{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2021:RZGRS3AJRJI23HNBHIMYAFGR45","short_pith_number":"pith:RZGRS3AJ","schema_version":"1.0","canonical_sha256":"8e4d196c098a51ad9da13a198014d1e77a6ef9860752ac3a00b362260bc7348d","source":{"kind":"arxiv","id":"2108.03325","version":3},"attestation_state":"computed","paper":{"title":"Continuous-variable optimization with neural network quantum states","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["math.OC"],"primary_cat":"quant-ph","authors_text":"David Gorsich, Paramsothy Jayakumar, Shravan Veerapaneni, Yabin Zhang","submitted_at":"2021-08-06T22:45:09Z","abstract_excerpt":"Inspired by proposals for continuous-variable quantum approximate optimization (CV-QAOA), we investigate the utility of continuous-variable neural network quantum states (CV-NQS) for performing continuous optimization, focusing on the ground state optimization of the classical antiferromagnetic rotor model. Numerical experiments conducted using variational Monte Carlo with CV-NQS indicate that although the non-local algorithm succeeds in finding ground states competitive with the local gradient search methods, the proposal suffers from unfavorable scaling. A number of proposed extensions are p"},"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":"2108.03325","kind":"arxiv","version":3},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"quant-ph","submitted_at":"2021-08-06T22:45:09Z","cross_cats_sorted":["math.OC"],"title_canon_sha256":"58ef128f298c6b7de62e3017cc0681b4f4f5b71f65c5e0b50c21613332e05c1a","abstract_canon_sha256":"85527751c3d6c27ba29cb4a8c10a22a2b68d7f4efd6f00796be8faa2f11dc53b"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T03:46:21.230077Z","signature_b64":"rPb7X5O13r6fyXAQwaIIkSv3vh9H9qxvZopytFkS4nUIdqwPNIWx6fEIPRJBXgKB8jX6GijrcpBeBVJv0tUZBg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"8e4d196c098a51ad9da13a198014d1e77a6ef9860752ac3a00b362260bc7348d","last_reissued_at":"2026-07-05T03:46:21.229568Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T03:46:21.229568Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Continuous-variable optimization with neural network quantum states","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["math.OC"],"primary_cat":"quant-ph","authors_text":"David Gorsich, Paramsothy Jayakumar, Shravan Veerapaneni, Yabin Zhang","submitted_at":"2021-08-06T22:45:09Z","abstract_excerpt":"Inspired by proposals for continuous-variable quantum approximate optimization (CV-QAOA), we investigate the utility of continuous-variable neural network quantum states (CV-NQS) for performing continuous optimization, focusing on the ground state optimization of the classical antiferromagnetic rotor model. Numerical experiments conducted using variational Monte Carlo with CV-NQS indicate that although the non-local algorithm succeeds in finding ground states competitive with the local gradient search methods, the proposal suffers from unfavorable scaling. A number of proposed extensions are p"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2108.03325","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/2108.03325/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":"2108.03325","created_at":"2026-07-05T03:46:21.229633+00:00"},{"alias_kind":"arxiv_version","alias_value":"2108.03325v3","created_at":"2026-07-05T03:46:21.229633+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2108.03325","created_at":"2026-07-05T03:46:21.229633+00:00"},{"alias_kind":"pith_short_12","alias_value":"RZGRS3AJRJI2","created_at":"2026-07-05T03:46:21.229633+00:00"},{"alias_kind":"pith_short_16","alias_value":"RZGRS3AJRJI23HNB","created_at":"2026-07-05T03:46:21.229633+00:00"},{"alias_kind":"pith_short_8","alias_value":"RZGRS3AJ","created_at":"2026-07-05T03:46:21.229633+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/RZGRS3AJRJI23HNBHIMYAFGR45","json":"https://pith.science/pith/RZGRS3AJRJI23HNBHIMYAFGR45.json","graph_json":"https://pith.science/api/pith-number/RZGRS3AJRJI23HNBHIMYAFGR45/graph.json","events_json":"https://pith.science/api/pith-number/RZGRS3AJRJI23HNBHIMYAFGR45/events.json","paper":"https://pith.science/paper/RZGRS3AJ"},"agent_actions":{"view_html":"https://pith.science/pith/RZGRS3AJRJI23HNBHIMYAFGR45","download_json":"https://pith.science/pith/RZGRS3AJRJI23HNBHIMYAFGR45.json","view_paper":"https://pith.science/paper/RZGRS3AJ","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2108.03325&json=true","fetch_graph":"https://pith.science/api/pith-number/RZGRS3AJRJI23HNBHIMYAFGR45/graph.json","fetch_events":"https://pith.science/api/pith-number/RZGRS3AJRJI23HNBHIMYAFGR45/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/RZGRS3AJRJI23HNBHIMYAFGR45/action/timestamp_anchor","attest_storage":"https://pith.science/pith/RZGRS3AJRJI23HNBHIMYAFGR45/action/storage_attestation","attest_author":"https://pith.science/pith/RZGRS3AJRJI23HNBHIMYAFGR45/action/author_attestation","sign_citation":"https://pith.science/pith/RZGRS3AJRJI23HNBHIMYAFGR45/action/citation_signature","submit_replication":"https://pith.science/pith/RZGRS3AJRJI23HNBHIMYAFGR45/action/replication_record"}},"created_at":"2026-07-05T03:46:21.229633+00:00","updated_at":"2026-07-05T03:46:21.229633+00:00"}