{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2019:QUWSGUFL2MBKYWZ7YWCDJKOQ5W","merge_version":"pith-open-graph-merge-v1","event_count":2,"valid_event_count":2,"invalid_event_count":0,"equivocation_count":0,"current":{"canonical_record":{"metadata":{"abstract_canon_sha256":"81c5b35d657e212f31eee3a6b2f142e81d9e5d1beeff00fdcb5746be035be986","cross_cats_sorted":["astro-ph.IM"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"astro-ph.CO","submitted_at":"2019-03-25T18:00:16Z","title_canon_sha256":"133ca33f1b4b792563d1757fe4a243c3e11c0ae2e644eaff0dff978cdae06b53"},"schema_version":"1.0","source":{"id":"1903.10524","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1903.10524","created_at":"2026-07-04T23:55:38Z"},{"alias_kind":"arxiv_version","alias_value":"1903.10524v2","created_at":"2026-07-04T23:55:38Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1903.10524","created_at":"2026-07-04T23:55:38Z"},{"alias_kind":"pith_short_12","alias_value":"QUWSGUFL2MBK","created_at":"2026-07-04T23:55:38Z"},{"alias_kind":"pith_short_16","alias_value":"QUWSGUFL2MBKYWZ7","created_at":"2026-07-04T23:55:38Z"},{"alias_kind":"pith_short_8","alias_value":"QUWSGUFL","created_at":"2026-07-04T23:55:38Z"}],"graph_snapshots":[{"event_id":"sha256:3fcb5196ef26d34811ae748584557a8a1765797395fde853b4dc11173134b95c","target":"graph","created_at":"2026-07-04T23:55:38Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"graph_snapshot":{"author_claims":{"count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","strong_count":0},"builder_version":"pith-number-builder-2026-05-17-v1","claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"integrity":{"available":true,"clean":true,"detectors_run":[],"endpoint":"/pith/1903.10524/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"We present a novel halo painting network that learns to map approximate 3D dark matter fields to realistic halo distributions. This map is provided via a physically motivated network with which we can learn the non-trivial local relation between dark matter density field and halo distributions without relying on a physical model. Unlike other generative or regressive models, a well motivated prior and simple physical principles allow us to train the mapping network quickly and with relatively little data. In learning to paint halo distributions from computationally cheap, analytical and non-li","authors_text":"Doogesh Kodi Ramanah, Guilhem Lavaux, Tom Charnock","cross_cats":["astro-ph.IM"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"astro-ph.CO","submitted_at":"2019-03-25T18:00:16Z","title":"Painting halos from cosmic density fields of dark matter with physically motivated neural networks"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1903.10524","kind":"arxiv","version":2},"verdict":{"created_at":null,"id":null,"model_set":{},"one_line_summary":"","pipeline_version":null,"pith_extraction_headline":"","strongest_claim":"","weakest_assumption":""}},"verdict_id":null}}],"author_attestations":[],"timestamp_anchors":[],"storage_attestations":[],"citation_signatures":[],"replication_records":[],"corrections":[],"mirror_hints":[],"record_created":{"event_id":"sha256:43e5396a5913b1498d06f033f9e99546f0103caaad564e5f0de89173b20cdad2","target":"record","created_at":"2026-07-04T23:55:38Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"attestation_state":"computed","canonical_record":{"metadata":{"abstract_canon_sha256":"81c5b35d657e212f31eee3a6b2f142e81d9e5d1beeff00fdcb5746be035be986","cross_cats_sorted":["astro-ph.IM"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"astro-ph.CO","submitted_at":"2019-03-25T18:00:16Z","title_canon_sha256":"133ca33f1b4b792563d1757fe4a243c3e11c0ae2e644eaff0dff978cdae06b53"},"schema_version":"1.0","source":{"id":"1903.10524","kind":"arxiv","version":2}},"canonical_sha256":"852d2350abd302ac5b3fc58434a9d0ed8160390c08703333f86dc579b43e939a","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"852d2350abd302ac5b3fc58434a9d0ed8160390c08703333f86dc579b43e939a","first_computed_at":"2026-07-04T23:55:38.839480Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-04T23:55:38.839480Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"BQ7nsr0Y0IAdmNyHVLanmXVI/wx921OGRV2Q7EL33joHWf7sqXsK+ZVoHLp/sxp5aMq1VSIa4szK0RN16qybDQ==","signature_status":"signed_v1","signed_at":"2026-07-04T23:55:38.839984Z","signed_message":"canonical_sha256_bytes"},"source_id":"1903.10524","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:43e5396a5913b1498d06f033f9e99546f0103caaad564e5f0de89173b20cdad2","sha256:3fcb5196ef26d34811ae748584557a8a1765797395fde853b4dc11173134b95c"],"state_sha256":"b2afed8c679ed4b858a122340186af79d1326c5bfbc00f205260c5217d77ba45"}