{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2018:PAKRMM3B3WQHCBAZNM3BWUDFWL","short_pith_number":"pith:PAKRMM3B","canonical_record":{"source":{"id":"1802.03297","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.DS","submitted_at":"2018-02-08T16:41:57Z","cross_cats_sorted":[],"title_canon_sha256":"0ece2b78d1c0f5b1436dec2e996d8f35f84606d498c94e9e1694f7f66ab794ca","abstract_canon_sha256":"031e3e879f630b3f52df9953ddc83afd7764d21f03df6d4f6196461c6e2b6a18"},"schema_version":"1.0"},"canonical_sha256":"7815163361dda07104196b361b5065b2d7229005acf998dc7d2b569909c7c11b","source":{"kind":"arxiv","id":"1802.03297","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1802.03297","created_at":"2026-05-18T00:23:58Z"},{"alias_kind":"arxiv_version","alias_value":"1802.03297v1","created_at":"2026-05-18T00:23:58Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1802.03297","created_at":"2026-05-18T00:23:58Z"},{"alias_kind":"pith_short_12","alias_value":"PAKRMM3B3WQH","created_at":"2026-05-18T12:32:43Z"},{"alias_kind":"pith_short_16","alias_value":"PAKRMM3B3WQHCBAZ","created_at":"2026-05-18T12:32:43Z"},{"alias_kind":"pith_short_8","alias_value":"PAKRMM3B","created_at":"2026-05-18T12:32:43Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2018:PAKRMM3B3WQHCBAZNM3BWUDFWL","target":"record","payload":{"canonical_record":{"source":{"id":"1802.03297","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.DS","submitted_at":"2018-02-08T16:41:57Z","cross_cats_sorted":[],"title_canon_sha256":"0ece2b78d1c0f5b1436dec2e996d8f35f84606d498c94e9e1694f7f66ab794ca","abstract_canon_sha256":"031e3e879f630b3f52df9953ddc83afd7764d21f03df6d4f6196461c6e2b6a18"},"schema_version":"1.0"},"canonical_sha256":"7815163361dda07104196b361b5065b2d7229005acf998dc7d2b569909c7c11b","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:23:58.054775Z","signature_b64":"RbkQhowbtWKHiqR95iH3aKa6YVlIioMVlyeX3vATGqPe5ywCbS9qpjzQLHE6m6sgUII+zpvpX3cu4W+jfoXEDQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"7815163361dda07104196b361b5065b2d7229005acf998dc7d2b569909c7c11b","last_reissued_at":"2026-05-18T00:23:58.054253Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:23:58.054253Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1802.03297","source_version":1,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-05-18T00:23:58Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"StO2vykMCAPv/bPZiV5D/dt/GrPMXlCnqN6wm0rQCZRY1K8FmTU0YSFv9b6cGyntG7BpBe47cfiY6ZNhCzRoDg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-24T20:03:03.457749Z"},"content_sha256":"edb22218a31423cf075d97d0ee67a9b114e6f3b15c9731a7e0dc425a8e8c4c85","schema_version":"1.0","event_id":"sha256:edb22218a31423cf075d97d0ee67a9b114e6f3b15c9731a7e0dc425a8e8c4c85"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2018:PAKRMM3B3WQHCBAZNM3BWUDFWL","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Updating Dynamic Random Hyperbolic Graphs in Sublinear Time","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.DS","authors_text":"Henning Meyerhenke, Moritz von Looz","submitted_at":"2018-02-08T16:41:57Z","abstract_excerpt":"Generative network models play an important role in algorithm development, scaling studies, network analysis, and realistic system benchmarks for graph data sets. A complex network model gaining considerable popularity builds random hyperbolic graphs, generated by distributing points within a disk in the hyperbolic plane and then adding edges between points with a probability depending on their hyperbolic distance.\n  We present a dynamic extension to model gradual network change, while preserving at each step the point position probabilities. To process the dynamic changes efficiently, we form"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1802.03297","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"},"verdict_id":null},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-05-18T00:23:58Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"TyhYWyY4VN8j5ltPiR9L15740lRteF7U0Nq0hVm6VYaFO37vRoo0vG9Kh4rqfIrrHexNxw2vKeanmNnpe6hxAw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-24T20:03:03.458098Z"},"content_sha256":"7140793bbc8350b04f3b7025eb63b4857850ed95c7fcd0ee75435002384caef2","schema_version":"1.0","event_id":"sha256:7140793bbc8350b04f3b7025eb63b4857850ed95c7fcd0ee75435002384caef2"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/PAKRMM3B3WQHCBAZNM3BWUDFWL/bundle.json","state_url":"https://pith.science/pith/PAKRMM3B3WQHCBAZNM3BWUDFWL/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/PAKRMM3B3WQHCBAZNM3BWUDFWL/bundle.json","status":"primary"}],"public_keys":[{"key_id":"pith-v1-2026-05","algorithm":"ed25519","format":"raw","public_key_b64":"stVStoiQhXFxp4s2pdzPNoqVNBMojDU/fJ2db5S3CbM=","public_key_hex":"b2d552b68890857171a78b36a5dccf368a953413288c353f7c9d9d6f94b709b3","fingerprint_sha256_b32_first128bits":"RVFV5Z2OI2J3ZUO7ERDEBCYNKS","fingerprint_sha256_hex":"8d4b5ee74e4693bcd1df2446408b0d54","rotates_at":null,"url":"https://pith.science/pith-signing-key.json","notes":"Pith uses this Ed25519 key to sign canonical record SHA-256 digests. Verify with: ed25519_verify(public_key, message=canonical_sha256_bytes, signature=base64decode(signature_b64))."}],"merge_version":"pith-open-graph-merge-v1","built_at":"2026-06-24T20:03:03Z","links":{"resolver":"https://pith.science/pith/PAKRMM3B3WQHCBAZNM3BWUDFWL","bundle":"https://pith.science/pith/PAKRMM3B3WQHCBAZNM3BWUDFWL/bundle.json","state":"https://pith.science/pith/PAKRMM3B3WQHCBAZNM3BWUDFWL/state.json","well_known_bundle":"https://pith.science/.well-known/pith/PAKRMM3B3WQHCBAZNM3BWUDFWL/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2018:PAKRMM3B3WQHCBAZNM3BWUDFWL","merge_version":"pith-open-graph-merge-v1","event_count":2,"valid_event_count":2,"invalid_event_count":0,"equivocation_count":0,"current":{"canonical_record":{"metadata":{"abstract_canon_sha256":"031e3e879f630b3f52df9953ddc83afd7764d21f03df6d4f6196461c6e2b6a18","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.DS","submitted_at":"2018-02-08T16:41:57Z","title_canon_sha256":"0ece2b78d1c0f5b1436dec2e996d8f35f84606d498c94e9e1694f7f66ab794ca"},"schema_version":"1.0","source":{"id":"1802.03297","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1802.03297","created_at":"2026-05-18T00:23:58Z"},{"alias_kind":"arxiv_version","alias_value":"1802.03297v1","created_at":"2026-05-18T00:23:58Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1802.03297","created_at":"2026-05-18T00:23:58Z"},{"alias_kind":"pith_short_12","alias_value":"PAKRMM3B3WQH","created_at":"2026-05-18T12:32:43Z"},{"alias_kind":"pith_short_16","alias_value":"PAKRMM3B3WQHCBAZ","created_at":"2026-05-18T12:32:43Z"},{"alias_kind":"pith_short_8","alias_value":"PAKRMM3B","created_at":"2026-05-18T12:32:43Z"}],"graph_snapshots":[{"event_id":"sha256:7140793bbc8350b04f3b7025eb63b4857850ed95c7fcd0ee75435002384caef2","target":"graph","created_at":"2026-05-18T00:23:58Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"graph_snapshot":{"author_claims":{"count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","strong_count":0},"builder_version":"pith-number-builder-2026-05-17-v1","claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"paper":{"abstract_excerpt":"Generative network models play an important role in algorithm development, scaling studies, network analysis, and realistic system benchmarks for graph data sets. A complex network model gaining considerable popularity builds random hyperbolic graphs, generated by distributing points within a disk in the hyperbolic plane and then adding edges between points with a probability depending on their hyperbolic distance.\n  We present a dynamic extension to model gradual network change, while preserving at each step the point position probabilities. To process the dynamic changes efficiently, we form","authors_text":"Henning Meyerhenke, Moritz von Looz","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.DS","submitted_at":"2018-02-08T16:41:57Z","title":"Updating Dynamic Random Hyperbolic Graphs in Sublinear Time"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1802.03297","kind":"arxiv","version":1},"verdict":{"created_at":null,"id":null,"model_set":{},"one_line_summary":"","pipeline_version":null,"pith_extraction_headline":"","strongest_claim":"","weakest_assumption":""}},"verdict_id":null}}],"author_attestations":[],"timestamp_anchors":[],"storage_attestations":[],"citation_signatures":[],"replication_records":[],"corrections":[],"mirror_hints":[],"record_created":{"event_id":"sha256:edb22218a31423cf075d97d0ee67a9b114e6f3b15c9731a7e0dc425a8e8c4c85","target":"record","created_at":"2026-05-18T00:23:58Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"attestation_state":"computed","canonical_record":{"metadata":{"abstract_canon_sha256":"031e3e879f630b3f52df9953ddc83afd7764d21f03df6d4f6196461c6e2b6a18","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.DS","submitted_at":"2018-02-08T16:41:57Z","title_canon_sha256":"0ece2b78d1c0f5b1436dec2e996d8f35f84606d498c94e9e1694f7f66ab794ca"},"schema_version":"1.0","source":{"id":"1802.03297","kind":"arxiv","version":1}},"canonical_sha256":"7815163361dda07104196b361b5065b2d7229005acf998dc7d2b569909c7c11b","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"7815163361dda07104196b361b5065b2d7229005acf998dc7d2b569909c7c11b","first_computed_at":"2026-05-18T00:23:58.054253Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T00:23:58.054253Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"RbkQhowbtWKHiqR95iH3aKa6YVlIioMVlyeX3vATGqPe5ywCbS9qpjzQLHE6m6sgUII+zpvpX3cu4W+jfoXEDQ==","signature_status":"signed_v1","signed_at":"2026-05-18T00:23:58.054775Z","signed_message":"canonical_sha256_bytes"},"source_id":"1802.03297","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:edb22218a31423cf075d97d0ee67a9b114e6f3b15c9731a7e0dc425a8e8c4c85","sha256:7140793bbc8350b04f3b7025eb63b4857850ed95c7fcd0ee75435002384caef2"],"state_sha256":"acba6dd2818af4c981d2ccf00a64a1f5a5982d882ed41ff321d36fea0ff21c18"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"yi166HfAAfktdvUZQo1iYkNjd+Q5nGxO37ixVeSLb+fOtApnrpEJ7oEEx/V0dUo/XstXi9imtdUA7/NCOo2fDw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-06-24T20:03:03.460138Z","bundle_sha256":"b18afcf07cbe84288540faf5b70b18f6c3ea9524a9cf921e4bf7caefaf22095f"}}