{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2024:ONIRXJSEWGAT3LGLWTLJEDMG7C","short_pith_number":"pith:ONIRXJSE","schema_version":"1.0","canonical_sha256":"73511ba644b1813daccbb4d6920d86f88b7fab0a13e656bf3b006c70ddc724d3","source":{"kind":"arxiv","id":"2408.03840","version":3},"attestation_state":"computed","paper":{"title":"A New Metric Function for SC-based Polar Decoders: Polarization, Pruning, and Fast Decoders","license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","headline":"","cross_cats":["math.IT"],"primary_cat":"cs.IT","authors_text":"Hessam Mahdavifar, Mohsen Moradi","submitted_at":"2024-08-07T15:25:50Z","abstract_excerpt":"In this paper, we propose a method to obtain the optimal metric function at each depth of the polarization tree through a process we call polarization of the metric function. This polarization process generates an optimal metric at intermediate levels of the polarization tree, which can be applied in fast successive-cancellation-based (FSC) and SC list-based (FSCL) decoders -- decoders that partially explore the binary tree representation. We prove that at each step of the polarization tree, the expected value of the metric function random variable is the mutual information of the correspondin"},"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":"2408.03840","kind":"arxiv","version":3},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.IT","submitted_at":"2024-08-07T15:25:50Z","cross_cats_sorted":["math.IT"],"title_canon_sha256":"b14d1997b6e6d09b798ddddb01e49da2cac6201b0c1d4864be573f75911748bd","abstract_canon_sha256":"e1521109e2606532f183787f73ff1bf8cfa9e71f351f263335b288255f67ded5"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T12:05:09.579554Z","signature_b64":"XQdowXI/uaQ8ZTnMimOkPxk6u3ar5xjFasgn5cvu+g85luwed400kLqUsJmvzPwpWoCr73r5VPq5yO/Fa5jfAQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"73511ba644b1813daccbb4d6920d86f88b7fab0a13e656bf3b006c70ddc724d3","last_reissued_at":"2026-07-05T12:05:09.578939Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T12:05:09.578939Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"A New Metric Function for SC-based Polar Decoders: Polarization, Pruning, and Fast Decoders","license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","headline":"","cross_cats":["math.IT"],"primary_cat":"cs.IT","authors_text":"Hessam Mahdavifar, Mohsen Moradi","submitted_at":"2024-08-07T15:25:50Z","abstract_excerpt":"In this paper, we propose a method to obtain the optimal metric function at each depth of the polarization tree through a process we call polarization of the metric function. This polarization process generates an optimal metric at intermediate levels of the polarization tree, which can be applied in fast successive-cancellation-based (FSC) and SC list-based (FSCL) decoders -- decoders that partially explore the binary tree representation. We prove that at each step of the polarization tree, the expected value of the metric function random variable is the mutual information of the correspondin"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2408.03840","kind":"arxiv","version":3},"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/2408.03840/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":"2408.03840","created_at":"2026-07-05T12:05:09.579018+00:00"},{"alias_kind":"arxiv_version","alias_value":"2408.03840v3","created_at":"2026-07-05T12:05:09.579018+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2408.03840","created_at":"2026-07-05T12:05:09.579018+00:00"},{"alias_kind":"pith_short_12","alias_value":"ONIRXJSEWGAT","created_at":"2026-07-05T12:05:09.579018+00:00"},{"alias_kind":"pith_short_16","alias_value":"ONIRXJSEWGAT3LGL","created_at":"2026-07-05T12:05:09.579018+00:00"},{"alias_kind":"pith_short_8","alias_value":"ONIRXJSE","created_at":"2026-07-05T12:05:09.579018+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":1,"internal_anchor_count":1,"sample":[{"citing_arxiv_id":"2412.06072","citing_title":"PAC codes with Bounded-Complexity Sequential Decoding: Pareto Distribution and Code Design","ref_index":8,"is_internal_anchor":true}]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/ONIRXJSEWGAT3LGLWTLJEDMG7C","json":"https://pith.science/pith/ONIRXJSEWGAT3LGLWTLJEDMG7C.json","graph_json":"https://pith.science/api/pith-number/ONIRXJSEWGAT3LGLWTLJEDMG7C/graph.json","events_json":"https://pith.science/api/pith-number/ONIRXJSEWGAT3LGLWTLJEDMG7C/events.json","paper":"https://pith.science/paper/ONIRXJSE"},"agent_actions":{"view_html":"https://pith.science/pith/ONIRXJSEWGAT3LGLWTLJEDMG7C","download_json":"https://pith.science/pith/ONIRXJSEWGAT3LGLWTLJEDMG7C.json","view_paper":"https://pith.science/paper/ONIRXJSE","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2408.03840&json=true","fetch_graph":"https://pith.science/api/pith-number/ONIRXJSEWGAT3LGLWTLJEDMG7C/graph.json","fetch_events":"https://pith.science/api/pith-number/ONIRXJSEWGAT3LGLWTLJEDMG7C/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/ONIRXJSEWGAT3LGLWTLJEDMG7C/action/timestamp_anchor","attest_storage":"https://pith.science/pith/ONIRXJSEWGAT3LGLWTLJEDMG7C/action/storage_attestation","attest_author":"https://pith.science/pith/ONIRXJSEWGAT3LGLWTLJEDMG7C/action/author_attestation","sign_citation":"https://pith.science/pith/ONIRXJSEWGAT3LGLWTLJEDMG7C/action/citation_signature","submit_replication":"https://pith.science/pith/ONIRXJSEWGAT3LGLWTLJEDMG7C/action/replication_record"}},"created_at":"2026-07-05T12:05:09.579018+00:00","updated_at":"2026-07-05T12:05:09.579018+00:00"}