{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2024:7ZL2CIRLSUMP7QFEVULZSYWAL4","short_pith_number":"pith:7ZL2CIRL","schema_version":"1.0","canonical_sha256":"fe57a1222b9518ffc0a4ad179962c05f207f9462b43170371c1b96b5c7c6226b","source":{"kind":"arxiv","id":"2411.12207","version":1},"attestation_state":"computed","paper":{"title":"CMBAnalysis: A Modern Framework for High-Precision Cosmic Microwave Background Analysis","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["astro-ph.IM","cs.CE"],"primary_cat":"astro-ph.CO","authors_text":"Srikrishna S Kashyap","submitted_at":"2024-11-19T03:53:51Z","abstract_excerpt":"I present CMBAnalysis, a state-of-the-art Python framework designed for high-precision analysis of Cosmic Microwave Background (CMB) radiation data. This comprehensive package implements parallel Markov Chain Monte Carlo (MCMC) techniques for robust cosmological parameter estimation, featuring adaptive integration methods and sophisticated error propagation. The framework incorporates recent advances in computational cosmology, including support for extended cosmological models, detailed systematic error analysis, and optimized numerical algorithms. I demonstrate its capabilities through analy"},"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":"2411.12207","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"astro-ph.CO","submitted_at":"2024-11-19T03:53:51Z","cross_cats_sorted":["astro-ph.IM","cs.CE"],"title_canon_sha256":"b7605ce1fc36ebbcd21cd22d9485e2b78ae413123f3ce062268ba6b72f381c5f","abstract_canon_sha256":"3258c55a46b0dac41a8b01b9ea471082de4f746acfac077280cbe0d180e3acfd"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T09:37:17.696518Z","signature_b64":"AGwycG+StuGhI3uIioAdKSmpOi/+gAcDmHT/LqKqG2C9Tww8s7YbW070w11mlfBU+NMvhETGMOIHp7qZnNFQBA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"fe57a1222b9518ffc0a4ad179962c05f207f9462b43170371c1b96b5c7c6226b","last_reissued_at":"2026-07-05T09:37:17.696025Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T09:37:17.696025Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"CMBAnalysis: A Modern Framework for High-Precision Cosmic Microwave Background Analysis","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["astro-ph.IM","cs.CE"],"primary_cat":"astro-ph.CO","authors_text":"Srikrishna S Kashyap","submitted_at":"2024-11-19T03:53:51Z","abstract_excerpt":"I present CMBAnalysis, a state-of-the-art Python framework designed for high-precision analysis of Cosmic Microwave Background (CMB) radiation data. This comprehensive package implements parallel Markov Chain Monte Carlo (MCMC) techniques for robust cosmological parameter estimation, featuring adaptive integration methods and sophisticated error propagation. The framework incorporates recent advances in computational cosmology, including support for extended cosmological models, detailed systematic error analysis, and optimized numerical algorithms. I demonstrate its capabilities through analy"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2411.12207","kind":"arxiv","version":1},"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/2411.12207/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":"2411.12207","created_at":"2026-07-05T09:37:17.696085+00:00"},{"alias_kind":"arxiv_version","alias_value":"2411.12207v1","created_at":"2026-07-05T09:37:17.696085+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2411.12207","created_at":"2026-07-05T09:37:17.696085+00:00"},{"alias_kind":"pith_short_12","alias_value":"7ZL2CIRLSUMP","created_at":"2026-07-05T09:37:17.696085+00:00"},{"alias_kind":"pith_short_16","alias_value":"7ZL2CIRLSUMP7QFE","created_at":"2026-07-05T09:37:17.696085+00:00"},{"alias_kind":"pith_short_8","alias_value":"7ZL2CIRL","created_at":"2026-07-05T09:37:17.696085+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":0,"internal_anchor_count":0,"sample":[]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/7ZL2CIRLSUMP7QFEVULZSYWAL4","json":"https://pith.science/pith/7ZL2CIRLSUMP7QFEVULZSYWAL4.json","graph_json":"https://pith.science/api/pith-number/7ZL2CIRLSUMP7QFEVULZSYWAL4/graph.json","events_json":"https://pith.science/api/pith-number/7ZL2CIRLSUMP7QFEVULZSYWAL4/events.json","paper":"https://pith.science/paper/7ZL2CIRL"},"agent_actions":{"view_html":"https://pith.science/pith/7ZL2CIRLSUMP7QFEVULZSYWAL4","download_json":"https://pith.science/pith/7ZL2CIRLSUMP7QFEVULZSYWAL4.json","view_paper":"https://pith.science/paper/7ZL2CIRL","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2411.12207&json=true","fetch_graph":"https://pith.science/api/pith-number/7ZL2CIRLSUMP7QFEVULZSYWAL4/graph.json","fetch_events":"https://pith.science/api/pith-number/7ZL2CIRLSUMP7QFEVULZSYWAL4/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/7ZL2CIRLSUMP7QFEVULZSYWAL4/action/timestamp_anchor","attest_storage":"https://pith.science/pith/7ZL2CIRLSUMP7QFEVULZSYWAL4/action/storage_attestation","attest_author":"https://pith.science/pith/7ZL2CIRLSUMP7QFEVULZSYWAL4/action/author_attestation","sign_citation":"https://pith.science/pith/7ZL2CIRLSUMP7QFEVULZSYWAL4/action/citation_signature","submit_replication":"https://pith.science/pith/7ZL2CIRLSUMP7QFEVULZSYWAL4/action/replication_record"}},"created_at":"2026-07-05T09:37:17.696085+00:00","updated_at":"2026-07-05T09:37:17.696085+00:00"}