{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2026:IDHUQACJ5Z6P7PLCOQG45FS3NG","short_pith_number":"pith:IDHUQACJ","schema_version":"1.0","canonical_sha256":"40cf480049ee7cffbd62740dce965b69a61011d0a3b9e2725d58f9c1f5056d96","source":{"kind":"arxiv","id":"2607.23469","version":1},"attestation_state":"computed","paper":{"title":"When Every Simulation Counts: Value-Based Reinforcement Learning for Accelerated Photonics Inverse Design","license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","headline":"","cross_cats":["cs.AI","cs.LG","physics.app-ph"],"primary_cat":"physics.optics","authors_text":"Chongxian Yuan, Feiyang Wu, Jinglin Yu, Longying Wen, Renjie Li, Zhaoyu Zhang","submitted_at":"2026-07-26T05:50:46Z","abstract_excerpt":"Photonic-crystal surface-emitting lasers (PCSELs) can combine high-power operation with narrow-divergence surface emission, but optimizing coupled parameters requires costly full-wave simulations. Deep Q-network (DQN) optimization can reuse simulated transitions to guide edits, yet which value-learning mechanisms remain reliable under tight simulation budgets is unknown. We address this gap by comparing baseline DQN and six value-based variants for a seven-variable PCSEL design under a shared objective, simulator, 83-call budget, and four matched initializations. Beyond endpoints, we analyze s"},"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":"2607.23469","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"physics.optics","submitted_at":"2026-07-26T05:50:46Z","cross_cats_sorted":["cs.AI","cs.LG","physics.app-ph"],"title_canon_sha256":"8322a11ff5320ee5c4d7b456700ccf01bbe5ee6b193f295c0b0ec888baf57ba7","abstract_canon_sha256":"1923febd198a5b5563ee191a4347341c704380298730b2a15d9424e701494a41"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-28T01:22:54.169988Z","signature_b64":"rSd2dUAA6FHPOkPlYjptV/Q1MNcExosZ+lJKIhSHjB+10rqQ3jNgCsEIRNLxSJJc0xZim2yBtPx2hWrO6ySKDg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"40cf480049ee7cffbd62740dce965b69a61011d0a3b9e2725d58f9c1f5056d96","last_reissued_at":"2026-07-28T01:22:54.169158Z","signature_status":"signed_v1","first_computed_at":"2026-07-28T01:22:54.169158Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"When Every Simulation Counts: Value-Based Reinforcement Learning for Accelerated Photonics Inverse Design","license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","headline":"","cross_cats":["cs.AI","cs.LG","physics.app-ph"],"primary_cat":"physics.optics","authors_text":"Chongxian Yuan, Feiyang Wu, Jinglin Yu, Longying Wen, Renjie Li, Zhaoyu Zhang","submitted_at":"2026-07-26T05:50:46Z","abstract_excerpt":"Photonic-crystal surface-emitting lasers (PCSELs) can combine high-power operation with narrow-divergence surface emission, but optimizing coupled parameters requires costly full-wave simulations. Deep Q-network (DQN) optimization can reuse simulated transitions to guide edits, yet which value-learning mechanisms remain reliable under tight simulation budgets is unknown. We address this gap by comparing baseline DQN and six value-based variants for a seven-variable PCSEL design under a shared objective, simulator, 83-call budget, and four matched initializations. Beyond endpoints, we analyze s"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2607.23469","kind":"arxiv","version":1},"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/2607.23469/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":"2607.23469","created_at":"2026-07-28T01:22:54.169591+00:00"},{"alias_kind":"arxiv_version","alias_value":"2607.23469v1","created_at":"2026-07-28T01:22:54.169591+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2607.23469","created_at":"2026-07-28T01:22:54.169591+00:00"},{"alias_kind":"pith_short_12","alias_value":"IDHUQACJ5Z6P","created_at":"2026-07-28T01:22:54.169591+00:00"},{"alias_kind":"pith_short_16","alias_value":"IDHUQACJ5Z6P7PLC","created_at":"2026-07-28T01:22:54.169591+00:00"},{"alias_kind":"pith_short_8","alias_value":"IDHUQACJ","created_at":"2026-07-28T01:22:54.169591+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/IDHUQACJ5Z6P7PLCOQG45FS3NG","json":"https://pith.science/pith/IDHUQACJ5Z6P7PLCOQG45FS3NG.json","graph_json":"https://pith.science/api/pith-number/IDHUQACJ5Z6P7PLCOQG45FS3NG/graph.json","events_json":"https://pith.science/api/pith-number/IDHUQACJ5Z6P7PLCOQG45FS3NG/events.json","paper":"https://pith.science/paper/IDHUQACJ"},"agent_actions":{"view_html":"https://pith.science/pith/IDHUQACJ5Z6P7PLCOQG45FS3NG","download_json":"https://pith.science/pith/IDHUQACJ5Z6P7PLCOQG45FS3NG.json","view_paper":"https://pith.science/paper/IDHUQACJ","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2607.23469&json=true","fetch_graph":"https://pith.science/api/pith-number/IDHUQACJ5Z6P7PLCOQG45FS3NG/graph.json","fetch_events":"https://pith.science/api/pith-number/IDHUQACJ5Z6P7PLCOQG45FS3NG/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/IDHUQACJ5Z6P7PLCOQG45FS3NG/action/timestamp_anchor","attest_storage":"https://pith.science/pith/IDHUQACJ5Z6P7PLCOQG45FS3NG/action/storage_attestation","attest_author":"https://pith.science/pith/IDHUQACJ5Z6P7PLCOQG45FS3NG/action/author_attestation","sign_citation":"https://pith.science/pith/IDHUQACJ5Z6P7PLCOQG45FS3NG/action/citation_signature","submit_replication":"https://pith.science/pith/IDHUQACJ5Z6P7PLCOQG45FS3NG/action/replication_record"}},"created_at":"2026-07-28T01:22:54.169591+00:00","updated_at":"2026-07-28T01:22:54.169591+00:00"}