{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2023:FYNX3C4V7ILEQAHDNLKJWRGRJ3","short_pith_number":"pith:FYNX3C4V","schema_version":"1.0","canonical_sha256":"2e1b7d8b95fa164800e36ad49b44d14ec998ffcdc8948fbba7e9e7be9978207f","source":{"kind":"arxiv","id":"2310.17834","version":1},"attestation_state":"computed","paper":{"title":"Full Shape Cosmology Analysis from BOSS in configuration space using Neural Network Acceleration","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"astro-ph.CO","authors_text":"Alejandro Aviles, Mariana Vargas-Maga\\~na, Miguel Icaza-Lizaola, Sadi Ramirez, Sebastien Fromenteau","submitted_at":"2023-10-27T01:10:10Z","abstract_excerpt":"Recently, a new wave of full modeling analyses have emerged within the Large-Scale Structure community, leading mostly to tighter constraints on the estimation of cosmological parameters, when compared with standard approaches used over the last decade by collaboration analyses of stage III experiments. However, the majority of these full-shape analyses have primarily been conducted in Fourier space, with limited emphasis on exploring the configuration space. Investigating n-point correlations in configuration space demands a higher computational cost compared to Fourier space because it typic"},"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":"2310.17834","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"astro-ph.CO","submitted_at":"2023-10-27T01:10:10Z","cross_cats_sorted":[],"title_canon_sha256":"7b28317ab04b073b1a8034a7b3f1932b835b316f92d3f8ed3121adc929857523","abstract_canon_sha256":"9570bb5fc7a1d0a64c4d63727321ab7ceffe77bfe702cbc4cd04e6378361c2db"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T07:05:53.417565Z","signature_b64":"dH2of8XIkbXiorlFqfFvmCuoL+VVjhNl+An6NDULckTQ1j4u9w2u+Tj8OklVo1HzV8ynbWzFYXMhS8LV1s87Ag==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"2e1b7d8b95fa164800e36ad49b44d14ec998ffcdc8948fbba7e9e7be9978207f","last_reissued_at":"2026-07-05T07:05:53.417189Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T07:05:53.417189Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Full Shape Cosmology Analysis from BOSS in configuration space using Neural Network Acceleration","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"astro-ph.CO","authors_text":"Alejandro Aviles, Mariana Vargas-Maga\\~na, Miguel Icaza-Lizaola, Sadi Ramirez, Sebastien Fromenteau","submitted_at":"2023-10-27T01:10:10Z","abstract_excerpt":"Recently, a new wave of full modeling analyses have emerged within the Large-Scale Structure community, leading mostly to tighter constraints on the estimation of cosmological parameters, when compared with standard approaches used over the last decade by collaboration analyses of stage III experiments. However, the majority of these full-shape analyses have primarily been conducted in Fourier space, with limited emphasis on exploring the configuration space. Investigating n-point correlations in configuration space demands a higher computational cost compared to Fourier space because it typic"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2310.17834","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/2310.17834/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":"2310.17834","created_at":"2026-07-05T07:05:53.417245+00:00"},{"alias_kind":"arxiv_version","alias_value":"2310.17834v1","created_at":"2026-07-05T07:05:53.417245+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2310.17834","created_at":"2026-07-05T07:05:53.417245+00:00"},{"alias_kind":"pith_short_12","alias_value":"FYNX3C4V7ILE","created_at":"2026-07-05T07:05:53.417245+00:00"},{"alias_kind":"pith_short_16","alias_value":"FYNX3C4V7ILEQAHD","created_at":"2026-07-05T07:05:53.417245+00:00"},{"alias_kind":"pith_short_8","alias_value":"FYNX3C4V","created_at":"2026-07-05T07:05:53.417245+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":1,"internal_anchor_count":0,"sample":[{"citing_arxiv_id":"2604.08895","citing_title":"FolpsD: combining EFT and phenomenological approaches for joint power spectrum and bispectrum analyses","ref_index":21,"is_internal_anchor":false}]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/FYNX3C4V7ILEQAHDNLKJWRGRJ3","json":"https://pith.science/pith/FYNX3C4V7ILEQAHDNLKJWRGRJ3.json","graph_json":"https://pith.science/api/pith-number/FYNX3C4V7ILEQAHDNLKJWRGRJ3/graph.json","events_json":"https://pith.science/api/pith-number/FYNX3C4V7ILEQAHDNLKJWRGRJ3/events.json","paper":"https://pith.science/paper/FYNX3C4V"},"agent_actions":{"view_html":"https://pith.science/pith/FYNX3C4V7ILEQAHDNLKJWRGRJ3","download_json":"https://pith.science/pith/FYNX3C4V7ILEQAHDNLKJWRGRJ3.json","view_paper":"https://pith.science/paper/FYNX3C4V","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2310.17834&json=true","fetch_graph":"https://pith.science/api/pith-number/FYNX3C4V7ILEQAHDNLKJWRGRJ3/graph.json","fetch_events":"https://pith.science/api/pith-number/FYNX3C4V7ILEQAHDNLKJWRGRJ3/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/FYNX3C4V7ILEQAHDNLKJWRGRJ3/action/timestamp_anchor","attest_storage":"https://pith.science/pith/FYNX3C4V7ILEQAHDNLKJWRGRJ3/action/storage_attestation","attest_author":"https://pith.science/pith/FYNX3C4V7ILEQAHDNLKJWRGRJ3/action/author_attestation","sign_citation":"https://pith.science/pith/FYNX3C4V7ILEQAHDNLKJWRGRJ3/action/citation_signature","submit_replication":"https://pith.science/pith/FYNX3C4V7ILEQAHDNLKJWRGRJ3/action/replication_record"}},"created_at":"2026-07-05T07:05:53.417245+00:00","updated_at":"2026-07-05T07:05:53.417245+00:00"}