{"as_of":"2026-08-20T02:41:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:e595ed24f7569a1af09855443d4f105d3c5f0ca2f41f5590168d08c535fbe046","coverage":[{"denominator":60,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":60,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-03T23:27:17.171951Z","state":"measured"},{"denominator":60,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":60,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-19T06:32:44.657259+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/2511.06126/citation-record","integrity":"/paper/2511.06126/integrity","json":"/paper/2511.06126/citation-record.json","paper":"/paper/2511.06126"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-03T23:27:11.858310Z","title":"Space –bandwidth product of optical signals and systems","venue":null,"work_id":null,"year":1996},"citing_paper":{"arxiv_id":"2511.06126","last_updated":"2025-11-08T20:35:04Z","snapshot_observed_at":"2026-08-03T23:27:10.922366Z","submitted_at":"2025-11-08T20:35:04Z","title":"Video-rate gigapixel ptychography via space-time neural field representations","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-03T23:27:11.858310Z"},"links":{"citing_paper":"/paper/2511.06126"},"observation_digest":"sha256:243f4f4e19853c8a5bb6e2b8d082d247d7457240c6e638af6e7e58e30c17799e","observation_id":"2cd69bcf-3af3-4830-8afd-c2902c12af7c","resolution":{"observed_at":"2026-08-03T23:27:11.858310Z","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":"2026-08-03T23:27:11.943389Z","title":"Review of bio-optical imaging systems with a high space-bandwidth product","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2511.06126","last_updated":"2025-11-08T20:35:04Z","snapshot_observed_at":"2026-08-03T23:27:10.922366Z","submitted_at":"2025-11-08T20:35:04Z","title":"Video-rate gigapixel ptychography via space-time neural field representations","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-03T23:27:11.943389Z"},"links":{"citing_paper":"/paper/2511.06126"},"observation_digest":"sha256:6c34a4343c369781168553313988bd4e31dd4b2a2bbad2a7f30e9b24fc52a8f0","observation_id":"cc9b9824-b156-4cf3-96f7-73af2b4e0786","resolution":{"observed_at":"2026-08-03T23:27:11.943389Z","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":"2026-08-03T23:27:12.076481Z","title":"Whole slide imaging in pathology: advantages, limitations, and emerging perspectives","venue":null,"work_id":null,"year":2015},"citing_paper":{"arxiv_id":"2511.06126","last_updated":"2025-11-08T20:35:04Z","snapshot_observed_at":"2026-08-03T23:27:10.922366Z","submitted_at":"2025-11-08T20:35:04Z","title":"Video-rate gigapixel ptychography via space-time neural field representations","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-03T23:27:12.076481Z"},"links":{"citing_paper":"/paper/2511.06126"},"observation_digest":"sha256:7b0b6523a92158943a3f7b86688f9f9adbde4a4d456b48f428fecafbc5ddd427","observation_id":"f65b58f2-7921-41b4-93e2-20fdbb1205bc","resolution":{"observed_at":"2026-08-03T23:27:12.076481Z","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":"2026-08-03T23:27:12.116554Z","title":"OpenWSI: a low-cost, high-throughput whole slide imaging system via single-frame autofocusing and open-source hardware","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2511.06126","last_updated":"2025-11-08T20:35:04Z","snapshot_observed_at":"2026-08-03T23:27:10.922366Z","submitted_at":"2025-11-08T20:35:04Z","title":"Video-rate gigapixel ptychography via space-time neural field representations","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-03T23:27:12.116554Z"},"links":{"citing_paper":"/paper/2511.06126"},"observation_digest":"sha256:532955aeebd586b390a41b77e765a69e5a29481115dcbacbccdc6736bc47ee07","observation_id":"018fbb5c-a7e3-466e-90b0-e6f3f33114d2","resolution":{"observed_at":"2026-08-03T23:27:12.116554Z","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":"2026-08-03T23:27:12.198968Z","title":"High-throughput digital pathology via a handheld, multiplexed, and AI-powered ptychographic whole slide scanner","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2511.06126","last_updated":"2025-11-08T20:35:04Z","snapshot_observed_at":"2026-08-03T23:27:10.922366Z","submitted_at":"2025-11-08T20:35:04Z","title":"Video-rate gigapixel ptychography via space-time neural field representations","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-03T23:27:12.198968Z"},"links":{"citing_paper":"/paper/2511.06126"},"observation_digest":"sha256:4529dddded15a8f31595abd2318063e3f0cb7acfcce46a7ee25c02777a90f32b","observation_id":"0f126171-096f-449a-a774-f677c5f73209","resolution":{"observed_at":"2026-08-03T23:27:12.198968Z","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":"2026-08-03T23:27:12.251806Z","title":"Resolution-Enhanced Parallel Coded Ptychography for High-Throughput Optical Imaging","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2511.06126","last_updated":"2025-11-08T20:35:04Z","snapshot_observed_at":"2026-08-03T23:27:10.922366Z","submitted_at":"2025-11-08T20:35:04Z","title":"Video-rate gigapixel ptychography via space-time neural field representations","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-03T23:27:12.251806Z"},"links":{"citing_paper":"/paper/2511.06126"},"observation_digest":"sha256:c560a6c70c8381c6dcb8bad2a09ac13040e9f356a35191f6a538aafdbe23dacf","observation_id":"65e0195d-cbfb-40af-b337-ae87ec3cb1ec","resolution":{"observed_at":"2026-08-03T23:27:12.251806Z","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":"2026-08-03T23:27:12.311901Z","title":"Wide -field, high -resolution Fourier ptychographic microscopy","venue":null,"work_id":null,"year":2013},"citing_paper":{"arxiv_id":"2511.06126","last_updated":"2025-11-08T20:35:04Z","snapshot_observed_at":"2026-08-03T23:27:10.922366Z","submitted_at":"2025-11-08T20:35:04Z","title":"Video-rate gigapixel ptychography via space-time neural field representations","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-03T23:27:12.311901Z"},"links":{"citing_paper":"/paper/2511.06126"},"observation_digest":"sha256:baa91532910de958ea2758e235241656ec4a15a8f1ef49eba4a6895bf49ca2ee","observation_id":"0c40d2b8-65a4-4d8b-a2ba-f6a06d8d84ad","resolution":{"observed_at":"2026-08-03T23:27:12.311901Z","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":"2026-08-03T23:27:12.391131Z","title":"Concept, implementations and applications of Fourier ptychography","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2511.06126","last_updated":"2025-11-08T20:35:04Z","snapshot_observed_at":"2026-08-03T23:27:10.922366Z","submitted_at":"2025-11-08T20:35:04Z","title":"Video-rate gigapixel ptychography via space-time neural field representations","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-03T23:27:12.391131Z"},"links":{"citing_paper":"/paper/2511.06126"},"observation_digest":"sha256:ac2fe5b36795fae505ab5d2d954a7db7d523e01acfcbc9811d03984f7bf838b5","observation_id":"bf2af399-5886-42e1-a69d-d13d40750e2d","resolution":{"observed_at":"2026-08-03T23:27:12.391131Z","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":"2026-08-03T23:27:12.427492Z","title":"Coded aperture compressive temporal imaging","venue":null,"work_id":null,"year":2013},"citing_paper":{"arxiv_id":"2511.06126","last_updated":"2025-11-08T20:35:04Z","snapshot_observed_at":"2026-08-03T23:27:10.922366Z","submitted_at":"2025-11-08T20:35:04Z","title":"Video-rate gigapixel ptychography via space-time neural field representations","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-03T23:27:12.427492Z"},"links":{"citing_paper":"/paper/2511.06126"},"observation_digest":"sha256:08a4c91eee0edc32f92eaaf65efb60bfc7d8d1747068f8799244c3babd4aeb8a","observation_id":"eab40513-a088-4da9-9947-27b2345cf150","resolution":{"observed_at":"2026-08-03T23:27:12.427492Z","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":"2026-08-03T23:27:12.492725Z","title":"Multiscale lens design","venue":null,"work_id":null,"year":2009},"citing_paper":{"arxiv_id":"2511.06126","last_updated":"2025-11-08T20:35:04Z","snapshot_observed_at":"2026-08-03T23:27:10.922366Z","submitted_at":"2025-11-08T20:35:04Z","title":"Video-rate gigapixel ptychography via space-time neural field representations","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-03T23:27:12.492725Z"},"links":{"citing_paper":"/paper/2511.06126"},"observation_digest":"sha256:51d0e5fbdd0b0d5ed406751f28f3955f2c0d4520e910f648733e892b73c8bfd7","observation_id":"22d12d3e-4a27-4148-bac3-ef6eed076d85","resolution":{"observed_at":"2026-08-03T23:27:12.492725Z","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":"2026-08-03T23:27:12.539409Z","title":"Multiscale gigapixel photography","venue":null,"work_id":null,"year":2012},"citing_paper":{"arxiv_id":"2511.06126","last_updated":"2025-11-08T20:35:04Z","snapshot_observed_at":"2026-08-03T23:27:10.922366Z","submitted_at":"2025-11-08T20:35:04Z","title":"Video-rate gigapixel ptychography via space-time neural field representations","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-03T23:27:12.539409Z"},"links":{"citing_paper":"/paper/2511.06126"},"observation_digest":"sha256:e6475fa509d1c8c2c0ad7278b18b9cc05a09945b55020b2b2889880f748211c4","observation_id":"d62c0669-55da-478f-b411-60a10bfa36f9","resolution":{"observed_at":"2026-08-03T23:27:12.539409Z","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":"2026-08-03T23:27:12.636795Z","title":"Design and scaling of monocentric multiscale imagers","venue":null,"work_id":null,"year":2012},"citing_paper":{"arxiv_id":"2511.06126","last_updated":"2025-11-08T20:35:04Z","snapshot_observed_at":"2026-08-03T23:27:10.922366Z","submitted_at":"2025-11-08T20:35:04Z","title":"Video-rate gigapixel ptychography via space-time neural field representations","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-03T23:27:12.636795Z"},"links":{"citing_paper":"/paper/2511.06126"},"observation_digest":"sha256:b6e52e84f90904ab8489a5d07c590b59622a1d45761bc513613adad23f620bbe","observation_id":"17678519-bcb6-448a-a70c-44a3f144f302","resolution":{"observed_at":"2026-08-03T23:27:12.636795Z","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":"2026-08-03T23:27:12.712392Z","title":"Video-rate imaging of biological dynamics at centimetre scale and micrometre resolution","venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2511.06126","last_updated":"2025-11-08T20:35:04Z","snapshot_observed_at":"2026-08-03T23:27:10.922366Z","submitted_at":"2025-11-08T20:35:04Z","title":"Video-rate gigapixel ptychography via space-time neural field representations","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-03T23:27:12.712392Z"},"links":{"citing_paper":"/paper/2511.06126"},"observation_digest":"sha256:142fc029192291957fa6694b20ba6b37a48c221cb8da8146e0adc84c6ca99438","observation_id":"f42c015c-7903-4cde-820e-7fe2cdbe63fe","resolution":{"observed_at":"2026-08-03T23:27:12.712392Z","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":"2026-08-03T23:27:12.776100Z","title":"Parallelized computational 3D video microscopy of freely moving organisms at multiple gigapixels per second","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2511.06126","last_updated":"2025-11-08T20:35:04Z","snapshot_observed_at":"2026-08-03T23:27:10.922366Z","submitted_at":"2025-11-08T20:35:04Z","title":"Video-rate gigapixel ptychography via space-time neural field representations","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-03T23:27:12.776100Z"},"links":{"citing_paper":"/paper/2511.06126"},"observation_digest":"sha256:548d9c18997c3d546269e15b78c7c5fd174dc266715781a99c26f22c5284005e","observation_id":"5daf34bd-2af3-45fd-8abe-23669e1c2c8e","resolution":{"observed_at":"2026-08-03T23:27:12.776100Z","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":"2026-08-03T23:27:12.863252Z","title":"An array microscope for ultrarapid virtual slide processing and telepathology","venue":null,"work_id":null,"year":2004},"citing_paper":{"arxiv_id":"2511.06126","last_updated":"2025-11-08T20:35:04Z","snapshot_observed_at":"2026-08-03T23:27:10.922366Z","submitted_at":"2025-11-08T20:35:04Z","title":"Video-rate gigapixel ptychography via space-time neural field representations","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-03T23:27:12.863252Z"},"links":{"citing_paper":"/paper/2511.06126"},"observation_digest":"sha256:a79aad0a2e60a68db39972ac159fe74930d298ecbb51a3d56733d46b0bcb4d87","observation_id":"a909058b-29c6-42e3-84a8-ad28053e0688","resolution":{"observed_at":"2026-08-03T23:27:12.863252Z","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":"2026-08-03T23:27:12.965702Z","title":"Nerf: Representing scenes as neural radiance fields for view synthesis","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2511.06126","last_updated":"2025-11-08T20:35:04Z","snapshot_observed_at":"2026-08-03T23:27:10.922366Z","submitted_at":"2025-11-08T20:35:04Z","title":"Video-rate gigapixel ptychography via space-time neural field representations","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-03T23:27:12.965702Z"},"links":{"citing_paper":"/paper/2511.06126"},"observation_digest":"sha256:f41608a8cea535933216b361bef2f80296dd8c21baedec59d540ef10c2062ef3","observation_id":"0f95052d-7d27-4e92-b2f3-fc3735277423","resolution":{"observed_at":"2026-08-03T23:27:12.965702Z","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":"2026-08-03T23:27:13.033861Z","title":"Fourier features let networks learn high frequency functions in low dimensional domains","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2511.06126","last_updated":"2025-11-08T20:35:04Z","snapshot_observed_at":"2026-08-03T23:27:10.922366Z","submitted_at":"2025-11-08T20:35:04Z","title":"Video-rate gigapixel ptychography via space-time neural field representations","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-03T23:27:13.033861Z"},"links":{"citing_paper":"/paper/2511.06126"},"observation_digest":"sha256:b8c804654c93a3c7ceb80c0310cc59e948c5b611a860df6e087ba70c2e04dcc5","observation_id":"5e11dbb7-aac7-4fca-9023-2140dcbd97b5","resolution":{"observed_at":"2026-08-03T23:27:13.033861Z","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":"2026-08-03T23:27:13.121382Z","title":"Nerv: Neural representations for videos","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2511.06126","last_updated":"2025-11-08T20:35:04Z","snapshot_observed_at":"2026-08-03T23:27:10.922366Z","submitted_at":"2025-11-08T20:35:04Z","title":"Video-rate gigapixel ptychography via space-time neural field representations","version":1},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-03T23:27:13.121382Z"},"links":{"citing_paper":"/paper/2511.06126"},"observation_digest":"sha256:f59dd1373b6d1eb5f4c76587c590834565d2748d389f7c8270c659bf9b79eafe","observation_id":"30110bd1-5a52-4145-b466-1b883b03abb5","resolution":{"observed_at":"2026-08-03T23:27:13.121382Z","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":"2026-08-03T23:27:13.214977Z","title":"Instant neural graphics primitives with a multiresolution hash encoding","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2511.06126","last_updated":"2025-11-08T20:35:04Z","snapshot_observed_at":"2026-08-03T23:27:10.922366Z","submitted_at":"2025-11-08T20:35:04Z","title":"Video-rate gigapixel ptychography via space-time neural field representations","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-03T23:27:13.214977Z"},"links":{"citing_paper":"/paper/2511.06126"},"observation_digest":"sha256:05c81f5c65163b429636065e874b4d21dbce846052ba8becdcece500a7707598","observation_id":"fc63848b-8dcc-471b-9080-22f5bc61ca4d","resolution":{"observed_at":"2026-08-03T23:27:13.214977Z","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":"2026-08-03T23:27:13.262021Z","title":"Tensorf: Tensorial radiance fields","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2511.06126","last_updated":"2025-11-08T20:35:04Z","snapshot_observed_at":"2026-08-03T23:27:10.922366Z","submitted_at":"2025-11-08T20:35:04Z","title":"Video-rate gigapixel ptychography via space-time neural field representations","version":1},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-03T23:27:13.262021Z"},"links":{"citing_paper":"/paper/2511.06126"},"observation_digest":"sha256:bbcea31d297cd3c4f279dda65aa4952e03161385409a62347ceb1149cd33a968","observation_id":"05e00248-da3b-4b39-9b0f-c6ac583ee37d","resolution":{"observed_at":"2026-08-03T23:27:13.262021Z","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":"2026-08-03T23:27:13.356431Z","title":"Implicit neural representations with periodic activation functions","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2511.06126","last_updated":"2025-11-08T20:35:04Z","snapshot_observed_at":"2026-08-03T23:27:10.922366Z","submitted_at":"2025-11-08T20:35:04Z","title":"Video-rate gigapixel ptychography via space-time neural field representations","version":1},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-03T23:27:13.356431Z"},"links":{"citing_paper":"/paper/2511.06126"},"observation_digest":"sha256:28800c7501c22d4af7c7536dd402a08455ea0c7a6612465bd163fe06662085bf","observation_id":"6be4877d-1a05-4df4-8945-8201635ec474","resolution":{"observed_at":"2026-08-03T23:27:13.356431Z","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":"2026-08-03T23:27:13.424829Z","title":"K-planes: Explicit radiance fields in space, time, and appearance","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2511.06126","last_updated":"2025-11-08T20:35:04Z","snapshot_observed_at":"2026-08-03T23:27:10.922366Z","submitted_at":"2025-11-08T20:35:04Z","title":"Video-rate gigapixel ptychography via space-time neural field representations","version":1},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-03T23:27:13.424829Z"},"links":{"citing_paper":"/paper/2511.06126"},"observation_digest":"sha256:60973e734f7b4bc9662f44d43e563f77045c53a93d85ca70ae96116d662324ec","observation_id":"f46da5c5-9fd6-4978-9cc8-23477364dc54","resolution":{"observed_at":"2026-08-03T23:27:13.424829Z","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":"2026-08-03T23:27:13.495449Z","title":"FPM -WSI: Fourier ptychographic whole slide imaging via feature-domain backdiffraction","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2511.06126","last_updated":"2025-11-08T20:35:04Z","snapshot_observed_at":"2026-08-03T23:27:10.922366Z","submitted_at":"2025-11-08T20:35:04Z","title":"Video-rate gigapixel ptychography via space-time neural field representations","version":1},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-03T23:27:13.495449Z"},"links":{"citing_paper":"/paper/2511.06126"},"observation_digest":"sha256:9ddaf7123c776fc01c4048ccc956e61301e1b8f089604bc14214cce1e8e3a223","observation_id":"f34b3130-1674-4bb7-846d-64e10623d676","resolution":{"observed_at":"2026-08-03T23:27:13.495449Z","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":"2026-08-03T23:27:13.562270Z","title":"DNF: diffractive neural field for lensless microscopic imaging","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2511.06126","last_updated":"2025-11-08T20:35:04Z","snapshot_observed_at":"2026-08-03T23:27:10.922366Z","submitted_at":"2025-11-08T20:35:04Z","title":"Video-rate gigapixel ptychography via space-time neural field representations","version":1},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-08-03T23:27:13.562270Z"},"links":{"citing_paper":"/paper/2511.06126"},"observation_digest":"sha256:f259c541c6e485ea9efe3b9715fa076516585d6e9774cb7b83af79b6b7eff78e","observation_id":"daeefdd4-43d9-4811-8317-7424d27b53ac","resolution":{"observed_at":"2026-08-03T23:27:13.562270Z","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":"2026-08-03T23:27:13.611939Z","title":"Recovery of continuous 3D refractive index maps from discrete intensity-only measurements using neural fields","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2511.06126","last_updated":"2025-11-08T20:35:04Z","snapshot_observed_at":"2026-08-03T23:27:10.922366Z","submitted_at":"2025-11-08T20:35:04Z","title":"Video-rate gigapixel ptychography via space-time neural field representations","version":1},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-08-03T23:27:13.611939Z"},"links":{"citing_paper":"/paper/2511.06126"},"observation_digest":"sha256:5d8ccc609fb2efdbfa5b80b8a4ba8abec68c20e488534af096c523fb9afa88aa","observation_id":"ac660261-4c9e-4250-9885-daf489c77b27","resolution":{"observed_at":"2026-08-03T23:27:13.611939Z","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":"2026-08-03T23:27:13.712261Z","title":"Fourier ptychographic microscopy image stack reconstruction using implicit neural representations","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2511.06126","last_updated":"2025-11-08T20:35:04Z","snapshot_observed_at":"2026-08-03T23:27:10.922366Z","submitted_at":"2025-11-08T20:35:04Z","title":"Video-rate gigapixel ptychography via space-time neural field representations","version":1},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-08-03T23:27:13.712261Z"},"links":{"citing_paper":"/paper/2511.06126"},"observation_digest":"sha256:7ac1a2e8bcc1a7b3ccfa3e326683d293bd2eb8c762d6c522751da50160b3559b","observation_id":"66cb2a82-c649-47e5-b410-b3dd4c156a5b","resolution":{"observed_at":"2026-08-03T23:27:13.712261Z","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":"2026-08-03T23:27:13.784669Z","title":"Whole-field, high-resolution Fourier ptychography with neural pupil engineering","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2511.06126","last_updated":"2025-11-08T20:35:04Z","snapshot_observed_at":"2026-08-03T23:27:10.922366Z","submitted_at":"2025-11-08T20:35:04Z","title":"Video-rate gigapixel ptychography via space-time neural field representations","version":1},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-08-03T23:27:13.784669Z"},"links":{"citing_paper":"/paper/2511.06126"},"observation_digest":"sha256:f91d3e7367325e4596701ffb2195f2a597af65349fa5a70bc853167ec47fe8da","observation_id":"9ff89f0d-5914-41a5-98da-017b2e636313","resolution":{"observed_at":"2026-08-03T23:27:13.784669Z","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":"2026-08-03T23:27:13.828526Z","title":"Neural space –time model for dynamic multi -shot imaging","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2511.06126","last_updated":"2025-11-08T20:35:04Z","snapshot_observed_at":"2026-08-03T23:27:10.922366Z","submitted_at":"2025-11-08T20:35:04Z","title":"Video-rate gigapixel ptychography via space-time neural field representations","version":1},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-08-03T23:27:13.828526Z"},"links":{"citing_paper":"/paper/2511.06126"},"observation_digest":"sha256:20eb232b63b29f4618266b84e444046f45047f591d6ba19d83676a10e8901936","observation_id":"f360250c-0f12-49cf-96fb-34a707c44591","resolution":{"observed_at":"2026-08-03T23:27:13.828526Z","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":"2026-08-03T23:27:13.929834Z","title":"RHINO: regularizing the hash-based implicit neural representation","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2511.06126","last_updated":"2025-11-08T20:35:04Z","snapshot_observed_at":"2026-08-03T23:27:10.922366Z","submitted_at":"2025-11-08T20:35:04Z","title":"Video-rate gigapixel ptychography via space-time neural field representations","version":1},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-08-03T23:27:13.929834Z"},"links":{"citing_paper":"/paper/2511.06126"},"observation_digest":"sha256:b0e5935c637d699718e54802ccf30dd82a9c98313e5814f0efa2af93fb93a9b4","observation_id":"f47bc5a5-fa96-428a-a812-c8c59bb06e13","resolution":{"observed_at":"2026-08-03T23:27:13.929834Z","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":"2026-08-03T23:27:14.003576Z","title":"Neural-field-assisted transport-of-intensity phase microscopy: partially coherent quantitative phase imaging under unknown defocus distance","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2511.06126","last_updated":"2025-11-08T20:35:04Z","snapshot_observed_at":"2026-08-03T23:27:10.922366Z","submitted_at":"2025-11-08T20:35:04Z","title":"Video-rate gigapixel ptychography via space-time neural field representations","version":1},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-08-03T23:27:14.003576Z"},"links":{"citing_paper":"/paper/2511.06126"},"observation_digest":"sha256:ecdded9abbd1e15b03571b625d20c4f455bea5414badc95fd156b5f71841cc54","observation_id":"1bb969a0-3290-411b-9e68-41ddf85faaf9","resolution":{"observed_at":"2026-08-03T23:27:14.003576Z","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":"2026-08-03T23:27:14.102731Z","title":"High -speed and wide- field nanoscale table-top ptychographic EUV imaging and beam characterization with a sCMOS detector","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2511.06126","last_updated":"2025-11-08T20:35:04Z","snapshot_observed_at":"2026-08-03T23:27:10.922366Z","submitted_at":"2025-11-08T20:35:04Z","title":"Video-rate gigapixel ptychography via space-time neural field representations","version":1},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-08-03T23:27:14.102731Z"},"links":{"citing_paper":"/paper/2511.06126"},"observation_digest":"sha256:26ddc3b7d75ed535eadd076e29f6f2bbe4bcf35d3a9e8324d5c9396bdc2a66d9","observation_id":"d5b12e7a-e91d-4d40-88fb-859870a27b87","resolution":{"observed_at":"2026-08-03T23:27:14.102731Z","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":"2026-08-03T23:27:14.237280Z","title":"Ptychographic electron microscopy using high- angle dark-field scattering for sub-nanometre resolution imaging","venue":null,"work_id":null,"year":2012},"citing_paper":{"arxiv_id":"2511.06126","last_updated":"2025-11-08T20:35:04Z","snapshot_observed_at":"2026-08-03T23:27:10.922366Z","submitted_at":"2025-11-08T20:35:04Z","title":"Video-rate gigapixel ptychography via space-time neural field representations","version":1},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-08-03T23:27:14.237280Z"},"links":{"citing_paper":"/paper/2511.06126"},"observation_digest":"sha256:49b21db7a3c5c13ce762b740db20778f1e8b4f677f79195355fadc57d4cb3574","observation_id":"0e795fb5-58c1-4f13-87e5-bdb143509d5f","resolution":{"observed_at":"2026-08-03T23:27:14.237280Z","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":"2026-08-03T23:27:14.357163Z","title":"Electron ptychography of 2D materials to deep sub-ångström resolution","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2511.06126","last_updated":"2025-11-08T20:35:04Z","snapshot_observed_at":"2026-08-03T23:27:10.922366Z","submitted_at":"2025-11-08T20:35:04Z","title":"Video-rate gigapixel ptychography via space-time neural field representations","version":1},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-08-03T23:27:14.357163Z"},"links":{"citing_paper":"/paper/2511.06126"},"observation_digest":"sha256:a2ab3ece868799ffd06ffad694b94a0c568d1d5631470f1bcfb0d5e2118d697f","observation_id":"5145e6d7-ad5d-46cc-99fe-64dcd8627a7c","resolution":{"observed_at":"2026-08-03T23:27:14.357163Z","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":"2026-08-03T23:27:14.472009Z","title":"X-ray ptychography","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2511.06126","last_updated":"2025-11-08T20:35:04Z","snapshot_observed_at":"2026-08-03T23:27:10.922366Z","submitted_at":"2025-11-08T20:35:04Z","title":"Video-rate gigapixel ptychography via space-time neural field representations","version":1},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-08-03T23:27:14.472009Z"},"links":{"citing_paper":"/paper/2511.06126"},"observation_digest":"sha256:e48c654aecffa22eeda6ce66c3124005616f96d346719dbb271ab263656438f4","observation_id":"6a72aae7-74c9-4eb6-9eec-b26bb6e97a9c","resolution":{"observed_at":"2026-08-03T23:27:14.472009Z","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":"2026-08-03T23:27:14.566602Z","title":"Ptychography at all wavelengths","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2511.06126","last_updated":"2025-11-08T20:35:04Z","snapshot_observed_at":"2026-08-03T23:27:10.922366Z","submitted_at":"2025-11-08T20:35:04Z","title":"Video-rate gigapixel ptychography via space-time neural field representations","version":1},"reference_index":35,"source":"pdf_text","source_observed_at":"2026-08-03T23:27:14.566602Z"},"links":{"citing_paper":"/paper/2511.06126"},"observation_digest":"sha256:7a9eb7eb43aa84268ddf961eda09c35b54b73ba7e9b98d03dec167bab60fa7a6","observation_id":"2abb36b7-ce5a-4c53-b39e-f94c4ad0f6bc","resolution":{"observed_at":"2026-08-03T23:27:14.566602Z","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":"2026-08-03T23:27:14.652976Z","title":"Poisson image editing","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2511.06126","last_updated":"2025-11-08T20:35:04Z","snapshot_observed_at":"2026-08-03T23:27:10.922366Z","submitted_at":"2025-11-08T20:35:04Z","title":"Video-rate gigapixel ptychography via space-time neural field representations","version":1},"reference_index":36,"source":"pdf_text","source_observed_at":"2026-08-03T23:27:14.652976Z"},"links":{"citing_paper":"/paper/2511.06126"},"observation_digest":"sha256:b54dc047937fff67492fcb864c009cd14fb1af2a7613d0a4dcd3b50bba3806bb","observation_id":"46f126b3-7561-4060-adce-7680eb73ea04","resolution":{"observed_at":"2026-08-03T23:27:14.652976Z","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":"2026-08-03T23:27:14.740799Z","title":"Gradientshop: A gradient -domain optimization framework for image and video filtering","venue":null,"work_id":null,"year":2010},"citing_paper":{"arxiv_id":"2511.06126","last_updated":"2025-11-08T20:35:04Z","snapshot_observed_at":"2026-08-03T23:27:10.922366Z","submitted_at":"2025-11-08T20:35:04Z","title":"Video-rate gigapixel ptychography via space-time neural field representations","version":1},"reference_index":37,"source":"pdf_text","source_observed_at":"2026-08-03T23:27:14.740799Z"},"links":{"citing_paper":"/paper/2511.06126"},"observation_digest":"sha256:17c7dfd5292f25b1ebe57223c8b44186e382cb3294d34509b992ba69a53e9088","observation_id":"d44f9322-bfc3-4f13-9425-c67f5ca6c868","resolution":{"observed_at":"2026-08-03T23:27:14.740799Z","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":"2026-08-03T23:27:14.793779Z","title":"ELFPIE: an error -laxity Fourier ptychographic iterative engine","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2511.06126","last_updated":"2025-11-08T20:35:04Z","snapshot_observed_at":"2026-08-03T23:27:10.922366Z","submitted_at":"2025-11-08T20:35:04Z","title":"Video-rate gigapixel ptychography via space-time neural field representations","version":1},"reference_index":38,"source":"pdf_text","source_observed_at":"2026-08-03T23:27:14.793779Z"},"links":{"citing_paper":"/paper/2511.06126"},"observation_digest":"sha256:f330cda1f59b3c7a30fd31a48d7f88374593c3e535f2bd28249fcdbbdcc11f11","observation_id":"3e93120c-9174-41b1-b319-acce47ce4958","resolution":{"observed_at":"2026-08-03T23:27:14.793779Z","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":"2026-08-03T23:27:14.860869Z","title":"Deep-ultraviolet Fourier ptychography (DUV-FP) for label- free biochemical imaging via feature-domain optimization","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2511.06126","last_updated":"2025-11-08T20:35:04Z","snapshot_observed_at":"2026-08-03T23:27:10.922366Z","submitted_at":"2025-11-08T20:35:04Z","title":"Video-rate gigapixel ptychography via space-time neural field representations","version":1},"reference_index":39,"source":"pdf_text","source_observed_at":"2026-08-03T23:27:14.860869Z"},"links":{"citing_paper":"/paper/2511.06126"},"observation_digest":"sha256:f8ef95e5715e88dd90ed75df1288639fe30b2947ee6d0e5ee0c6d6e2010992fd","observation_id":"8603231e-4081-4d82-93c0-71275cfe3d94","resolution":{"observed_at":"2026-08-03T23:27:14.860869Z","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":"2026-08-03T23:27:14.924601Z","title":"An improved ptychographical phase retrieval algorithm for diffractive imaging","venue":null,"work_id":null,"year":2009},"citing_paper":{"arxiv_id":"2511.06126","last_updated":"2025-11-08T20:35:04Z","snapshot_observed_at":"2026-08-03T23:27:10.922366Z","submitted_at":"2025-11-08T20:35:04Z","title":"Video-rate gigapixel ptychography via space-time neural field representations","version":1},"reference_index":40,"source":"pdf_text","source_observed_at":"2026-08-03T23:27:14.924601Z"},"links":{"citing_paper":"/paper/2511.06126"},"observation_digest":"sha256:1cbb26e4f5352e044b2517aab206236bf444f832776cf1c8832470cfd9039564","observation_id":"6dae0caf-096d-4e89-8cc3-dc57df0d6aaa","resolution":{"observed_at":"2026-08-03T23:27:14.924601Z","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":"2026-08-03T23:27:14.996490Z","title":"Further improvements to the ptychographical iterative engine","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2511.06126","last_updated":"2025-11-08T20:35:04Z","snapshot_observed_at":"2026-08-03T23:27:10.922366Z","submitted_at":"2025-11-08T20:35:04Z","title":"Video-rate gigapixel ptychography via space-time neural field representations","version":1},"reference_index":41,"source":"pdf_text","source_observed_at":"2026-08-03T23:27:14.996490Z"},"links":{"citing_paper":"/paper/2511.06126"},"observation_digest":"sha256:eb388edf2fd27e66f236fa990d98d15cff60c74e491a793d6f393965b3150b9a","observation_id":"74e0c0e5-9aa2-4093-a323-92eed3025583","resolution":{"observed_at":"2026-08-03T23:27:14.996490Z","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":"2026-08-03T23:27:15.147444Z","title":"Multiplexed coded illumination for Fourier Ptychography with an LED array microscope","venue":null,"work_id":null,"year":2014},"citing_paper":{"arxiv_id":"2511.06126","last_updated":"2025-11-08T20:35:04Z","snapshot_observed_at":"2026-08-03T23:27:10.922366Z","submitted_at":"2025-11-08T20:35:04Z","title":"Video-rate gigapixel ptychography via space-time neural field representations","version":1},"reference_index":42,"source":"pdf_text","source_observed_at":"2026-08-03T23:27:15.147444Z"},"links":{"citing_paper":"/paper/2511.06126"},"observation_digest":"sha256:6ae52eac12413a7074ef014a24a5c9650f001c47eb4a93941abb3e2af47a14b8","observation_id":"504431ff-331b-48dc-8f32-2e7d3cbc548f","resolution":{"observed_at":"2026-08-03T23:27:15.147444Z","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":"2026-08-03T23:27:15.314450Z","title":"Iterative least -squares solver for generalized maximum -likelihood ptychography","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2511.06126","last_updated":"2025-11-08T20:35:04Z","snapshot_observed_at":"2026-08-03T23:27:10.922366Z","submitted_at":"2025-11-08T20:35:04Z","title":"Video-rate gigapixel ptychography via space-time neural field representations","version":1},"reference_index":43,"source":"pdf_text","source_observed_at":"2026-08-03T23:27:15.314450Z"},"links":{"citing_paper":"/paper/2511.06126"},"observation_digest":"sha256:05099f5c49200c8c06d7bfd66d65432f43c4cca1e780f0e533244f9c260741eb","observation_id":"0f893b71-601b-4eb8-a88a-e00ecc35cb67","resolution":{"observed_at":"2026-08-03T23:27:15.314450Z","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":"2026-08-03T23:27:15.421248Z","title":"Aperture-scanning Fourier ptychography for 3D refocusing and super-resolution macroscopic imaging","venue":null,"work_id":null,"year":2014},"citing_paper":{"arxiv_id":"2511.06126","last_updated":"2025-11-08T20:35:04Z","snapshot_observed_at":"2026-08-03T23:27:10.922366Z","submitted_at":"2025-11-08T20:35:04Z","title":"Video-rate gigapixel ptychography via space-time neural field representations","version":1},"reference_index":44,"source":"pdf_text","source_observed_at":"2026-08-03T23:27:15.421248Z"},"links":{"citing_paper":"/paper/2511.06126"},"observation_digest":"sha256:acfa08d76e206df28f5ab4904851a5994b818c56286ef5e27e9ae2f45807ddb3","observation_id":"e7b0fb96-482b-45ea-9fcf-b837b48cd850","resolution":{"observed_at":"2026-08-03T23:27:15.421248Z","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":"2026-08-03T23:27:15.552385Z","title":"Optical ptychography for biomedical imaging: recent progress and future directions","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2511.06126","last_updated":"2025-11-08T20:35:04Z","snapshot_observed_at":"2026-08-03T23:27:10.922366Z","submitted_at":"2025-11-08T20:35:04Z","title":"Video-rate gigapixel ptychography via space-time neural field representations","version":1},"reference_index":45,"source":"pdf_text","source_observed_at":"2026-08-03T23:27:15.552385Z"},"links":{"citing_paper":"/paper/2511.06126"},"observation_digest":"sha256:3ed7d18cf1a9c37da7b6d3cd8f825d890305a2be894ac55365c201ad11f7c1fa","observation_id":"ccc0806b-9fa7-4fd1-89c6-87cef77415ec","resolution":{"observed_at":"2026-08-03T23:27:15.552385Z","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":"2026-08-03T23:27:15.655080Z","title":"Ptychographic coherent diffractive imaging with orthogonal probe relaxation","venue":null,"work_id":null,"year":2016},"citing_paper":{"arxiv_id":"2511.06126","last_updated":"2025-11-08T20:35:04Z","snapshot_observed_at":"2026-08-03T23:27:10.922366Z","submitted_at":"2025-11-08T20:35:04Z","title":"Video-rate gigapixel ptychography via space-time neural field representations","version":1},"reference_index":46,"source":"pdf_text","source_observed_at":"2026-08-03T23:27:15.655080Z"},"links":{"citing_paper":"/paper/2511.06126"},"observation_digest":"sha256:161058bb49f9e9c8319949309c129a08e6a36be8e143f9452c692fdc1dae0b6f","observation_id":"f7a85428-3816-478c-9e8c-574a94ed8b5a","resolution":{"observed_at":"2026-08-03T23:27:15.655080Z","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":"2026-08-03T23:27:15.790979Z","title":"Atomically resolved edges and defects in lead halide perovskites","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2511.06126","last_updated":"2025-11-08T20:35:04Z","snapshot_observed_at":"2026-08-03T23:27:10.922366Z","submitted_at":"2025-11-08T20:35:04Z","title":"Video-rate gigapixel ptychography via space-time neural field representations","version":1},"reference_index":47,"source":"pdf_text","source_observed_at":"2026-08-03T23:27:15.790979Z"},"links":{"citing_paper":"/paper/2511.06126"},"observation_digest":"sha256:dbb0a3ac09f447b9adb3a9bc0458630880c0948a1579d6d41d6671cfc28b53f7","observation_id":"9dc4d33b-cc4c-45e8-ae88-94a200b27cc6","resolution":{"observed_at":"2026-08-03T23:27:15.790979Z","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":"2026-08-03T23:27:15.939888Z","title":"Ptychography","venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2511.06126","last_updated":"2025-11-08T20:35:04Z","snapshot_observed_at":"2026-08-03T23:27:10.922366Z","submitted_at":"2025-11-08T20:35:04Z","title":"Video-rate gigapixel ptychography via space-time neural field representations","version":1},"reference_index":48,"source":"pdf_text","source_observed_at":"2026-08-03T23:27:15.939888Z"},"links":{"citing_paper":"/paper/2511.06126"},"observation_digest":"sha256:1eca196cdd09f628030965241ef673d0a26b5a9fb60e6f55f4e91834d7fd680d","observation_id":"71c534e3-79e6-4c88-bb21-d061e7823304","resolution":{"observed_at":"2026-08-03T23:27:15.939888Z","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":"2026-08-03T23:27:16.007910Z","title":"Ptychography: A solution to the phase problem","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2511.06126","last_updated":"2025-11-08T20:35:04Z","snapshot_observed_at":"2026-08-03T23:27:10.922366Z","submitted_at":"2025-11-08T20:35:04Z","title":"Video-rate gigapixel ptychography via space-time neural field representations","version":1},"reference_index":49,"source":"pdf_text","source_observed_at":"2026-08-03T23:27:16.007910Z"},"links":{"citing_paper":"/paper/2511.06126"},"observation_digest":"sha256:18ddc8b3f0a91821b256f785d4acac84a900299ee7bdaf3ec3838199f9bbd0a7","observation_id":"beaa9bda-92bc-4102-868c-313fd28eca7a","resolution":{"observed_at":"2026-08-03T23:27:16.007910Z","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":"2026-08-03T23:27:16.112497Z","title":"200 mm optical synthetic aperture imaging over 120 meters distance via macroscopic Fourier ptychography","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2511.06126","last_updated":"2025-11-08T20:35:04Z","snapshot_observed_at":"2026-08-03T23:27:10.922366Z","submitted_at":"2025-11-08T20:35:04Z","title":"Video-rate gigapixel ptychography via space-time neural field representations","version":1},"reference_index":50,"source":"pdf_text","source_observed_at":"2026-08-03T23:27:16.112497Z"},"links":{"citing_paper":"/paper/2511.06126"},"observation_digest":"sha256:b51582988343462c10c67293cd1042b0d6afb28c6741118b0d83a7a62fb08d08","observation_id":"48342a92-04bb-4e93-b06c-51af93cf30f5","resolution":{"observed_at":"2026-08-03T23:27:16.112497Z","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":"2026-08-03T23:27:16.270100Z","title":"A phase retrieval algorithm for shifting illumination","venue":null,"work_id":null,"year":2004},"citing_paper":{"arxiv_id":"2511.06126","last_updated":"2025-11-08T20:35:04Z","snapshot_observed_at":"2026-08-03T23:27:10.922366Z","submitted_at":"2025-11-08T20:35:04Z","title":"Video-rate gigapixel ptychography via space-time neural field representations","version":1},"reference_index":51,"source":"pdf_text","source_observed_at":"2026-08-03T23:27:16.270100Z"},"links":{"citing_paper":"/paper/2511.06126"},"observation_digest":"sha256:062cc4a50aa10145dab110221c33585de7c9ec724448d66edf1bbdd3e1138806","observation_id":"cf737319-d52a-4a71-a6d6-1b841235ba64","resolution":{"observed_at":"2026-08-03T23:27:16.270100Z","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":"2026-08-03T23:27:16.447288Z","title":"Incoherent Fourier ptychographic photography using structured light","venue":null,"work_id":null,"year":2015},"citing_paper":{"arxiv_id":"2511.06126","last_updated":"2025-11-08T20:35:04Z","snapshot_observed_at":"2026-08-03T23:27:10.922366Z","submitted_at":"2025-11-08T20:35:04Z","title":"Video-rate gigapixel ptychography via space-time neural field representations","version":1},"reference_index":52,"source":"pdf_text","source_observed_at":"2026-08-03T23:27:16.447288Z"},"links":{"citing_paper":"/paper/2511.06126"},"observation_digest":"sha256:01d7bc2be837cda316e4916c962afa62320b014e1dc5727b632a4074b8d4feeb","observation_id":"1213c7c6-bc85-4206-8478-c937bf3f21b3","resolution":{"observed_at":"2026-08-03T23:27:16.447288Z","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":"2026-08-03T23:27:16.609664Z","title":"Near-field Fourier ptychography: super-resolution phase retrieval via speckle illumination","venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2511.06126","last_updated":"2025-11-08T20:35:04Z","snapshot_observed_at":"2026-08-03T23:27:10.922366Z","submitted_at":"2025-11-08T20:35:04Z","title":"Video-rate gigapixel ptychography via space-time neural field representations","version":1},"reference_index":53,"source":"pdf_text","source_observed_at":"2026-08-03T23:27:16.609664Z"},"links":{"citing_paper":"/paper/2511.06126"},"observation_digest":"sha256:f5240af023e14b9312188635da6bf5279b3330c7a4d68f01c7fef27ce3220e5e","observation_id":"9159763c-b3f2-4f08-9838-cbbd58b31dde","resolution":{"observed_at":"2026-08-03T23:27:16.609664Z","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":"2026-08-03T23:27:16.798996Z","title":"Ptycho-endoscopy on a lensless ultrathin fiber bundle tip","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2511.06126","last_updated":"2025-11-08T20:35:04Z","snapshot_observed_at":"2026-08-03T23:27:10.922366Z","submitted_at":"2025-11-08T20:35:04Z","title":"Video-rate gigapixel ptychography via space-time neural field representations","version":1},"reference_index":54,"source":"pdf_text","source_observed_at":"2026-08-03T23:27:16.798996Z"},"links":{"citing_paper":"/paper/2511.06126"},"observation_digest":"sha256:e618c3df62dabaa68ba4f2b48f4ca8eafa7b211905df29bf39bad1445ec8c890","observation_id":"7b002c79-61d5-427e-a095-1ca5f8eec92b","resolution":{"observed_at":"2026-08-03T23:27:16.798996Z","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":"2026-08-03T23:27:16.862477Z","title":"Ptychographic lensless coherent endomicroscopy through a flexible fiber bundle","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2511.06126","last_updated":"2025-11-08T20:35:04Z","snapshot_observed_at":"2026-08-03T23:27:10.922366Z","submitted_at":"2025-11-08T20:35:04Z","title":"Video-rate gigapixel ptychography via space-time neural field representations","version":1},"reference_index":55,"source":"pdf_text","source_observed_at":"2026-08-03T23:27:16.862477Z"},"links":{"citing_paper":"/paper/2511.06126"},"observation_digest":"sha256:c3f8e5b001b01a1cd97677fca783d04d3ab7d503976f871a8671715439d32052","observation_id":"122c5d23-4416-43ff-80eb-3f31ebbcc239","resolution":{"observed_at":"2026-08-03T23:27:16.862477Z","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":"2026-08-03T23:27:16.921453Z","title":"Deep-ultraviolet ptychographic pocket-scope (DART): mesoscale lensless molecular imaging with label-free spectroscopic contrast","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2511.06126","last_updated":"2025-11-08T20:35:04Z","snapshot_observed_at":"2026-08-03T23:27:10.922366Z","submitted_at":"2025-11-08T20:35:04Z","title":"Video-rate gigapixel ptychography via space-time neural field representations","version":1},"reference_index":56,"source":"pdf_text","source_observed_at":"2026-08-03T23:27:16.921453Z"},"links":{"citing_paper":"/paper/2511.06126"},"observation_digest":"sha256:a5e44604c6b0b74cb541b41db6b3892f11ce212665035803b1d59c12629fee8d","observation_id":"f870440a-b89e-48b2-8bc5-b139515051bb","resolution":{"observed_at":"2026-08-03T23:27:16.921453Z","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":"2026-08-03T23:27:16.977326Z","title":"Super-resolved multispectral lensless microscopy via angle-tilted, wavelength-multiplexed ptychographic modulation","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2511.06126","last_updated":"2025-11-08T20:35:04Z","snapshot_observed_at":"2026-08-03T23:27:10.922366Z","submitted_at":"2025-11-08T20:35:04Z","title":"Video-rate gigapixel ptychography via space-time neural field representations","version":1},"reference_index":57,"source":"pdf_text","source_observed_at":"2026-08-03T23:27:16.977326Z"},"links":{"citing_paper":"/paper/2511.06126"},"observation_digest":"sha256:5c3cbb7d9a2475290e683046378538b8a0077d320332d723a9cf984523ecff6e","observation_id":"b086c687-6da1-4c4d-a717-b4d93d73e765","resolution":{"observed_at":"2026-08-03T23:27:16.977326Z","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":"2026-08-03T23:27:17.034809Z","title":"Diffraction tomography with Fourier ptychography","venue":null,"work_id":null,"year":2016},"citing_paper":{"arxiv_id":"2511.06126","last_updated":"2025-11-08T20:35:04Z","snapshot_observed_at":"2026-08-03T23:27:10.922366Z","submitted_at":"2025-11-08T20:35:04Z","title":"Video-rate gigapixel ptychography via space-time neural field representations","version":1},"reference_index":58,"source":"pdf_text","source_observed_at":"2026-08-03T23:27:17.034809Z"},"links":{"citing_paper":"/paper/2511.06126"},"observation_digest":"sha256:92547c73306252f74c39cd1962b2d30c851703389e8b54d91705d68061cbaddb","observation_id":"0621ba7a-1825-4b76-8f91-b7f9991c5fe4","resolution":{"observed_at":"2026-08-03T23:27:17.034809Z","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":"2026-08-03T23:27:17.092393Z","title":"Wide -field high-resolution 3D microscopy with Fourier ptychographic diffraction tomography","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2511.06126","last_updated":"2025-11-08T20:35:04Z","snapshot_observed_at":"2026-08-03T23:27:10.922366Z","submitted_at":"2025-11-08T20:35:04Z","title":"Video-rate gigapixel ptychography via space-time neural field representations","version":1},"reference_index":59,"source":"pdf_text","source_observed_at":"2026-08-03T23:27:17.092393Z"},"links":{"citing_paper":"/paper/2511.06126"},"observation_digest":"sha256:f72c96f18da1a1528334b5fcbc47dcc30cf235f8e89a8c29b4a82172872bf37d","observation_id":"bf2e0c87-f5b1-47b5-b030-e64440df820f","resolution":{"observed_at":"2026-08-03T23:27:17.092393Z","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":"2026-08-03T23:27:17.171951Z","title":"Optical measurement of cycle -dependent cell growth","venue":null,"work_id":null,"year":2011},"citing_paper":{"arxiv_id":"2511.06126","last_updated":"2025-11-08T20:35:04Z","snapshot_observed_at":"2026-08-03T23:27:10.922366Z","submitted_at":"2025-11-08T20:35:04Z","title":"Video-rate gigapixel ptychography via space-time neural field representations","version":1},"reference_index":60,"source":"pdf_text","source_observed_at":"2026-08-03T23:27:17.171951Z"},"links":{"citing_paper":"/paper/2511.06126"},"observation_digest":"sha256:5c566623c4dd229083acfe8502e8cd16075b7953f5e969df6d265820e3db80ff","observation_id":"c44826a1-04af-4e0c-92c3-61e47a641a96","resolution":{"observed_at":"2026-08-03T23:27:17.171951Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"paper":{"arxiv_id":"2511.06126","last_updated":"2025-11-08T20:35:04Z","latest_version":1,"primary_category":"physics.optics","snapshot_observed_at":"2026-08-03T23:27:10.922366Z","submitted_at":"2025-11-08T20:35:04Z","title":"Video-rate gigapixel ptychography via space-time neural field representations"},"reference_resolution":{"displayed":60,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":60,"verified_exact":0,"verified_fuzzy":0},"total_outbound_references":60},"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":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"thesis":"As of 20 August 2026, this Paper Citation Record lists 60 of 60 outbound references and 0 inbound Pith citation observations for arXiv:2511.06126."}