{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2024:YVL6WNMZVOQJ5BA56L6VMJDQCC","short_pith_number":"pith:YVL6WNMZ","schema_version":"1.0","canonical_sha256":"c557eb3599aba09e841df2fd56247010930f7b6a3d27d36e1438eb30d566a3fd","source":{"kind":"arxiv","id":"2404.18100","version":1},"attestation_state":"computed","paper":{"title":"Accurate and Unbiased Reconstruction of CMB B Mode using Deep Learning","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"astro-ph.CO","authors_text":"Rajib Saha, Sarvesh Kumar Yadav, Srikanta Pal, Tarun Souradeep","submitted_at":"2024-04-28T07:29:18Z","abstract_excerpt":"An ingeniously designed autoencoder (PrimeNet) using simulated observations of future generation ECHO satellite mission recovers CMB B mode map, angular spectrum for multipoles $\\ell \\lesssim 9$ and tensor to scalar ratio $r$ {\\it limited only by cosmic variance down to $r= 0.0001$ and below}. We use diverse, realistically complex and detailed foreground models. PrimeNet predicts accurate results even when data with $r=0$ are tested which were not used in training, implying robust and efficient predictive power. The work eliminates a major bottleneck of weak CMB B mode reconstruction and takes"},"verification_status":{"content_addressed":true,"pith_receipt":true,"author_attested":false,"weak_author_claims":0,"strong_author_claims":0,"externally_anchored":false,"storage_verified":false,"citation_signatures":0,"replication_records":0,"graph_snapshot":true,"references_resolved":false,"formal_links_present":false},"canonical_record":{"source":{"id":"2404.18100","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"astro-ph.CO","submitted_at":"2024-04-28T07:29:18Z","cross_cats_sorted":[],"title_canon_sha256":"6876c0b7fdf02063d626797dbe42e770a2b0eb23681713c602aed2e4f37ffb22","abstract_canon_sha256":"34891cf6b8f57d6a36c08b880a9dc959d577e994c80da33c354e6b3d07325f6c"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T08:12:58.378574Z","signature_b64":"J1faKo6gah5YMlKXyOaD+vaNwkKPKvUrYA+ouNbk3EMMmetsMY2xS/ZWC/hqWhUhk1kFHabzx4LKzNO4XbwTAw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"c557eb3599aba09e841df2fd56247010930f7b6a3d27d36e1438eb30d566a3fd","last_reissued_at":"2026-07-05T08:12:58.378089Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T08:12:58.378089Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Accurate and Unbiased Reconstruction of CMB B Mode using Deep Learning","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"astro-ph.CO","authors_text":"Rajib Saha, Sarvesh Kumar Yadav, Srikanta Pal, Tarun Souradeep","submitted_at":"2024-04-28T07:29:18Z","abstract_excerpt":"An ingeniously designed autoencoder (PrimeNet) using simulated observations of future generation ECHO satellite mission recovers CMB B mode map, angular spectrum for multipoles $\\ell \\lesssim 9$ and tensor to scalar ratio $r$ {\\it limited only by cosmic variance down to $r= 0.0001$ and below}. We use diverse, realistically complex and detailed foreground models. PrimeNet predicts accurate results even when data with $r=0$ are tested which were not used in training, implying robust and efficient predictive power. The work eliminates a major bottleneck of weak CMB B mode reconstruction and takes"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2404.18100","kind":"arxiv","version":1},"verdict":{"id":null,"model_set":{},"created_at":null,"strongest_claim":"","one_line_summary":"","pipeline_version":null,"weakest_assumption":"","pith_extraction_headline":""},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/2404.18100/integrity.json","findings":[],"available":true,"detectors_run":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938"},"references":{"count":0,"sample":[],"resolved_work":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","internal_anchors":0},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"author_claims":{"count":0,"strong_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"builder_version":"pith-number-builder-2026-05-17-v1"},"aliases":[{"alias_kind":"arxiv","alias_value":"2404.18100","created_at":"2026-07-05T08:12:58.378146+00:00"},{"alias_kind":"arxiv_version","alias_value":"2404.18100v1","created_at":"2026-07-05T08:12:58.378146+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2404.18100","created_at":"2026-07-05T08:12:58.378146+00:00"},{"alias_kind":"pith_short_12","alias_value":"YVL6WNMZVOQJ","created_at":"2026-07-05T08:12:58.378146+00:00"},{"alias_kind":"pith_short_16","alias_value":"YVL6WNMZVOQJ5BA5","created_at":"2026-07-05T08:12:58.378146+00:00"},{"alias_kind":"pith_short_8","alias_value":"YVL6WNMZ","created_at":"2026-07-05T08:12:58.378146+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":1,"internal_anchor_count":1,"sample":[{"citing_arxiv_id":"2501.07469","citing_title":"Deep Needlet: A CNN based full sky component separation method in Needlet space","ref_index":41,"is_internal_anchor":true}]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/YVL6WNMZVOQJ5BA56L6VMJDQCC","json":"https://pith.science/pith/YVL6WNMZVOQJ5BA56L6VMJDQCC.json","graph_json":"https://pith.science/api/pith-number/YVL6WNMZVOQJ5BA56L6VMJDQCC/graph.json","events_json":"https://pith.science/api/pith-number/YVL6WNMZVOQJ5BA56L6VMJDQCC/events.json","paper":"https://pith.science/paper/YVL6WNMZ"},"agent_actions":{"view_html":"https://pith.science/pith/YVL6WNMZVOQJ5BA56L6VMJDQCC","download_json":"https://pith.science/pith/YVL6WNMZVOQJ5BA56L6VMJDQCC.json","view_paper":"https://pith.science/paper/YVL6WNMZ","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2404.18100&json=true","fetch_graph":"https://pith.science/api/pith-number/YVL6WNMZVOQJ5BA56L6VMJDQCC/graph.json","fetch_events":"https://pith.science/api/pith-number/YVL6WNMZVOQJ5BA56L6VMJDQCC/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/YVL6WNMZVOQJ5BA56L6VMJDQCC/action/timestamp_anchor","attest_storage":"https://pith.science/pith/YVL6WNMZVOQJ5BA56L6VMJDQCC/action/storage_attestation","attest_author":"https://pith.science/pith/YVL6WNMZVOQJ5BA56L6VMJDQCC/action/author_attestation","sign_citation":"https://pith.science/pith/YVL6WNMZVOQJ5BA56L6VMJDQCC/action/citation_signature","submit_replication":"https://pith.science/pith/YVL6WNMZVOQJ5BA56L6VMJDQCC/action/replication_record"}},"created_at":"2026-07-05T08:12:58.378146+00:00","updated_at":"2026-07-05T08:12:58.378146+00:00"}