{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2018:U36IUKG5GECAPU4CKYDO36J7YQ","short_pith_number":"pith:U36IUKG5","canonical_record":{"source":{"id":"1804.04574","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"math.CO","submitted_at":"2018-04-12T15:36:51Z","cross_cats_sorted":[],"title_canon_sha256":"8c290f14407af6e1689d5ebb72c8b35eab1bbe361ec31761e4fb58c36f33b230","abstract_canon_sha256":"fb684f972fff9eba4c0c1cdb98d4ce3f7df00dd40fda304de8b9ae9ff834184a"},"schema_version":"1.0"},"canonical_sha256":"a6fc8a28dd310407d3825606edf93fc4079cb1867913a72445a19c41e7507755","source":{"kind":"arxiv","id":"1804.04574","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1804.04574","created_at":"2026-05-17T23:59:09Z"},{"alias_kind":"arxiv_version","alias_value":"1804.04574v2","created_at":"2026-05-17T23:59:09Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1804.04574","created_at":"2026-05-17T23:59:09Z"},{"alias_kind":"pith_short_12","alias_value":"U36IUKG5GECA","created_at":"2026-05-18T12:32:56Z"},{"alias_kind":"pith_short_16","alias_value":"U36IUKG5GECAPU4C","created_at":"2026-05-18T12:32:56Z"},{"alias_kind":"pith_short_8","alias_value":"U36IUKG5","created_at":"2026-05-18T12:32:56Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2018:U36IUKG5GECAPU4CKYDO36J7YQ","target":"record","payload":{"canonical_record":{"source":{"id":"1804.04574","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"math.CO","submitted_at":"2018-04-12T15:36:51Z","cross_cats_sorted":[],"title_canon_sha256":"8c290f14407af6e1689d5ebb72c8b35eab1bbe361ec31761e4fb58c36f33b230","abstract_canon_sha256":"fb684f972fff9eba4c0c1cdb98d4ce3f7df00dd40fda304de8b9ae9ff834184a"},"schema_version":"1.0"},"canonical_sha256":"a6fc8a28dd310407d3825606edf93fc4079cb1867913a72445a19c41e7507755","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-17T23:59:09.253450Z","signature_b64":"72qphQZvdIKbEhjz6LHWpJnKgwatA774yDm74P762hFVPn7kgIZfx6u45nd8U5LK4mZeiS1TU2oLP3+7wfGYDw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"a6fc8a28dd310407d3825606edf93fc4079cb1867913a72445a19c41e7507755","last_reissued_at":"2026-05-17T23:59:09.252903Z","signature_status":"signed_v1","first_computed_at":"2026-05-17T23:59:09.252903Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1804.04574","source_version":2,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-05-17T23:59:09Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"aEbkule1ylBMFinqKGh14jPnfkDGiw4S4uC3hME82LQK0dVaxjtl5+KwOJEGMOsUQBIO4l/9Qe4MQV2zhlJLDg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-03T22:58:15.207585Z"},"content_sha256":"5e05e2f39bf2d29bb5d782ac3d896ba68056ce4c3ffc145cca4657cffbbffaf4","schema_version":"1.0","event_id":"sha256:5e05e2f39bf2d29bb5d782ac3d896ba68056ce4c3ffc145cca4657cffbbffaf4"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2018:U36IUKG5GECAPU4CKYDO36J7YQ","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Graph Reconstruction from Path Correlation Data","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"math.CO","authors_text":"Gregory Berkolaiko, Kyriakos Manousakis, Mahmood Ettehad, Nick Duffield","submitted_at":"2018-04-12T15:36:51Z","abstract_excerpt":"A communication network can be modeled as a directed connected graph with edge weights that characterize performance metrics such as loss and delay. Network tomography aims to infer these edge weights from their pathwise versions measured on a set of intersecting paths between a subset of boundary vertices, and even the underlying graph when this is not known. In particular, temporal correlations between path metrics have been used infer composite weights on the subpath formed by the path intersection. We call these subpath weights the Path Correlation Data. In this paper we ask the following "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1804.04574","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":""},"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":"2026-05-17T23:59:09Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"Lz+lTKcBoUtzwU1f/bERpMpZKr9QLqV/axJmaz/radiBi1LN5Q0wGaOqE+xMV3xIMDWTe9k3LDjO8JMpdBIVCw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-03T22:58:15.207922Z"},"content_sha256":"d8b0b427974c00077624ffdd4c1c7d8212c8f65c1dd1ed222fbd61627afbfb7a","schema_version":"1.0","event_id":"sha256:d8b0b427974c00077624ffdd4c1c7d8212c8f65c1dd1ed222fbd61627afbfb7a"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/U36IUKG5GECAPU4CKYDO36J7YQ/bundle.json","state_url":"https://pith.science/pith/U36IUKG5GECAPU4CKYDO36J7YQ/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/U36IUKG5GECAPU4CKYDO36J7YQ/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":"2026-06-03T22:58:15Z","links":{"resolver":"https://pith.science/pith/U36IUKG5GECAPU4CKYDO36J7YQ","bundle":"https://pith.science/pith/U36IUKG5GECAPU4CKYDO36J7YQ/bundle.json","state":"https://pith.science/pith/U36IUKG5GECAPU4CKYDO36J7YQ/state.json","well_known_bundle":"https://pith.science/.well-known/pith/U36IUKG5GECAPU4CKYDO36J7YQ/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2018:U36IUKG5GECAPU4CKYDO36J7YQ","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":"fb684f972fff9eba4c0c1cdb98d4ce3f7df00dd40fda304de8b9ae9ff834184a","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"math.CO","submitted_at":"2018-04-12T15:36:51Z","title_canon_sha256":"8c290f14407af6e1689d5ebb72c8b35eab1bbe361ec31761e4fb58c36f33b230"},"schema_version":"1.0","source":{"id":"1804.04574","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1804.04574","created_at":"2026-05-17T23:59:09Z"},{"alias_kind":"arxiv_version","alias_value":"1804.04574v2","created_at":"2026-05-17T23:59:09Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1804.04574","created_at":"2026-05-17T23:59:09Z"},{"alias_kind":"pith_short_12","alias_value":"U36IUKG5GECA","created_at":"2026-05-18T12:32:56Z"},{"alias_kind":"pith_short_16","alias_value":"U36IUKG5GECAPU4C","created_at":"2026-05-18T12:32:56Z"},{"alias_kind":"pith_short_8","alias_value":"U36IUKG5","created_at":"2026-05-18T12:32:56Z"}],"graph_snapshots":[{"event_id":"sha256:d8b0b427974c00077624ffdd4c1c7d8212c8f65c1dd1ed222fbd61627afbfb7a","target":"graph","created_at":"2026-05-17T23:59:09Z","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":"A communication network can be modeled as a directed connected graph with edge weights that characterize performance metrics such as loss and delay. Network tomography aims to infer these edge weights from their pathwise versions measured on a set of intersecting paths between a subset of boundary vertices, and even the underlying graph when this is not known. In particular, temporal correlations between path metrics have been used infer composite weights on the subpath formed by the path intersection. We call these subpath weights the Path Correlation Data. In this paper we ask the following ","authors_text":"Gregory Berkolaiko, Kyriakos Manousakis, Mahmood Ettehad, Nick Duffield","cross_cats":[],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"math.CO","submitted_at":"2018-04-12T15:36:51Z","title":"Graph Reconstruction from Path Correlation Data"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1804.04574","kind":"arxiv","version":2},"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":"sha256:5e05e2f39bf2d29bb5d782ac3d896ba68056ce4c3ffc145cca4657cffbbffaf4","target":"record","created_at":"2026-05-17T23:59:09Z","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":"fb684f972fff9eba4c0c1cdb98d4ce3f7df00dd40fda304de8b9ae9ff834184a","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"math.CO","submitted_at":"2018-04-12T15:36:51Z","title_canon_sha256":"8c290f14407af6e1689d5ebb72c8b35eab1bbe361ec31761e4fb58c36f33b230"},"schema_version":"1.0","source":{"id":"1804.04574","kind":"arxiv","version":2}},"canonical_sha256":"a6fc8a28dd310407d3825606edf93fc4079cb1867913a72445a19c41e7507755","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"a6fc8a28dd310407d3825606edf93fc4079cb1867913a72445a19c41e7507755","first_computed_at":"2026-05-17T23:59:09.252903Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-17T23:59:09.252903Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"72qphQZvdIKbEhjz6LHWpJnKgwatA774yDm74P762hFVPn7kgIZfx6u45nd8U5LK4mZeiS1TU2oLP3+7wfGYDw==","signature_status":"signed_v1","signed_at":"2026-05-17T23:59:09.253450Z","signed_message":"canonical_sha256_bytes"},"source_id":"1804.04574","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:5e05e2f39bf2d29bb5d782ac3d896ba68056ce4c3ffc145cca4657cffbbffaf4","sha256:d8b0b427974c00077624ffdd4c1c7d8212c8f65c1dd1ed222fbd61627afbfb7a"],"state_sha256":"2067091828ea10f3fb52f714c8441d9f4284bb57ef40b2ba39f0c6b46299ed8f"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"FjSTsfzEbUkGaXliwcs3uyD0QYWL3Ci/4rCoBHDBfHhnPdtRwW2zwPaMUrimh0MZlwDW7pV2OT811BQ+cbYJAw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-06-03T22:58:15.209797Z","bundle_sha256":"34159d749562d0c2d322ac06cd9878b38fb9da04d40112276279cbbdfbe4148a"}}