{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2018:N2BKAGYYXVBW3RSESGZNV5ZW5T","short_pith_number":"pith:N2BKAGYY","schema_version":"1.0","canonical_sha256":"6e82a01b18bd436dc64491b2daf736ecd3585fe95b40b3e5f6d57bcc703f8293","source":{"kind":"arxiv","id":"1802.04743","version":1},"attestation_state":"computed","paper":{"title":"Direct sampling of the self-energy with Connected Determinant Monte Carlo","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cond-mat.str-el","authors_text":"Riccardo Rossi","submitted_at":"2018-02-13T17:08:15Z","abstract_excerpt":"In this note, we present an efficient algorithm to sample directly the self-energy in the framework of the Connected Determinant technique. The introduction of the formalism of many-variable formal power series is essential to the proof, and more generally it is a natural mathematical tool for diagrammatic expansions."},"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":"1802.04743","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cond-mat.str-el","submitted_at":"2018-02-13T17:08:15Z","cross_cats_sorted":[],"title_canon_sha256":"d8cbbd4d02cd8ce372558bb9aacd277f32a794407ebc3ddb5ae555e3705e0fd6","abstract_canon_sha256":"dd4a3a3cf113ed866ebf940b7afa775d9c1a768fe1ad76598d747445288597b0"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:23:41.531729Z","signature_b64":"6mq8tE7LWafPpwE515Q8VVk83Vd+S7u6vZmU2UHZTh9lq5ULMA4fkgBkm4yQl2UTJgK+h/O+VXHeZV1O7HDjCQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"6e82a01b18bd436dc64491b2daf736ecd3585fe95b40b3e5f6d57bcc703f8293","last_reissued_at":"2026-05-18T00:23:41.530993Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:23:41.530993Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Direct sampling of the self-energy with Connected Determinant Monte Carlo","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cond-mat.str-el","authors_text":"Riccardo Rossi","submitted_at":"2018-02-13T17:08:15Z","abstract_excerpt":"In this note, we present an efficient algorithm to sample directly the self-energy in the framework of the Connected Determinant technique. The introduction of the formalism of many-variable formal power series is essential to the proof, and more generally it is a natural mathematical tool for diagrammatic expansions."},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1802.04743","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":""},"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":"1802.04743","created_at":"2026-05-18T00:23:41.531115+00:00"},{"alias_kind":"arxiv_version","alias_value":"1802.04743v1","created_at":"2026-05-18T00:23:41.531115+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1802.04743","created_at":"2026-05-18T00:23:41.531115+00:00"},{"alias_kind":"pith_short_12","alias_value":"N2BKAGYYXVBW","created_at":"2026-05-18T12:32:40.477152+00:00"},{"alias_kind":"pith_short_16","alias_value":"N2BKAGYYXVBW3RSE","created_at":"2026-05-18T12:32:40.477152+00:00"},{"alias_kind":"pith_short_8","alias_value":"N2BKAGYY","created_at":"2026-05-18T12:32:40.477152+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/N2BKAGYYXVBW3RSESGZNV5ZW5T","json":"https://pith.science/pith/N2BKAGYYXVBW3RSESGZNV5ZW5T.json","graph_json":"https://pith.science/api/pith-number/N2BKAGYYXVBW3RSESGZNV5ZW5T/graph.json","events_json":"https://pith.science/api/pith-number/N2BKAGYYXVBW3RSESGZNV5ZW5T/events.json","paper":"https://pith.science/paper/N2BKAGYY"},"agent_actions":{"view_html":"https://pith.science/pith/N2BKAGYYXVBW3RSESGZNV5ZW5T","download_json":"https://pith.science/pith/N2BKAGYYXVBW3RSESGZNV5ZW5T.json","view_paper":"https://pith.science/paper/N2BKAGYY","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1802.04743&json=true","fetch_graph":"https://pith.science/api/pith-number/N2BKAGYYXVBW3RSESGZNV5ZW5T/graph.json","fetch_events":"https://pith.science/api/pith-number/N2BKAGYYXVBW3RSESGZNV5ZW5T/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/N2BKAGYYXVBW3RSESGZNV5ZW5T/action/timestamp_anchor","attest_storage":"https://pith.science/pith/N2BKAGYYXVBW3RSESGZNV5ZW5T/action/storage_attestation","attest_author":"https://pith.science/pith/N2BKAGYYXVBW3RSESGZNV5ZW5T/action/author_attestation","sign_citation":"https://pith.science/pith/N2BKAGYYXVBW3RSESGZNV5ZW5T/action/citation_signature","submit_replication":"https://pith.science/pith/N2BKAGYYXVBW3RSESGZNV5ZW5T/action/replication_record"}},"created_at":"2026-05-18T00:23:41.531115+00:00","updated_at":"2026-05-18T00:23:41.531115+00:00"}