{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2024:2MUU6CLRGFISTUDBKRE53MRNSW","short_pith_number":"pith:2MUU6CLR","schema_version":"1.0","canonical_sha256":"d3294f0971315129d0615449ddb22d9582a99510095bc2e57bb83e6b5646904f","source":{"kind":"arxiv","id":"2403.14750","version":2},"attestation_state":"computed","paper":{"title":"Fast likelihood-free inference in the LSS Stage IV era","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["astro-ph.IM"],"primary_cat":"astro-ph.CO","authors_text":"Christoph Weniger, Davide Sciotti, Guadalupe Ca\\~nas Herrera, Guillermo Franco Abell\\'an, Matteo Martinelli, Oleg Savchenko","submitted_at":"2024-03-21T18:00:02Z","abstract_excerpt":"Forthcoming large-scale structure (LSS) Stage IV surveys will provide us with unprecedented data to probe the nature of dark matter and dark energy. However, analysing these data with conventional Markov Chain Monte Carlo (MCMC) methods will be challenging, due to the increase in the number of nuisance parameters and the presence of intractable likelihoods. In light of this, we present the first application of Marginal Neural Ratio Estimation (MNRE) (a recent approach in simulation-based inference) to LSS photometric probes: weak lensing, galaxy clustering and the cross-correlation power spect"},"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":"2403.14750","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"astro-ph.CO","submitted_at":"2024-03-21T18:00:02Z","cross_cats_sorted":["astro-ph.IM"],"title_canon_sha256":"708a51685dfae795f0f801fd4c5f29fa9e155462c64d1a94bcaa0ad846688593","abstract_canon_sha256":"45362d1020ac82b0d170d57b2ad96f3258e4d6132c4ed7b6c64c7904753f4a90"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T09:41:33.264091Z","signature_b64":"coPBmxzFsSaQBqcGW6v5CBZHgpZu7uia/itxM127IWadFlKWUdZ7w+L97RGJ6yfSOMK1khwL3y26UfJ0LDemBQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"d3294f0971315129d0615449ddb22d9582a99510095bc2e57bb83e6b5646904f","last_reissued_at":"2026-07-05T09:41:33.263641Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T09:41:33.263641Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Fast likelihood-free inference in the LSS Stage IV era","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["astro-ph.IM"],"primary_cat":"astro-ph.CO","authors_text":"Christoph Weniger, Davide Sciotti, Guadalupe Ca\\~nas Herrera, Guillermo Franco Abell\\'an, Matteo Martinelli, Oleg Savchenko","submitted_at":"2024-03-21T18:00:02Z","abstract_excerpt":"Forthcoming large-scale structure (LSS) Stage IV surveys will provide us with unprecedented data to probe the nature of dark matter and dark energy. However, analysing these data with conventional Markov Chain Monte Carlo (MCMC) methods will be challenging, due to the increase in the number of nuisance parameters and the presence of intractable likelihoods. In light of this, we present the first application of Marginal Neural Ratio Estimation (MNRE) (a recent approach in simulation-based inference) to LSS photometric probes: weak lensing, galaxy clustering and the cross-correlation power spect"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2403.14750","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":""},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/2403.14750/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":"2403.14750","created_at":"2026-07-05T09:41:33.263703+00:00"},{"alias_kind":"arxiv_version","alias_value":"2403.14750v2","created_at":"2026-07-05T09:41:33.263703+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2403.14750","created_at":"2026-07-05T09:41:33.263703+00:00"},{"alias_kind":"pith_short_12","alias_value":"2MUU6CLRGFIS","created_at":"2026-07-05T09:41:33.263703+00:00"},{"alias_kind":"pith_short_16","alias_value":"2MUU6CLRGFISTUDB","created_at":"2026-07-05T09:41:33.263703+00:00"},{"alias_kind":"pith_short_8","alias_value":"2MUU6CLR","created_at":"2026-07-05T09:41:33.263703+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":1,"internal_anchor_count":1,"sample":[{"citing_arxiv_id":"2505.20193","citing_title":"A frequentist view on the two-body decaying dark matter model","ref_index":91,"is_internal_anchor":true}]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/2MUU6CLRGFISTUDBKRE53MRNSW","json":"https://pith.science/pith/2MUU6CLRGFISTUDBKRE53MRNSW.json","graph_json":"https://pith.science/api/pith-number/2MUU6CLRGFISTUDBKRE53MRNSW/graph.json","events_json":"https://pith.science/api/pith-number/2MUU6CLRGFISTUDBKRE53MRNSW/events.json","paper":"https://pith.science/paper/2MUU6CLR"},"agent_actions":{"view_html":"https://pith.science/pith/2MUU6CLRGFISTUDBKRE53MRNSW","download_json":"https://pith.science/pith/2MUU6CLRGFISTUDBKRE53MRNSW.json","view_paper":"https://pith.science/paper/2MUU6CLR","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2403.14750&json=true","fetch_graph":"https://pith.science/api/pith-number/2MUU6CLRGFISTUDBKRE53MRNSW/graph.json","fetch_events":"https://pith.science/api/pith-number/2MUU6CLRGFISTUDBKRE53MRNSW/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/2MUU6CLRGFISTUDBKRE53MRNSW/action/timestamp_anchor","attest_storage":"https://pith.science/pith/2MUU6CLRGFISTUDBKRE53MRNSW/action/storage_attestation","attest_author":"https://pith.science/pith/2MUU6CLRGFISTUDBKRE53MRNSW/action/author_attestation","sign_citation":"https://pith.science/pith/2MUU6CLRGFISTUDBKRE53MRNSW/action/citation_signature","submit_replication":"https://pith.science/pith/2MUU6CLRGFISTUDBKRE53MRNSW/action/replication_record"}},"created_at":"2026-07-05T09:41:33.263703+00:00","updated_at":"2026-07-05T09:41:33.263703+00:00"}