{"as_of":"2026-08-16T09:08:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:89166bc52d339393e7b88b5c2bd17600adcbfb45aa8cb72726bcc8bcac0856a3","coverage":[{"denominator":42,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":42,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-10T23:58:38.414050Z","state":"measured"},{"denominator":42,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":42,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-16T06:30:59.297886+00:00","state":"measured"},{"denominator":0,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":0,"source":"paper_references, paper_reference_links","source_observed_at":null,"state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"cited_works","source_observed_at":null,"state":"measured"}],"external_citation_measurements":[],"inbound":[],"links":{"evidence":"/evidence","html":"/paper/2501.00046/citation-record","integrity":"/paper/2501.00046/integrity","json":"/paper/2501.00046/citation-record.json","paper":"/paper/2501.00046"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T23:58:39.677886Z","title":"1986 The Kuramoto-Sivashinsky equation: a bridge between PDE’s and dynamical systems","venue":null,"work_id":"1fe5a06d-b4a9-44d5-a0d0-a0d63a8a7e0a","year":1986},"citing_paper":{"arxiv_id":"2501.00046","last_updated":"2024-12-27T18:01:34Z","snapshot_observed_at":"2026-08-14T22:57:11.033630Z","submitted_at":"2024-12-27T18:01:34Z","title":"Numerical solutions of fixed points in two-dimensional Kuramoto-Sivashinsky equation expedited by reinforcement learning","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-10T23:58:37.938689Z"},"links":{"citing_paper":"/paper/2501.00046"},"observation_digest":"sha256:af51d8c1269c88261e2ee215a25e6e17129ea25cafddfbec2f783e23ceb293c9","observation_id":"5037b467-4373-4ca2-a7fd-48b00f838f5f","resolution":{"observed_at":"2026-08-10T23:58:39.682485Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T23:58:39.662921Z","title":"2010 On the state space geometry of the Kuramoto– Sivashinsky flow in a periodic domain","venue":null,"work_id":"bb46ce8d-f4ad-4247-bb35-778f943c37c7","year":2010},"citing_paper":{"arxiv_id":"2501.00046","last_updated":"2024-12-27T18:01:34Z","snapshot_observed_at":"2026-08-14T22:57:11.033630Z","submitted_at":"2024-12-27T18:01:34Z","title":"Numerical solutions of fixed points in two-dimensional Kuramoto-Sivashinsky equation expedited by reinforcement learning","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-10T23:58:37.943832Z"},"links":{"citing_paper":"/paper/2501.00046"},"observation_digest":"sha256:0e0e86681ca0d83204ff328b0c7da250ee63f64e4c68c55f0e5ff2c4e20c523c","observation_id":"6667aef1-c019-4d21-928a-ffb2cfc436cf","resolution":{"observed_at":"2026-08-10T23:58:39.668100Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T23:58:39.648587Z","title":"1975 On the formation of dissipative structures in reaction-diffusion systems: Reductive perturbation approach","venue":null,"work_id":"e7140e3e-ee02-4243-85dc-8ca2a00368bb","year":1975},"citing_paper":{"arxiv_id":"2501.00046","last_updated":"2024-12-27T18:01:34Z","snapshot_observed_at":"2026-08-14T22:57:11.033630Z","submitted_at":"2024-12-27T18:01:34Z","title":"Numerical solutions of fixed points in two-dimensional Kuramoto-Sivashinsky equation expedited by reinforcement learning","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-10T23:58:37.948880Z"},"links":{"citing_paper":"/paper/2501.00046"},"observation_digest":"sha256:7edd5f0113e364b276d2723f0de6651df03cb5a417879d91c51db26f8dc1d00a","observation_id":"98e90e68-65e5-490b-9593-8259ce471839","resolution":{"observed_at":"2026-08-10T23:58:39.653356Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T23:58:39.633101Z","title":"1988 Nonlinear analysis of hydrodynamic instability in laminar flames—I","venue":null,"work_id":"88978b09-e805-4e22-949c-281d9b40b98a","year":1988},"citing_paper":{"arxiv_id":"2501.00046","last_updated":"2024-12-27T18:01:34Z","snapshot_observed_at":"2026-08-14T22:57:11.033630Z","submitted_at":"2024-12-27T18:01:34Z","title":"Numerical solutions of fixed points in two-dimensional Kuramoto-Sivashinsky equation expedited by reinforcement learning","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-10T23:58:37.953636Z"},"links":{"citing_paper":"/paper/2501.00046"},"observation_digest":"sha256:cde127f4815e5f695b0554a4f0afc51a98b782f464e1ea9bfc0948357b13b383","observation_id":"d5da5973-bbd9-42fc-a3f8-0d990d2ce8b5","resolution":{"observed_at":"2026-08-10T23:58:39.638333Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T23:58:39.618279Z","title":"2014 Nonlinear dynamics and chaos: With applications to physics, biology, chemistry, and engineering","venue":null,"work_id":"394fe9de-8e26-4a09-9500-e95183356a0c","year":2014},"citing_paper":{"arxiv_id":"2501.00046","last_updated":"2024-12-27T18:01:34Z","snapshot_observed_at":"2026-08-14T22:57:11.033630Z","submitted_at":"2024-12-27T18:01:34Z","title":"Numerical solutions of fixed points in two-dimensional Kuramoto-Sivashinsky equation expedited by reinforcement learning","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-10T23:58:37.958567Z"},"links":{"citing_paper":"/paper/2501.00046"},"observation_digest":"sha256:344fd6842add115a8e868d392d0f240764963cb607d307552b91a7b5fb76c7c9","observation_id":"77b94c55-53a3-4e48-a5d6-594a002950cb","resolution":{"observed_at":"2026-08-10T23:58:39.622521Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T23:58:39.530748Z","title":"1982 The strange attractor theory of turbulence.Annual Review of Fluid Mechanics 14, 347–364","venue":null,"work_id":"f8f0eeac-b52a-447d-aa49-aa266187b610","year":1982},"citing_paper":{"arxiv_id":"2501.00046","last_updated":"2024-12-27T18:01:34Z","snapshot_observed_at":"2026-08-14T22:57:11.033630Z","submitted_at":"2024-12-27T18:01:34Z","title":"Numerical solutions of fixed points in two-dimensional Kuramoto-Sivashinsky equation expedited by reinforcement learning","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-10T23:58:37.963721Z"},"links":{"citing_paper":"/paper/2501.00046"},"observation_digest":"sha256:6b76c70af4722d40d525b7ef99324d3aea5ea3ca8f944f85eec1fcee3a3c557f","observation_id":"cc6b1379-4a3a-4350-b759-a5a4b0aee73f","resolution":{"observed_at":"2026-08-10T23:58:39.567464Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T23:58:39.437881Z","title":"2005 Recent progress in understanding the transition to turbulence in a pipe","venue":null,"work_id":"1928ac89-efbd-4ba6-87e8-d0fd4a1bde19","year":2005},"citing_paper":{"arxiv_id":"2501.00046","last_updated":"2024-12-27T18:01:34Z","snapshot_observed_at":"2026-08-14T22:57:11.033630Z","submitted_at":"2024-12-27T18:01:34Z","title":"Numerical solutions of fixed points in two-dimensional Kuramoto-Sivashinsky equation expedited by reinforcement learning","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-10T23:58:37.969429Z"},"links":{"citing_paper":"/paper/2501.00046"},"observation_digest":"sha256:92837e2624f398a3bdbf5b8cdb82315ca26b4378ab2a42c2fb418da1952e721b","observation_id":"8dca96d7-fba2-4ec6-b3a2-e4e08cbd0ccb","resolution":{"observed_at":"2026-08-10T23:58:39.470771Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T23:58:39.415471Z","title":"2011 The Significance of Simple Invariant Solutions in Turbulent Flows","venue":null,"work_id":"131bb820-1ce4-49dd-a9d2-4e2cb8ebb897","year":2011},"citing_paper":{"arxiv_id":"2501.00046","last_updated":"2024-12-27T18:01:34Z","snapshot_observed_at":"2026-08-14T22:57:11.033630Z","submitted_at":"2024-12-27T18:01:34Z","title":"Numerical solutions of fixed points in two-dimensional Kuramoto-Sivashinsky equation expedited by reinforcement learning","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-10T23:58:37.973785Z"},"links":{"citing_paper":"/paper/2501.00046"},"observation_digest":"sha256:6a3158895f908ebee4326f7eb240e77a77f6d2319017a08cda5c281567d489ee","observation_id":"25ba015e-3305-4b76-8f24-38b1961cca6d","resolution":{"observed_at":"2026-08-10T23:58:39.420276Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T23:58:39.400663Z","title":"2021 Exact Coherent States and the Nonlinear Dynamics of Wall- Bounded Turbulent Flows","venue":null,"work_id":"03bf831c-5ede-427e-8c37-a66ce9b4166a","year":2021},"citing_paper":{"arxiv_id":"2501.00046","last_updated":"2024-12-27T18:01:34Z","snapshot_observed_at":"2026-08-14T22:57:11.033630Z","submitted_at":"2024-12-27T18:01:34Z","title":"Numerical solutions of fixed points in two-dimensional Kuramoto-Sivashinsky equation expedited by reinforcement learning","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-10T23:58:37.978228Z"},"links":{"citing_paper":"/paper/2501.00046"},"observation_digest":"sha256:e9c0dfcb1a3daa097af33517b80684e1ebbc7f3aafddecaf4a7d14ecc2757740","observation_id":"36dbd4b8-c78b-4c34-bdc9-8939d2290518","resolution":{"observed_at":"2026-08-10T23:58:39.405330Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T23:58:39.385134Z","title":"1986 The well-posedness of the Kuramoto–Sivashinsky equation","venue":null,"work_id":"52a3a5d8-33d3-4ad5-8690-08800415d790","year":1986},"citing_paper":{"arxiv_id":"2501.00046","last_updated":"2024-12-27T18:01:34Z","snapshot_observed_at":"2026-08-14T22:57:11.033630Z","submitted_at":"2024-12-27T18:01:34Z","title":"Numerical solutions of fixed points in two-dimensional Kuramoto-Sivashinsky equation expedited by reinforcement learning","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-10T23:58:37.982598Z"},"links":{"citing_paper":"/paper/2501.00046"},"observation_digest":"sha256:39828b12de76ef78d1a6e1dd0c16de956fbdc304eec6ce92f4bbd51e98497ed9","observation_id":"c473ad43-5693-44d7-960f-7fec5a0a5587","resolution":{"observed_at":"2026-08-10T23:58:39.390327Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T23:58:39.370746Z","title":"1991 Predicting chaos for infinite dimensional dynamical systems: the Kuramoto-Sivashinsky equation, a case study..Proceedings of the National Academy of Sciences 88, 11129–11132","venue":null,"work_id":"ef30a7bd-5d41-4c20-930c-ad9d9fa1853d","year":1991},"citing_paper":{"arxiv_id":"2501.00046","last_updated":"2024-12-27T18:01:34Z","snapshot_observed_at":"2026-08-14T22:57:11.033630Z","submitted_at":"2024-12-27T18:01:34Z","title":"Numerical solutions of fixed points in two-dimensional Kuramoto-Sivashinsky equation expedited by reinforcement learning","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-10T23:58:37.987467Z"},"links":{"citing_paper":"/paper/2501.00046"},"observation_digest":"sha256:76a266100b139877cabd223cd436495485c2e49b9a99830e9319981a0526a832","observation_id":"869b016f-c78f-4727-8dd8-3dc7b0dae516","resolution":{"observed_at":"2026-08-10T23:58:39.375274Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T23:58:39.355016Z","title":"1990 Back in the saddle again: a computer assisted study of the Kuramoto–Sivashinsky equation","venue":null,"work_id":"97ec0a43-07be-4e8c-839f-07eaba38aa48","year":1990},"citing_paper":{"arxiv_id":"2501.00046","last_updated":"2024-12-27T18:01:34Z","snapshot_observed_at":"2026-08-14T22:57:11.033630Z","submitted_at":"2024-12-27T18:01:34Z","title":"Numerical solutions of fixed points in two-dimensional Kuramoto-Sivashinsky equation expedited by reinforcement learning","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-10T23:58:37.991728Z"},"links":{"citing_paper":"/paper/2501.00046"},"observation_digest":"sha256:5c1fbec5b9c625b6b562c405f59775ff1790d19fcadb975888e19024317e2d53","observation_id":"8d6f8300-728c-4a3a-acb5-267d64a58e7e","resolution":{"observed_at":"2026-08-10T23:58:39.360592Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T23:58:39.339556Z","title":"2019 Linearly recurrent autoencoder networks for learning dynamics","venue":null,"work_id":"21ab4ed5-9d03-4539-9e02-75de34881a2d","year":2019},"citing_paper":{"arxiv_id":"2501.00046","last_updated":"2024-12-27T18:01:34Z","snapshot_observed_at":"2026-08-14T22:57:11.033630Z","submitted_at":"2024-12-27T18:01:34Z","title":"Numerical solutions of fixed points in two-dimensional Kuramoto-Sivashinsky equation expedited by reinforcement learning","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-10T23:58:37.996740Z"},"links":{"citing_paper":"/paper/2501.00046"},"observation_digest":"sha256:e224a061a94457f8073e1aa516ba2ebeb25713d5d4a3a7a9469a0c115135fd5a","observation_id":"5ae2ebe9-3a8e-426e-b199-5027ad652920","resolution":{"observed_at":"2026-08-10T23:58:39.344787Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T23:58:39.324442Z","title":"1988 The steady states of the Kuramoto-Sivashinsky equation","venue":null,"work_id":"79fb6e92-adee-4975-a280-3ed4f031b333","year":1988},"citing_paper":{"arxiv_id":"2501.00046","last_updated":"2024-12-27T18:01:34Z","snapshot_observed_at":"2026-08-14T22:57:11.033630Z","submitted_at":"2024-12-27T18:01:34Z","title":"Numerical solutions of fixed points in two-dimensional Kuramoto-Sivashinsky equation expedited by reinforcement learning","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-10T23:58:38.039517Z"},"links":{"citing_paper":"/paper/2501.00046"},"observation_digest":"sha256:e1132a86437f057d36f20f6b212ea75b623f353d89844727b1ad562751f70aeb","observation_id":"4f8bec65-fc2e-4bfe-b4f2-bb84999cdc6f","resolution":{"observed_at":"2026-08-10T23:58:39.329567Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T23:58:39.309437Z","title":"2008 Unstable recurrent patterns in Kuramoto-Sivashinsky dynamics","venue":null,"work_id":"01f7d3e7-7df4-4f37-ab61-96d8c149ac48","year":2008},"citing_paper":{"arxiv_id":"2501.00046","last_updated":"2024-12-27T18:01:34Z","snapshot_observed_at":"2026-08-14T22:57:11.033630Z","submitted_at":"2024-12-27T18:01:34Z","title":"Numerical solutions of fixed points in two-dimensional Kuramoto-Sivashinsky equation expedited by reinforcement learning","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-10T23:58:38.095756Z"},"links":{"citing_paper":"/paper/2501.00046"},"observation_digest":"sha256:6d34b166acb849fbab6ada56cef072ea3be98b2e139dc31eee01045912462422","observation_id":"c16c3979-8e34-4a6b-b008-03a36ce0550b","resolution":{"observed_at":"2026-08-10T23:58:39.313839Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T23:58:39.293676Z","title":"2004 Jacobian-free Newton–Krylov methods: a survey of approaches and applications","venue":null,"work_id":"461a13ce-fc4f-4553-9a11-d038de942181","year":2004},"citing_paper":{"arxiv_id":"2501.00046","last_updated":"2024-12-27T18:01:34Z","snapshot_observed_at":"2026-08-14T22:57:11.033630Z","submitted_at":"2024-12-27T18:01:34Z","title":"Numerical solutions of fixed points in two-dimensional Kuramoto-Sivashinsky equation expedited by reinforcement learning","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-10T23:58:38.108794Z"},"links":{"citing_paper":"/paper/2501.00046"},"observation_digest":"sha256:fb1584945a8aaddfdd9631a86b5d66f2382999486293d6ab338cdaedd9773a44","observation_id":"3bb9a68e-7eef-4662-b284-eef5466e38ed","resolution":{"observed_at":"2026-08-10T23:58:39.298502Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1710.06542","last_updated":"2017-10-18T01:10:37Z","snapshot_observed_at":"2026-08-14T20:22:42.955584Z","submitted_at":"2017-10-18T01:10:37Z","title":"Asymmetric Actor Critic for Image-Based Robot Learning","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1710.06542","snapshot_observed_at":"2026-08-10T23:58:38.113225Z","title":"2017 Asymmetric actor critic for image-based robot learning","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2501.00046","last_updated":"2024-12-27T18:01:34Z","snapshot_observed_at":"2026-08-14T22:57:11.033630Z","submitted_at":"2024-12-27T18:01:34Z","title":"Numerical solutions of fixed points in two-dimensional Kuramoto-Sivashinsky equation expedited by reinforcement learning","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-10T23:58:38.113225Z"},"links":{"cited_paper":"/paper/1710.06542","citing_paper":"/paper/2501.00046"},"observation_digest":"sha256:369472d131dbb74569176218e129e2bdb07625cab0e19aeb3b2af467ac4e13ee","observation_id":"8602ba92-d3f9-4573-912b-d345486a5b74","resolution":{"observed_at":"2026-08-10T23:58:38.113225Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1607.07086","last_updated":"2017-03-03T15:43:52Z","snapshot_observed_at":"2026-08-14T21:47:03.259242Z","submitted_at":"2016-07-24T20:05:07Z","title":"An Actor-Critic Algorithm for Sequence Prediction","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1607.07086","snapshot_observed_at":"2026-08-10T23:58:38.118420Z","title":"2016 An actor-critic algorithm for sequence prediction","venue":null,"work_id":null,"year":2016},"citing_paper":{"arxiv_id":"2501.00046","last_updated":"2024-12-27T18:01:34Z","snapshot_observed_at":"2026-08-14T22:57:11.033630Z","submitted_at":"2024-12-27T18:01:34Z","title":"Numerical solutions of fixed points in two-dimensional Kuramoto-Sivashinsky equation expedited by reinforcement learning","version":1},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-10T23:58:38.118420Z"},"links":{"cited_paper":"/paper/1607.07086","citing_paper":"/paper/2501.00046"},"observation_digest":"sha256:43d73d02fce5821cf8861e743b7175cb5eed30f2b0c15ee75001536d337b80a7","observation_id":"5251836a-eb0e-41f6-b2a1-8473a3de6cd6","resolution":{"observed_at":"2026-08-10T23:58:38.118420Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1312.5602","last_updated":"2013-12-19T16:00:08Z","snapshot_observed_at":"2026-08-14T03:19:40.736445Z","submitted_at":"2013-12-19T16:00:08Z","title":"Playing Atari with Deep Reinforcement Learning","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1312.5602","snapshot_observed_at":"2026-08-10T23:58:38.124139Z","title":"2013 Playing atari with deep reinforcement learning","venue":null,"work_id":null,"year":2013},"citing_paper":{"arxiv_id":"2501.00046","last_updated":"2024-12-27T18:01:34Z","snapshot_observed_at":"2026-08-14T22:57:11.033630Z","submitted_at":"2024-12-27T18:01:34Z","title":"Numerical solutions of fixed points in two-dimensional Kuramoto-Sivashinsky equation expedited by reinforcement learning","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-10T23:58:38.124139Z"},"links":{"cited_paper":"/paper/1312.5602","citing_paper":"/paper/2501.00046"},"observation_digest":"sha256:ce65978fc13ec607fbd48a1e30825b7dad334aac7d7938831988d68cdedd6687","observation_id":"de3bdbfc-b7c3-4026-84fe-b2ffbf84b18c","resolution":{"observed_at":"2026-08-10T23:58:38.124139Z","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":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T23:58:39.278137Z","title":"2017 Mastering the game of go without human knowledge","venue":null,"work_id":"6fc2f199-c383-42ad-a8f1-8e1c8318f036","year":2017},"citing_paper":{"arxiv_id":"2501.00046","last_updated":"2024-12-27T18:01:34Z","snapshot_observed_at":"2026-08-14T22:57:11.033630Z","submitted_at":"2024-12-27T18:01:34Z","title":"Numerical solutions of fixed points in two-dimensional Kuramoto-Sivashinsky equation expedited by reinforcement learning","version":1},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-10T23:58:38.129014Z"},"links":{"citing_paper":"/paper/2501.00046"},"observation_digest":"sha256:e21c0d4ba0a8e1d2634320161a4ab66a18458a2cc2c6bb7ac7aeb16ade81d0cb","observation_id":"9de5cab0-b3aa-4eaa-a7c4-6e27e1a217a9","resolution":{"observed_at":"2026-08-10T23:58:39.283330Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T23:58:39.175678Z","title":"2019 Learning to drive in a day","venue":null,"work_id":"a412dda8-b4ca-472a-a88b-7eea8e545665","year":2019},"citing_paper":{"arxiv_id":"2501.00046","last_updated":"2024-12-27T18:01:34Z","snapshot_observed_at":"2026-08-14T22:57:11.033630Z","submitted_at":"2024-12-27T18:01:34Z","title":"Numerical solutions of fixed points in two-dimensional Kuramoto-Sivashinsky equation expedited by reinforcement learning","version":1},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-10T23:58:38.134506Z"},"links":{"citing_paper":"/paper/2501.00046"},"observation_digest":"sha256:96a58d93da3c7de46cfe05b980d0fe2db477e62f3b70db55ee8915b9b87c39ea","observation_id":"fbb04a38-a2bc-4709-84e9-1b0c8d100220","resolution":{"observed_at":"2026-08-10T23:58:39.202198Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T23:58:39.160568Z","title":"2020 Machine Learning for Fluid Mechanics.Annual Review of Fluid Mechanics 52, 477–508","venue":null,"work_id":"f88ad6c6-678b-471c-9efe-772476bccddc","year":2020},"citing_paper":{"arxiv_id":"2501.00046","last_updated":"2024-12-27T18:01:34Z","snapshot_observed_at":"2026-08-14T22:57:11.033630Z","submitted_at":"2024-12-27T18:01:34Z","title":"Numerical solutions of fixed points in two-dimensional Kuramoto-Sivashinsky equation expedited by reinforcement learning","version":1},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-10T23:58:38.138635Z"},"links":{"citing_paper":"/paper/2501.00046"},"observation_digest":"sha256:1574fc51ad1ef7fa7d47625c39d25e975ded4bdec8ce6c72405045d85c0f95a9","observation_id":"582199cd-a91a-439f-9cb9-203adabd08a6","resolution":{"observed_at":"2026-08-10T23:58:39.165261Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T23:58:39.145068Z","title":"2020 Deep reinforcement learning in fluid mechanics: A promising method for both active flow control and shape optimization","venue":null,"work_id":"8160ed34-1ae2-4be1-b4e5-4c3f101f2a63","year":2020},"citing_paper":{"arxiv_id":"2501.00046","last_updated":"2024-12-27T18:01:34Z","snapshot_observed_at":"2026-08-14T22:57:11.033630Z","submitted_at":"2024-12-27T18:01:34Z","title":"Numerical solutions of fixed points in two-dimensional Kuramoto-Sivashinsky equation expedited by reinforcement learning","version":1},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-10T23:58:38.144008Z"},"links":{"citing_paper":"/paper/2501.00046"},"observation_digest":"sha256:6b896fa8845ed4dbae2480e2a7fe5202b0147ac20d2c4035b5f583dbd22fce0b","observation_id":"9fce1897-2c5d-45d9-b8f9-e0cedc40653b","resolution":{"observed_at":"2026-08-10T23:58:39.149850Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T23:58:39.129631Z","title":"2019 Artificial neural networks trained through deep reinforcement learning discover control strategies for active flow control.Journal of fluid mechanics 865, 281–302","venue":null,"work_id":"fea99630-b580-4119-9f69-7da111f5e4a6","year":2019},"citing_paper":{"arxiv_id":"2501.00046","last_updated":"2024-12-27T18:01:34Z","snapshot_observed_at":"2026-08-14T22:57:11.033630Z","submitted_at":"2024-12-27T18:01:34Z","title":"Numerical solutions of fixed points in two-dimensional Kuramoto-Sivashinsky equation expedited by reinforcement learning","version":1},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-08-10T23:58:38.148202Z"},"links":{"citing_paper":"/paper/2501.00046"},"observation_digest":"sha256:85b96aeb6e0a54f13dd324c4cef8ae58acd0dee063b033614a48e87e43a0b6c2","observation_id":"141497d2-bd9c-47b2-b0aa-bd65c6d0d613","resolution":{"observed_at":"2026-08-10T23:58:39.134644Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T23:58:39.114136Z","title":"2021 Robust flow control and optimal sensor placement using deep reinforcement learning","venue":null,"work_id":"159d5ce7-fcd4-437b-938c-6b1cff9945a4","year":2021},"citing_paper":{"arxiv_id":"2501.00046","last_updated":"2024-12-27T18:01:34Z","snapshot_observed_at":"2026-08-14T22:57:11.033630Z","submitted_at":"2024-12-27T18:01:34Z","title":"Numerical solutions of fixed points in two-dimensional Kuramoto-Sivashinsky equation expedited by reinforcement learning","version":1},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-08-10T23:58:38.152447Z"},"links":{"citing_paper":"/paper/2501.00046"},"observation_digest":"sha256:9e11cadcd5dd2482f63d1dcbc994e942d24a3ac11acdc52ba802875fb33c2693","observation_id":"f45641e7-35d4-4b55-842b-ef35427857a1","resolution":{"observed_at":"2026-08-10T23:58:39.119306Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T23:58:39.098466Z","title":"2022 Reinforcement-learning-based control of confined cylinder wakes with stability analyses","venue":null,"work_id":"7bac73c3-f0e3-4956-801e-e3fad9056af5","year":2022},"citing_paper":{"arxiv_id":"2501.00046","last_updated":"2024-12-27T18:01:34Z","snapshot_observed_at":"2026-08-14T22:57:11.033630Z","submitted_at":"2024-12-27T18:01:34Z","title":"Numerical solutions of fixed points in two-dimensional Kuramoto-Sivashinsky equation expedited by reinforcement learning","version":1},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-08-10T23:58:38.156632Z"},"links":{"citing_paper":"/paper/2501.00046"},"observation_digest":"sha256:8969fa9a37e1d21bab2b9a4c4e665604ecc935c605e350408a0b5be12910e2f2","observation_id":"63235c03-6aeb-4619-a040-941350a851b3","resolution":{"observed_at":"2026-08-10T23:58:39.103339Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T23:58:39.083932Z","title":"2023 Reinforcement-learning-based control of convectively unstable flows","venue":null,"work_id":"a4733249-135e-472f-b2a9-e7b4853bf107","year":2023},"citing_paper":{"arxiv_id":"2501.00046","last_updated":"2024-12-27T18:01:34Z","snapshot_observed_at":"2026-08-14T22:57:11.033630Z","submitted_at":"2024-12-27T18:01:34Z","title":"Numerical solutions of fixed points in two-dimensional Kuramoto-Sivashinsky equation expedited by reinforcement learning","version":1},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-08-10T23:58:38.161059Z"},"links":{"citing_paper":"/paper/2501.00046"},"observation_digest":"sha256:3d54c94d4a41d53a4fc06dcb18de735893a97d8f0028291071fc64e3bb68246c","observation_id":"1b33bc67-93bf-4031-a50d-e44df463b9ed","resolution":{"observed_at":"2026-08-10T23:58:39.088537Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T23:58:39.067610Z","title":"2023 Reinforcement learning of control strategies for reducing skin friction drag in a fully developed turbulent channel flow","venue":null,"work_id":"011e8e10-ac14-4f32-911d-ab14552e6e9e","year":2023},"citing_paper":{"arxiv_id":"2501.00046","last_updated":"2024-12-27T18:01:34Z","snapshot_observed_at":"2026-08-14T22:57:11.033630Z","submitted_at":"2024-12-27T18:01:34Z","title":"Numerical solutions of fixed points in two-dimensional Kuramoto-Sivashinsky equation expedited by reinforcement learning","version":1},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-08-10T23:58:38.166102Z"},"links":{"citing_paper":"/paper/2501.00046"},"observation_digest":"sha256:a5a742fe126cccfa861885f519b28588450f24e9e0579c2dd4ee039ae58cfe15","observation_id":"1aa90a85-2b03-4c71-b6a7-144afafc292e","resolution":{"observed_at":"2026-08-10T23:58:39.072924Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T23:58:39.052485Z","title":"2020 Controlling Rayleigh–Bénard convection via reinforcement learning","venue":null,"work_id":"3b673cbe-3eaa-421c-8ce6-d8a78d5b846d","year":2020},"citing_paper":{"arxiv_id":"2501.00046","last_updated":"2024-12-27T18:01:34Z","snapshot_observed_at":"2026-08-14T22:57:11.033630Z","submitted_at":"2024-12-27T18:01:34Z","title":"Numerical solutions of fixed points in two-dimensional Kuramoto-Sivashinsky equation expedited by reinforcement learning","version":1},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-08-10T23:58:38.171165Z"},"links":{"citing_paper":"/paper/2501.00046"},"observation_digest":"sha256:7c7ba9f3a1f8b249eb055f8329a9aee3205a234621bb579bea776a0dd09733b2","observation_id":"93e8d33a-91c8-4679-bc0c-f8c6900453be","resolution":{"observed_at":"2026-08-10T23:58:39.057829Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T23:58:39.037158Z","title":"2018 On-line building energy optimization using deep reinforcement learning.IEEE transactions on smart grid 10, 3698–3708","venue":null,"work_id":"67574ca2-c3b6-401b-9b64-c260d33be921","year":2018},"citing_paper":{"arxiv_id":"2501.00046","last_updated":"2024-12-27T18:01:34Z","snapshot_observed_at":"2026-08-14T22:57:11.033630Z","submitted_at":"2024-12-27T18:01:34Z","title":"Numerical solutions of fixed points in two-dimensional Kuramoto-Sivashinsky equation expedited by reinforcement learning","version":1},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-08-10T23:58:38.175843Z"},"links":{"citing_paper":"/paper/2501.00046"},"observation_digest":"sha256:6b04c833711274450507c33230957acfb14a9f745b6131da988905337024af69","observation_id":"2012e563-1665-4d4d-a8a0-1a15715abfc8","resolution":{"observed_at":"2026-08-10T23:58:39.041844Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T23:58:38.982970Z","title":"2020 Reinforcement learning for bluff body active flow control in experiments and simulations","venue":null,"work_id":"db07a219-da56-41fe-8f46-a2fae3a71a6e","year":2020},"citing_paper":{"arxiv_id":"2501.00046","last_updated":"2024-12-27T18:01:34Z","snapshot_observed_at":"2026-08-14T22:57:11.033630Z","submitted_at":"2024-12-27T18:01:34Z","title":"Numerical solutions of fixed points in two-dimensional Kuramoto-Sivashinsky equation expedited by reinforcement learning","version":1},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-08-10T23:58:38.180415Z"},"links":{"citing_paper":"/paper/2501.00046"},"observation_digest":"sha256:6f73231d4a60fd4b80fe1e379245cb32667cfbe9bd68b32ecc4747bda60920a8","observation_id":"a6256ef9-afca-479f-a974-6569e8a969a1","resolution":{"observed_at":"2026-08-10T23:58:39.026013Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T23:58:38.871296Z","title":"2021 Symmetry reduction for deep reinforcement learning active control of chaotic spatiotemporal dynamics","venue":null,"work_id":"2b364043-d44e-40ec-8764-2f9a19941a8f","year":2021},"citing_paper":{"arxiv_id":"2501.00046","last_updated":"2024-12-27T18:01:34Z","snapshot_observed_at":"2026-08-14T22:57:11.033630Z","submitted_at":"2024-12-27T18:01:34Z","title":"Numerical solutions of fixed points in two-dimensional Kuramoto-Sivashinsky equation expedited by reinforcement learning","version":1},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-08-10T23:58:38.184574Z"},"links":{"citing_paper":"/paper/2501.00046"},"observation_digest":"sha256:da9b44714f30f527da4a38590fabd44a12297bba83fd089321c858a8e0892aea","observation_id":"3c88f585-fc38-476e-bfd1-b8e728388019","resolution":{"observed_at":"2026-08-10T23:58:38.928989Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T23:58:38.770236Z","title":"2019 Control of chaotic systems by deep reinforcement learning","venue":null,"work_id":"9cbddf26-4a2b-439a-813d-5a85a3ca1caf","year":2019},"citing_paper":{"arxiv_id":"2501.00046","last_updated":"2024-12-27T18:01:34Z","snapshot_observed_at":"2026-08-14T22:57:11.033630Z","submitted_at":"2024-12-27T18:01:34Z","title":"Numerical solutions of fixed points in two-dimensional Kuramoto-Sivashinsky equation expedited by reinforcement learning","version":1},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-08-10T23:58:38.189205Z"},"links":{"citing_paper":"/paper/2501.00046"},"observation_digest":"sha256:f1d0385adcb518c3d067224f92b733f32b4091499b38aeb8f879a3948f5084d0","observation_id":"95dba1d2-b0c2-44bc-b596-9767bc6b6932","resolution":{"observed_at":"2026-08-10T23:58:38.815580Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T23:58:38.698843Z","title":"2005 Fourth-order time-stepping for stiff PDEs","venue":null,"work_id":"e056aa92-2c91-430c-97d0-cd01c49837af","year":2005},"citing_paper":{"arxiv_id":"2501.00046","last_updated":"2024-12-27T18:01:34Z","snapshot_observed_at":"2026-08-14T22:57:11.033630Z","submitted_at":"2024-12-27T18:01:34Z","title":"Numerical solutions of fixed points in two-dimensional Kuramoto-Sivashinsky equation expedited by reinforcement learning","version":1},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-08-10T23:58:38.194082Z"},"links":{"citing_paper":"/paper/2501.00046"},"observation_digest":"sha256:a7213023be1c0c3a185e4cd81c2d73852258d544c40220932a2a970880f80151","observation_id":"83193531-cfa6-476f-84e3-de7dfa0e75bc","resolution":{"observed_at":"2026-08-10T23:58:38.709501Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T23:58:38.680802Z","title":"2015 An in-depth numerical study of the two- dimensional Kuramoto–Sivashinsky equation","venue":null,"work_id":"a4040209-6648-4171-a82d-9f308c9d1819","year":2015},"citing_paper":{"arxiv_id":"2501.00046","last_updated":"2024-12-27T18:01:34Z","snapshot_observed_at":"2026-08-14T22:57:11.033630Z","submitted_at":"2024-12-27T18:01:34Z","title":"Numerical solutions of fixed points in two-dimensional Kuramoto-Sivashinsky equation expedited by reinforcement learning","version":1},"reference_index":35,"source":"pdf_text","source_observed_at":"2026-08-10T23:58:38.198808Z"},"links":{"citing_paper":"/paper/2501.00046"},"observation_digest":"sha256:574b300398ef601fbb2c17b48c29d5b5720ce1cfb52b2079e102d85a872f80d4","observation_id":"94b5bc5b-3f3f-4ff2-a5fd-7c139e6b1f67","resolution":{"observed_at":"2026-08-10T23:58:38.686218Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1908.06730","last_updated":"2019-09-10T11:27:05Z","snapshot_observed_at":"2026-08-15T13:32:41.944609Z","submitted_at":"2019-08-09T10:08:12Z","title":"Equilibria, periodic orbits and computing them","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1908.06730","snapshot_observed_at":"2026-08-10T23:58:38.203781Z","title":"2019 Equilibria, periodic orbits and computing them","venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2501.00046","last_updated":"2024-12-27T18:01:34Z","snapshot_observed_at":"2026-08-14T22:57:11.033630Z","submitted_at":"2024-12-27T18:01:34Z","title":"Numerical solutions of fixed points in two-dimensional Kuramoto-Sivashinsky equation expedited by reinforcement learning","version":1},"reference_index":36,"source":"pdf_text","source_observed_at":"2026-08-10T23:58:38.203781Z"},"links":{"cited_paper":"/paper/1908.06730","citing_paper":"/paper/2501.00046"},"observation_digest":"sha256:32ff54028088b18a326ff68530cb83f5c6fc0c66ce64e52b6ce2ce020a8f0ce0","observation_id":"77383de3-25c4-4314-b9b7-6440955a8e5a","resolution":{"observed_at":"2026-08-10T23:58:38.203781Z","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":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T23:58:38.664976Z","title":"2014 Deterministic policy gradient algorithms","venue":null,"work_id":"60366755-20a8-434d-9402-32edf81a9990","year":2014},"citing_paper":{"arxiv_id":"2501.00046","last_updated":"2024-12-27T18:01:34Z","snapshot_observed_at":"2026-08-14T22:57:11.033630Z","submitted_at":"2024-12-27T18:01:34Z","title":"Numerical solutions of fixed points in two-dimensional Kuramoto-Sivashinsky equation expedited by reinforcement learning","version":1},"reference_index":37,"source":"pdf_text","source_observed_at":"2026-08-10T23:58:38.231426Z"},"links":{"citing_paper":"/paper/2501.00046"},"observation_digest":"sha256:aa59c2f171e1132eabf96a4b3075e0c09938d8824749b25cfc92e1aa50929376","observation_id":"cc4be6c4-f115-4a07-8da8-77be2247e9bd","resolution":{"observed_at":"2026-08-10T23:58:38.669984Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1509.02971","last_updated":"2019-07-05T10:47:27Z","snapshot_observed_at":"2026-08-16T03:28:20.767090Z","submitted_at":"2015-09-09T23:01:36Z","title":"Continuous control with deep reinforcement learning","version":6},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1509.02971","snapshot_observed_at":"2026-08-10T23:58:38.254815Z","title":"2015 Continuous control with deep reinforcement learning","venue":null,"work_id":null,"year":2015},"citing_paper":{"arxiv_id":"2501.00046","last_updated":"2024-12-27T18:01:34Z","snapshot_observed_at":"2026-08-14T22:57:11.033630Z","submitted_at":"2024-12-27T18:01:34Z","title":"Numerical solutions of fixed points in two-dimensional Kuramoto-Sivashinsky equation expedited by reinforcement learning","version":1},"reference_index":38,"source":"pdf_text","source_observed_at":"2026-08-10T23:58:38.254815Z"},"links":{"cited_paper":"/paper/1509.02971","citing_paper":"/paper/2501.00046"},"observation_digest":"sha256:b0f16087704024691ae1740e24c3de00197d3b34ab66a6bbf0ca86c1ebf5a5d3","observation_id":"5cfb9522-4f53-4b1a-bca6-4d89d32d8169","resolution":{"observed_at":"2026-08-10T23:58:38.254815Z","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":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T23:58:38.648967Z","title":"2017 Surfing the edge: using feedback control to find nonlinear solutions","venue":null,"work_id":"42bc6bfc-e3ab-4309-91a3-3ad74e2eea94","year":2017},"citing_paper":{"arxiv_id":"2501.00046","last_updated":"2024-12-27T18:01:34Z","snapshot_observed_at":"2026-08-14T22:57:11.033630Z","submitted_at":"2024-12-27T18:01:34Z","title":"Numerical solutions of fixed points in two-dimensional Kuramoto-Sivashinsky equation expedited by reinforcement learning","version":1},"reference_index":39,"source":"pdf_text","source_observed_at":"2026-08-10T23:58:38.288953Z"},"links":{"citing_paper":"/paper/2501.00046"},"observation_digest":"sha256:5873ced0380754bd235acfc2704df12086217546c1ccc560593998c849de4556","observation_id":"92966f9a-cef8-4413-a81c-7efae5b1f973","resolution":{"observed_at":"2026-08-10T23:58:38.653802Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1807.02811","last_updated":"2018-07-08T13:06:26Z","snapshot_observed_at":"2026-08-13T17:25:53.968899Z","submitted_at":"2018-07-08T13:06:26Z","title":"A Tutorial on Bayesian Optimization","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1807.02811","snapshot_observed_at":"2026-08-10T23:58:38.334812Z","title":"2018 A tutorial on Bayesian optimization","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2501.00046","last_updated":"2024-12-27T18:01:34Z","snapshot_observed_at":"2026-08-14T22:57:11.033630Z","submitted_at":"2024-12-27T18:01:34Z","title":"Numerical solutions of fixed points in two-dimensional Kuramoto-Sivashinsky equation expedited by reinforcement learning","version":1},"reference_index":40,"source":"pdf_text","source_observed_at":"2026-08-10T23:58:38.334812Z"},"links":{"cited_paper":"/paper/1807.02811","citing_paper":"/paper/2501.00046"},"observation_digest":"sha256:1b3d780cc37d81dba1f808c9b2743ef1e8e0caca904cd7fe8c6acf88e7aa158f","observation_id":"7033feea-75ab-4069-8216-ca4aa81f852a","resolution":{"observed_at":"2026-08-10T23:58:38.334812Z","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":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T23:58:38.632546Z","title":"2012 Practical bayesian optimization of machine learning algorithms","venue":null,"work_id":"88bc1cad-204e-43ac-8a76-e352eba85fce","year":2012},"citing_paper":{"arxiv_id":"2501.00046","last_updated":"2024-12-27T18:01:34Z","snapshot_observed_at":"2026-08-14T22:57:11.033630Z","submitted_at":"2024-12-27T18:01:34Z","title":"Numerical solutions of fixed points in two-dimensional Kuramoto-Sivashinsky equation expedited by reinforcement learning","version":1},"reference_index":41,"source":"pdf_text","source_observed_at":"2026-08-10T23:58:38.378125Z"},"links":{"citing_paper":"/paper/2501.00046"},"observation_digest":"sha256:3cd2bfbc338050f6d519f7f905e2e5fd35039a0ac78483df416270d9dcbab052","observation_id":"0dbc8150-bb96-4de1-8a75-4fa371b7daea","resolution":{"observed_at":"2026-08-10T23:58:38.637940Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T23:58:38.614443Z","title":"2015 Scalable bayesian optimization using deep neural networks","venue":null,"work_id":"3c2b724d-8a4b-4d77-9b9a-c60000c0d205","year":2015},"citing_paper":{"arxiv_id":"2501.00046","last_updated":"2024-12-27T18:01:34Z","snapshot_observed_at":"2026-08-14T22:57:11.033630Z","submitted_at":"2024-12-27T18:01:34Z","title":"Numerical solutions of fixed points in two-dimensional Kuramoto-Sivashinsky equation expedited by reinforcement learning","version":1},"reference_index":42,"source":"pdf_text","source_observed_at":"2026-08-10T23:58:38.414050Z"},"links":{"citing_paper":"/paper/2501.00046"},"observation_digest":"sha256:873743c8f812b711f71299263b612d879973e11420994b2bba601a2d83d98a71","observation_id":"dd4d9f8f-737f-493f-9f8b-fa6eff6d0322","resolution":{"observed_at":"2026-08-10T23:58:38.621328Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}}],"paper":{"arxiv_id":"2501.00046","last_updated":"2024-12-27T18:01:34Z","latest_version":1,"primary_category":"cs.LG","snapshot_observed_at":"2026-08-14T22:57:11.033630Z","submitted_at":"2024-12-27T18:01:34Z","title":"Numerical solutions of fixed points in two-dimensional Kuramoto-Sivashinsky equation expedited by reinforcement learning"},"reference_resolution":{"displayed":42,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":6,"verified_exact":0,"verified_fuzzy":36},"total_outbound_references":42},"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":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"thesis":"As of 16 August 2026, this Paper Citation Record lists 42 of 42 outbound references and 0 inbound Pith citation observations for arXiv:2501.00046."}