6, 1.9, 1.2] h^{-1} Mpc, which roughly sets the reconstruction scale. We simulate"},"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":"1309.1477","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"astro-ph.CO","submitted_at":"2013-09-05T20:05:11Z","cross_cats_sorted":[],"title_canon_sha256":"7ed877d38c83c73361d7a29c656d272bfbf3016728ddd597367d4eb1b5608c1d","abstract_canon_sha256":"3cd3fde143d01ba088473ffa9ce1e9dd13d3e54fb536c4d5ea1d473bf63ae52c"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T02:51:23.224275Z","signature_b64":"2eeEf4+bFdq98ygwCGFJWZmKNGCIRcSiEOjfDu83onWKsKjH8HoRm+fhOdU097UPN/uI88cQPdA15kM/7KIHBA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"248dc67a657cc008cf396064a50e25bf0c2c1dab1db6ed7341fe9479e5cc7de7","last_reissued_at":"2026-05-18T02:51:23.223587Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T02:51:23.223587Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Observational Requirements for Lyman-alpha Forest Tomographic Mapping of Large-Scale Structure at z ~ 2","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"astro-ph.CO","authors_text":"Joseph F. Hennawi, Khee-Gan Lee, Martin White, Melih Ozbek, Rupert Croft","submitted_at":"2013-09-05T20:05:11Z","abstract_excerpt":"The z > 2 Lyman-alpha (Lya) forest traces the underlying dark-matter distribution on large scales and, given sufficient sightlines, can be used to create 3D maps of large-scale structure. We examine the observational requirements to construct such maps and estimate the signal-to-noise as a function of exposure time and sightline density. Sightline densities at z = 2.25 are n_los = [360, 1200,3300] deg^{-2} at limiting magnitudes of g =[24.0, 24.5,25.0], resulting in transverse sightline separations of d_perp = [3.6, 1.9, 1.2] h^{-1} Mpc, which roughly sets the reconstruction scale. We simulate"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1309.1477","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":""},"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":"1309.1477","created_at":"2026-05-18T02:51:23.223687+00:00"},{"alias_kind":"arxiv_version","alias_value":"1309.1477v2","created_at":"2026-05-18T02:51:23.223687+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1309.1477","created_at":"2026-05-18T02:51:23.223687+00:00"},{"alias_kind":"pith_short_12","alias_value":"ESG4M6TFPTAA","created_at":"2026-05-18T12:27:43.054852+00:00"},{"alias_kind":"pith_short_16","alias_value":"ESG4M6TFPTAARTZZ","created_at":"2026-05-18T12:27:43.054852+00:00"},{"alias_kind":"pith_short_8","alias_value":"ESG4M6TF","created_at":"2026-05-18T12:27:43.054852+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":1,"internal_anchor_count":1,"sample":[{"citing_arxiv_id":"2605.22489","citing_title":"Machine Learning Techniques for Astrophysics and Cosmology: Lyman-$\\alpha$ forest","ref_index":241,"is_internal_anchor":true}]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/ESG4M6TFPTAARTZZMBSKKDRFX4","json":"https://pith.science/pith/ESG4M6TFPTAARTZZMBSKKDRFX4.json","graph_json":"https://pith.science/api/pith-number/ESG4M6TFPTAARTZZMBSKKDRFX4/graph.json","events_json":"https://pith.science/api/pith-number/ESG4M6TFPTAARTZZMBSKKDRFX4/events.json","paper":"https://pith.science/paper/ESG4M6TF"},"agent_actions":{"view_html":"https://pith.science/pith/ESG4M6TFPTAARTZZMBSKKDRFX4","download_json":"https://pith.science/pith/ESG4M6TFPTAARTZZMBSKKDRFX4.json","view_paper":"https://pith.science/paper/ESG4M6TF","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1309.1477&json=true","fetch_graph":"https://pith.science/api/pith-number/ESG4M6TFPTAARTZZMBSKKDRFX4/graph.json","fetch_events":"https://pith.science/api/pith-number/ESG4M6TFPTAARTZZMBSKKDRFX4/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/ESG4M6TFPTAARTZZMBSKKDRFX4/action/timestamp_anchor","attest_storage":"https://pith.science/pith/ESG4M6TFPTAARTZZMBSKKDRFX4/action/storage_attestation","attest_author":"https://pith.science/pith/ESG4M6TFPTAARTZZMBSKKDRFX4/action/author_attestation","sign_citation":"https://pith.science/pith/ESG4M6TFPTAARTZZMBSKKDRFX4/action/citation_signature","submit_replication":"https://pith.science/pith/ESG4M6TFPTAARTZZMBSKKDRFX4/action/replication_record"}},"created_at":"2026-05-18T02:51:23.223687+00:00","updated_at":"2026-05-18T02:51:23.223687+00:00"}