{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:C7TRQEA7O5V4DBHM23MQLROIVG","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":"aed3bbe5c73ff6033b82277a34b21718f606cc3a880d5aeb071fcbca70a70577","cross_cats_sorted":["hep-ph"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"hep-ex","submitted_at":"2024-02-18T12:45:36Z","title_canon_sha256":"b33abc16d5040c271e5bd80536628c226a88956d9bacc2670598634cc530c66d"},"schema_version":"1.0","source":{"id":"2402.11575","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2402.11575","created_at":"2026-07-05T09:20:40Z"},{"alias_kind":"arxiv_version","alias_value":"2402.11575v1","created_at":"2026-07-05T09:20:40Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2402.11575","created_at":"2026-07-05T09:20:40Z"},{"alias_kind":"pith_short_12","alias_value":"C7TRQEA7O5V4","created_at":"2026-07-05T09:20:40Z"},{"alias_kind":"pith_short_16","alias_value":"C7TRQEA7O5V4DBHM","created_at":"2026-07-05T09:20:40Z"},{"alias_kind":"pith_short_8","alias_value":"C7TRQEA7","created_at":"2026-07-05T09:20:40Z"}],"graph_snapshots":[{"event_id":"sha256:8e48768d422088a4edeb5e41eb2e0e54092c4383a338b3024e2c611411bf5985","target":"graph","created_at":"2026-07-05T09:20:40Z","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/2402.11575/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Denoising diffusion models have gained prominence in various generative tasks, prompting their exploration for the generation of calorimeter responses. Given the computational challenges posed by detector simulations in high-energy physics experiments, the necessity to explore new machine-learning-based approaches is evident. This study introduces a novel graph-based diffusion model designed specifically for rapid calorimeter simulations. The methodology is particularly well-suited for low-granularity detectors featuring irregular geometries. We apply this model to the ATLAS dataset published ","authors_text":"Dmitrii Kobylianskii, Eilam Gross, Etienne Dreyer, Nathalie Soybelman","cross_cats":["hep-ph"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"hep-ex","submitted_at":"2024-02-18T12:45:36Z","title":"CaloGraph: Graph-based diffusion model for fast shower generation in calorimeters with irregular geometry"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2402.11575","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":"sha256:860457f00db27b9df1fb0d4bf2c1943cff32973796641d68299ca721f1f74303","target":"record","created_at":"2026-07-05T09:20:40Z","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":"aed3bbe5c73ff6033b82277a34b21718f606cc3a880d5aeb071fcbca70a70577","cross_cats_sorted":["hep-ph"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"hep-ex","submitted_at":"2024-02-18T12:45:36Z","title_canon_sha256":"b33abc16d5040c271e5bd80536628c226a88956d9bacc2670598634cc530c66d"},"schema_version":"1.0","source":{"id":"2402.11575","kind":"arxiv","version":1}},"canonical_sha256":"17e718101f776bc184ecd6d905c5c8a99ca6aa0d3e97eadbd628301327c9ea09","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"17e718101f776bc184ecd6d905c5c8a99ca6aa0d3e97eadbd628301327c9ea09","first_computed_at":"2026-07-05T09:20:40.306438Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T09:20:40.306438Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"V7X9bl4UxVrT3cXdEh37Qmbg9M8Od5T9pj10ilEO9pTAPCPHUfFOnFm+NLyl49hGD1K46XZcjOwU6kF74clnCA==","signature_status":"signed_v1","signed_at":"2026-07-05T09:20:40.306932Z","signed_message":"canonical_sha256_bytes"},"source_id":"2402.11575","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:860457f00db27b9df1fb0d4bf2c1943cff32973796641d68299ca721f1f74303","sha256:8e48768d422088a4edeb5e41eb2e0e54092c4383a338b3024e2c611411bf5985"],"state_sha256":"c9b27a223f9d852ed68e5a1418371761f4631b8028a104a6fedda67da2b92831"}