{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2017:SAZ3HG7DSGSP3NDBJBRJRI3OMO","short_pith_number":"pith:SAZ3HG7D","schema_version":"1.0","canonical_sha256":"9033b39be391a4fdb461486298a36e6383ca888c7750d019403a549e12afe7d6","source":{"kind":"arxiv","id":"1707.02958","version":3},"attestation_state":"computed","paper":{"title":"Convex optimization over classes of multiparticle entanglement","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"quant-ph","authors_text":"Jiangwei Shang, Otfried G\\\"uhne","submitted_at":"2017-07-10T17:34:28Z","abstract_excerpt":"A well-known strategy to characterize multiparticle entanglement utilizes the notion of stochastic local operations and classical communication (SLOCC), but characterizing the resulting entanglement classes is difficult. Given a multiparticle quantum state, we first show that Gilbert's algorithm can be adapted to prove separability or membership in a certain entanglement class. We then present two algorithms for convex optimization over SLOCC classes. The first algorithm uses a simple gradient approach, while the other one employs the accelerated projected-gradient method. For demonstration, t"},"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":"1707.02958","kind":"arxiv","version":3},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"quant-ph","submitted_at":"2017-07-10T17:34:28Z","cross_cats_sorted":[],"title_canon_sha256":"e2670eac2820bd9800db3935441275de8a85e0098afa79b9db763665561b8b56","abstract_canon_sha256":"515bffcf76f49778b2574142b1b31f63ab90d752bb85de336b0c632d1ff2b0b2"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:24:35.290966Z","signature_b64":"2eDQJYNlyggUj3eiMd0rIqYd+i5lVDGty+zReUP+DsRWj+L+RyTFirjyPEIs6efsqb5KzvEvByjI91z0zQC1Dw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"9033b39be391a4fdb461486298a36e6383ca888c7750d019403a549e12afe7d6","last_reissued_at":"2026-05-18T00:24:35.290575Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:24:35.290575Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Convex optimization over classes of multiparticle entanglement","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"quant-ph","authors_text":"Jiangwei Shang, Otfried G\\\"uhne","submitted_at":"2017-07-10T17:34:28Z","abstract_excerpt":"A well-known strategy to characterize multiparticle entanglement utilizes the notion of stochastic local operations and classical communication (SLOCC), but characterizing the resulting entanglement classes is difficult. Given a multiparticle quantum state, we first show that Gilbert's algorithm can be adapted to prove separability or membership in a certain entanglement class. We then present two algorithms for convex optimization over SLOCC classes. The first algorithm uses a simple gradient approach, while the other one employs the accelerated projected-gradient method. For demonstration, t"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1707.02958","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":"1707.02958","created_at":"2026-05-18T00:24:35.290638+00:00"},{"alias_kind":"arxiv_version","alias_value":"1707.02958v3","created_at":"2026-05-18T00:24:35.290638+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1707.02958","created_at":"2026-05-18T00:24:35.290638+00:00"},{"alias_kind":"pith_short_12","alias_value":"SAZ3HG7DSGSP","created_at":"2026-05-18T12:31:43.269735+00:00"},{"alias_kind":"pith_short_16","alias_value":"SAZ3HG7DSGSP3NDB","created_at":"2026-05-18T12:31:43.269735+00:00"},{"alias_kind":"pith_short_8","alias_value":"SAZ3HG7D","created_at":"2026-05-18T12:31:43.269735+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":1,"internal_anchor_count":1,"sample":[{"citing_arxiv_id":"2504.07814","citing_title":"Estimating the best separable approximation of non-pure spin-squeezed states","ref_index":60,"is_internal_anchor":true}]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/SAZ3HG7DSGSP3NDBJBRJRI3OMO","json":"https://pith.science/pith/SAZ3HG7DSGSP3NDBJBRJRI3OMO.json","graph_json":"https://pith.science/api/pith-number/SAZ3HG7DSGSP3NDBJBRJRI3OMO/graph.json","events_json":"https://pith.science/api/pith-number/SAZ3HG7DSGSP3NDBJBRJRI3OMO/events.json","paper":"https://pith.science/paper/SAZ3HG7D"},"agent_actions":{"view_html":"https://pith.science/pith/SAZ3HG7DSGSP3NDBJBRJRI3OMO","download_json":"https://pith.science/pith/SAZ3HG7DSGSP3NDBJBRJRI3OMO.json","view_paper":"https://pith.science/paper/SAZ3HG7D","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1707.02958&json=true","fetch_graph":"https://pith.science/api/pith-number/SAZ3HG7DSGSP3NDBJBRJRI3OMO/graph.json","fetch_events":"https://pith.science/api/pith-number/SAZ3HG7DSGSP3NDBJBRJRI3OMO/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/SAZ3HG7DSGSP3NDBJBRJRI3OMO/action/timestamp_anchor","attest_storage":"https://pith.science/pith/SAZ3HG7DSGSP3NDBJBRJRI3OMO/action/storage_attestation","attest_author":"https://pith.science/pith/SAZ3HG7DSGSP3NDBJBRJRI3OMO/action/author_attestation","sign_citation":"https://pith.science/pith/SAZ3HG7DSGSP3NDBJBRJRI3OMO/action/citation_signature","submit_replication":"https://pith.science/pith/SAZ3HG7DSGSP3NDBJBRJRI3OMO/action/replication_record"}},"created_at":"2026-05-18T00:24:35.290638+00:00","updated_at":"2026-05-18T00:24:35.290638+00:00"}