{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2023:6YWXLBLHPVNDS3X5EC2IQCM2DN","short_pith_number":"pith:6YWXLBLH","schema_version":"1.0","canonical_sha256":"f62d7585677d5a396efd20b488099a1b6b80e86d16e5e70c0349ad926dc4dc65","source":{"kind":"arxiv","id":"2307.00971","version":4},"attestation_state":"computed","paper":{"title":"New Prophet Inequalities via Poissonization and Sharding","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.DS","authors_text":"Elfarouk Harb","submitted_at":"2023-07-03T12:44:00Z","abstract_excerpt":"This work introduces \\emph{sharding} and \\emph{Poissonization} as a unified framework for analyzing prophet inequalities. Sharding involves splitting a random variable into several independent random variables, shards, that collectively mimic the original variable's behavior. We combine this with Poissonization, where these shards are modeled using a Poisson distribution. Despite the simplicity of our framework, we improve the competitive ratio analysis of a dozen well studied prophet inequalities in the literature, some of which have been studied for decades. This includes the \\textsc{Top-$1$"},"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":"2307.00971","kind":"arxiv","version":4},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.DS","submitted_at":"2023-07-03T12:44:00Z","cross_cats_sorted":[],"title_canon_sha256":"7731dbd94a8582deb61aadf5e286bb144c696c1a84db52f69308cee3b2aa8f17","abstract_canon_sha256":"a23b771e6cb642e498549352acc9236a48131364999b015bb24361d1be281021"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T08:04:13.184715Z","signature_b64":"325JVHkRx8z0ygVrHrihG2rYL6jDMN3rQPzgrlfx/+apPpFyoxPkEK6l8DQuPJbzuQyedKjoSG6rP3ESXZv5Cg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"f62d7585677d5a396efd20b488099a1b6b80e86d16e5e70c0349ad926dc4dc65","last_reissued_at":"2026-07-05T08:04:13.184250Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T08:04:13.184250Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"New Prophet Inequalities via Poissonization and Sharding","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.DS","authors_text":"Elfarouk Harb","submitted_at":"2023-07-03T12:44:00Z","abstract_excerpt":"This work introduces \\emph{sharding} and \\emph{Poissonization} as a unified framework for analyzing prophet inequalities. Sharding involves splitting a random variable into several independent random variables, shards, that collectively mimic the original variable's behavior. We combine this with Poissonization, where these shards are modeled using a Poisson distribution. Despite the simplicity of our framework, we improve the competitive ratio analysis of a dozen well studied prophet inequalities in the literature, some of which have been studied for decades. This includes the \\textsc{Top-$1$"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2307.00971","kind":"arxiv","version":4},"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/2307.00971/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":"2307.00971","created_at":"2026-07-05T08:04:13.184325+00:00"},{"alias_kind":"arxiv_version","alias_value":"2307.00971v4","created_at":"2026-07-05T08:04:13.184325+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2307.00971","created_at":"2026-07-05T08:04:13.184325+00:00"},{"alias_kind":"pith_short_12","alias_value":"6YWXLBLHPVND","created_at":"2026-07-05T08:04:13.184325+00:00"},{"alias_kind":"pith_short_16","alias_value":"6YWXLBLHPVNDS3X5","created_at":"2026-07-05T08:04:13.184325+00:00"},{"alias_kind":"pith_short_8","alias_value":"6YWXLBLH","created_at":"2026-07-05T08:04:13.184325+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":1,"internal_anchor_count":1,"sample":[{"citing_arxiv_id":"2411.10892","citing_title":"The Competition Complexity of Prophet Secretary","ref_index":25,"is_internal_anchor":true}]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/6YWXLBLHPVNDS3X5EC2IQCM2DN","json":"https://pith.science/pith/6YWXLBLHPVNDS3X5EC2IQCM2DN.json","graph_json":"https://pith.science/api/pith-number/6YWXLBLHPVNDS3X5EC2IQCM2DN/graph.json","events_json":"https://pith.science/api/pith-number/6YWXLBLHPVNDS3X5EC2IQCM2DN/events.json","paper":"https://pith.science/paper/6YWXLBLH"},"agent_actions":{"view_html":"https://pith.science/pith/6YWXLBLHPVNDS3X5EC2IQCM2DN","download_json":"https://pith.science/pith/6YWXLBLHPVNDS3X5EC2IQCM2DN.json","view_paper":"https://pith.science/paper/6YWXLBLH","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2307.00971&json=true","fetch_graph":"https://pith.science/api/pith-number/6YWXLBLHPVNDS3X5EC2IQCM2DN/graph.json","fetch_events":"https://pith.science/api/pith-number/6YWXLBLHPVNDS3X5EC2IQCM2DN/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/6YWXLBLHPVNDS3X5EC2IQCM2DN/action/timestamp_anchor","attest_storage":"https://pith.science/pith/6YWXLBLHPVNDS3X5EC2IQCM2DN/action/storage_attestation","attest_author":"https://pith.science/pith/6YWXLBLHPVNDS3X5EC2IQCM2DN/action/author_attestation","sign_citation":"https://pith.science/pith/6YWXLBLHPVNDS3X5EC2IQCM2DN/action/citation_signature","submit_replication":"https://pith.science/pith/6YWXLBLHPVNDS3X5EC2IQCM2DN/action/replication_record"}},"created_at":"2026-07-05T08:04:13.184325+00:00","updated_at":"2026-07-05T08:04:13.184325+00:00"}