{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2026:I4TDLP5IIWQJEDNJYNU7UEIPRK","short_pith_number":"pith:I4TDLP5I","schema_version":"1.0","canonical_sha256":"472635bfa845a0920da9c369fa110f8a9cc09a9c217735699a4cf0068a5c341e","source":{"kind":"arxiv","id":"2605.18778","version":1},"attestation_state":"computed","paper":{"title":"T-REX: Fast and Dynamic Journey Planning for Continental-Scale Public Transit Networks","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.SI","authors_text":"Jonas Sauer, Patrick Steil, Sascha Witt","submitted_at":"2026-04-24T06:46:53Z","abstract_excerpt":"We present T-REX (Transfer-Ranked EXploration), a new algorithm for journey planning in public transit networks on the country and continental scale. Our algorithm applies the principles of multi-level overlays to Trip-Based Public Transit Routing (TB). Using a multi-level partition of the network, T-REX identifies transfers between trips that are relevant for long-distance travel in a short precomputation phase. This information is then used to prune irrelevant local transfers during a query. Like other state-of-the-art algorithms, T-REX Pareto-optimizes arrival time and the number of used tr"},"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":"2605.18778","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.SI","submitted_at":"2026-04-24T06:46:53Z","cross_cats_sorted":[],"title_canon_sha256":"35850b056855a950664f3a5065c5e8acd19959981237be8d71f80901e956d347","abstract_canon_sha256":"73d2b75780a6f5d95cc02cad7a6fdf4b1887d0a255193b9edaacc7890a1022f1"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-20T00:06:21.718860Z","signature_b64":"yVZX83yB2L1OebVJzqgFKs4uG5RC8RzpTvnUffC5qMIl8qc36kEwZgX8RrSf4e7a25xf2vyoR8sVsfDJqvKwCw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"472635bfa845a0920da9c369fa110f8a9cc09a9c217735699a4cf0068a5c341e","last_reissued_at":"2026-05-20T00:06:21.717504Z","signature_status":"signed_v1","first_computed_at":"2026-05-20T00:06:21.717504Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"T-REX: Fast and Dynamic Journey Planning for Continental-Scale Public Transit Networks","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.SI","authors_text":"Jonas Sauer, Patrick Steil, Sascha Witt","submitted_at":"2026-04-24T06:46:53Z","abstract_excerpt":"We present T-REX (Transfer-Ranked EXploration), a new algorithm for journey planning in public transit networks on the country and continental scale. Our algorithm applies the principles of multi-level overlays to Trip-Based Public Transit Routing (TB). Using a multi-level partition of the network, T-REX identifies transfers between trips that are relevant for long-distance travel in a short precomputation phase. This information is then used to prune irrelevant local transfers during a query. Like other state-of-the-art algorithms, T-REX Pareto-optimizes arrival time and the number of used tr"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2605.18778","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/2605.18778/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":"2605.18778","created_at":"2026-05-20T00:06:21.717651+00:00"},{"alias_kind":"arxiv_version","alias_value":"2605.18778v1","created_at":"2026-05-20T00:06:21.717651+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2605.18778","created_at":"2026-05-20T00:06:21.717651+00:00"},{"alias_kind":"pith_short_12","alias_value":"I4TDLP5IIWQJ","created_at":"2026-05-20T00:06:21.717651+00:00"},{"alias_kind":"pith_short_16","alias_value":"I4TDLP5IIWQJEDNJ","created_at":"2026-05-20T00:06:21.717651+00:00"},{"alias_kind":"pith_short_8","alias_value":"I4TDLP5I","created_at":"2026-05-20T00:06:21.717651+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/I4TDLP5IIWQJEDNJYNU7UEIPRK","json":"https://pith.science/pith/I4TDLP5IIWQJEDNJYNU7UEIPRK.json","graph_json":"https://pith.science/api/pith-number/I4TDLP5IIWQJEDNJYNU7UEIPRK/graph.json","events_json":"https://pith.science/api/pith-number/I4TDLP5IIWQJEDNJYNU7UEIPRK/events.json","paper":"https://pith.science/paper/I4TDLP5I"},"agent_actions":{"view_html":"https://pith.science/pith/I4TDLP5IIWQJEDNJYNU7UEIPRK","download_json":"https://pith.science/pith/I4TDLP5IIWQJEDNJYNU7UEIPRK.json","view_paper":"https://pith.science/paper/I4TDLP5I","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2605.18778&json=true","fetch_graph":"https://pith.science/api/pith-number/I4TDLP5IIWQJEDNJYNU7UEIPRK/graph.json","fetch_events":"https://pith.science/api/pith-number/I4TDLP5IIWQJEDNJYNU7UEIPRK/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/I4TDLP5IIWQJEDNJYNU7UEIPRK/action/timestamp_anchor","attest_storage":"https://pith.science/pith/I4TDLP5IIWQJEDNJYNU7UEIPRK/action/storage_attestation","attest_author":"https://pith.science/pith/I4TDLP5IIWQJEDNJYNU7UEIPRK/action/author_attestation","sign_citation":"https://pith.science/pith/I4TDLP5IIWQJEDNJYNU7UEIPRK/action/citation_signature","submit_replication":"https://pith.science/pith/I4TDLP5IIWQJEDNJYNU7UEIPRK/action/replication_record"}},"created_at":"2026-05-20T00:06:21.717651+00:00","updated_at":"2026-05-20T00:06:21.717651+00:00"}