{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2011:CRKASHXUEKUM4TAJZDS2KAB3BE","short_pith_number":"pith:CRKASHXU","schema_version":"1.0","canonical_sha256":"1454091ef422a8ce4c09c8e5a5003b0920e6e522ef2c53169b4e5bf33986757a","source":{"kind":"arxiv","id":"1111.6323","version":3},"attestation_state":"computed","paper":{"title":"Compressive Phase Retrieval From Squared Output Measurements Via Semidefinite Programming","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["stat.TH"],"primary_cat":"math.ST","authors_text":"Allen Y. Yang, Henrik Ohlsson, Roy Dong, S. Shankar Sastry","submitted_at":"2011-11-28T00:15:58Z","abstract_excerpt":"Given a linear system in a real or complex domain, linear regression aims to recover the model parameters from a set of observations. Recent studies in compressive sensing have successfully shown that under certain conditions, a linear program, namely, l1-minimization, guarantees recovery of sparse parameter signals even when the system is underdetermined. In this paper, we consider a more challenging problem: when the phase of the output measurements from a linear system is omitted. Using a lifting technique, we show that even though the phase information is missing, the sparse signal can be "},"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":"1111.6323","kind":"arxiv","version":3},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"math.ST","submitted_at":"2011-11-28T00:15:58Z","cross_cats_sorted":["stat.TH"],"title_canon_sha256":"bdb49f2df1e004fb91539df67cfe9ec66e1385d7f3364f995f626539bdb77a16","abstract_canon_sha256":"a9fe6f6448657a58a2157c578c1622be972ffc70ffe8b765b7e7914e237c0927"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:59:09.997428Z","signature_b64":"K7+IuOmmkRs3BLvDlyrVP3kYhjdmlcU9iFaDWKkgrQeZMIOHrOwqr3jOo6aBzNmypkHotRiqS9ZLTN/zH2jwDw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"1454091ef422a8ce4c09c8e5a5003b0920e6e522ef2c53169b4e5bf33986757a","last_reissued_at":"2026-05-18T00:59:09.996777Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:59:09.996777Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Compressive Phase Retrieval From Squared Output Measurements Via Semidefinite Programming","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["stat.TH"],"primary_cat":"math.ST","authors_text":"Allen Y. Yang, Henrik Ohlsson, Roy Dong, S. Shankar Sastry","submitted_at":"2011-11-28T00:15:58Z","abstract_excerpt":"Given a linear system in a real or complex domain, linear regression aims to recover the model parameters from a set of observations. Recent studies in compressive sensing have successfully shown that under certain conditions, a linear program, namely, l1-minimization, guarantees recovery of sparse parameter signals even when the system is underdetermined. In this paper, we consider a more challenging problem: when the phase of the output measurements from a linear system is omitted. Using a lifting technique, we show that even though the phase information is missing, the sparse signal can be "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1111.6323","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":""},"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":"1111.6323","created_at":"2026-05-18T00:59:09.996874+00:00"},{"alias_kind":"arxiv_version","alias_value":"1111.6323v3","created_at":"2026-05-18T00:59:09.996874+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1111.6323","created_at":"2026-05-18T00:59:09.996874+00:00"},{"alias_kind":"pith_short_12","alias_value":"CRKASHXUEKUM","created_at":"2026-05-18T12:26:26.731475+00:00"},{"alias_kind":"pith_short_16","alias_value":"CRKASHXUEKUM4TAJ","created_at":"2026-05-18T12:26:26.731475+00:00"},{"alias_kind":"pith_short_8","alias_value":"CRKASHXU","created_at":"2026-05-18T12:26:26.731475+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/CRKASHXUEKUM4TAJZDS2KAB3BE","json":"https://pith.science/pith/CRKASHXUEKUM4TAJZDS2KAB3BE.json","graph_json":"https://pith.science/api/pith-number/CRKASHXUEKUM4TAJZDS2KAB3BE/graph.json","events_json":"https://pith.science/api/pith-number/CRKASHXUEKUM4TAJZDS2KAB3BE/events.json","paper":"https://pith.science/paper/CRKASHXU"},"agent_actions":{"view_html":"https://pith.science/pith/CRKASHXUEKUM4TAJZDS2KAB3BE","download_json":"https://pith.science/pith/CRKASHXUEKUM4TAJZDS2KAB3BE.json","view_paper":"https://pith.science/paper/CRKASHXU","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1111.6323&json=true","fetch_graph":"https://pith.science/api/pith-number/CRKASHXUEKUM4TAJZDS2KAB3BE/graph.json","fetch_events":"https://pith.science/api/pith-number/CRKASHXUEKUM4TAJZDS2KAB3BE/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/CRKASHXUEKUM4TAJZDS2KAB3BE/action/timestamp_anchor","attest_storage":"https://pith.science/pith/CRKASHXUEKUM4TAJZDS2KAB3BE/action/storage_attestation","attest_author":"https://pith.science/pith/CRKASHXUEKUM4TAJZDS2KAB3BE/action/author_attestation","sign_citation":"https://pith.science/pith/CRKASHXUEKUM4TAJZDS2KAB3BE/action/citation_signature","submit_replication":"https://pith.science/pith/CRKASHXUEKUM4TAJZDS2KAB3BE/action/replication_record"}},"created_at":"2026-05-18T00:59:09.996874+00:00","updated_at":"2026-05-18T00:59:09.996874+00:00"}