{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2026:KRWG74GNKKFKBBE2YQ3MXCRCMX","short_pith_number":"pith:KRWG74GN","schema_version":"1.0","canonical_sha256":"546c6ff0cd528aa0849ac436cb8a2265da581b32c33cbcebe27570a951eb79ba","source":{"kind":"arxiv","id":"2606.22929","version":1},"attestation_state":"computed","paper":{"title":"Mode Collapse in Nested Sampling","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["astro-ph.IM"],"primary_cat":"stat.CO","authors_text":"Johannes Buchner","submitted_at":"2026-06-22T07:05:58Z","abstract_excerpt":"Nested Sampling is a Monte Carlo algorithm enabling posterior estimation and Bayesian model comparison, and is especially robust in multi-modal posteriors. This is because nested sampling maintains a population of live points sampled from the entire prior. In each iteration, the population is advanced above a likelihood threshold, potentially discarding modes ruled out by the data. However, the Monte Carlo nature of point replenishment can also accidentally discard a mode. We draw a connection to the neutral Moran process in genetics, and quantify the occurrence probability of this failure mod"},"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":"2606.22929","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"stat.CO","submitted_at":"2026-06-22T07:05:58Z","cross_cats_sorted":["astro-ph.IM"],"title_canon_sha256":"4bb8de8fd2047e85b6ff771701be7b2e0f3786bda08d0a2c3b373523ef991446","abstract_canon_sha256":"8ccd6e866163384baa450841928790fc944b28169d126af2a9359bb3c046ac39"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-06-23T03:14:04.529089Z","signature_b64":"N7QMqXDeJKaupWWuU6cgVo+hya8FcL5744ML/jaY5XfoggSP/lWeXWDPAdLVZ+/6dH7QjQhv9ADZHiIfxLwLDw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"546c6ff0cd528aa0849ac436cb8a2265da581b32c33cbcebe27570a951eb79ba","last_reissued_at":"2026-06-23T03:14:04.528615Z","signature_status":"signed_v1","first_computed_at":"2026-06-23T03:14:04.528615Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Mode Collapse in Nested Sampling","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["astro-ph.IM"],"primary_cat":"stat.CO","authors_text":"Johannes Buchner","submitted_at":"2026-06-22T07:05:58Z","abstract_excerpt":"Nested Sampling is a Monte Carlo algorithm enabling posterior estimation and Bayesian model comparison, and is especially robust in multi-modal posteriors. This is because nested sampling maintains a population of live points sampled from the entire prior. In each iteration, the population is advanced above a likelihood threshold, potentially discarding modes ruled out by the data. However, the Monte Carlo nature of point replenishment can also accidentally discard a mode. We draw a connection to the neutral Moran process in genetics, and quantify the occurrence probability of this failure mod"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2606.22929","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/2606.22929/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":"2606.22929","created_at":"2026-06-23T03:14:04.528671+00:00"},{"alias_kind":"arxiv_version","alias_value":"2606.22929v1","created_at":"2026-06-23T03:14:04.528671+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2606.22929","created_at":"2026-06-23T03:14:04.528671+00:00"},{"alias_kind":"pith_short_12","alias_value":"KRWG74GNKKFK","created_at":"2026-06-23T03:14:04.528671+00:00"},{"alias_kind":"pith_short_16","alias_value":"KRWG74GNKKFKBBE2","created_at":"2026-06-23T03:14:04.528671+00:00"},{"alias_kind":"pith_short_8","alias_value":"KRWG74GN","created_at":"2026-06-23T03:14:04.528671+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/KRWG74GNKKFKBBE2YQ3MXCRCMX","json":"https://pith.science/pith/KRWG74GNKKFKBBE2YQ3MXCRCMX.json","graph_json":"https://pith.science/api/pith-number/KRWG74GNKKFKBBE2YQ3MXCRCMX/graph.json","events_json":"https://pith.science/api/pith-number/KRWG74GNKKFKBBE2YQ3MXCRCMX/events.json","paper":"https://pith.science/paper/KRWG74GN"},"agent_actions":{"view_html":"https://pith.science/pith/KRWG74GNKKFKBBE2YQ3MXCRCMX","download_json":"https://pith.science/pith/KRWG74GNKKFKBBE2YQ3MXCRCMX.json","view_paper":"https://pith.science/paper/KRWG74GN","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2606.22929&json=true","fetch_graph":"https://pith.science/api/pith-number/KRWG74GNKKFKBBE2YQ3MXCRCMX/graph.json","fetch_events":"https://pith.science/api/pith-number/KRWG74GNKKFKBBE2YQ3MXCRCMX/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/KRWG74GNKKFKBBE2YQ3MXCRCMX/action/timestamp_anchor","attest_storage":"https://pith.science/pith/KRWG74GNKKFKBBE2YQ3MXCRCMX/action/storage_attestation","attest_author":"https://pith.science/pith/KRWG74GNKKFKBBE2YQ3MXCRCMX/action/author_attestation","sign_citation":"https://pith.science/pith/KRWG74GNKKFKBBE2YQ3MXCRCMX/action/citation_signature","submit_replication":"https://pith.science/pith/KRWG74GNKKFKBBE2YQ3MXCRCMX/action/replication_record"}},"created_at":"2026-06-23T03:14:04.528671+00:00","updated_at":"2026-06-23T03:14:04.528671+00:00"}