{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2025:ASRMQMWTZ6JFEUTEQYYHII44NI","short_pith_number":"pith:ASRMQMWT","schema_version":"1.0","canonical_sha256":"04a2c832d3cf92525264863074239c6a0a429328e40cef3bbcdcb596b936c1eb","source":{"kind":"arxiv","id":"2505.09318","version":1},"attestation_state":"computed","paper":{"title":"Normal approximation for subgraph counts in age-dependent random connection models","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"math.PR","authors_text":"Christian Hirsch, Rapha\\\"el Lachi\\`eze-Rey, Takashi Owada","submitted_at":"2025-05-14T12:14:17Z","abstract_excerpt":"We study normal approximation of subgraph counts in a model of spatial scale-free random networks known as the age-dependent random connection model. In the light-tailed regime where only moments of order $(2 + \\varepsilon)$ are finite, we study the asymptotic normality of both clique and subtree counts. For clique counts, we establish a multivariate quantitative normal approximation result through the Malliavin-Stein method. In the more delicate case of subtree counts, we obtain distributional convergence based on a central limit theorem for sequences of associated random variables."},"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":"2505.09318","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"math.PR","submitted_at":"2025-05-14T12:14:17Z","cross_cats_sorted":[],"title_canon_sha256":"fdc9691d8540a081ddad3cb5a627250cb57c084b1a35db7ea8a0d53991381886","abstract_canon_sha256":"b864588818910973e2b3d60371d1046503dd2c3ef472fdbb898f530f2ccbca8a"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T11:03:06.282501Z","signature_b64":"dp10jKfTTHnmqHEsI5wBovsmby/4tlzGrb7M6eHd71vOeTsHJ952+dFA4oDukWSV0tuTkyRWyVCfF2c+er7GDw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"04a2c832d3cf92525264863074239c6a0a429328e40cef3bbcdcb596b936c1eb","last_reissued_at":"2026-07-05T11:03:06.282001Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T11:03:06.282001Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Normal approximation for subgraph counts in age-dependent random connection models","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"math.PR","authors_text":"Christian Hirsch, Rapha\\\"el Lachi\\`eze-Rey, Takashi Owada","submitted_at":"2025-05-14T12:14:17Z","abstract_excerpt":"We study normal approximation of subgraph counts in a model of spatial scale-free random networks known as the age-dependent random connection model. In the light-tailed regime where only moments of order $(2 + \\varepsilon)$ are finite, we study the asymptotic normality of both clique and subtree counts. For clique counts, we establish a multivariate quantitative normal approximation result through the Malliavin-Stein method. In the more delicate case of subtree counts, we obtain distributional convergence based on a central limit theorem for sequences of associated random variables."},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2505.09318","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/2505.09318/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":"2505.09318","created_at":"2026-07-05T11:03:06.282060+00:00"},{"alias_kind":"arxiv_version","alias_value":"2505.09318v1","created_at":"2026-07-05T11:03:06.282060+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2505.09318","created_at":"2026-07-05T11:03:06.282060+00:00"},{"alias_kind":"pith_short_12","alias_value":"ASRMQMWTZ6JF","created_at":"2026-07-05T11:03:06.282060+00:00"},{"alias_kind":"pith_short_16","alias_value":"ASRMQMWTZ6JFEUTE","created_at":"2026-07-05T11:03:06.282060+00:00"},{"alias_kind":"pith_short_8","alias_value":"ASRMQMWT","created_at":"2026-07-05T11:03:06.282060+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":1,"internal_anchor_count":0,"sample":[{"citing_arxiv_id":"2606.27898","citing_title":"Quantitative CLTs for Geometric Statistics of Dependent Marked Point Processes","ref_index":19,"is_internal_anchor":false}]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/ASRMQMWTZ6JFEUTEQYYHII44NI","json":"https://pith.science/pith/ASRMQMWTZ6JFEUTEQYYHII44NI.json","graph_json":"https://pith.science/api/pith-number/ASRMQMWTZ6JFEUTEQYYHII44NI/graph.json","events_json":"https://pith.science/api/pith-number/ASRMQMWTZ6JFEUTEQYYHII44NI/events.json","paper":"https://pith.science/paper/ASRMQMWT"},"agent_actions":{"view_html":"https://pith.science/pith/ASRMQMWTZ6JFEUTEQYYHII44NI","download_json":"https://pith.science/pith/ASRMQMWTZ6JFEUTEQYYHII44NI.json","view_paper":"https://pith.science/paper/ASRMQMWT","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2505.09318&json=true","fetch_graph":"https://pith.science/api/pith-number/ASRMQMWTZ6JFEUTEQYYHII44NI/graph.json","fetch_events":"https://pith.science/api/pith-number/ASRMQMWTZ6JFEUTEQYYHII44NI/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/ASRMQMWTZ6JFEUTEQYYHII44NI/action/timestamp_anchor","attest_storage":"https://pith.science/pith/ASRMQMWTZ6JFEUTEQYYHII44NI/action/storage_attestation","attest_author":"https://pith.science/pith/ASRMQMWTZ6JFEUTEQYYHII44NI/action/author_attestation","sign_citation":"https://pith.science/pith/ASRMQMWTZ6JFEUTEQYYHII44NI/action/citation_signature","submit_replication":"https://pith.science/pith/ASRMQMWTZ6JFEUTEQYYHII44NI/action/replication_record"}},"created_at":"2026-07-05T11:03:06.282060+00:00","updated_at":"2026-07-05T11:03:06.282060+00:00"}