{"as_of":"2026-08-24T03:41:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:95db0129269e925bb1fe3853575033e50105e11ee84ea99949297cc0acb7b6e2","coverage":[{"denominator":29,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":29,"source":"paper_references, paper_reference_links","source_observed_at":"2026-07-12T23:50:25.262273Z","state":"measured"},{"denominator":30,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":30,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-23T06:30:58.430688+00:00","state":"measured"},{"denominator":1,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":1,"source":"paper_references, paper_reference_links","source_observed_at":"2026-07-10T21:55:25.824880Z","state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"pith","source_observed_at":"2026-07-10T21:57:37.176840Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2604.13096","last_updated":"2026-07-02T06:37:25Z","snapshot_observed_at":"2026-08-02T10:16:33.529256Z","submitted_at":"2026-04-09T17:42:37Z","title":"Complexity scaling and optimal policy degeneracy in quantum reinforcement learning via analytically solvable unitary-control-then-measure models","version":2},"cited_work":{"arxiv_id":"2604.13096","doi":null,"metadata_source":"pith","pith_arxiv_id":"2604.13096","snapshot_observed_at":"2026-07-10T21:57:37.176840Z","title":"Complexity scaling and optimal policy degeneracy in quantum reinforcement learning via analytically solvable unitary-control-then-measure models","venue":"math.GM","work_id":"89d5fc2a-c88f-4f82-9852-c9fa49786034","year":2026},"citing_paper":{"arxiv_id":"2607.06760","last_updated":"2026-07-07T19:43:32Z","snapshot_observed_at":"2026-08-19T06:03:36.003487Z","submitted_at":"2026-07-07T19:43:32Z","title":"QANTIS: Hardware-Calibrated Sequential POMDP Belief Updates on IBM Heron","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-07-10T21:55:25.824880Z"},"links":{"cited_paper":"/paper/2604.13096","citing_paper":"/paper/2607.06760"},"observation_digest":"sha256:aa19c7872e5cb77f70d9b390ca2b13b53d37b11754582aa66f1ce051c1dd0b6e","observation_id":"cbade1af-33a9-40fe-9b59-25c4ad3a47fa","resolution":{"observed_at":"2026-07-10T21:57:37.195751Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+00:00","source":"retraction_watch"}],"state":"measured"}}],"links":{"evidence":"/evidence","html":"/paper/2604.13096/citation-record","integrity":"/paper/2604.13096/integrity","json":"/paper/2604.13096/citation-record.json","paper":"/paper/2604.13096"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-07-12T23:50:25.262273Z","title":"Aharonov, L","venue":null,"work_id":null,"year":1993},"citing_paper":{"arxiv_id":"2604.13096","last_updated":"2026-07-02T06:37:25Z","snapshot_observed_at":"2026-08-02T10:16:33.529256Z","submitted_at":"2026-04-09T17:42:37Z","title":"Complexity scaling and optimal policy degeneracy in quantum reinforcement learning via analytically solvable unitary-control-then-measure models","version":2},"reference_index":1,"source":"arxiv_source","source_observed_at":"2026-07-12T23:50:25.262273Z"},"links":{"citing_paper":"/paper/2604.13096"},"observation_digest":"sha256:21be8d10cd407d6f6d515c6bbf3156059ea57eba42e9663de8ac7cf27782c0c2","observation_id":"0229e809-cf55-4b0d-9c84-4aef3a0da4aa","resolution":{"observed_at":"2026-07-12T23:50:25.262273Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-07-12T23:50:25.262273Z","title":"Arulkumaran, M","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2604.13096","last_updated":"2026-07-02T06:37:25Z","snapshot_observed_at":"2026-08-02T10:16:33.529256Z","submitted_at":"2026-04-09T17:42:37Z","title":"Complexity scaling and optimal policy degeneracy in quantum reinforcement learning via analytically solvable unitary-control-then-measure models","version":2},"reference_index":2,"source":"arxiv_source","source_observed_at":"2026-07-12T23:50:25.262273Z"},"links":{"citing_paper":"/paper/2604.13096"},"observation_digest":"sha256:17625467b3c11564e03e0da5aac532a53d8fa48de07e54c40693d03cdfcf245e","observation_id":"f1215055-c381-4515-9868-ebd4129bfd29","resolution":{"observed_at":"2026-07-12T23:50:25.262273Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-07-12T23:50:25.262273Z","title":"Attal, F","venue":null,"work_id":null,"year":2012},"citing_paper":{"arxiv_id":"2604.13096","last_updated":"2026-07-02T06:37:25Z","snapshot_observed_at":"2026-08-02T10:16:33.529256Z","submitted_at":"2026-04-09T17:42:37Z","title":"Complexity scaling and optimal policy degeneracy in quantum reinforcement learning via analytically solvable unitary-control-then-measure models","version":2},"reference_index":3,"source":"arxiv_source","source_observed_at":"2026-07-12T23:50:25.262273Z"},"links":{"citing_paper":"/paper/2604.13096"},"observation_digest":"sha256:54b683769735352fbdb6fc4d4dc97bb202c337f984916c1bc0112d1862b21db1","observation_id":"b5296702-9175-4f4d-94e2-25580dde954e","resolution":{"observed_at":"2026-07-12T23:50:25.262273Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-07-12T23:50:25.262273Z","title":null,"venue":null,"work_id":null,"year":2014},"citing_paper":{"arxiv_id":"2604.13096","last_updated":"2026-07-02T06:37:25Z","snapshot_observed_at":"2026-08-02T10:16:33.529256Z","submitted_at":"2026-04-09T17:42:37Z","title":"Complexity scaling and optimal policy degeneracy in quantum reinforcement learning via analytically solvable unitary-control-then-measure models","version":2},"reference_index":4,"source":"arxiv_source","source_observed_at":"2026-07-12T23:50:25.262273Z"},"links":{"citing_paper":"/paper/2604.13096"},"observation_digest":"sha256:62eac3401dedecba8bfedeab96091329e0c5660b20172dd7b47a67c94cdcfa6d","observation_id":"35e21dfd-4569-4a5a-8309-25be69977700","resolution":{"observed_at":"2026-07-12T23:50:25.262273Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-07-12T23:50:25.262273Z","title":null,"venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2604.13096","last_updated":"2026-07-02T06:37:25Z","snapshot_observed_at":"2026-08-02T10:16:33.529256Z","submitted_at":"2026-04-09T17:42:37Z","title":"Complexity scaling and optimal policy degeneracy in quantum reinforcement learning via analytically solvable unitary-control-then-measure models","version":2},"reference_index":5,"source":"arxiv_source","source_observed_at":"2026-07-12T23:50:25.262273Z"},"links":{"citing_paper":"/paper/2604.13096"},"observation_digest":"sha256:6cfeda58cc72d43f407c322ba18b81d446eecd191638feec42b2f29a9c49680c","observation_id":"d50f1f3d-1c9e-433b-90b8-d7c2c2f20935","resolution":{"observed_at":"2026-07-12T23:50:25.262273Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-07-12T23:50:25.262273Z","title":"Bertsekas , Reinforcement learning and optimal control , vol","venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2604.13096","last_updated":"2026-07-02T06:37:25Z","snapshot_observed_at":"2026-08-02T10:16:33.529256Z","submitted_at":"2026-04-09T17:42:37Z","title":"Complexity scaling and optimal policy degeneracy in quantum reinforcement learning via analytically solvable unitary-control-then-measure models","version":2},"reference_index":6,"source":"arxiv_source","source_observed_at":"2026-07-12T23:50:25.262273Z"},"links":{"citing_paper":"/paper/2604.13096"},"observation_digest":"sha256:a3da65f03c01ff85fc7360c4a1fa193693e600d52cbe3c256a45b26a869a0c68","observation_id":"9a6352c5-bd4b-41ef-8bee-ee0d897b93f5","resolution":{"observed_at":"2026-07-12T23:50:25.262273Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-07-12T23:50:25.262273Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2604.13096","last_updated":"2026-07-02T06:37:25Z","snapshot_observed_at":"2026-08-02T10:16:33.529256Z","submitted_at":"2026-04-09T17:42:37Z","title":"Complexity scaling and optimal policy degeneracy in quantum reinforcement learning via analytically solvable unitary-control-then-measure models","version":2},"reference_index":7,"source":"arxiv_source","source_observed_at":"2026-07-12T23:50:25.262273Z"},"links":{"citing_paper":"/paper/2604.13096"},"observation_digest":"sha256:96283b12a6f79312ed9379da5cc5fef91f438a2f232483390d1e6c057a290740","observation_id":"1dc13588-5e9a-44ea-9d9c-c5c9938f2acd","resolution":{"observed_at":"2026-07-12T23:50:25.262273Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-07-12T23:50:25.262273Z","title":null,"venue":null,"work_id":null,"year":2012},"citing_paper":{"arxiv_id":"2604.13096","last_updated":"2026-07-02T06:37:25Z","snapshot_observed_at":"2026-08-02T10:16:33.529256Z","submitted_at":"2026-04-09T17:42:37Z","title":"Complexity scaling and optimal policy degeneracy in quantum reinforcement learning via analytically solvable unitary-control-then-measure models","version":2},"reference_index":8,"source":"arxiv_source","source_observed_at":"2026-07-12T23:50:25.262273Z"},"links":{"citing_paper":"/paper/2604.13096"},"observation_digest":"sha256:276ec191e7dfcbf6f97e496402456c116dc99fa8fdab816a7566d56cd1e6320f","observation_id":"0917b840-a4a9-4521-8519-15173b9f0c5c","resolution":{"observed_at":"2026-07-12T23:50:25.262273Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-07-12T23:50:25.262273Z","title":"Clarke and F","venue":null,"work_id":null,"year":2008},"citing_paper":{"arxiv_id":"2604.13096","last_updated":"2026-07-02T06:37:25Z","snapshot_observed_at":"2026-08-02T10:16:33.529256Z","submitted_at":"2026-04-09T17:42:37Z","title":"Complexity scaling and optimal policy degeneracy in quantum reinforcement learning via analytically solvable unitary-control-then-measure models","version":2},"reference_index":9,"source":"arxiv_source","source_observed_at":"2026-07-12T23:50:25.262273Z"},"links":{"citing_paper":"/paper/2604.13096"},"observation_digest":"sha256:3c89811c170141adda16c0da64321c934a72ba2dc0129f8876a4cdc71489820d","observation_id":"1654085e-9a21-47d8-9f5e-acdd17379a64","resolution":{"observed_at":"2026-07-12T23:50:25.262273Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-07-12T23:50:25.262273Z","title":"Cohen-Tannoudji, B","venue":null,"work_id":null,"year":1977},"citing_paper":{"arxiv_id":"2604.13096","last_updated":"2026-07-02T06:37:25Z","snapshot_observed_at":"2026-08-02T10:16:33.529256Z","submitted_at":"2026-04-09T17:42:37Z","title":"Complexity scaling and optimal policy degeneracy in quantum reinforcement learning via analytically solvable unitary-control-then-measure models","version":2},"reference_index":10,"source":"arxiv_source","source_observed_at":"2026-07-12T23:50:25.262273Z"},"links":{"citing_paper":"/paper/2604.13096"},"observation_digest":"sha256:b48eac7a041cf46c5a743d3782427433010e39b3455ad027c544d5b50b96541c","observation_id":"4f84e960-5cf8-42f7-ac1c-12336cd3cb21","resolution":{"observed_at":"2026-07-12T23:50:25.262273Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-07-12T23:50:25.262273Z","title":null,"venue":null,"work_id":null,"year":2008},"citing_paper":{"arxiv_id":"2604.13096","last_updated":"2026-07-02T06:37:25Z","snapshot_observed_at":"2026-08-02T10:16:33.529256Z","submitted_at":"2026-04-09T17:42:37Z","title":"Complexity scaling and optimal policy degeneracy in quantum reinforcement learning via analytically solvable unitary-control-then-measure models","version":2},"reference_index":11,"source":"arxiv_source","source_observed_at":"2026-07-12T23:50:25.262273Z"},"links":{"citing_paper":"/paper/2604.13096"},"observation_digest":"sha256:1ebd79b3673bd46959761ddbda0546bc08713397869c84b50bc63207742455bc","observation_id":"928fa734-1348-439b-abfd-6feba2ddb8ce","resolution":{"observed_at":"2026-07-12T23:50:25.262273Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-07-12T23:50:25.262273Z","title":"1207--1220","venue":null,"work_id":null,"year":2008},"citing_paper":{"arxiv_id":"2604.13096","last_updated":"2026-07-02T06:37:25Z","snapshot_observed_at":"2026-08-02T10:16:33.529256Z","submitted_at":"2026-04-09T17:42:37Z","title":"Complexity scaling and optimal policy degeneracy in quantum reinforcement learning via analytically solvable unitary-control-then-measure models","version":2},"reference_index":12,"source":"arxiv_source","source_observed_at":"2026-07-12T23:50:25.262273Z"},"links":{"citing_paper":"/paper/2604.13096"},"observation_digest":"sha256:472c54973f1d8cf287109b4aae6bb1b2775f422ebd9b5b49548220180361b2c3","observation_id":"4c84f4ae-1bf6-43d3-8702-41fdf3b76165","resolution":{"observed_at":"2026-07-12T23:50:25.262273Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-07-12T23:50:25.262273Z","title":"Facchi and S","venue":null,"work_id":null,"year":2008},"citing_paper":{"arxiv_id":"2604.13096","last_updated":"2026-07-02T06:37:25Z","snapshot_observed_at":"2026-08-02T10:16:33.529256Z","submitted_at":"2026-04-09T17:42:37Z","title":"Complexity scaling and optimal policy degeneracy in quantum reinforcement learning via analytically solvable unitary-control-then-measure models","version":2},"reference_index":13,"source":"arxiv_source","source_observed_at":"2026-07-12T23:50:25.262273Z"},"links":{"citing_paper":"/paper/2604.13096"},"observation_digest":"sha256:ce02970e07d1d109e77f6cce866462ac9a3051873d73cf1e28fd28f16ed3ccbc","observation_id":"c2a02b34-a980-4449-a819-43ba04c8f017","resolution":{"observed_at":"2026-07-12T23:50:25.262273Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-07-12T23:50:25.262273Z","title":"Hsieh and H","venue":null,"work_id":null,"year":2008},"citing_paper":{"arxiv_id":"2604.13096","last_updated":"2026-07-02T06:37:25Z","snapshot_observed_at":"2026-08-02T10:16:33.529256Z","submitted_at":"2026-04-09T17:42:37Z","title":"Complexity scaling and optimal policy degeneracy in quantum reinforcement learning via analytically solvable unitary-control-then-measure models","version":2},"reference_index":14,"source":"arxiv_source","source_observed_at":"2026-07-12T23:50:25.262273Z"},"links":{"citing_paper":"/paper/2604.13096"},"observation_digest":"sha256:e86680c1e7e5830dbc5c276450dbae5a82585ad50aeb68861165806ab2cb7f6c","observation_id":"b935bd23-b814-4672-b10f-7f85eccd73cb","resolution":{"observed_at":"2026-07-12T23:50:25.262273Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-07-12T23:50:25.262273Z","title":"Hsieh, R","venue":null,"work_id":null,"year":2010},"citing_paper":{"arxiv_id":"2604.13096","last_updated":"2026-07-02T06:37:25Z","snapshot_observed_at":"2026-08-02T10:16:33.529256Z","submitted_at":"2026-04-09T17:42:37Z","title":"Complexity scaling and optimal policy degeneracy in quantum reinforcement learning via analytically solvable unitary-control-then-measure models","version":2},"reference_index":15,"source":"arxiv_source","source_observed_at":"2026-07-12T23:50:25.262273Z"},"links":{"citing_paper":"/paper/2604.13096"},"observation_digest":"sha256:9e414026a830e4f27edb1c0ae0b509456974ce2f609f58730e28587bc0433d9d","observation_id":"b4bead5e-641c-4368-a3ad-01798c3e5c77","resolution":{"observed_at":"2026-07-12T23:50:25.262273Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-07-12T23:50:25.262273Z","title":null,"venue":null,"work_id":null,"year":1996},"citing_paper":{"arxiv_id":"2604.13096","last_updated":"2026-07-02T06:37:25Z","snapshot_observed_at":"2026-08-02T10:16:33.529256Z","submitted_at":"2026-04-09T17:42:37Z","title":"Complexity scaling and optimal policy degeneracy in quantum reinforcement learning via analytically solvable unitary-control-then-measure models","version":2},"reference_index":16,"source":"arxiv_source","source_observed_at":"2026-07-12T23:50:25.262273Z"},"links":{"citing_paper":"/paper/2604.13096"},"observation_digest":"sha256:24f7e2c2244f315a9905d2eb5fc6b4c409310bc24d067d9447c67fc8a813e6c1","observation_id":"1355fdc0-56e7-4496-ac7e-0a5cb8ea7fde","resolution":{"observed_at":"2026-07-12T23:50:25.262273Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-07-12T23:50:25.262273Z","title":"Leibfried, R","venue":null,"work_id":null,"year":2003},"citing_paper":{"arxiv_id":"2604.13096","last_updated":"2026-07-02T06:37:25Z","snapshot_observed_at":"2026-08-02T10:16:33.529256Z","submitted_at":"2026-04-09T17:42:37Z","title":"Complexity scaling and optimal policy degeneracy in quantum reinforcement learning via analytically solvable unitary-control-then-measure models","version":2},"reference_index":17,"source":"arxiv_source","source_observed_at":"2026-07-12T23:50:25.262273Z"},"links":{"citing_paper":"/paper/2604.13096"},"observation_digest":"sha256:1ccb2c700f05ea12d3afb4efb9d883c43aba9f81aeea1a914de5d439e102446e","observation_id":"10defe37-f487-4988-b1bd-df76c36c172d","resolution":{"observed_at":"2026-07-12T23:50:25.262273Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2211.03464","last_updated":"2024-03-08T10:06:43Z","snapshot_observed_at":"2026-08-16T16:18:08.501171Z","submitted_at":"2022-11-07T11:25:47Z","title":"A Survey on Quantum Reinforcement Learning","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2211.03464","snapshot_observed_at":"2026-07-12T23:50:25.262273Z","title":"Meyer, C","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2604.13096","last_updated":"2026-07-02T06:37:25Z","snapshot_observed_at":"2026-08-02T10:16:33.529256Z","submitted_at":"2026-04-09T17:42:37Z","title":"Complexity scaling and optimal policy degeneracy in quantum reinforcement learning via analytically solvable unitary-control-then-measure models","version":2},"reference_index":18,"source":"arxiv_source","source_observed_at":"2026-07-12T23:50:25.262273Z"},"links":{"cited_paper":"/paper/2211.03464","citing_paper":"/paper/2604.13096"},"observation_digest":"sha256:60b429fb197fa50113175383958a7708a174cc29cac194bc30525cf6ec2814eb","observation_id":"d84c2b34-7957-49ab-89ed-0ed0fc1feb66","resolution":{"observed_at":"2026-07-12T23:50:25.262273Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-07-12T23:50:25.262273Z","title":null,"venue":null,"work_id":null,"year":2014},"citing_paper":{"arxiv_id":"2604.13096","last_updated":"2026-07-02T06:37:25Z","snapshot_observed_at":"2026-08-02T10:16:33.529256Z","submitted_at":"2026-04-09T17:42:37Z","title":"Complexity scaling and optimal policy degeneracy in quantum reinforcement learning via analytically solvable unitary-control-then-measure models","version":2},"reference_index":19,"source":"arxiv_source","source_observed_at":"2026-07-12T23:50:25.262273Z"},"links":{"citing_paper":"/paper/2604.13096"},"observation_digest":"sha256:4568a42483d19a70833ed2a07a45a39e57101a23b7838d87dbce4078d7ef989f","observation_id":"90c657bd-9423-4853-a1c7-60e8b718b381","resolution":{"observed_at":"2026-07-12T23:50:25.262273Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-07-12T23:50:25.262273Z","title":null,"venue":null,"work_id":null,"year":2014},"citing_paper":{"arxiv_id":"2604.13096","last_updated":"2026-07-02T06:37:25Z","snapshot_observed_at":"2026-08-02T10:16:33.529256Z","submitted_at":"2026-04-09T17:42:37Z","title":"Complexity scaling and optimal policy degeneracy in quantum reinforcement learning via analytically solvable unitary-control-then-measure models","version":2},"reference_index":20,"source":"arxiv_source","source_observed_at":"2026-07-12T23:50:25.262273Z"},"links":{"citing_paper":"/paper/2604.13096"},"observation_digest":"sha256:21a2c13e08c973cc64d9ad9d14ae7601aba5208f137b085108a7d8f44e8b7c8f","observation_id":"5b91d1da-4b3b-4cf5-8e54-5bba0a87edf2","resolution":{"observed_at":"2026-07-12T23:50:25.262273Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-07-12T23:50:25.262273Z","title":null,"venue":null,"work_id":null,"year":2002},"citing_paper":{"arxiv_id":"2604.13096","last_updated":"2026-07-02T06:37:25Z","snapshot_observed_at":"2026-08-02T10:16:33.529256Z","submitted_at":"2026-04-09T17:42:37Z","title":"Complexity scaling and optimal policy degeneracy in quantum reinforcement learning via analytically solvable unitary-control-then-measure models","version":2},"reference_index":21,"source":"arxiv_source","source_observed_at":"2026-07-12T23:50:25.262273Z"},"links":{"citing_paper":"/paper/2604.13096"},"observation_digest":"sha256:2c57bcf5d7b7af4cede93ba57074924dc0f2fc07503a50047ad9d5b2bed27691","observation_id":"da5c4acd-67d6-45f0-bed2-a9094af7229e","resolution":{"observed_at":"2026-07-12T23:50:25.262273Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-07-12T23:50:25.262273Z","title":"Schenk, E","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2604.13096","last_updated":"2026-07-02T06:37:25Z","snapshot_observed_at":"2026-08-02T10:16:33.529256Z","submitted_at":"2026-04-09T17:42:37Z","title":"Complexity scaling and optimal policy degeneracy in quantum reinforcement learning via analytically solvable unitary-control-then-measure models","version":2},"reference_index":22,"source":"arxiv_source","source_observed_at":"2026-07-12T23:50:25.262273Z"},"links":{"citing_paper":"/paper/2604.13096"},"observation_digest":"sha256:65efab3f242e3e12e3e61146fac154d55be8efc80f5fb00434c5ba135f463307","observation_id":"ace3bfd6-c609-47f5-890c-adc94c7e2554","resolution":{"observed_at":"2026-07-12T23:50:25.262273Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-07-12T23:50:25.262273Z","title":"Sugny and C","venue":null,"work_id":null,"year":2008},"citing_paper":{"arxiv_id":"2604.13096","last_updated":"2026-07-02T06:37:25Z","snapshot_observed_at":"2026-08-02T10:16:33.529256Z","submitted_at":"2026-04-09T17:42:37Z","title":"Complexity scaling and optimal policy degeneracy in quantum reinforcement learning via analytically solvable unitary-control-then-measure models","version":2},"reference_index":23,"source":"arxiv_source","source_observed_at":"2026-07-12T23:50:25.262273Z"},"links":{"citing_paper":"/paper/2604.13096"},"observation_digest":"sha256:8914b64138a406d6d842a7e0f557011172231309c1e5f71e3c34fce162742a97","observation_id":"f83b0fc2-5b6b-437c-9af9-8d1d322966b0","resolution":{"observed_at":"2026-07-12T23:50:25.262273Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-07-12T23:50:25.262273Z","title":null,"venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2604.13096","last_updated":"2026-07-02T06:37:25Z","snapshot_observed_at":"2026-08-02T10:16:33.529256Z","submitted_at":"2026-04-09T17:42:37Z","title":"Complexity scaling and optimal policy degeneracy in quantum reinforcement learning via analytically solvable unitary-control-then-measure models","version":2},"reference_index":24,"source":"arxiv_source","source_observed_at":"2026-07-12T23:50:25.262273Z"},"links":{"citing_paper":"/paper/2604.13096"},"observation_digest":"sha256:7e6fd5a09547a8f05c821eb0b4e494d41b1f0dad8eb3f39666d84854789892cb","observation_id":"872055e0-5960-47ba-8eee-dde0ce3fc006","resolution":{"observed_at":"2026-07-12T23:50:25.262273Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-07-12T23:50:25.262273Z","title":"Szepesv \\'a ri , Algorithms for reinforcement learning , Springer nature, 2022","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2604.13096","last_updated":"2026-07-02T06:37:25Z","snapshot_observed_at":"2026-08-02T10:16:33.529256Z","submitted_at":"2026-04-09T17:42:37Z","title":"Complexity scaling and optimal policy degeneracy in quantum reinforcement learning via analytically solvable unitary-control-then-measure models","version":2},"reference_index":25,"source":"arxiv_source","source_observed_at":"2026-07-12T23:50:25.262273Z"},"links":{"citing_paper":"/paper/2604.13096"},"observation_digest":"sha256:81ae3ec3660c593dcbbda6bc986aae7de531a7eadd915dd9e7e530d17b95a7b1","observation_id":"09ec34e8-c2fd-459e-8244-a6765f8e2237","resolution":{"observed_at":"2026-07-12T23:50:25.262273Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-07-12T23:50:25.262273Z","title":null,"venue":null,"work_id":null,"year":2012},"citing_paper":{"arxiv_id":"2604.13096","last_updated":"2026-07-02T06:37:25Z","snapshot_observed_at":"2026-08-02T10:16:33.529256Z","submitted_at":"2026-04-09T17:42:37Z","title":"Complexity scaling and optimal policy degeneracy in quantum reinforcement learning via analytically solvable unitary-control-then-measure models","version":2},"reference_index":26,"source":"arxiv_source","source_observed_at":"2026-07-12T23:50:25.262273Z"},"links":{"citing_paper":"/paper/2604.13096"},"observation_digest":"sha256:b7a0b886005c88f9b3819180267cacd7ee6e7a2b611bf499abf3f66207a34575","observation_id":"f2a37b1e-ed7b-4fe5-8f34-c75edbdc577f","resolution":{"observed_at":"2026-07-12T23:50:25.262273Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-07-12T23:50:25.262273Z","title":"Volkov, A","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2604.13096","last_updated":"2026-07-02T06:37:25Z","snapshot_observed_at":"2026-08-02T10:16:33.529256Z","submitted_at":"2026-04-09T17:42:37Z","title":"Complexity scaling and optimal policy degeneracy in quantum reinforcement learning via analytically solvable unitary-control-then-measure models","version":2},"reference_index":27,"source":"arxiv_source","source_observed_at":"2026-07-12T23:50:25.262273Z"},"links":{"citing_paper":"/paper/2604.13096"},"observation_digest":"sha256:bebeb2bfa00875db1e5b38960983f8cd87a0b1f99d6511682bb9d07d38a0f35a","observation_id":"a9cc5858-02f3-48ec-b8c9-62117f9dd0ed","resolution":{"observed_at":"2026-07-12T23:50:25.262273Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-07-12T23:50:25.262273Z","title":"Wendin , Quantum information processing with superconducting circuits: a review , Reports on Progress in Physics, 80 (2017), p","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2604.13096","last_updated":"2026-07-02T06:37:25Z","snapshot_observed_at":"2026-08-02T10:16:33.529256Z","submitted_at":"2026-04-09T17:42:37Z","title":"Complexity scaling and optimal policy degeneracy in quantum reinforcement learning via analytically solvable unitary-control-then-measure models","version":2},"reference_index":28,"source":"arxiv_source","source_observed_at":"2026-07-12T23:50:25.262273Z"},"links":{"citing_paper":"/paper/2604.13096"},"observation_digest":"sha256:dbb785d461cb7c9bda249f2bd04f07b1b856344de22bc9b0411f654e40a647cc","observation_id":"ba660a26-d1fc-495f-bf52-19456302c726","resolution":{"observed_at":"2026-07-12T23:50:25.262273Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-07-12T23:50:25.262273Z","title":null,"venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2604.13096","last_updated":"2026-07-02T06:37:25Z","snapshot_observed_at":"2026-08-02T10:16:33.529256Z","submitted_at":"2026-04-09T17:42:37Z","title":"Complexity scaling and optimal policy degeneracy in quantum reinforcement learning via analytically solvable unitary-control-then-measure models","version":2},"reference_index":29,"source":"arxiv_source","source_observed_at":"2026-07-12T23:50:25.262273Z"},"links":{"citing_paper":"/paper/2604.13096"},"observation_digest":"sha256:d5584c336d1baf9dc935e10a8771c0de30214bb138590507904a37e6872c24c6","observation_id":"f3c627ac-58f3-459a-8e86-eae20bacdd19","resolution":{"observed_at":"2026-07-12T23:50:25.262273Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"paper":{"arxiv_id":"2604.13096","last_updated":"2026-07-02T06:37:25Z","latest_version":2,"primary_category":"math.GM","snapshot_observed_at":"2026-08-02T10:16:33.529256Z","submitted_at":"2026-04-09T17:42:37Z","title":"Complexity scaling and optimal policy degeneracy in quantum reinforcement learning via analytically solvable unitary-control-then-measure models"},"reference_resolution":{"displayed":29,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":29,"verified_exact":0,"verified_fuzzy":0},"total_outbound_references":29},"refusal":"A citation records a reference. It does not transfer a finding from one paper to another.","schema":"pith.paper-citation-record.v1","standing_sources":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+00:00","source":"retraction_watch"}],"thesis":"As of 24 August 2026, this Paper Citation Record lists 29 of 29 outbound references and 1 inbound Pith citation observation for arXiv:2604.13096."}