{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2024:D2BLN5TFCW2BDC3IN3VXAHHZ2A","short_pith_number":"pith:D2BLN5TF","canonical_record":{"source":{"id":"2403.06308","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"physics.med-ph","submitted_at":"2024-03-10T20:51:36Z","cross_cats_sorted":[],"title_canon_sha256":"6820fce4fc5083486e12351dcc5cd639a8187276467400757184509eaccda0b2","abstract_canon_sha256":"7b2075b048c900f1ec403f0b6ea123c3edc4288f46953a51cbb8f7e307f750e2"},"schema_version":"1.0"},"canonical_sha256":"1e82b6f66515b4118b686eeb701cf9d020915e6a7ded2dc77f2cb31d520637fe","source":{"kind":"arxiv","id":"2403.06308","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2403.06308","created_at":"2026-07-05T07:56:22Z"},{"alias_kind":"arxiv_version","alias_value":"2403.06308v2","created_at":"2026-07-05T07:56:22Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2403.06308","created_at":"2026-07-05T07:56:22Z"},{"alias_kind":"pith_short_12","alias_value":"D2BLN5TFCW2B","created_at":"2026-07-05T07:56:22Z"},{"alias_kind":"pith_short_16","alias_value":"D2BLN5TFCW2BDC3I","created_at":"2026-07-05T07:56:22Z"},{"alias_kind":"pith_short_8","alias_value":"D2BLN5TF","created_at":"2026-07-05T07:56:22Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2024:D2BLN5TFCW2BDC3IN3VXAHHZ2A","target":"record","payload":{"canonical_record":{"source":{"id":"2403.06308","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"physics.med-ph","submitted_at":"2024-03-10T20:51:36Z","cross_cats_sorted":[],"title_canon_sha256":"6820fce4fc5083486e12351dcc5cd639a8187276467400757184509eaccda0b2","abstract_canon_sha256":"7b2075b048c900f1ec403f0b6ea123c3edc4288f46953a51cbb8f7e307f750e2"},"schema_version":"1.0"},"canonical_sha256":"1e82b6f66515b4118b686eeb701cf9d020915e6a7ded2dc77f2cb31d520637fe","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T07:56:22.007100Z","signature_b64":"Isi4UOfb/0OKXHI+nb8Qz3+cQ/SvEehlBw3U3VAGsBlIJcr5y+3Iv8StkIFIMkNepayIniYtlh04y5tPXeRNCA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"1e82b6f66515b4118b686eeb701cf9d020915e6a7ded2dc77f2cb31d520637fe","last_reissued_at":"2026-07-05T07:56:22.006541Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T07:56:22.006541Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2403.06308","source_version":2,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T07:56:22Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"0WCOaakyFNpTPz5MgUkhJgPF3fCHzYJwfvb9fPN8fm0EWlf+nXeDyMU93L4f6Hf7e+d8VnffLID1vnnd6KbHAw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-05T09:16:04.651931Z"},"content_sha256":"59080d9c83a911678c4c298860f2337adf1cd7c013429752c625e7c2361b11eb","schema_version":"1.0","event_id":"sha256:59080d9c83a911678c4c298860f2337adf1cd7c013429752c625e7c2361b11eb"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2024:D2BLN5TFCW2BDC3IN3VXAHHZ2A","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Diffusion Posterior Sampling for Synergistic Reconstruction in Spectral Computed Tomography","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"physics.med-ph","authors_text":"Alexandre Bousse, B\\'eatrice Vedel, Corentin Vazia, Dimitris Visvikis, Franck Vermet, Jacques Froment, Jean-Pierre Tasu, Thore Dassow, Zhihan Wang","submitted_at":"2024-03-10T20:51:36Z","abstract_excerpt":"Using recent advances in generative artificial intelligence (AI) brought by diffusion models, this paper introduces a new synergistic method for spectral computed tomography (CT) reconstruction. Diffusion models define a neural network to approximate the gradient of the log-density of the training data, which is then used to generate new images similar to the training ones. Following the inverse problem paradigm, we propose to adapt this generative process to synergistically reconstruct multiple images at different energy bins from multiple measurements. The experiments suggest that using mult"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2403.06308","kind":"arxiv","version":2},"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/2403.06308/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":"2026-07-05T07:56:22Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"4jwcWaW0ucbWUFxRWs0VHkmqC/ZPcTvXFRREtu2HMpxioVsPMU/76DV34qd8zqs5915I/Xxj9Ty07fnk0IXECA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-05T09:16:04.652453Z"},"content_sha256":"e26550825529d046b240e4776a98c3e3b0e965f6fe4251e2e620531e22c6bc63","schema_version":"1.0","event_id":"sha256:e26550825529d046b240e4776a98c3e3b0e965f6fe4251e2e620531e22c6bc63"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/D2BLN5TFCW2BDC3IN3VXAHHZ2A/bundle.json","state_url":"https://pith.science/pith/D2BLN5TFCW2BDC3IN3VXAHHZ2A/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/D2BLN5TFCW2BDC3IN3VXAHHZ2A/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":"2026-08-05T09:16:04Z","links":{"resolver":"https://pith.science/pith/D2BLN5TFCW2BDC3IN3VXAHHZ2A","bundle":"https://pith.science/pith/D2BLN5TFCW2BDC3IN3VXAHHZ2A/bundle.json","state":"https://pith.science/pith/D2BLN5TFCW2BDC3IN3VXAHHZ2A/state.json","well_known_bundle":"https://pith.science/.well-known/pith/D2BLN5TFCW2BDC3IN3VXAHHZ2A/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:D2BLN5TFCW2BDC3IN3VXAHHZ2A","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":"7b2075b048c900f1ec403f0b6ea123c3edc4288f46953a51cbb8f7e307f750e2","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"physics.med-ph","submitted_at":"2024-03-10T20:51:36Z","title_canon_sha256":"6820fce4fc5083486e12351dcc5cd639a8187276467400757184509eaccda0b2"},"schema_version":"1.0","source":{"id":"2403.06308","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2403.06308","created_at":"2026-07-05T07:56:22Z"},{"alias_kind":"arxiv_version","alias_value":"2403.06308v2","created_at":"2026-07-05T07:56:22Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2403.06308","created_at":"2026-07-05T07:56:22Z"},{"alias_kind":"pith_short_12","alias_value":"D2BLN5TFCW2B","created_at":"2026-07-05T07:56:22Z"},{"alias_kind":"pith_short_16","alias_value":"D2BLN5TFCW2BDC3I","created_at":"2026-07-05T07:56:22Z"},{"alias_kind":"pith_short_8","alias_value":"D2BLN5TF","created_at":"2026-07-05T07:56:22Z"}],"graph_snapshots":[{"event_id":"sha256:e26550825529d046b240e4776a98c3e3b0e965f6fe4251e2e620531e22c6bc63","target":"graph","created_at":"2026-07-05T07:56:22Z","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/2403.06308/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Using recent advances in generative artificial intelligence (AI) brought by diffusion models, this paper introduces a new synergistic method for spectral computed tomography (CT) reconstruction. Diffusion models define a neural network to approximate the gradient of the log-density of the training data, which is then used to generate new images similar to the training ones. Following the inverse problem paradigm, we propose to adapt this generative process to synergistically reconstruct multiple images at different energy bins from multiple measurements. The experiments suggest that using mult","authors_text":"Alexandre Bousse, B\\'eatrice Vedel, Corentin Vazia, Dimitris Visvikis, Franck Vermet, Jacques Froment, Jean-Pierre Tasu, Thore Dassow, Zhihan Wang","cross_cats":[],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"physics.med-ph","submitted_at":"2024-03-10T20:51:36Z","title":"Diffusion Posterior Sampling for Synergistic Reconstruction in Spectral Computed Tomography"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2403.06308","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":"sha256:59080d9c83a911678c4c298860f2337adf1cd7c013429752c625e7c2361b11eb","target":"record","created_at":"2026-07-05T07:56:22Z","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":"7b2075b048c900f1ec403f0b6ea123c3edc4288f46953a51cbb8f7e307f750e2","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"physics.med-ph","submitted_at":"2024-03-10T20:51:36Z","title_canon_sha256":"6820fce4fc5083486e12351dcc5cd639a8187276467400757184509eaccda0b2"},"schema_version":"1.0","source":{"id":"2403.06308","kind":"arxiv","version":2}},"canonical_sha256":"1e82b6f66515b4118b686eeb701cf9d020915e6a7ded2dc77f2cb31d520637fe","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"1e82b6f66515b4118b686eeb701cf9d020915e6a7ded2dc77f2cb31d520637fe","first_computed_at":"2026-07-05T07:56:22.006541Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T07:56:22.006541Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"Isi4UOfb/0OKXHI+nb8Qz3+cQ/SvEehlBw3U3VAGsBlIJcr5y+3Iv8StkIFIMkNepayIniYtlh04y5tPXeRNCA==","signature_status":"signed_v1","signed_at":"2026-07-05T07:56:22.007100Z","signed_message":"canonical_sha256_bytes"},"source_id":"2403.06308","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:59080d9c83a911678c4c298860f2337adf1cd7c013429752c625e7c2361b11eb","sha256:e26550825529d046b240e4776a98c3e3b0e965f6fe4251e2e620531e22c6bc63"],"state_sha256":"84764736526f6c35cacf9929d2aa7b4a189482b6353694625f9ecaed1bc49c73"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"Ptw/AEC3EM0AtScUsAcgXGxUlEOfr++b5Qu8M4AAhU/df64weOjAbszyBMKQVobV5R2TkuXXZ0DERzQoY3+nDw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-05T09:16:04.656024Z","bundle_sha256":"899f9d336aac83eece6c8e7dbec9ae08b3a092fae2734c815dd06b1305a365df"}}