{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2011:HCAKPSWNWCSCA532ZJDILQDIK5","short_pith_number":"pith:HCAKPSWN","schema_version":"1.0","canonical_sha256":"3880a7cacdb0a420777aca4685c068576112221255fc05efdeafc0230d82ed9f","source":{"kind":"arxiv","id":"1109.4440","version":2},"attestation_state":"computed","paper":{"title":"The cosmological analysis of X-ray cluster surveys: I- A new method for interpreting number counts","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"astro-ph.CO","authors_text":"Florian Pacaud, Marguerite Pierre, Nicolas Clerc, Tatyana Sadibekova","submitted_at":"2011-09-20T22:33:43Z","abstract_excerpt":"We present a new method aiming to simplify the cosmological analysis of X-ray cluster surveys. It is based on purely instrumental observable quantities, considered in a two-dimensional X-ray colour-magnitude diagram (hardness ratio versus count-rate). The basic principle is that, even in rather shallow surveys, substantial information on cluster redshift and temperature is present in the raw X-ray data and can be statistically extracted; in parallel, such diagrams can be readily predicted from an ab initio cosmological modeling. We illustrate the methodology for the case of a 100 deg2 XMM surv"},"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":"1109.4440","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"astro-ph.CO","submitted_at":"2011-09-20T22:33:43Z","cross_cats_sorted":[],"title_canon_sha256":"f2871a789d376eb219de26b5b26b66ee2dfc25d08b9af8c50bc5166702ec8447","abstract_canon_sha256":"fa38b0d27deaabc9471eec19f6173701e3a898479bb2956278910459d7159f79"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T02:00:27.408471Z","signature_b64":"KdwVJxD/Zaw/lt5Aot2gT+Y5dyIaaUvRw+LA2EC4voq7J3BuYbvG7cf4V5hMpGHheCvU2a79urifVdVkxMEcCw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"3880a7cacdb0a420777aca4685c068576112221255fc05efdeafc0230d82ed9f","last_reissued_at":"2026-05-18T02:00:27.407523Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T02:00:27.407523Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"The cosmological analysis of X-ray cluster surveys: I- A new method for interpreting number counts","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"astro-ph.CO","authors_text":"Florian Pacaud, Marguerite Pierre, Nicolas Clerc, Tatyana Sadibekova","submitted_at":"2011-09-20T22:33:43Z","abstract_excerpt":"We present a new method aiming to simplify the cosmological analysis of X-ray cluster surveys. It is based on purely instrumental observable quantities, considered in a two-dimensional X-ray colour-magnitude diagram (hardness ratio versus count-rate). The basic principle is that, even in rather shallow surveys, substantial information on cluster redshift and temperature is present in the raw X-ray data and can be statistically extracted; in parallel, such diagrams can be readily predicted from an ab initio cosmological modeling. We illustrate the methodology for the case of a 100 deg2 XMM surv"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1109.4440","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":"1109.4440","created_at":"2026-05-18T02:00:27.407724+00:00"},{"alias_kind":"arxiv_version","alias_value":"1109.4440v2","created_at":"2026-05-18T02:00:27.407724+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1109.4440","created_at":"2026-05-18T02:00:27.407724+00:00"},{"alias_kind":"pith_short_12","alias_value":"HCAKPSWNWCSC","created_at":"2026-05-18T12:26:30.835961+00:00"},{"alias_kind":"pith_short_16","alias_value":"HCAKPSWNWCSCA532","created_at":"2026-05-18T12:26:30.835961+00:00"},{"alias_kind":"pith_short_8","alias_value":"HCAKPSWN","created_at":"2026-05-18T12:26:30.835961+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":1,"internal_anchor_count":1,"sample":[{"citing_arxiv_id":"2507.01820","citing_title":"The Cosmological analysis of X-ray cluster surveys VII. Bypassing scaling relations with Lagrangian Deep Learning and Simulation-based inference","ref_index":15,"is_internal_anchor":true}]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/HCAKPSWNWCSCA532ZJDILQDIK5","json":"https://pith.science/pith/HCAKPSWNWCSCA532ZJDILQDIK5.json","graph_json":"https://pith.science/api/pith-number/HCAKPSWNWCSCA532ZJDILQDIK5/graph.json","events_json":"https://pith.science/api/pith-number/HCAKPSWNWCSCA532ZJDILQDIK5/events.json","paper":"https://pith.science/paper/HCAKPSWN"},"agent_actions":{"view_html":"https://pith.science/pith/HCAKPSWNWCSCA532ZJDILQDIK5","download_json":"https://pith.science/pith/HCAKPSWNWCSCA532ZJDILQDIK5.json","view_paper":"https://pith.science/paper/HCAKPSWN","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1109.4440&json=true","fetch_graph":"https://pith.science/api/pith-number/HCAKPSWNWCSCA532ZJDILQDIK5/graph.json","fetch_events":"https://pith.science/api/pith-number/HCAKPSWNWCSCA532ZJDILQDIK5/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/HCAKPSWNWCSCA532ZJDILQDIK5/action/timestamp_anchor","attest_storage":"https://pith.science/pith/HCAKPSWNWCSCA532ZJDILQDIK5/action/storage_attestation","attest_author":"https://pith.science/pith/HCAKPSWNWCSCA532ZJDILQDIK5/action/author_attestation","sign_citation":"https://pith.science/pith/HCAKPSWNWCSCA532ZJDILQDIK5/action/citation_signature","submit_replication":"https://pith.science/pith/HCAKPSWNWCSCA532ZJDILQDIK5/action/replication_record"}},"created_at":"2026-05-18T02:00:27.407724+00:00","updated_at":"2026-05-18T02:00:27.407724+00:00"}