{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2013:PRO4KLUWOJEQULJOLZKCD2WRFZ","short_pith_number":"pith:PRO4KLUW","schema_version":"1.0","canonical_sha256":"7c5dc52e9672490a2d2e5e5421ead12e410588edf4f0b31e90796d324be49343","source":{"kind":"arxiv","id":"1301.1423","version":2},"attestation_state":"computed","paper":{"title":"Statistical mechanics approach to 1-bit compressed sensing","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cond-mat.dis-nn","math.IT"],"primary_cat":"cs.IT","authors_text":"Yingying Xu, Yoshiyuki Kabashima","submitted_at":"2013-01-08T06:36:47Z","abstract_excerpt":"Compressed sensing is a technique for recovering a high-dimensional signal from lower-dimensional data, whose components represent partial information about the signal, utilizing prior knowledge on the sparsity of the signal. For further reducing the data size of the compressed expression, a scheme to recover the original signal utilizing only the sign of each entry of the linearly transformed vector was recently proposed. This approach is often termed the 1-bit compressed sensing. Here we analyze the typical performance of an L1-norm based signal recovery scheme for the 1-bit compressed sensi"},"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":"1301.1423","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.IT","submitted_at":"2013-01-08T06:36:47Z","cross_cats_sorted":["cond-mat.dis-nn","math.IT"],"title_canon_sha256":"72b9ad60ecdbc7d26a6c4d0a490c7e7a353cef1020334362132b701a6c7a04a5","abstract_canon_sha256":"4d42df9519a873edb173ee7c29a0375cb173e591fcc8c5369a46c61c90225d7d"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T02:58:57.492803Z","signature_b64":"t+73icp5WTiyE64TvfACdzzKHupVcTXB4bB1ggMG/l/upbghcA81KnJqyNfwJkoGh2PUHD2HF24V5Rx0Af+9DA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"7c5dc52e9672490a2d2e5e5421ead12e410588edf4f0b31e90796d324be49343","last_reissued_at":"2026-05-18T02:58:57.492020Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T02:58:57.492020Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Statistical mechanics approach to 1-bit compressed sensing","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cond-mat.dis-nn","math.IT"],"primary_cat":"cs.IT","authors_text":"Yingying Xu, Yoshiyuki Kabashima","submitted_at":"2013-01-08T06:36:47Z","abstract_excerpt":"Compressed sensing is a technique for recovering a high-dimensional signal from lower-dimensional data, whose components represent partial information about the signal, utilizing prior knowledge on the sparsity of the signal. For further reducing the data size of the compressed expression, a scheme to recover the original signal utilizing only the sign of each entry of the linearly transformed vector was recently proposed. This approach is often termed the 1-bit compressed sensing. Here we analyze the typical performance of an L1-norm based signal recovery scheme for the 1-bit compressed sensi"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1301.1423","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"},"aliases":[{"alias_kind":"arxiv","alias_value":"1301.1423","created_at":"2026-05-18T02:58:57.492159+00:00"},{"alias_kind":"arxiv_version","alias_value":"1301.1423v2","created_at":"2026-05-18T02:58:57.492159+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1301.1423","created_at":"2026-05-18T02:58:57.492159+00:00"},{"alias_kind":"pith_short_12","alias_value":"PRO4KLUWOJEQ","created_at":"2026-05-18T12:27:54.935989+00:00"},{"alias_kind":"pith_short_16","alias_value":"PRO4KLUWOJEQULJO","created_at":"2026-05-18T12:27:54.935989+00:00"},{"alias_kind":"pith_short_8","alias_value":"PRO4KLUW","created_at":"2026-05-18T12:27:54.935989+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/PRO4KLUWOJEQULJOLZKCD2WRFZ","json":"https://pith.science/pith/PRO4KLUWOJEQULJOLZKCD2WRFZ.json","graph_json":"https://pith.science/api/pith-number/PRO4KLUWOJEQULJOLZKCD2WRFZ/graph.json","events_json":"https://pith.science/api/pith-number/PRO4KLUWOJEQULJOLZKCD2WRFZ/events.json","paper":"https://pith.science/paper/PRO4KLUW"},"agent_actions":{"view_html":"https://pith.science/pith/PRO4KLUWOJEQULJOLZKCD2WRFZ","download_json":"https://pith.science/pith/PRO4KLUWOJEQULJOLZKCD2WRFZ.json","view_paper":"https://pith.science/paper/PRO4KLUW","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1301.1423&json=true","fetch_graph":"https://pith.science/api/pith-number/PRO4KLUWOJEQULJOLZKCD2WRFZ/graph.json","fetch_events":"https://pith.science/api/pith-number/PRO4KLUWOJEQULJOLZKCD2WRFZ/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/PRO4KLUWOJEQULJOLZKCD2WRFZ/action/timestamp_anchor","attest_storage":"https://pith.science/pith/PRO4KLUWOJEQULJOLZKCD2WRFZ/action/storage_attestation","attest_author":"https://pith.science/pith/PRO4KLUWOJEQULJOLZKCD2WRFZ/action/author_attestation","sign_citation":"https://pith.science/pith/PRO4KLUWOJEQULJOLZKCD2WRFZ/action/citation_signature","submit_replication":"https://pith.science/pith/PRO4KLUWOJEQULJOLZKCD2WRFZ/action/replication_record"}},"created_at":"2026-05-18T02:58:57.492159+00:00","updated_at":"2026-05-18T02:58:57.492159+00:00"}