{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2022:E5ANCAH7RUK7DPFHUUIFUY245Y","short_pith_number":"pith:E5ANCAH7","canonical_record":{"source":{"id":"2212.00044","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"astro-ph.IM","submitted_at":"2022-11-30T19:00:03Z","cross_cats_sorted":["astro-ph.CO"],"title_canon_sha256":"370b5eb928643fcff20fa5a7a9244564630b3e5e5383bf282ad3bd372bc523d3","abstract_canon_sha256":"2f5ca58aab65e971cdf1e547985bdfba253b14101b5032f0df987426c1e10212"},"schema_version":"1.0"},"canonical_sha256":"2740d100ff8d15f1bca7a5105a635cee26b813a34491eb0368593378fd225aa0","source":{"kind":"arxiv","id":"2212.00044","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2212.00044","created_at":"2026-07-05T05:35:29Z"},{"alias_kind":"arxiv_version","alias_value":"2212.00044v1","created_at":"2026-07-05T05:35:29Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2212.00044","created_at":"2026-07-05T05:35:29Z"},{"alias_kind":"pith_short_12","alias_value":"E5ANCAH7RUK7","created_at":"2026-07-05T05:35:29Z"},{"alias_kind":"pith_short_16","alias_value":"E5ANCAH7RUK7DPFH","created_at":"2026-07-05T05:35:29Z"},{"alias_kind":"pith_short_8","alias_value":"E5ANCAH7","created_at":"2026-07-05T05:35:29Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2022:E5ANCAH7RUK7DPFHUUIFUY245Y","target":"record","payload":{"canonical_record":{"source":{"id":"2212.00044","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"astro-ph.IM","submitted_at":"2022-11-30T19:00:03Z","cross_cats_sorted":["astro-ph.CO"],"title_canon_sha256":"370b5eb928643fcff20fa5a7a9244564630b3e5e5383bf282ad3bd372bc523d3","abstract_canon_sha256":"2f5ca58aab65e971cdf1e547985bdfba253b14101b5032f0df987426c1e10212"},"schema_version":"1.0"},"canonical_sha256":"2740d100ff8d15f1bca7a5105a635cee26b813a34491eb0368593378fd225aa0","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T05:35:29.927821Z","signature_b64":"Mi7L+2iYU5HUcD7/oOfm9/4IdxcbeHAgBKdxSiey4ZV5JdAdD/g8/zjGIPd1pF9FSw8jwbfinffXdWDOFvlwCw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"2740d100ff8d15f1bca7a5105a635cee26b813a34491eb0368593378fd225aa0","last_reissued_at":"2026-07-05T05:35:29.927372Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T05:35:29.927372Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2212.00044","source_version":1,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T05:35:29Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"1hMmvrstvIyawd7ksJG13VGx8oIS3jqoVEBhhFTBm3K0P8EVCkkmC8wAyvOIfJ+sbAqBFWXiL0GLUBOMT9kOAA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-10T21:09:07.765329Z"},"content_sha256":"eb519a009549e8fa0fa7b1fd2d72196672408496aea546af15cea2cde4a09b7c","schema_version":"1.0","event_id":"sha256:eb519a009549e8fa0fa7b1fd2d72196672408496aea546af15cea2cde4a09b7c"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2022:E5ANCAH7RUK7DPFHUUIFUY245Y","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"A Framework for Obtaining Accurate Posteriors of Strong Gravitational Lensing Parameters with Flexible Priors and Implicit Likelihoods using Density Estimation","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["astro-ph.CO"],"primary_cat":"astro-ph.IM","authors_text":"Benjamin Wandelt, Laurence Perreault-Levasseur, Ronan Legin, Yashar Hezaveh","submitted_at":"2022-11-30T19:00:03Z","abstract_excerpt":"We report the application of implicit likelihood inference to the prediction of the macro-parameters of strong lensing systems with neural networks. This allows us to perform deep learning analysis of lensing systems within a well-defined Bayesian statistical framework to explicitly impose desired priors on lensing variables, to obtain accurate posteriors, and to guarantee convergence to the optimal posterior in the limit of perfect performance. We train neural networks to perform a regression task to produce point estimates of lensing parameters. We then interpret these estimates as compresse"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2212.00044","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/2212.00044/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"},"verdict_id":null},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T05:35:29Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"C2dRssDhv4S2GPND1tYTgyxoPZJSMRU0b2TUsolyCOtm/Hbu7/pyOt+cBfqsTNQUEjaZIAoQTz3trWZo8chkDA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-10T21:09:07.765980Z"},"content_sha256":"70a5efbae7ffd8c8d81ed66f9e6d2f32159acaddab2b14d616db96f21679cd46","schema_version":"1.0","event_id":"sha256:70a5efbae7ffd8c8d81ed66f9e6d2f32159acaddab2b14d616db96f21679cd46"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/E5ANCAH7RUK7DPFHUUIFUY245Y/bundle.json","state_url":"https://pith.science/pith/E5ANCAH7RUK7DPFHUUIFUY245Y/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/E5ANCAH7RUK7DPFHUUIFUY245Y/bundle.json","status":"primary"}],"public_keys":[{"key_id":"pith-v1-2026-05","algorithm":"ed25519","format":"raw","public_key_b64":"stVStoiQhXFxp4s2pdzPNoqVNBMojDU/fJ2db5S3CbM=","public_key_hex":"b2d552b68890857171a78b36a5dccf368a953413288c353f7c9d9d6f94b709b3","fingerprint_sha256_b32_first128bits":"RVFV5Z2OI2J3ZUO7ERDEBCYNKS","fingerprint_sha256_hex":"8d4b5ee74e4693bcd1df2446408b0d54","rotates_at":null,"url":"https://pith.science/pith-signing-key.json","notes":"Pith uses this Ed25519 key to sign canonical record SHA-256 digests. Verify with: ed25519_verify(public_key, message=canonical_sha256_bytes, signature=base64decode(signature_b64))."}],"merge_version":"pith-open-graph-merge-v1","built_at":"2026-08-10T21:09:07Z","links":{"resolver":"https://pith.science/pith/E5ANCAH7RUK7DPFHUUIFUY245Y","bundle":"https://pith.science/pith/E5ANCAH7RUK7DPFHUUIFUY245Y/bundle.json","state":"https://pith.science/pith/E5ANCAH7RUK7DPFHUUIFUY245Y/state.json","well_known_bundle":"https://pith.science/.well-known/pith/E5ANCAH7RUK7DPFHUUIFUY245Y/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2022:E5ANCAH7RUK7DPFHUUIFUY245Y","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":"2f5ca58aab65e971cdf1e547985bdfba253b14101b5032f0df987426c1e10212","cross_cats_sorted":["astro-ph.CO"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"astro-ph.IM","submitted_at":"2022-11-30T19:00:03Z","title_canon_sha256":"370b5eb928643fcff20fa5a7a9244564630b3e5e5383bf282ad3bd372bc523d3"},"schema_version":"1.0","source":{"id":"2212.00044","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2212.00044","created_at":"2026-07-05T05:35:29Z"},{"alias_kind":"arxiv_version","alias_value":"2212.00044v1","created_at":"2026-07-05T05:35:29Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2212.00044","created_at":"2026-07-05T05:35:29Z"},{"alias_kind":"pith_short_12","alias_value":"E5ANCAH7RUK7","created_at":"2026-07-05T05:35:29Z"},{"alias_kind":"pith_short_16","alias_value":"E5ANCAH7RUK7DPFH","created_at":"2026-07-05T05:35:29Z"},{"alias_kind":"pith_short_8","alias_value":"E5ANCAH7","created_at":"2026-07-05T05:35:29Z"}],"graph_snapshots":[{"event_id":"sha256:70a5efbae7ffd8c8d81ed66f9e6d2f32159acaddab2b14d616db96f21679cd46","target":"graph","created_at":"2026-07-05T05:35:29Z","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/2212.00044/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"We report the application of implicit likelihood inference to the prediction of the macro-parameters of strong lensing systems with neural networks. This allows us to perform deep learning analysis of lensing systems within a well-defined Bayesian statistical framework to explicitly impose desired priors on lensing variables, to obtain accurate posteriors, and to guarantee convergence to the optimal posterior in the limit of perfect performance. We train neural networks to perform a regression task to produce point estimates of lensing parameters. We then interpret these estimates as compresse","authors_text":"Benjamin Wandelt, Laurence Perreault-Levasseur, Ronan Legin, Yashar Hezaveh","cross_cats":["astro-ph.CO"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"astro-ph.IM","submitted_at":"2022-11-30T19:00:03Z","title":"A Framework for Obtaining Accurate Posteriors of Strong Gravitational Lensing Parameters with Flexible Priors and Implicit Likelihoods using Density Estimation"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2212.00044","kind":"arxiv","version":1},"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:eb519a009549e8fa0fa7b1fd2d72196672408496aea546af15cea2cde4a09b7c","target":"record","created_at":"2026-07-05T05:35:29Z","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":"2f5ca58aab65e971cdf1e547985bdfba253b14101b5032f0df987426c1e10212","cross_cats_sorted":["astro-ph.CO"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"astro-ph.IM","submitted_at":"2022-11-30T19:00:03Z","title_canon_sha256":"370b5eb928643fcff20fa5a7a9244564630b3e5e5383bf282ad3bd372bc523d3"},"schema_version":"1.0","source":{"id":"2212.00044","kind":"arxiv","version":1}},"canonical_sha256":"2740d100ff8d15f1bca7a5105a635cee26b813a34491eb0368593378fd225aa0","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"2740d100ff8d15f1bca7a5105a635cee26b813a34491eb0368593378fd225aa0","first_computed_at":"2026-07-05T05:35:29.927372Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T05:35:29.927372Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"Mi7L+2iYU5HUcD7/oOfm9/4IdxcbeHAgBKdxSiey4ZV5JdAdD/g8/zjGIPd1pF9FSw8jwbfinffXdWDOFvlwCw==","signature_status":"signed_v1","signed_at":"2026-07-05T05:35:29.927821Z","signed_message":"canonical_sha256_bytes"},"source_id":"2212.00044","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:eb519a009549e8fa0fa7b1fd2d72196672408496aea546af15cea2cde4a09b7c","sha256:70a5efbae7ffd8c8d81ed66f9e6d2f32159acaddab2b14d616db96f21679cd46"],"state_sha256":"6e6d0f3ae7da5168aae412b2b4675b3d2a590033a161f0b8d2a2aa6c0d16f1ad"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"/LJeyBMfoGT/+AEEyRf8enpOVUEA/716MwRqYzrBiEbtF7bGutI/MpPCeEda5PL29XTymA/UOAO7T4eDO0HmAA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-10T21:09:07.771203Z","bundle_sha256":"e903690587a3470caf639518828ae409c9cdfb63416abe87246b7c26513b0f0a"}}