{"as_of":"2026-08-11T13:48:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:1635fec6b0d2fb074d2b041338b8897b14768f1afa3d60ea7d91edf6d437ebd7","coverage":[{"denominator":73,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":73,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-10T20:48:08.979867Z","state":"measured"},{"denominator":74,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":74,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-11T06:34:44.6726+00:00","state":"measured"},{"denominator":1,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":1,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-03T00:45:31.718141Z","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":[{"citation":{"cited_paper":{"arxiv_id":"2501.07469","last_updated":"2025-08-25T11:45:06Z","snapshot_observed_at":"2026-08-10T23:55:18.264631Z","submitted_at":"2025-01-13T16:35:55Z","title":"Deep Needlet: A CNN based full sky component separation method in Needlet space","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2501.07469","snapshot_observed_at":"2026-08-03T00:45:31.718141Z","title":null,"venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2607.28712","last_updated":"2026-07-30T17:59:02Z","snapshot_observed_at":"2026-08-10T22:46:02.307483Z","submitted_at":"2026-07-30T17:59:02Z","title":"Single Frequency CMB Foreground Removal with Inter-scale Machine Learning","version":1},"reference_index":56,"source":"pdf_text","source_observed_at":"2026-08-03T00:45:31.718141Z"},"links":{"cited_paper":"/paper/2501.07469","citing_paper":"/paper/2607.28712"},"observation_digest":"sha256:2970fa226e6baf4dbec9365d99c7dfb50b913f70c133a3720dce4c6e8a12f778","observation_id":"f7731046-dafd-48c6-9ee3-6e864af58a2a","resolution":{"observed_at":"2026-08-03T00:45:31.718141Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"links":{"evidence":"/evidence","html":"/paper/2501.07469/citation-record","integrity":"/paper/2501.07469/integrity","json":"/paper/2501.07469/citation-record.json","paper":"/paper/2501.07469"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T20:48:17.794793Z","title":null,"venue":null,"work_id":"a9cbe3d9-51c7-4860-a789-eebf674503df","year":2014},"citing_paper":{"arxiv_id":"2501.07469","last_updated":"2025-08-25T11:45:06Z","snapshot_observed_at":"2026-08-10T23:55:18.264631Z","submitted_at":"2025-01-13T16:35:55Z","title":"Deep Needlet: A CNN based full sky component separation method in Needlet space","version":2},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-10T20:48:05.704755Z"},"links":{"citing_paper":"/paper/2501.07469"},"observation_digest":"sha256:f11d6a5063eb886f6955082460e452feeed33aa718d6c619dc0762af7e595137","observation_id":"3fe05a9c-25b4-452e-a100-a70cdcc4cee6","resolution":{"observed_at":"2026-08-10T20:48:17.849320Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1501.04491","last_updated":"2015-01-19T13:34:00Z","snapshot_observed_at":"2026-08-09T12:48:16.424266Z","submitted_at":"2015-01-19T13:34:00Z","title":"Measurements of the Intensity and Polarization of the Anomalous Microwave Emission in the Perseus molecular complex with QUIJOTE","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1501.04491","snapshot_observed_at":"2026-08-10T20:48:05.774751Z","title":"G´ enova-Santos, J","venue":null,"work_id":null,"year":2015},"citing_paper":{"arxiv_id":"2501.07469","last_updated":"2025-08-25T11:45:06Z","snapshot_observed_at":"2026-08-10T23:55:18.264631Z","submitted_at":"2025-01-13T16:35:55Z","title":"Deep Needlet: A CNN based full sky component separation method in Needlet space","version":2},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-10T20:48:05.774751Z"},"links":{"cited_paper":"/paper/1501.04491","citing_paper":"/paper/2501.07469"},"observation_digest":"sha256:b243a6b6b3aa82be424733e841547dfa750c9649e03e9f90aff1e5550b045f3c","observation_id":"8ba78d3a-1ab9-45bf-bb20-b79c0a48f67d","resolution":{"observed_at":"2026-08-10T20:48:05.774751Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1810.02465","last_updated":"2018-10-05T00:01:53Z","snapshot_observed_at":"2026-08-10T23:55:31.542298Z","submitted_at":"2018-10-05T00:01:53Z","title":"The Simons Observatory: Project Overview","version":1},"cited_work":{"arxiv_id":"1810.02465","doi":null,"metadata_source":"pith","pith_arxiv_id":"1810.02465","snapshot_observed_at":"2026-08-10T20:48:15.889024Z","title":"The Simons Observatory: Project Overview","venue":"astro-ph.IM","work_id":"574ca3e3-1674-4d4c-8a85-465bcdf7f16c","year":2018},"citing_paper":{"arxiv_id":"2501.07469","last_updated":"2025-08-25T11:45:06Z","snapshot_observed_at":"2026-08-10T23:55:18.264631Z","submitted_at":"2025-01-13T16:35:55Z","title":"Deep Needlet: A CNN based full sky component separation method in Needlet space","version":2},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-10T20:48:05.819108Z"},"links":{"cited_paper":"/paper/1810.02465","citing_paper":"/paper/2501.07469"},"observation_digest":"sha256:a7de6e4114414abe0d22f24d1cab1af305d1c093df78b4bec54ba794992c60c7","observation_id":"82ec6366-ebb5-4826-836a-315b673f3edb","resolution":{"observed_at":"2026-08-10T20:48:15.896219Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-10T20:48:17.643867Z","title":"Gualtieri, J","venue":null,"work_id":"b96bc23d-26b4-4276-b818-17219abb1838","year":2018},"citing_paper":{"arxiv_id":"2501.07469","last_updated":"2025-08-25T11:45:06Z","snapshot_observed_at":"2026-08-10T23:55:18.264631Z","submitted_at":"2025-01-13T16:35:55Z","title":"Deep Needlet: A CNN based full sky component separation method in Needlet space","version":2},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-10T20:48:05.864833Z"},"links":{"citing_paper":"/paper/2501.07469"},"observation_digest":"sha256:586061b331647b23876dc9c4e9de375e937646fdb8f381553827b2f94743503a","observation_id":"3c33e855-4cba-43c0-84ca-c93193ea3e6d","resolution":{"observed_at":"2026-08-10T20:48:17.674765Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1808.00567","last_updated":"2018-08-01T21:10:03Z","snapshot_observed_at":"2026-08-10T23:03:05.234897Z","submitted_at":"2018-08-01T21:10:03Z","title":"2017 upgrade and performance of BICEP3: a 95GHz refracting telescope for degree-scale CMB polarization","version":1},"cited_work":{"arxiv_id":"1808.00567","doi":null,"metadata_source":"pith","pith_arxiv_id":"1808.00567","snapshot_observed_at":"2026-08-10T20:48:15.666912Z","title":"2017 upgrade and performance of BICEP3: a 95GHz refracting telescope for degree-scale CMB polarization","venue":"astro-ph.IM","work_id":"a521d460-d0d3-4f71-8185-2d1873217c18","year":2018},"citing_paper":{"arxiv_id":"2501.07469","last_updated":"2025-08-25T11:45:06Z","snapshot_observed_at":"2026-08-10T23:55:18.264631Z","submitted_at":"2025-01-13T16:35:55Z","title":"Deep Needlet: A CNN based full sky component separation method in Needlet space","version":2},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-10T20:48:05.912024Z"},"links":{"cited_paper":"/paper/1808.00567","citing_paper":"/paper/2501.07469"},"observation_digest":"sha256:abd416f39800e65869f1126bde8d22864b1079edcfdecc2d032cc372512d1cae","observation_id":"ccbbfb6d-df63-4b3c-9dd3-f350c3cef08f","resolution":{"observed_at":"2026-08-10T20:48:15.704861Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2007.07289","last_updated":"2020-11-23T17:53:40Z","snapshot_observed_at":"2026-08-09T21:55:14.708484Z","submitted_at":"2020-07-14T18:38:21Z","title":"The Atacama Cosmology Telescope: A Measurement of the Cosmic Microwave Background Power Spectra at 98 and 150 GHz","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2007.07289","snapshot_observed_at":"2026-08-10T20:48:05.955351Z","title":null,"venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2501.07469","last_updated":"2025-08-25T11:45:06Z","snapshot_observed_at":"2026-08-10T23:55:18.264631Z","submitted_at":"2025-01-13T16:35:55Z","title":"Deep Needlet: A CNN based full sky component separation method in Needlet space","version":2},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-10T20:48:05.955351Z"},"links":{"cited_paper":"/paper/2007.07289","citing_paper":"/paper/2501.07469"},"observation_digest":"sha256:eb002de9dbe4d50e83b7ae1ca449e25a7ba4b361c5d40fe536b651bbbc968874","observation_id":"24a71871-0454-488b-96a6-28d6106ea693","resolution":{"observed_at":"2026-08-10T20:48:05.955351Z","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":"2026-08-10T20:48:17.514308Z","title":null,"venue":null,"work_id":"18015a9d-b418-4fb8-acbb-425bf6d8255a","year":2020},"citing_paper":{"arxiv_id":"2501.07469","last_updated":"2025-08-25T11:45:06Z","snapshot_observed_at":"2026-08-10T23:55:18.264631Z","submitted_at":"2025-01-13T16:35:55Z","title":"Deep Needlet: A CNN based full sky component separation method in Needlet space","version":2},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-10T20:48:06.004838Z"},"links":{"citing_paper":"/paper/2501.07469"},"observation_digest":"sha256:73e45c7085a81a2ad0ac15b30b3a669ebfca40b89f1c98267cf8b6eab5c0bd80","observation_id":"eb89db86-f235-490d-8310-c07ea0b19358","resolution":{"observed_at":"2026-08-10T20:48:17.554771Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1807.06205","last_updated":"2019-12-03T18:36:28Z","snapshot_observed_at":"2026-08-06T20:42:17.427266Z","submitted_at":"2018-07-17T04:05:03Z","title":"Planck 2018 results. I. Overview and the cosmological legacy of Planck","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1807.06205","snapshot_observed_at":"2026-08-10T20:48:06.054872Z","title":null,"venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2501.07469","last_updated":"2025-08-25T11:45:06Z","snapshot_observed_at":"2026-08-10T23:55:18.264631Z","submitted_at":"2025-01-13T16:35:55Z","title":"Deep Needlet: A CNN based full sky component separation method in Needlet space","version":2},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-10T20:48:06.054872Z"},"links":{"cited_paper":"/paper/1807.06205","citing_paper":"/paper/2501.07469"},"observation_digest":"sha256:653ef7f1eff6efb9dd9da67ccda4a7d431d386d96c901228242ea35b3d0a1dba","observation_id":"99e2b372-45d5-4668-88fb-37a53bf9c4df","resolution":{"observed_at":"2026-08-10T20:48:06.054872Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1902.10541","last_updated":"2019-03-05T16:34:33Z","snapshot_observed_at":"2026-07-06T07:35:48.510196Z","submitted_at":"2019-02-26T18:25:42Z","title":"PICO: Probe of Inflation and Cosmic Origins","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1902.10541","snapshot_observed_at":"2026-08-10T20:48:06.104828Z","title":"Hanany, M","venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2501.07469","last_updated":"2025-08-25T11:45:06Z","snapshot_observed_at":"2026-08-10T23:55:18.264631Z","submitted_at":"2025-01-13T16:35:55Z","title":"Deep Needlet: A CNN based full sky component separation method in Needlet space","version":2},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-10T20:48:06.104828Z"},"links":{"cited_paper":"/paper/1902.10541","citing_paper":"/paper/2501.07469"},"observation_digest":"sha256:0c90eaceaab7b9acc4efb1ef824842c94eeebe9c392d91d1146a55449e4e42c0","observation_id":"0cc5fe93-61bc-4524-85c6-90aecc2121a2","resolution":{"observed_at":"2026-08-10T20:48:06.104828Z","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":"2026-08-10T20:48:17.394670Z","title":"Hazumi et al., LiteBIRD: A Satellite for the Studies of B-Mode Polarization and Inflation from Cosmic Background Radiation Detection , J","venue":null,"work_id":"68e96234-c6e1-42be-a79d-fc43dccfef48","year":2019},"citing_paper":{"arxiv_id":"2501.07469","last_updated":"2025-08-25T11:45:06Z","snapshot_observed_at":"2026-08-10T23:55:18.264631Z","submitted_at":"2025-01-13T16:35:55Z","title":"Deep Needlet: A CNN based full sky component separation method in Needlet space","version":2},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-10T20:48:06.154922Z"},"links":{"citing_paper":"/paper/2501.07469"},"observation_digest":"sha256:bf73a688ab069a8f171a15d02374c8e41e192f24fb8ef7d7173a42811b27324d","observation_id":"a0f64071-0872-491c-a8db-e9d742e87610","resolution":{"observed_at":"2026-08-10T20:48:17.434868Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2110.12362","last_updated":"2022-07-25T05:34:30Z","snapshot_observed_at":"2026-08-10T23:57:40.505731Z","submitted_at":"2021-10-24T06:41:44Z","title":"$B$-mode forecast of CMB-Bh$\\overline{a}$rat","version":2},"cited_work":{"arxiv_id":"2110.12362","doi":null,"metadata_source":"pith","pith_arxiv_id":"2110.12362","snapshot_observed_at":"2026-08-10T20:48:15.247125Z","title":"$B$-mode forecast of CMB-Bh$\\overline{a}$rat","venue":"astro-ph.CO","work_id":"9507ec86-0365-4ca7-ab0b-ff2cddf795a6","year":2021},"citing_paper":{"arxiv_id":"2501.07469","last_updated":"2025-08-25T11:45:06Z","snapshot_observed_at":"2026-08-10T23:55:18.264631Z","submitted_at":"2025-01-13T16:35:55Z","title":"Deep Needlet: A CNN based full sky component separation method in Needlet space","version":2},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-10T20:48:06.219942Z"},"links":{"cited_paper":"/paper/2110.12362","citing_paper":"/paper/2501.07469"},"observation_digest":"sha256:63c3e9980209d87ef66d7d5f8087197985a8f2715bd538d7b3637dcbb2aee218","observation_id":"501597c2-8027-4cff-aa66-c16e105bbecc","resolution":{"observed_at":"2026-08-10T20:48:15.294756Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-10T20:48:17.282148Z","title":"Ichiki, CMB foreground: A concise review , Progress of Theoretical and Experimental Physics 2014 (2014) 06B109","venue":null,"work_id":"7fbca766-b804-458a-9f93-4c27a1793122","year":2014},"citing_paper":{"arxiv_id":"2501.07469","last_updated":"2025-08-25T11:45:06Z","snapshot_observed_at":"2026-08-10T23:55:18.264631Z","submitted_at":"2025-01-13T16:35:55Z","title":"Deep Needlet: A CNN based full sky component separation method in Needlet space","version":2},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-10T20:48:06.275504Z"},"links":{"citing_paper":"/paper/2501.07469"},"observation_digest":"sha256:c8222b77285e513bf3ae5c5d15dda6b56e364c15036f37bfd436548949ea0f10","observation_id":"02fe5598-59f0-4e9c-a865-e80a96797723","resolution":{"observed_at":"2026-08-10T20:48:17.324769Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-10T20:48:17.125320Z","title":"Tegmark, How to measure cmb power spectra without losing information , Phys","venue":null,"work_id":"78fd2a2e-cf33-4298-a095-8a4cfd470226","year":1997},"citing_paper":{"arxiv_id":"2501.07469","last_updated":"2025-08-25T11:45:06Z","snapshot_observed_at":"2026-08-10T23:55:18.264631Z","submitted_at":"2025-01-13T16:35:55Z","title":"Deep Needlet: A CNN based full sky component separation method in Needlet space","version":2},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-10T20:48:06.320268Z"},"links":{"citing_paper":"/paper/2501.07469"},"observation_digest":"sha256:1d98f73cb090d4f84974f94def7a1b27afdba8b4bfa5b7ac38579bb41e28593a","observation_id":"a56875a7-1548-43aa-b6c4-9d3062c2987b","resolution":{"observed_at":"2026-08-10T20:48:17.166111Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-10T20:48:16.980264Z","title":"Delabrouille, J.-F","venue":null,"work_id":"0e142db3-5f8c-4de1-9a4f-70ac33fd73c5","year":2003},"citing_paper":{"arxiv_id":"2501.07469","last_updated":"2025-08-25T11:45:06Z","snapshot_observed_at":"2026-08-10T23:55:18.264631Z","submitted_at":"2025-01-13T16:35:55Z","title":"Deep Needlet: A CNN based full sky component separation method in Needlet space","version":2},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-10T20:48:06.372071Z"},"links":{"citing_paper":"/paper/2501.07469"},"observation_digest":"sha256:7caccda837feac167d2b0555794d9dae9c1c8f78bf257586bde51e0312a91562","observation_id":"237ce9f8-a189-4af7-9412-9ccbc584d6ec","resolution":{"observed_at":"2026-08-10T20:48:17.024926Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"0709.1058","last_updated":"2007-11-05T15:48:47Z","snapshot_observed_at":"2026-08-06T12:50:19.254255Z","submitted_at":"2007-09-07T12:13:20Z","title":"Joint Bayesian component separation and CMB power spectrum estimation","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"0709.1058","snapshot_observed_at":"2026-08-10T20:48:06.412890Z","title":null,"venue":null,"work_id":null,"year":2008},"citing_paper":{"arxiv_id":"2501.07469","last_updated":"2025-08-25T11:45:06Z","snapshot_observed_at":"2026-08-10T23:55:18.264631Z","submitted_at":"2025-01-13T16:35:55Z","title":"Deep Needlet: A CNN based full sky component separation method in Needlet space","version":2},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-10T20:48:06.412890Z"},"links":{"cited_paper":"/paper/0709.1058","citing_paper":"/paper/2501.07469"},"observation_digest":"sha256:bdced3f4b9bf87bfea1f8ca054f34c4e04edc72a5e97b575ffcf9b606adc2e3f","observation_id":"a4dbbb9b-3965-4fcb-b886-c4c099047d60","resolution":{"observed_at":"2026-08-10T20:48:06.412890Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"0807.0773","last_updated":"2008-07-04T15:01:39Z","snapshot_observed_at":"2026-07-06T01:39:37.053100Z","submitted_at":"2008-07-04T15:01:39Z","title":"A full sky, low foreground, high resolution CMB map from WMAP","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"0807.0773","snapshot_observed_at":"2026-08-10T20:48:06.465194Z","title":"Delabrouille, J","venue":null,"work_id":null,"year":2009},"citing_paper":{"arxiv_id":"2501.07469","last_updated":"2025-08-25T11:45:06Z","snapshot_observed_at":"2026-08-10T23:55:18.264631Z","submitted_at":"2025-01-13T16:35:55Z","title":"Deep Needlet: A CNN based full sky component separation method in Needlet space","version":2},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-10T20:48:06.465194Z"},"links":{"cited_paper":"/paper/0807.0773","citing_paper":"/paper/2501.07469"},"observation_digest":"sha256:f7cbd62164ffb1c0e7d0fcfcc782f51f3b3f3c2b18d938947de227686ca3dd8d","observation_id":"7d48738b-76c9-4bdb-9a50-3d60f090d995","resolution":{"observed_at":"2026-08-10T20:48:06.465194Z","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":"2026-08-10T20:48:16.884756Z","title":"Basak and J","venue":null,"work_id":"a3714fd2-af42-4f41-badf-f63d25153b30","year":2011},"citing_paper":{"arxiv_id":"2501.07469","last_updated":"2025-08-25T11:45:06Z","snapshot_observed_at":"2026-08-10T23:55:18.264631Z","submitted_at":"2025-01-13T16:35:55Z","title":"Deep Needlet: A CNN based full sky component separation method in Needlet space","version":2},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-10T20:48:06.506577Z"},"links":{"citing_paper":"/paper/2501.07469"},"observation_digest":"sha256:9433d9318b47bbc1e8c5d45cc7eb882e06ca5e93966b0687ed95a1e90eebd521","observation_id":"bfc3392b-d5ae-4811-be4f-3d7b44143be0","resolution":{"observed_at":"2026-08-10T20:48:16.896713Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-10T20:48:16.654762Z","title":"Fern´ andez-Cobos, P","venue":null,"work_id":"27073e33-9c86-4034-a743-34ccce7821fa","year":2012},"citing_paper":{"arxiv_id":"2501.07469","last_updated":"2025-08-25T11:45:06Z","snapshot_observed_at":"2026-08-10T23:55:18.264631Z","submitted_at":"2025-01-13T16:35:55Z","title":"Deep Needlet: A CNN based full sky component separation method in Needlet space","version":2},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-10T20:48:06.534869Z"},"links":{"citing_paper":"/paper/2501.07469"},"observation_digest":"sha256:76881c0b3b214ec19469922d945134fa5875c38222fe9030d92ab1daaf41af33","observation_id":"8b8557de-7e98-42bb-ae87-a4a42512f8ba","resolution":{"observed_at":"2026-08-10T20:48:16.694983Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1601.01322","last_updated":"2016-06-23T15:51:46Z","snapshot_observed_at":"2026-08-10T23:57:41.148634Z","submitted_at":"2016-01-06T21:00:05Z","title":"SILC: a new Planck Internal Linear Combination CMB temperature map using directional wavelets","version":2},"cited_work":{"arxiv_id":"1601.01322","doi":null,"metadata_source":"pith","pith_arxiv_id":"1601.01322","snapshot_observed_at":"2026-08-10T20:48:14.954098Z","title":"SILC: a new Planck Internal Linear Combination CMB temperature map using directional wavelets","venue":"astro-ph.CO","work_id":"853a9d55-e35a-4d89-b1fa-ce1c396334c8","year":2016},"citing_paper":{"arxiv_id":"2501.07469","last_updated":"2025-08-25T11:45:06Z","snapshot_observed_at":"2026-08-10T23:55:18.264631Z","submitted_at":"2025-01-13T16:35:55Z","title":"Deep Needlet: A CNN based full sky component separation method in Needlet space","version":2},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-10T20:48:06.594820Z"},"links":{"cited_paper":"/paper/1601.01322","citing_paper":"/paper/2501.07469"},"observation_digest":"sha256:27c1f2ff054f64b294cd458d344b7cfb457af78fa7ef86ccc6a45ed87b927b80","observation_id":"1e311113-4164-417a-a4ad-a41652d37fb5","resolution":{"observed_at":"2026-08-10T20:48:14.961875Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2006.08628","last_updated":"2021-03-02T19:28:38Z","snapshot_observed_at":"2026-08-10T23:55:02.366141Z","submitted_at":"2020-06-15T18:00:02Z","title":"Peeling off foregrounds with the constrained moment ILC method to unveil primordial CMB $B$-modes","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2006.08628","snapshot_observed_at":"2026-08-10T20:48:06.634767Z","title":"Remazeilles, A","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2501.07469","last_updated":"2025-08-25T11:45:06Z","snapshot_observed_at":"2026-08-10T23:55:18.264631Z","submitted_at":"2025-01-13T16:35:55Z","title":"Deep Needlet: A CNN based full sky component separation method in Needlet space","version":2},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-10T20:48:06.634767Z"},"links":{"cited_paper":"/paper/2006.08628","citing_paper":"/paper/2501.07469"},"observation_digest":"sha256:3e6dbf9e7d73bca92f385c607f9bd3e3c0d21511c579631b1993a31727cdb4ea","observation_id":"73ce60f9-6dda-41a8-9aee-0f94298b17b6","resolution":{"observed_at":"2026-08-10T20:48:06.634767Z","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":"2026-08-10T20:48:16.474880Z","title":null,"venue":null,"work_id":"728d67d7-edd2-46ca-ba69-a69957223271","year":2021},"citing_paper":{"arxiv_id":"2501.07469","last_updated":"2025-08-25T11:45:06Z","snapshot_observed_at":"2026-08-10T23:55:18.264631Z","submitted_at":"2025-01-13T16:35:55Z","title":"Deep Needlet: A CNN based full sky component separation method in Needlet space","version":2},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-10T20:48:06.684755Z"},"links":{"citing_paper":"/paper/2501.07469"},"observation_digest":"sha256:cd538017e42cd8af8e1571f8040db81e7d7f6f28576d8d67036048a08839f0e4","observation_id":"bab192a9-5fdc-4776-884c-7a27d9edb683","resolution":{"observed_at":"2026-08-10T20:48:16.497573Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2402.17579","last_updated":"2024-06-10T15:42:45Z","snapshot_observed_at":"2026-08-10T23:57:09.285692Z","submitted_at":"2024-02-27T15:12:04Z","title":"Optimization of foreground moment deprojection for semi-blind CMB polarization reconstruction","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2402.17579","snapshot_observed_at":"2026-08-10T20:48:06.734856Z","title":"Carones and M","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2501.07469","last_updated":"2025-08-25T11:45:06Z","snapshot_observed_at":"2026-08-10T23:55:18.264631Z","submitted_at":"2025-01-13T16:35:55Z","title":"Deep Needlet: A CNN based full sky component separation method in Needlet space","version":2},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-10T20:48:06.734856Z"},"links":{"cited_paper":"/paper/2402.17579","citing_paper":"/paper/2501.07469"},"observation_digest":"sha256:8d4ffaa451e4979a9e8a729ca93ab0025007c7be1b9d529340ef3587bc545e70","observation_id":"bc71d8e4-1ac7-4e11-802f-e626af4725ad","resolution":{"observed_at":"2026-08-10T20:48:06.734856Z","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":"2026-08-10T20:48:16.348305Z","title":"Stompor, S","venue":null,"work_id":"e6fe2b15-7e58-4864-8b9c-deecb209ce45","year":2008},"citing_paper":{"arxiv_id":"2501.07469","last_updated":"2025-08-25T11:45:06Z","snapshot_observed_at":"2026-08-10T23:55:18.264631Z","submitted_at":"2025-01-13T16:35:55Z","title":"Deep Needlet: A CNN based full sky component separation method in Needlet space","version":2},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-10T20:48:06.804870Z"},"links":{"citing_paper":"/paper/2501.07469"},"observation_digest":"sha256:5847db8f1147a892f4b1171f650df5384c438d731ee39019e3971f1657b8d4c8","observation_id":"420f6397-0ac4-42b9-83f1-cd354ba4e360","resolution":{"observed_at":"2026-08-10T20:48:16.391406Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-10T20:48:16.303528Z","title":"Basak and J","venue":null,"work_id":"d647d4b4-1861-45ca-8383-0d4ec00ba35c","year":2013},"citing_paper":{"arxiv_id":"2501.07469","last_updated":"2025-08-25T11:45:06Z","snapshot_observed_at":"2026-08-10T23:55:18.264631Z","submitted_at":"2025-01-13T16:35:55Z","title":"Deep Needlet: A CNN based full sky component separation method in Needlet space","version":2},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-08-10T20:48:06.836215Z"},"links":{"citing_paper":"/paper/2501.07469"},"observation_digest":"sha256:08d60b85d53c59ab185ac059b51135b3ad9e40eae9bea4077c4c46ef50b47708","observation_id":"6f2f22f3-8328-48ab-866f-ac9dd3d312eb","resolution":{"observed_at":"2026-08-10T20:48:16.311871Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"0803.1394","last_updated":"2008-05-28T13:31:25Z","snapshot_observed_at":"2026-08-10T23:56:09.304607Z","submitted_at":"2008-03-10T12:37:02Z","title":"CMB map derived from the WMAP data through Harmonic Internal Linear Combination","version":7},"cited_work":{"arxiv_id":"0803.1394","doi":null,"metadata_source":"pith","pith_arxiv_id":"0803.1394","snapshot_observed_at":"2026-08-10T20:48:14.625177Z","title":"CMB map derived from the WMAP data through Harmonic Internal Linear Combination","venue":"astro-ph","work_id":"47528684-9d3a-4df2-a3f2-7e1d1794128e","year":2008},"citing_paper":{"arxiv_id":"2501.07469","last_updated":"2025-08-25T11:45:06Z","snapshot_observed_at":"2026-08-10T23:55:18.264631Z","submitted_at":"2025-01-13T16:35:55Z","title":"Deep Needlet: A CNN based full sky component separation method in Needlet space","version":2},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-08-10T20:48:06.892347Z"},"links":{"cited_paper":"/paper/0803.1394","citing_paper":"/paper/2501.07469"},"observation_digest":"sha256:4124026102fe976257e8d8cab3f194c6f848065f755e91f4c2f13126b8bc2e88","observation_id":"b2bfe81d-be57-4479-9ffc-19bc982c041d","resolution":{"observed_at":"2026-08-10T20:48:14.664923Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-10T20:48:16.204843Z","title":null,"venue":null,"work_id":"48381775-d0a6-46d4-ba95-ea090f06c870","year":2010},"citing_paper":{"arxiv_id":"2501.07469","last_updated":"2025-08-25T11:45:06Z","snapshot_observed_at":"2026-08-10T23:55:18.264631Z","submitted_at":"2025-01-13T16:35:55Z","title":"Deep Needlet: A CNN based full sky component separation method in Needlet space","version":2},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-08-10T20:48:06.931001Z"},"links":{"citing_paper":"/paper/2501.07469"},"observation_digest":"sha256:df3f62b2a559e74a0c587f8950f47a599147450fd798bcc6eb73aeea4332559e","observation_id":"5d2ba8bd-fcca-4e3a-bc75-2c2b6e37c170","resolution":{"observed_at":"2026-08-10T20:48:16.245019Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-10T20:48:16.107682Z","title":"Russell and P","venue":null,"work_id":"0e22634c-0c25-43a8-b670-b363ad74371a","year":2010},"citing_paper":{"arxiv_id":"2501.07469","last_updated":"2025-08-25T11:45:06Z","snapshot_observed_at":"2026-08-10T23:55:18.264631Z","submitted_at":"2025-01-13T16:35:55Z","title":"Deep Needlet: A CNN based full sky component separation method in Needlet space","version":2},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-08-10T20:48:06.949363Z"},"links":{"citing_paper":"/paper/2501.07469"},"observation_digest":"sha256:1f225c9d3e652f961e1305ac6eb515c3748f7ab01eac3181c437d018028165e3","observation_id":"ffdf5f07-0878-4d99-b1bc-2829bde7dbc5","resolution":{"observed_at":"2026-08-10T20:48:16.137588Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1010.1634","last_updated":"2010-10-08T09:20:36Z","snapshot_observed_at":"2026-07-06T02:16:39.689546Z","submitted_at":"2010-10-08T09:20:36Z","title":"Foreground removal from WMAP 5yr temperature maps using an MLP neural network","version":1},"cited_work":{"arxiv_id":"1010.1634","doi":null,"metadata_source":"pith","pith_arxiv_id":"1010.1634","snapshot_observed_at":"2026-08-10T20:48:14.414293Z","title":"Foreground removal from WMAP 5yr temperature maps using an MLP neural network","venue":"astro-ph.CO","work_id":"48965264-b6d6-42a8-a183-027a1b2b501b","year":2010},"citing_paper":{"arxiv_id":"2501.07469","last_updated":"2025-08-25T11:45:06Z","snapshot_observed_at":"2026-08-10T23:55:18.264631Z","submitted_at":"2025-01-13T16:35:55Z","title":"Deep Needlet: A CNN based full sky component separation method in Needlet space","version":2},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-08-10T20:48:06.973666Z"},"links":{"cited_paper":"/paper/1010.1634","citing_paper":"/paper/2501.07469"},"observation_digest":"sha256:37ae161c159495bbefc9c4bc7980e653134e5d515622d8fbfb7fab6753e3de51","observation_id":"fee83045-9ea1-4ab3-8d55-d3e10cef8e64","resolution":{"observed_at":"2026-08-10T20:48:14.454761Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1711.02033","last_updated":"2017-11-06T17:37:43Z","snapshot_observed_at":"2026-07-31T07:19:26.144768Z","submitted_at":"2017-11-06T17:37:43Z","title":"Estimating Cosmological Parameters from the Dark Matter Distribution","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1711.02033","snapshot_observed_at":"2026-08-10T20:48:07.010993Z","title":"Ravanbakhsh, J","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2501.07469","last_updated":"2025-08-25T11:45:06Z","snapshot_observed_at":"2026-08-10T23:55:18.264631Z","submitted_at":"2025-01-13T16:35:55Z","title":"Deep Needlet: A CNN based full sky component separation method in Needlet space","version":2},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-08-10T20:48:07.010993Z"},"links":{"cited_paper":"/paper/1711.02033","citing_paper":"/paper/2501.07469"},"observation_digest":"sha256:df9347714d83dd29ca1c6d945547317961e9c8fb0757cd486e815565d5a34714","observation_id":"e66c372d-b28c-40c4-addc-0194a09915b9","resolution":{"observed_at":"2026-08-10T20:48:07.010993Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2101.11181","last_updated":"2021-01-27T03:07:42Z","snapshot_observed_at":"2026-07-06T10:35:57.315660Z","submitted_at":"2021-01-27T03:07:42Z","title":"A Generative Model of Galactic Dust Emission Using Variational Inference","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2101.11181","snapshot_observed_at":"2026-08-10T20:48:07.054816Z","title":"Thorne, L","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2501.07469","last_updated":"2025-08-25T11:45:06Z","snapshot_observed_at":"2026-08-10T23:55:18.264631Z","submitted_at":"2025-01-13T16:35:55Z","title":"Deep Needlet: A CNN based full sky component separation method in Needlet space","version":2},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-08-10T20:48:07.054816Z"},"links":{"cited_paper":"/paper/2101.11181","citing_paper":"/paper/2501.07469"},"observation_digest":"sha256:0afad4d2f70874f6ff6063aae10106555d86d2ca6805346bf595515dfc8f7c17","observation_id":"2eca24b9-7ac8-4173-937d-bf7ecd404a93","resolution":{"observed_at":"2026-08-10T20:48:07.054816Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1905.06958","last_updated":"2019-10-18T11:42:12Z","snapshot_observed_at":"2026-07-06T07:53:37.491380Z","submitted_at":"2019-05-16T18:00:02Z","title":"A deep learning model to emulate simulations of cosmic reionization","version":2},"cited_work":{"arxiv_id":"1905.06958","doi":null,"metadata_source":"pith","pith_arxiv_id":"1905.06958","snapshot_observed_at":"2026-08-10T20:48:13.967299Z","title":"A deep learning model to emulate simulations of cosmic reionization","venue":"astro-ph.CO","work_id":"b493669f-5878-48d1-b8e8-5264d7f429a5","year":2019},"citing_paper":{"arxiv_id":"2501.07469","last_updated":"2025-08-25T11:45:06Z","snapshot_observed_at":"2026-08-10T23:55:18.264631Z","submitted_at":"2025-01-13T16:35:55Z","title":"Deep Needlet: A CNN based full sky component separation method in Needlet space","version":2},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-08-10T20:48:07.096292Z"},"links":{"cited_paper":"/paper/1905.06958","citing_paper":"/paper/2501.07469"},"observation_digest":"sha256:7a88f2a64bcd1af517a33fa91357148cc30ebef322c5d7c46519ab63f8863e20","observation_id":"6f104b59-e9ff-42dc-8aef-45c2f628ef2f","resolution":{"observed_at":"2026-08-10T20:48:14.013836Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1810.01483","last_updated":"2020-06-12T22:33:45Z","snapshot_observed_at":"2026-08-10T23:56:28.771773Z","submitted_at":"2018-10-02T20:04:07Z","title":"DeepCMB: Lensing Reconstruction of the Cosmic Microwave Background with Deep Neural Networks","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1810.01483","snapshot_observed_at":"2026-08-10T20:48:07.134857Z","title":"Caldeira, W","venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2501.07469","last_updated":"2025-08-25T11:45:06Z","snapshot_observed_at":"2026-08-10T23:55:18.264631Z","submitted_at":"2025-01-13T16:35:55Z","title":"Deep Needlet: A CNN based full sky component separation method in Needlet space","version":2},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-08-10T20:48:07.134857Z"},"links":{"cited_paper":"/paper/1810.01483","citing_paper":"/paper/2501.07469"},"observation_digest":"sha256:d56e15359cea1f2c5812e0f2254fd28e1a1bee0290bce1a352f383c70151dc62","observation_id":"c113c801-d048-4739-a5dc-12f00f097e42","resolution":{"observed_at":"2026-08-10T20:48:07.134857Z","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":"2026-08-10T20:48:16.055138Z","title":"Choudhury, A","venue":null,"work_id":"31b73948-5587-481f-8f5f-ef99211f6186","year":2022},"citing_paper":{"arxiv_id":"2501.07469","last_updated":"2025-08-25T11:45:06Z","snapshot_observed_at":"2026-08-10T23:55:18.264631Z","submitted_at":"2025-01-13T16:35:55Z","title":"Deep Needlet: A CNN based full sky component separation method in Needlet space","version":2},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-08-10T20:48:07.184861Z"},"links":{"citing_paper":"/paper/2501.07469"},"observation_digest":"sha256:dd160fbd370d8f131fbe6cbbcbc8da9b8bac444590d55bef81732192d04d1994","observation_id":"a32017c5-da5f-43b3-a422-36d55f5c53a0","resolution":{"observed_at":"2026-08-10T20:48:16.066723Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1907.07787","last_updated":"2020-04-21T14:20:41Z","snapshot_observed_at":"2026-08-06T18:34:06.176471Z","submitted_at":"2019-07-17T21:59:04Z","title":"Constraining the astrophysics and cosmology from 21cm tomography using deep learning with the SKA","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1907.07787","snapshot_observed_at":"2026-08-10T20:48:07.234756Z","title":"Hassan, S","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2501.07469","last_updated":"2025-08-25T11:45:06Z","snapshot_observed_at":"2026-08-10T23:55:18.264631Z","submitted_at":"2025-01-13T16:35:55Z","title":"Deep Needlet: A CNN based full sky component separation method in Needlet space","version":2},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-08-10T20:48:07.234756Z"},"links":{"cited_paper":"/paper/1907.07787","citing_paper":"/paper/2501.07469"},"observation_digest":"sha256:57148f4205caca07a27e578d49c713dd12d40f47c192d0022da0875a090c1d29","observation_id":"40b0943b-0cda-4a21-87f5-8bcc8cc424b2","resolution":{"observed_at":"2026-08-10T20:48:07.234756Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2404.05794","last_updated":"2024-04-08T18:00:06Z","snapshot_observed_at":"2026-08-10T23:56:26.035375Z","submitted_at":"2024-04-08T18:00:06Z","title":"Deep Learning the Intergalactic Medium using Lyman-alpha Forest at $ 4 \\leq z \\leq 5$","version":1},"cited_work":{"arxiv_id":"2404.05794","doi":null,"metadata_source":"pith","pith_arxiv_id":"2404.05794","snapshot_observed_at":"2026-08-10T20:48:13.454760Z","title":"Deep Learning the Intergalactic Medium using Lyman-alpha Forest at $ 4 \\leq z \\leq 5$","venue":"astro-ph.CO","work_id":"f1c5f538-b321-4b60-9852-a4b602194fa1","year":2024},"citing_paper":{"arxiv_id":"2501.07469","last_updated":"2025-08-25T11:45:06Z","snapshot_observed_at":"2026-08-10T23:55:18.264631Z","submitted_at":"2025-01-13T16:35:55Z","title":"Deep Needlet: A CNN based full sky component separation method in Needlet space","version":2},"reference_index":35,"source":"pdf_text","source_observed_at":"2026-08-10T20:48:07.284748Z"},"links":{"cited_paper":"/paper/2404.05794","citing_paper":"/paper/2501.07469"},"observation_digest":"sha256:5b8f598bc2e78ca551e70756fa4e5d3d6e9fc6a2c3af19d3c889327037c96e90","observation_id":"a6347e36-1f37-4dae-ab18-1062ac3e947a","resolution":{"observed_at":"2026-08-10T20:48:13.484784Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2101.01214","last_updated":"2021-08-20T15:40:26Z","snapshot_observed_at":"2026-08-10T23:57:55.470924Z","submitted_at":"2021-01-04T19:58:28Z","title":"Reconstructing Patchy Reionization with Deep Learning","version":2},"cited_work":{"arxiv_id":"2101.01214","doi":null,"metadata_source":"pith","pith_arxiv_id":"2101.01214","snapshot_observed_at":"2026-08-10T20:48:13.275917Z","title":"Reconstructing Patchy Reionization with Deep Learning","venue":"astro-ph.CO","work_id":"285ec319-9b97-41e2-ba7e-e988e9b25983","year":2021},"citing_paper":{"arxiv_id":"2501.07469","last_updated":"2025-08-25T11:45:06Z","snapshot_observed_at":"2026-08-10T23:55:18.264631Z","submitted_at":"2025-01-13T16:35:55Z","title":"Deep Needlet: A CNN based full sky component separation method in Needlet space","version":2},"reference_index":36,"source":"pdf_text","source_observed_at":"2026-08-10T20:48:07.334887Z"},"links":{"cited_paper":"/paper/2101.01214","citing_paper":"/paper/2501.07469"},"observation_digest":"sha256:4785e8860c2d29a04f549e399bd4596b4eda5fac8242faa4905bb0cf1331ceb0","observation_id":"e7ed6be7-aba2-4493-9304-5d4e191dbaf6","resolution":{"observed_at":"2026-08-10T20:48:13.284771Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2102.04327","last_updated":"2021-09-23T03:04:56Z","snapshot_observed_at":"2026-08-10T23:57:53.891710Z","submitted_at":"2021-02-08T16:30:31Z","title":"An Unbiased Estimator of the Full-sky CMB Angular Power Spectrum at Large Scales using Neural Networks","version":2},"cited_work":{"arxiv_id":"2102.04327","doi":null,"metadata_source":"pith","pith_arxiv_id":"2102.04327","snapshot_observed_at":"2026-08-10T20:48:13.190303Z","title":"An Unbiased Estimator of the Full-sky CMB Angular Power Spectrum at Large Scales using Neural Networks","venue":"astro-ph.CO","work_id":"d0a94e23-78c0-48da-95ac-60aaba784bf3","year":2021},"citing_paper":{"arxiv_id":"2501.07469","last_updated":"2025-08-25T11:45:06Z","snapshot_observed_at":"2026-08-10T23:55:18.264631Z","submitted_at":"2025-01-13T16:35:55Z","title":"Deep Needlet: A CNN based full sky component separation method in Needlet space","version":2},"reference_index":37,"source":"pdf_text","source_observed_at":"2026-08-10T20:48:07.373866Z"},"links":{"cited_paper":"/paper/2102.04327","citing_paper":"/paper/2501.07469"},"observation_digest":"sha256:f35df21151a42e030ef04d51e45e78447fa33bd75003fd9e6ad5521301266c2e","observation_id":"63f7086b-31ae-4e51-b6a4-5f87abb93bea","resolution":{"observed_at":"2026-08-10T20:48:13.207308Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2111.01138","last_updated":"2021-11-01T18:00:00Z","snapshot_observed_at":"2026-08-11T12:46:41.617427Z","submitted_at":"2021-11-01T18:00:00Z","title":"Single frequency CMB B-mode inference with realistic foregrounds from a single training image","version":1},"cited_work":{"arxiv_id":"2111.01138","doi":null,"metadata_source":"pith","pith_arxiv_id":"2111.01138","snapshot_observed_at":"2026-08-10T20:48:13.028703Z","title":"Single frequency CMB B-mode inference with realistic foregrounds from a single training image","venue":"astro-ph.CO","work_id":"5c04ae8b-4be1-4090-bb72-7dfa66ce6924","year":2021},"citing_paper":{"arxiv_id":"2501.07469","last_updated":"2025-08-25T11:45:06Z","snapshot_observed_at":"2026-08-10T23:55:18.264631Z","submitted_at":"2025-01-13T16:35:55Z","title":"Deep Needlet: A CNN based full sky component separation method in Needlet space","version":2},"reference_index":38,"source":"pdf_text","source_observed_at":"2026-08-10T20:48:07.424757Z"},"links":{"cited_paper":"/paper/2111.01138","citing_paper":"/paper/2501.07469"},"observation_digest":"sha256:73c53f9a8874a23c93ea110462859dfa1a29d2e5d6c1bdb7c62c6b0c95d7c496","observation_id":"76d22040-c61e-48cd-97e9-fded4a0a444d","resolution":{"observed_at":"2026-08-10T20:48:13.074852Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2404.03557","last_updated":"2024-07-31T19:30:46Z","snapshot_observed_at":"2026-08-11T07:19:55.017023Z","submitted_at":"2024-04-04T16:10:45Z","title":"Signal-preserving CMB component separation with machine learning","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2404.03557","snapshot_observed_at":"2026-08-10T20:48:07.464738Z","title":"McCarthy, J","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2501.07469","last_updated":"2025-08-25T11:45:06Z","snapshot_observed_at":"2026-08-10T23:55:18.264631Z","submitted_at":"2025-01-13T16:35:55Z","title":"Deep Needlet: A CNN based full sky component separation method in Needlet space","version":2},"reference_index":39,"source":"pdf_text","source_observed_at":"2026-08-10T20:48:07.464738Z"},"links":{"cited_paper":"/paper/2404.03557","citing_paper":"/paper/2501.07469"},"observation_digest":"sha256:20b1bec7ea813a79408529910b4eedc785ab0af4e48fe5149a95ee29e4e543ec","observation_id":"ab825f8e-e9cd-45b8-9904-8d8b94d0e79d","resolution":{"observed_at":"2026-08-10T20:48:07.464738Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2404.18897","last_updated":"2025-06-06T10:35:57Z","snapshot_observed_at":"2026-08-10T23:57:38.982220Z","submitted_at":"2024-04-29T17:34:24Z","title":"Neural network prediction of model parameters for strong lensing samples from Hyper Suprime-Cam Survey","version":3},"cited_work":{"arxiv_id":"2404.18897","doi":null,"metadata_source":"pith","pith_arxiv_id":"2404.18897","snapshot_observed_at":"2026-08-10T20:48:12.695439Z","title":"Neural network prediction of model parameters for strong lensing samples from Hyper Suprime-Cam Survey","venue":"astro-ph.CO","work_id":"5d763189-4900-4ff8-817e-82c3cd1bba3f","year":2024},"citing_paper":{"arxiv_id":"2501.07469","last_updated":"2025-08-25T11:45:06Z","snapshot_observed_at":"2026-08-10T23:55:18.264631Z","submitted_at":"2025-01-13T16:35:55Z","title":"Deep Needlet: A CNN based full sky component separation method in Needlet space","version":2},"reference_index":40,"source":"pdf_text","source_observed_at":"2026-08-10T20:48:07.514826Z"},"links":{"cited_paper":"/paper/2404.18897","citing_paper":"/paper/2501.07469"},"observation_digest":"sha256:88e2ee4597e3a8964d1bd3b4337fd96b2c2de7517d4f1e80d6ba1be08fee66dd","observation_id":"a9ff0828-4280-44ce-b551-c63da11beb83","resolution":{"observed_at":"2026-08-10T20:48:12.734758Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2404.18100","last_updated":"2024-04-28T07:29:18Z","snapshot_observed_at":"2026-08-11T08:59:30.947139Z","submitted_at":"2024-04-28T07:29:18Z","title":"Accurate and Unbiased Reconstruction of CMB B Mode using Deep Learning","version":1},"cited_work":{"arxiv_id":"2404.18100","doi":null,"metadata_source":"pith","pith_arxiv_id":"2404.18100","snapshot_observed_at":"2026-08-10T20:48:12.605574Z","title":"Accurate and Unbiased Reconstruction of CMB B Mode using Deep Learning","venue":"astro-ph.CO","work_id":"b185af75-7ee2-43e1-96f6-4b5c7e1ab110","year":2024},"citing_paper":{"arxiv_id":"2501.07469","last_updated":"2025-08-25T11:45:06Z","snapshot_observed_at":"2026-08-10T23:55:18.264631Z","submitted_at":"2025-01-13T16:35:55Z","title":"Deep Needlet: A CNN based full sky component separation method in Needlet space","version":2},"reference_index":41,"source":"pdf_text","source_observed_at":"2026-08-10T20:48:07.549733Z"},"links":{"cited_paper":"/paper/2404.18100","citing_paper":"/paper/2501.07469"},"observation_digest":"sha256:2a067adb0a6dd480feeae0a9ad74dfd670da9fcf1b453fc2c1ad76d7d0eed503","observation_id":"2256530d-5095-40dc-b61a-0e9f837a2e0f","resolution":{"observed_at":"2026-08-10T20:48:12.624342Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2302.13572","last_updated":"2023-04-17T16:15:55Z","snapshot_observed_at":"2026-08-10T23:57:37.849225Z","submitted_at":"2023-02-27T08:19:04Z","title":"Recovering Cosmic Microwave Background Polarization Signals with Machine Learning","version":2},"cited_work":{"arxiv_id":"2302.13572","doi":null,"metadata_source":"pith","pith_arxiv_id":"2302.13572","snapshot_observed_at":"2026-08-10T20:48:12.536642Z","title":"Recovering Cosmic Microwave Background Polarization Signals with Machine Learning","venue":"astro-ph.CO","work_id":"7318b267-459b-4ce3-8248-18a45f6177a0","year":2023},"citing_paper":{"arxiv_id":"2501.07469","last_updated":"2025-08-25T11:45:06Z","snapshot_observed_at":"2026-08-10T23:55:18.264631Z","submitted_at":"2025-01-13T16:35:55Z","title":"Deep Needlet: A CNN based full sky component separation method in Needlet space","version":2},"reference_index":42,"source":"pdf_text","source_observed_at":"2026-08-10T20:48:07.574775Z"},"links":{"cited_paper":"/paper/2302.13572","citing_paper":"/paper/2501.07469"},"observation_digest":"sha256:bcf9e98f5a59102e8787d2bbd5c655d7b9f36f66e9bff4ae6bf54d0b0aa48ecb","observation_id":"54020038-ab70-482c-a9d4-9ba901064337","resolution":{"observed_at":"2026-08-10T20:48:12.548831Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2501.06139","last_updated":"2025-05-22T18:05:02Z","snapshot_observed_at":"2026-08-10T23:57:36.813144Z","submitted_at":"2025-01-10T18:00:30Z","title":"Introducing a multiscale feature integration network for inpainting with applications to enhanced CMB map reconstruction","version":3},"cited_work":{"arxiv_id":"2501.06139","doi":null,"metadata_source":"pith","pith_arxiv_id":"2501.06139","snapshot_observed_at":"2026-08-10T20:48:12.456145Z","title":"Introducing a multiscale feature integration network for inpainting with applications to enhanced CMB map reconstruction","venue":"astro-ph.CO","work_id":"8270c8bb-8de1-49b1-931a-1ed4d9fc9dab","year":2025},"citing_paper":{"arxiv_id":"2501.07469","last_updated":"2025-08-25T11:45:06Z","snapshot_observed_at":"2026-08-10T23:55:18.264631Z","submitted_at":"2025-01-13T16:35:55Z","title":"Deep Needlet: A CNN based full sky component separation method in Needlet space","version":2},"reference_index":43,"source":"pdf_text","source_observed_at":"2026-08-10T20:48:07.623798Z"},"links":{"cited_paper":"/paper/2501.06139","citing_paper":"/paper/2501.07469"},"observation_digest":"sha256:d6c383bd7162f29c5cbdde1f26153b4f048e3094d0ccfcdd043735a553224f61","observation_id":"de4f8e30-a593-47f2-9b86-3a68cb1f368d","resolution":{"observed_at":"2026-08-10T20:48:12.479333Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"0707.0844","last_updated":"2007-07-05T17:54:13Z","snapshot_observed_at":"2026-07-06T01:31:41.310084Z","submitted_at":"2007-07-05T17:54:13Z","title":"Spherical Needlets for CMB Data Analysis","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"0707.0844","snapshot_observed_at":"2026-08-10T20:48:07.663248Z","title":"Marinucci, D","venue":null,"work_id":null,"year":2008},"citing_paper":{"arxiv_id":"2501.07469","last_updated":"2025-08-25T11:45:06Z","snapshot_observed_at":"2026-08-10T23:55:18.264631Z","submitted_at":"2025-01-13T16:35:55Z","title":"Deep Needlet: A CNN based full sky component separation method in Needlet space","version":2},"reference_index":44,"source":"pdf_text","source_observed_at":"2026-08-10T20:48:07.663248Z"},"links":{"cited_paper":"/paper/0707.0844","citing_paper":"/paper/2501.07469"},"observation_digest":"sha256:ed0e7c3ed5b7747a8d98c7d762584f2c305d85ecf0cc549f1c807b32c20bf1e6","observation_id":"c4c9e1fa-a5e6-45ba-af20-91da0ba5af03","resolution":{"observed_at":"2026-08-10T20:48:07.663248Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1801.10130","last_updated":"2018-02-25T13:43:49Z","snapshot_observed_at":"2026-07-06T06:20:59.047515Z","submitted_at":"2018-01-30T18:28:30Z","title":"Spherical CNNs","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1801.10130","snapshot_observed_at":"2026-08-10T20:48:07.750586Z","title":null,"venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2501.07469","last_updated":"2025-08-25T11:45:06Z","snapshot_observed_at":"2026-08-10T23:55:18.264631Z","submitted_at":"2025-01-13T16:35:55Z","title":"Deep Needlet: A CNN based full sky component separation method in Needlet space","version":2},"reference_index":45,"source":"pdf_text","source_observed_at":"2026-08-10T20:48:07.750586Z"},"links":{"cited_paper":"/paper/1801.10130","citing_paper":"/paper/2501.07469"},"observation_digest":"sha256:a515110892bfb14929985d4618d34f51f2435ae42092bb92e2325f657b2684dc","observation_id":"cf62437a-e48f-433c-88a6-2a9154ff4647","resolution":{"observed_at":"2026-08-10T20:48:07.750586Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1901.02039","last_updated":"2019-01-07T19:56:19Z","snapshot_observed_at":"2026-08-02T21:45:42.218581Z","submitted_at":"2019-01-07T19:56:19Z","title":"Spherical CNNs on Unstructured Grids","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1901.02039","snapshot_observed_at":"2026-08-10T20:48:07.763794Z","title":"”Max” Jiang, J","venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2501.07469","last_updated":"2025-08-25T11:45:06Z","snapshot_observed_at":"2026-08-10T23:55:18.264631Z","submitted_at":"2025-01-13T16:35:55Z","title":"Deep Needlet: A CNN based full sky component separation method in Needlet space","version":2},"reference_index":46,"source":"pdf_text","source_observed_at":"2026-08-10T20:48:07.763794Z"},"links":{"cited_paper":"/paper/1901.02039","citing_paper":"/paper/2501.07469"},"observation_digest":"sha256:1f9fee951afae22e060a3f6cda5e483e1b0de1c513b1a066ebb607a16ac7b68c","observation_id":"f82dad22-a95d-4708-a6b3-4f5b3e4bac4b","resolution":{"observed_at":"2026-08-10T20:48:07.763794Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1902.04083","last_updated":"2019-07-15T13:49:57Z","snapshot_observed_at":"2026-08-10T23:57:53.444917Z","submitted_at":"2019-02-11T19:00:02Z","title":"Convolutional Neural Networks on the HEALPix sphere: a pixel-based algorithm and its application to CMB data analysis","version":2},"cited_work":{"arxiv_id":"1902.04083","doi":null,"metadata_source":"pith","pith_arxiv_id":"1902.04083","snapshot_observed_at":"2026-08-10T20:48:12.116151Z","title":"Convolutional Neural Networks on the HEALPix sphere: a pixel-based algorithm and its application to CMB data analysis","venue":"astro-ph.IM","work_id":"2ae23792-e650-4b35-b164-d7c8406008d1","year":2019},"citing_paper":{"arxiv_id":"2501.07469","last_updated":"2025-08-25T11:45:06Z","snapshot_observed_at":"2026-08-10T23:55:18.264631Z","submitted_at":"2025-01-13T16:35:55Z","title":"Deep Needlet: A CNN based full sky component separation method in Needlet space","version":2},"reference_index":47,"source":"pdf_text","source_observed_at":"2026-08-10T20:48:07.794768Z"},"links":{"cited_paper":"/paper/1902.04083","citing_paper":"/paper/2501.07469"},"observation_digest":"sha256:cde41e279cb954324fbd8c0898d4e8ac8e6513c33a66f31bf613fe82b345f80d","observation_id":"d781a509-3ecd-4eea-acda-fe899d2eb639","resolution":{"observed_at":"2026-08-10T20:48:12.134755Z","resolver_source":"local_arxiv","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2206.10385","last_updated":"2022-06-17T17:21:56Z","snapshot_observed_at":"2026-08-10T23:57:54.479365Z","submitted_at":"2022-06-17T17:21:56Z","title":"Approximate Equivariance SO(3) Needlet Convolution","version":1},"cited_work":{"arxiv_id":"2206.10385","doi":null,"metadata_source":"pith","pith_arxiv_id":"2206.10385","snapshot_observed_at":"2026-08-10T20:48:11.984926Z","title":"Approximate Equivariance SO(3) Needlet Convolution","venue":"eess.IV","work_id":"34df45d6-6093-4cb0-8682-71e15fa4571a","year":2022},"citing_paper":{"arxiv_id":"2501.07469","last_updated":"2025-08-25T11:45:06Z","snapshot_observed_at":"2026-08-10T23:55:18.264631Z","submitted_at":"2025-01-13T16:35:55Z","title":"Deep Needlet: A CNN based full sky component separation method in Needlet space","version":2},"reference_index":48,"source":"pdf_text","source_observed_at":"2026-08-10T20:48:07.844751Z"},"links":{"cited_paper":"/paper/2206.10385","citing_paper":"/paper/2501.07469"},"observation_digest":"sha256:3f0031665540e1b8294b28d96ce465a8434e7981a42819f1fbedb31a53b91684","observation_id":"7d0b84be-d679-4d2e-8205-1f8f1029e3a8","resolution":{"observed_at":"2026-08-10T20:48:12.003529Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1810.12186","last_updated":"2019-03-26T17:11:17Z","snapshot_observed_at":"2026-08-10T23:57:04.476221Z","submitted_at":"2018-10-29T15:23:18Z","title":"DeepSphere: Efficient spherical Convolutional Neural Network with HEALPix sampling for cosmological applications","version":2},"cited_work":{"arxiv_id":"1810.12186","doi":null,"metadata_source":"pith","pith_arxiv_id":"1810.12186","snapshot_observed_at":"2026-08-10T20:48:11.814757Z","title":"DeepSphere: Efficient spherical Convolutional Neural Network with HEALPix sampling for cosmological applications","venue":"astro-ph.CO","work_id":"7ec9c909-b8da-46b4-b402-84ac6ed60fc9","year":2018},"citing_paper":{"arxiv_id":"2501.07469","last_updated":"2025-08-25T11:45:06Z","snapshot_observed_at":"2026-08-10T23:55:18.264631Z","submitted_at":"2025-01-13T16:35:55Z","title":"Deep Needlet: A CNN based full sky component separation method in Needlet space","version":2},"reference_index":49,"source":"pdf_text","source_observed_at":"2026-08-10T20:48:07.924755Z"},"links":{"cited_paper":"/paper/1810.12186","citing_paper":"/paper/2501.07469"},"observation_digest":"sha256:7c5328196af67cc24384ae677cedbfea8ab7448ed4a6bc106a06b052fb736685","observation_id":"b1e12303-d4b4-4e7a-b992-988f2d20c39c","resolution":{"observed_at":"2026-08-10T20:48:11.864745Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2004.11507","last_updated":"2020-11-06T22:57:19Z","snapshot_observed_at":"2026-08-10T23:56:45.604406Z","submitted_at":"2020-04-24T02:03:16Z","title":"Full-sky Cosmic Microwave Background Foreground Cleaning Using Machine Learning","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2004.11507","snapshot_observed_at":"2026-08-10T20:48:07.974755Z","title":null,"venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2501.07469","last_updated":"2025-08-25T11:45:06Z","snapshot_observed_at":"2026-08-10T23:55:18.264631Z","submitted_at":"2025-01-13T16:35:55Z","title":"Deep Needlet: A CNN based full sky component separation method in Needlet space","version":2},"reference_index":50,"source":"pdf_text","source_observed_at":"2026-08-10T20:48:07.974755Z"},"links":{"cited_paper":"/paper/2004.11507","citing_paper":"/paper/2501.07469"},"observation_digest":"sha256:3599fa04186e1bc725fcbeac97c6ecf31f37219eb290b88028bc63dc9ea7c575","observation_id":"67c2095c-53ed-4fa6-a8fa-0a7f50ffb6f0","resolution":{"observed_at":"2026-08-10T20:48:07.974755Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2204.01820","last_updated":"2022-05-11T11:02:18Z","snapshot_observed_at":"2026-08-10T23:56:42.455893Z","submitted_at":"2022-04-04T20:09:37Z","title":"Recovering the CMB Signal with Machine Learning","version":2},"cited_work":{"arxiv_id":"2204.01820","doi":null,"metadata_source":"pith","pith_arxiv_id":"2204.01820","snapshot_observed_at":"2026-08-10T20:48:11.566673Z","title":"Recovering the CMB Signal with Machine Learning","venue":"astro-ph.CO","work_id":"3cb5cbb5-d4cd-497e-ba35-b504bb583c1d","year":2022},"citing_paper":{"arxiv_id":"2501.07469","last_updated":"2025-08-25T11:45:06Z","snapshot_observed_at":"2026-08-10T23:55:18.264631Z","submitted_at":"2025-01-13T16:35:55Z","title":"Deep Needlet: A CNN based full sky component separation method in Needlet space","version":2},"reference_index":51,"source":"pdf_text","source_observed_at":"2026-08-10T20:48:08.024758Z"},"links":{"cited_paper":"/paper/2204.01820","citing_paper":"/paper/2501.07469"},"observation_digest":"sha256:c5af86853f4a2ce6414c596d31ba9a71623e1cf8381a87609722531abeb9670c","observation_id":"50dfd6cc-84e2-415c-a72a-a4de71d6c28e","resolution":{"observed_at":"2026-08-10T20:48:11.582771Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1505.04597","last_updated":"2015-05-18T11:28:37Z","snapshot_observed_at":"2026-08-06T11:05:16.105361Z","submitted_at":"2015-05-18T11:28:37Z","title":"U-Net: Convolutional Networks for Biomedical Image Segmentation","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1505.04597","snapshot_observed_at":"2026-08-10T20:48:08.054800Z","title":"Ronneberger, P","venue":null,"work_id":null,"year":2015},"citing_paper":{"arxiv_id":"2501.07469","last_updated":"2025-08-25T11:45:06Z","snapshot_observed_at":"2026-08-10T23:55:18.264631Z","submitted_at":"2025-01-13T16:35:55Z","title":"Deep Needlet: A CNN based full sky component separation method in Needlet space","version":2},"reference_index":52,"source":"pdf_text","source_observed_at":"2026-08-10T20:48:08.054800Z"},"links":{"cited_paper":"/paper/1505.04597","citing_paper":"/paper/2501.07469"},"observation_digest":"sha256:ced441288465ba3e86146e6d0a2894800cbbd4f35e0cd491e5123b50aa4d51c2","observation_id":"53fe6c32-96cf-46a8-8ac4-882b5bbd4e52","resolution":{"observed_at":"2026-08-10T20:48:08.054800Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2307.01043","last_updated":"2024-02-15T21:08:02Z","snapshot_observed_at":"2026-08-10T23:56:46.318383Z","submitted_at":"2023-07-03T14:20:30Z","title":"Component-separated, CIB-cleaned thermal Sunyaev--Zel'dovich maps from $\\textit{Planck}$ PR4 data with a flexible public needlet ILC pipeline","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2307.01043","snapshot_observed_at":"2026-08-10T20:48:08.094901Z","title":"McCarthy and J","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2501.07469","last_updated":"2025-08-25T11:45:06Z","snapshot_observed_at":"2026-08-10T23:55:18.264631Z","submitted_at":"2025-01-13T16:35:55Z","title":"Deep Needlet: A CNN based full sky component separation method in Needlet space","version":2},"reference_index":53,"source":"pdf_text","source_observed_at":"2026-08-10T20:48:08.094901Z"},"links":{"cited_paper":"/paper/2307.01043","citing_paper":"/paper/2501.07469"},"observation_digest":"sha256:301e70748c07550edda861cf372f7363abc211944e1ba3b31d43ae84c3bb9543","observation_id":"cd669a3a-9066-4a8a-8bc2-d235d3de4659","resolution":{"observed_at":"2026-08-10T20:48:08.094901Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1512.03385","last_updated":"2015-12-10T19:51:55Z","snapshot_observed_at":"2026-07-06T04:39:28.429064Z","submitted_at":"2015-12-10T19:51:55Z","title":"Deep Residual Learning for Image Recognition","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1512.03385","snapshot_observed_at":"2026-08-10T20:48:08.128987Z","title":null,"venue":null,"work_id":null,"year":2015},"citing_paper":{"arxiv_id":"2501.07469","last_updated":"2025-08-25T11:45:06Z","snapshot_observed_at":"2026-08-10T23:55:18.264631Z","submitted_at":"2025-01-13T16:35:55Z","title":"Deep Needlet: A CNN based full sky component separation method in Needlet space","version":2},"reference_index":54,"source":"pdf_text","source_observed_at":"2026-08-10T20:48:08.128987Z"},"links":{"cited_paper":"/paper/1512.03385","citing_paper":"/paper/2501.07469"},"observation_digest":"sha256:7077a791d724b0a9adaec8944a279831a6922f5ecb394115c4103f7110ce40f5","observation_id":"a317dc92-3df3-455e-b86a-de274b13a3c6","resolution":{"observed_at":"2026-08-10T20:48:08.128987Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1412.6980","last_updated":"2017-01-30T01:27:54Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2014-12-22T13:54:29Z","title":"Adam: A Method for Stochastic Optimization","version":9},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1412.6980","snapshot_observed_at":"2026-08-10T20:48:08.164334Z","title":null,"venue":null,"work_id":null,"year":2014},"citing_paper":{"arxiv_id":"2501.07469","last_updated":"2025-08-25T11:45:06Z","snapshot_observed_at":"2026-08-10T23:55:18.264631Z","submitted_at":"2025-01-13T16:35:55Z","title":"Deep Needlet: A CNN based full sky component separation method in Needlet space","version":2},"reference_index":55,"source":"pdf_text","source_observed_at":"2026-08-10T20:48:08.164334Z"},"links":{"cited_paper":"/paper/1412.6980","citing_paper":"/paper/2501.07469"},"observation_digest":"sha256:0329723865466d70192b5baef12c70b86cfe62d982860b90ee6e9b3e472d9826","observation_id":"a4f51680-c8a3-400e-bab8-ee85f6e8d707","resolution":{"observed_at":"2026-08-10T20:48:08.164334Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1807.06209","last_updated":"2021-08-09T10:43:18Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2018-07-17T04:05:07Z","title":"Planck 2018 results. VI. Cosmological parameters","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1807.06209","snapshot_observed_at":"2026-08-10T20:48:08.206000Z","title":"Aghanim, Y","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2501.07469","last_updated":"2025-08-25T11:45:06Z","snapshot_observed_at":"2026-08-10T23:55:18.264631Z","submitted_at":"2025-01-13T16:35:55Z","title":"Deep Needlet: A CNN based full sky component separation method in Needlet space","version":2},"reference_index":56,"source":"pdf_text","source_observed_at":"2026-08-10T20:48:08.206000Z"},"links":{"cited_paper":"/paper/1807.06209","citing_paper":"/paper/2501.07469"},"observation_digest":"sha256:e9ef95642ce4215259a65250b274b2504877e994e62bf31c95aff4686e99b0de","observation_id":"4e96580d-6b64-4092-881c-738f8f97b12c","resolution":{"observed_at":"2026-08-10T20:48:08.206000Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1608.02841","last_updated":"2016-08-09T15:38:49Z","snapshot_observed_at":"2026-07-06T05:06:28.719562Z","submitted_at":"2016-08-09T15:38:49Z","title":"The Python Sky Model: software for simulating the Galactic microwave sky","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1608.02841","snapshot_observed_at":"2026-08-10T20:48:08.255039Z","title":"Thorne, J","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2501.07469","last_updated":"2025-08-25T11:45:06Z","snapshot_observed_at":"2026-08-10T23:55:18.264631Z","submitted_at":"2025-01-13T16:35:55Z","title":"Deep Needlet: A CNN based full sky component separation method in Needlet space","version":2},"reference_index":57,"source":"pdf_text","source_observed_at":"2026-08-10T20:48:08.255039Z"},"links":{"cited_paper":"/paper/1608.02841","citing_paper":"/paper/2501.07469"},"observation_digest":"sha256:42a643ea94c1b9ef3274da863b8bc6e2add44a7a866897f865842e45c2f49d5f","observation_id":"9ce5190f-9d80-428f-8de2-8ee238561f86","resolution":{"observed_at":"2026-08-10T20:48:08.255039Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1502.01588","last_updated":"2015-02-25T23:40:37Z","snapshot_observed_at":"2026-08-05T18:23:44.689090Z","submitted_at":"2015-02-05T15:08:32Z","title":"Planck 2015 results. X. Diffuse component separation: Foreground maps","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1502.01588","snapshot_observed_at":"2026-08-10T20:48:08.281762Z","title":null,"venue":null,"work_id":null,"year":2016},"citing_paper":{"arxiv_id":"2501.07469","last_updated":"2025-08-25T11:45:06Z","snapshot_observed_at":"2026-08-10T23:55:18.264631Z","submitted_at":"2025-01-13T16:35:55Z","title":"Deep Needlet: A CNN based full sky component separation method in Needlet space","version":2},"reference_index":58,"source":"pdf_text","source_observed_at":"2026-08-10T20:48:08.281762Z"},"links":{"cited_paper":"/paper/1502.01588","citing_paper":"/paper/2501.07469"},"observation_digest":"sha256:d86415629a6d3a488d4cbd311c0bc3890c27a63eb931e4c76147bf4122955b3c","observation_id":"955976b8-a414-4717-ad05-d32d6a8b7a5b","resolution":{"observed_at":"2026-08-10T20:48:08.281762Z","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":"2026-08-10T20:48:15.976485Z","title":"Remazeilles, C","venue":null,"work_id":"2e4b0614-bbe4-4952-b4ec-8c3f4a7d5b12","year":2015},"citing_paper":{"arxiv_id":"2501.07469","last_updated":"2025-08-25T11:45:06Z","snapshot_observed_at":"2026-08-10T23:55:18.264631Z","submitted_at":"2025-01-13T16:35:55Z","title":"Deep Needlet: A CNN based full sky component separation method in Needlet space","version":2},"reference_index":59,"source":"pdf_text","source_observed_at":"2026-08-10T20:48:08.324749Z"},"links":{"citing_paper":"/paper/2501.07469"},"observation_digest":"sha256:5d78080a78679e1bafd586975b46d22c692a8e61f474f79ed911bd2b2feeb886","observation_id":"0cd7e08b-e303-4197-9f5b-6ced099955a9","resolution":{"observed_at":"2026-08-10T20:48:15.991659Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"0802.3345","last_updated":"2008-02-22T16:28:03Z","snapshot_observed_at":"2026-08-06T06:40:24.808532Z","submitted_at":"2008-02-22T16:28:03Z","title":"Separation of anomalous and synchrotron emissions using WMAP polarization data","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"0802.3345","snapshot_observed_at":"2026-08-10T20:48:08.364754Z","title":null,"venue":null,"work_id":null,"year":2008},"citing_paper":{"arxiv_id":"2501.07469","last_updated":"2025-08-25T11:45:06Z","snapshot_observed_at":"2026-08-10T23:55:18.264631Z","submitted_at":"2025-01-13T16:35:55Z","title":"Deep Needlet: A CNN based full sky component separation method in Needlet space","version":2},"reference_index":60,"source":"pdf_text","source_observed_at":"2026-08-10T20:48:08.364754Z"},"links":{"cited_paper":"/paper/0802.3345","citing_paper":"/paper/2501.07469"},"observation_digest":"sha256:e72ec3f99921174f421881c32bd91a3f38aad07baf6cb40832747b59d1492dce","observation_id":"27d324f9-bec9-4591-ad65-504df9bcf2ae","resolution":{"observed_at":"2026-08-10T20:48:08.364754Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"0812.2904","last_updated":"2009-08-03T20:14:08Z","snapshot_observed_at":"2026-07-06T01:48:48.399325Z","submitted_at":"2008-12-15T21:00:06Z","title":"A refined model for spinning dust radiation","version":2},"cited_work":{"arxiv_id":"0812.2904","doi":null,"metadata_source":"pith","pith_arxiv_id":"0812.2904","snapshot_observed_at":"2026-08-10T20:48:10.614752Z","title":"A refined model for spinning dust radiation","venue":"astro-ph","work_id":"b78385cf-e03c-44da-a9ff-9c57fe28987d","year":2008},"citing_paper":{"arxiv_id":"2501.07469","last_updated":"2025-08-25T11:45:06Z","snapshot_observed_at":"2026-08-10T23:55:18.264631Z","submitted_at":"2025-01-13T16:35:55Z","title":"Deep Needlet: A CNN based full sky component separation method in Needlet space","version":2},"reference_index":61,"source":"pdf_text","source_observed_at":"2026-08-10T20:48:08.425473Z"},"links":{"cited_paper":"/paper/0812.2904","citing_paper":"/paper/2501.07469"},"observation_digest":"sha256:908008979d567943ad3156bcf7cf5060ac792c7ff9f8c001ac968fe1e73ba292","observation_id":"832207a3-0872-466e-ad3c-367b8c2496de","resolution":{"observed_at":"2026-08-10T20:48:10.664188Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1605.06671","last_updated":"2016-05-21T16:37:15Z","snapshot_observed_at":"2026-08-07T02:35:06.754171Z","submitted_at":"2016-05-21T16:37:15Z","title":"Quantum Suppression of Alignment in Ultrasmall Grains: Microwave Emission from Spinning Dust will be Negligibly Polarized","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1605.06671","snapshot_observed_at":"2026-08-10T20:48:08.459722Z","title":null,"venue":null,"work_id":null,"year":2016},"citing_paper":{"arxiv_id":"2501.07469","last_updated":"2025-08-25T11:45:06Z","snapshot_observed_at":"2026-08-10T23:55:18.264631Z","submitted_at":"2025-01-13T16:35:55Z","title":"Deep Needlet: A CNN based full sky component separation method in Needlet space","version":2},"reference_index":62,"source":"pdf_text","source_observed_at":"2026-08-10T20:48:08.459722Z"},"links":{"cited_paper":"/paper/1605.06671","citing_paper":"/paper/2501.07469"},"observation_digest":"sha256:46afe8f2f16aad09181e1aa3daba6523f700ad2cc0f2f7e0d5d55001efe2b162","observation_id":"1fd34f86-b385-46fa-933c-7551d67e015c","resolution":{"observed_at":"2026-08-10T20:48:08.459722Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1312.1300","last_updated":"2014-09-23T09:26:19Z","snapshot_observed_at":"2026-08-10T20:35:25.072212Z","submitted_at":"2013-12-04T19:49:34Z","title":"Planck 2013 results. XI. All-sky model of thermal dust emission","version":5},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1312.1300","snapshot_observed_at":"2026-08-10T20:48:08.504876Z","title":"Abergel, P","venue":null,"work_id":null,"year":2014},"citing_paper":{"arxiv_id":"2501.07469","last_updated":"2025-08-25T11:45:06Z","snapshot_observed_at":"2026-08-10T23:55:18.264631Z","submitted_at":"2025-01-13T16:35:55Z","title":"Deep Needlet: A CNN based full sky component separation method in Needlet space","version":2},"reference_index":63,"source":"pdf_text","source_observed_at":"2026-08-10T20:48:08.504876Z"},"links":{"cited_paper":"/paper/1312.1300","citing_paper":"/paper/2501.07469"},"observation_digest":"sha256:394625e96863669a1b312513fd87034a977845ed3dd08d9dbcaab0b06dc2e9ba","observation_id":"ae190a53-ed2d-47d3-9183-ad4a1c242f41","resolution":{"observed_at":"2026-08-10T20:48:08.504876Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1506.06660","last_updated":"2016-06-11T15:12:51Z","snapshot_observed_at":"2026-07-06T04:21:38.071787Z","submitted_at":"2015-06-22T15:56:34Z","title":"Planck 2015 results. XXV. Diffuse low-frequency Galactic foregrounds","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1506.06660","snapshot_observed_at":"2026-08-10T20:48:08.544764Z","title":null,"venue":null,"work_id":null,"year":2016},"citing_paper":{"arxiv_id":"2501.07469","last_updated":"2025-08-25T11:45:06Z","snapshot_observed_at":"2026-08-10T23:55:18.264631Z","submitted_at":"2025-01-13T16:35:55Z","title":"Deep Needlet: A CNN based full sky component separation method in Needlet space","version":2},"reference_index":64,"source":"pdf_text","source_observed_at":"2026-08-10T20:48:08.544764Z"},"links":{"cited_paper":"/paper/1506.06660","citing_paper":"/paper/2501.07469"},"observation_digest":"sha256:c5e85d2c03cc81dc293e9c6fae7fd3036eb8a67ba6fe47cec505a5589e65c939","observation_id":"f5442af5-464f-4a96-b2b8-053cfacdadde","resolution":{"observed_at":"2026-08-10T20:48:08.544764Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2301.05113","last_updated":"2023-01-12T16:17:32Z","snapshot_observed_at":"2026-08-10T23:02:49.897014Z","submitted_at":"2023-01-12T16:17:32Z","title":"QUIJOTE scientific results -- IV. A northern sky survey in intensity and polarization at 10-20GHz with the Multi-Frequency Instrument","version":1},"cited_work":{"arxiv_id":"2301.05113","doi":null,"metadata_source":"pith","pith_arxiv_id":"2301.05113","snapshot_observed_at":"2026-08-10T20:48:10.118422Z","title":"QUIJOTE scientific results -- IV. A northern sky survey in intensity and polarization at 10-20GHz with the Multi-Frequency Instrument","venue":"astro-ph.GA","work_id":"33cc8e95-3750-4e7c-a534-7770928b58c5","year":2023},"citing_paper":{"arxiv_id":"2501.07469","last_updated":"2025-08-25T11:45:06Z","snapshot_observed_at":"2026-08-10T23:55:18.264631Z","submitted_at":"2025-01-13T16:35:55Z","title":"Deep Needlet: A CNN based full sky component separation method in Needlet space","version":2},"reference_index":65,"source":"pdf_text","source_observed_at":"2026-08-10T20:48:08.593463Z"},"links":{"cited_paper":"/paper/2301.05113","citing_paper":"/paper/2501.07469"},"observation_digest":"sha256:bbab09d5d489f8b9fd145ba4cdd33710b60324193b2de2169f5b43bbb2ed18a4","observation_id":"dbf15ece-1132-4538-82de-2b84f9914b43","resolution":{"observed_at":"2026-08-10T20:48:10.134632Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1007.1149","last_updated":"2013-05-20T07:39:52Z","snapshot_observed_at":"2026-07-06T02:12:41.634104Z","submitted_at":"2010-07-07T14:42:54Z","title":"MILCA, a Modified Internal Linear Combination Algorithm to extract astrophysical emissions from multi-frequency sky maps","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1007.1149","snapshot_observed_at":"2026-08-10T20:48:08.654994Z","title":"Hurier, J","venue":null,"work_id":null,"year":2013},"citing_paper":{"arxiv_id":"2501.07469","last_updated":"2025-08-25T11:45:06Z","snapshot_observed_at":"2026-08-10T23:55:18.264631Z","submitted_at":"2025-01-13T16:35:55Z","title":"Deep Needlet: A CNN based full sky component separation method in Needlet space","version":2},"reference_index":66,"source":"pdf_text","source_observed_at":"2026-08-10T20:48:08.654994Z"},"links":{"cited_paper":"/paper/1007.1149","citing_paper":"/paper/2501.07469"},"observation_digest":"sha256:7f0eb2dc8b1b04a41cb20f818b249193ce1e4252280a0046c30cf2bcaac2ca21","observation_id":"475bff8a-8f0f-4f5b-9252-326e870ea1f9","resolution":{"observed_at":"2026-08-10T20:48:08.654994Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2001.08787","last_updated":"2020-01-23T19:59:28Z","snapshot_observed_at":"2026-08-10T03:22:40.353722Z","submitted_at":"2020-01-23T19:59:28Z","title":"The Websky Extragalactic CMB Simulations","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2001.08787","snapshot_observed_at":"2026-08-10T20:48:08.714760Z","title":"Stein, M","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2501.07469","last_updated":"2025-08-25T11:45:06Z","snapshot_observed_at":"2026-08-10T23:55:18.264631Z","submitted_at":"2025-01-13T16:35:55Z","title":"Deep Needlet: A CNN based full sky component separation method in Needlet space","version":2},"reference_index":67,"source":"pdf_text","source_observed_at":"2026-08-10T20:48:08.714760Z"},"links":{"cited_paper":"/paper/2001.08787","citing_paper":"/paper/2501.07469"},"observation_digest":"sha256:a58e001fb7bf016232206d787e5fbe0767ccc3f056f79e0baa30fbefe8a972b7","observation_id":"1e44bd17-b240-4d46-b80f-1e4e5bcb305e","resolution":{"observed_at":"2026-08-10T20:48:08.714760Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"astro-ph/0409513","last_updated":"2004-09-21T18:00:00Z","snapshot_observed_at":"2026-07-07T00:44:53.460945Z","submitted_at":"2004-09-21T18:00:00Z","title":"HEALPix -- a Framework for High Resolution Discretization, and Fast Analysis of Data Distributed on the Sphere","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"astro-ph/0409513","snapshot_observed_at":"2026-08-10T20:48:08.754759Z","title":null,"venue":null,"work_id":null,"year":2005},"citing_paper":{"arxiv_id":"2501.07469","last_updated":"2025-08-25T11:45:06Z","snapshot_observed_at":"2026-08-10T23:55:18.264631Z","submitted_at":"2025-01-13T16:35:55Z","title":"Deep Needlet: A CNN based full sky component separation method in Needlet space","version":2},"reference_index":68,"source":"pdf_text","source_observed_at":"2026-08-10T20:48:08.754759Z"},"links":{"cited_paper":"/paper/astro-ph/0409513","citing_paper":"/paper/2501.07469"},"observation_digest":"sha256:c787966401acda71a8a03ab2ff6aadb39e9d52fdb564a1cb55d9b2cd44a41d7c","observation_id":"9b1d83f5-a944-46c5-8e20-4250c7e6ed08","resolution":{"observed_at":"2026-08-10T20:48:08.754759Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1807.06208","last_updated":"2020-09-26T14:25:24Z","snapshot_observed_at":"2026-08-09T00:05:31.254612Z","submitted_at":"2018-07-17T04:05:06Z","title":"Planck 2018 results. IV. Diffuse component separation","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1807.06208","snapshot_observed_at":"2026-08-10T20:48:08.804989Z","title":"Akrami, M","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2501.07469","last_updated":"2025-08-25T11:45:06Z","snapshot_observed_at":"2026-08-10T23:55:18.264631Z","submitted_at":"2025-01-13T16:35:55Z","title":"Deep Needlet: A CNN based full sky component separation method in Needlet space","version":2},"reference_index":69,"source":"pdf_text","source_observed_at":"2026-08-10T20:48:08.804989Z"},"links":{"cited_paper":"/paper/1807.06208","citing_paper":"/paper/2501.07469"},"observation_digest":"sha256:129540f25d3a583b62e6a32fb6ca8cf2d7fb84e71abe9e4535aea9b60d1bc3f0","observation_id":"5f729e03-9919-4db2-82eb-0c91e9275175","resolution":{"observed_at":"2026-08-10T20:48:08.804989Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1507.02058","last_updated":"2016-02-15T07:27:12Z","snapshot_observed_at":"2026-07-06T04:23:10.734075Z","submitted_at":"2015-07-08T08:11:06Z","title":"Planck 2015 results. XXVI. The Second Planck Catalogue of Compact Sources","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1507.02058","snapshot_observed_at":"2026-08-10T20:48:08.854036Z","title":null,"venue":null,"work_id":null,"year":2016},"citing_paper":{"arxiv_id":"2501.07469","last_updated":"2025-08-25T11:45:06Z","snapshot_observed_at":"2026-08-10T23:55:18.264631Z","submitted_at":"2025-01-13T16:35:55Z","title":"Deep Needlet: A CNN based full sky component separation method in Needlet space","version":2},"reference_index":70,"source":"pdf_text","source_observed_at":"2026-08-10T20:48:08.854036Z"},"links":{"cited_paper":"/paper/1507.02058","citing_paper":"/paper/2501.07469"},"observation_digest":"sha256:f623039cbe2ef36bdd0c63a0435ca94ca12f26360f464dbe27276597c10b11c5","observation_id":"0fd5aaab-c433-4fa5-bb80-7ce1d5017f90","resolution":{"observed_at":"2026-08-10T20:48:08.854036Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"astro-ph/0405575","last_updated":"2004-12-03T14:19:21Z","snapshot_observed_at":"2026-07-07T00:42:42.937805Z","submitted_at":"2004-05-28T12:23:14Z","title":"Xspect, estimation of the angular power spectrum by computing cross-power spectra with analytical error bars","version":2},"cited_work":{"arxiv_id":"astro-ph/0405575","doi":null,"metadata_source":"pith","pith_arxiv_id":"astro-ph/0405575","snapshot_observed_at":"2026-08-10T20:48:09.268739Z","title":"Xspect, estimation of the angular power spectrum by computing cross-power spectra with analytical error bars","venue":"astro-ph","work_id":"3bd2507a-aa4b-49cf-8da0-0248deffcd87","year":2004},"citing_paper":{"arxiv_id":"2501.07469","last_updated":"2025-08-25T11:45:06Z","snapshot_observed_at":"2026-08-10T23:55:18.264631Z","submitted_at":"2025-01-13T16:35:55Z","title":"Deep Needlet: A CNN based full sky component separation method in Needlet space","version":2},"reference_index":71,"source":"pdf_text","source_observed_at":"2026-08-10T20:48:08.895378Z"},"links":{"cited_paper":"/paper/astro-ph/0405575","citing_paper":"/paper/2501.07469"},"observation_digest":"sha256:a73d52acf5600f8aa3207443bd0821c425f7448296dddd73a33a88e703d62f40","observation_id":"b3344b9a-85e9-4960-a812-cb6fbb9ac3c6","resolution":{"observed_at":"2026-08-10T20:48:09.281253Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1807.06207","last_updated":"2018-07-17T04:05:05Z","snapshot_observed_at":"2026-08-10T23:56:23.660868Z","submitted_at":"2018-07-17T04:05:05Z","title":"Planck 2018 results. III. High Frequency Instrument data processing and frequency maps","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1807.06207","snapshot_observed_at":"2026-08-10T20:48:08.934742Z","title":"III., Planck 2018 results","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2501.07469","last_updated":"2025-08-25T11:45:06Z","snapshot_observed_at":"2026-08-10T23:55:18.264631Z","submitted_at":"2025-01-13T16:35:55Z","title":"Deep Needlet: A CNN based full sky component separation method in Needlet space","version":2},"reference_index":72,"source":"pdf_text","source_observed_at":"2026-08-10T20:48:08.934742Z"},"links":{"cited_paper":"/paper/1807.06207","citing_paper":"/paper/2501.07469"},"observation_digest":"sha256:d92da2b6c74b2bd0da98ec4bdd4fd0f4a6039c83c441f7114d7cb8b0417429d5","observation_id":"d773d6eb-e83d-45db-953d-32d878e153aa","resolution":{"observed_at":"2026-08-10T20:48:08.934742Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2407.18909","last_updated":"2024-07-26T17:59:26Z","snapshot_observed_at":"2026-08-10T23:58:10.822841Z","submitted_at":"2024-07-26T17:59:26Z","title":"Hybrid summary statistics: neural weak lensing inference beyond the power spectrum","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2407.18909","snapshot_observed_at":"2026-08-10T20:48:08.979867Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2501.07469","last_updated":"2025-08-25T11:45:06Z","snapshot_observed_at":"2026-08-10T23:55:18.264631Z","submitted_at":"2025-01-13T16:35:55Z","title":"Deep Needlet: A CNN based full sky component separation method in Needlet space","version":2},"reference_index":73,"source":"pdf_text","source_observed_at":"2026-08-10T20:48:08.979867Z"},"links":{"cited_paper":"/paper/2407.18909","citing_paper":"/paper/2501.07469"},"observation_digest":"sha256:b6f8f3a023f3c38897e65b5f066f7402a59cd2eb8a98fc122ee8974d72f2b5cd","observation_id":"76b09e5a-fec1-4857-aae8-af67a7b87e08","resolution":{"observed_at":"2026-08-10T20:48:08.979867Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"paper":{"arxiv_id":"2501.07469","last_updated":"2025-08-25T11:45:06Z","latest_version":2,"primary_category":"astro-ph.CO","snapshot_observed_at":"2026-08-10T23:55:18.264631Z","submitted_at":"2025-01-13T16:35:55Z","title":"Deep Needlet: A CNN based full sky component separation method in Needlet space"},"reference_resolution":{"displayed":73,"state_counts":{"malformed_identifier":0,"metadata_mismatch":1,"parse_uncertain":0,"unresolved":39,"verified_exact":21,"verified_fuzzy":12},"total_outbound_references":73},"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":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"thesis":"As of 11 August 2026, this Paper Citation Record lists 73 of 73 outbound references and 1 inbound Pith citation observation for arXiv:2501.07469."}