{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2023:2KT4AXW2VY3PI2UFF44PNKAICG","short_pith_number":"pith:2KT4AXW2","canonical_record":{"source":{"id":"2308.12339","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"physics.ins-det","submitted_at":"2023-08-23T18:00:02Z","cross_cats_sorted":["hep-ex","hep-ph"],"title_canon_sha256":"fb912b29eca956e794857ce075f6c5864f223f62f77d304d79f009f27b00cf4f","abstract_canon_sha256":"f43370ddd94d3f14e59386f361240d3a752f099ce4e27c9dd5ec545e69bd8fe2"},"schema_version":"1.0"},"canonical_sha256":"d2a7c05edaae36f46a852f38f6a80811b153ee6e5c804ff45e4eccbb6e09076b","source":{"kind":"arxiv","id":"2308.12339","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2308.12339","created_at":"2026-07-05T10:39:44Z"},{"alias_kind":"arxiv_version","alias_value":"2308.12339v2","created_at":"2026-07-05T10:39:44Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2308.12339","created_at":"2026-07-05T10:39:44Z"},{"alias_kind":"pith_short_12","alias_value":"2KT4AXW2VY3P","created_at":"2026-07-05T10:39:44Z"},{"alias_kind":"pith_short_16","alias_value":"2KT4AXW2VY3PI2UF","created_at":"2026-07-05T10:39:44Z"},{"alias_kind":"pith_short_8","alias_value":"2KT4AXW2","created_at":"2026-07-05T10:39:44Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2023:2KT4AXW2VY3PI2UFF44PNKAICG","target":"record","payload":{"canonical_record":{"source":{"id":"2308.12339","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"physics.ins-det","submitted_at":"2023-08-23T18:00:02Z","cross_cats_sorted":["hep-ex","hep-ph"],"title_canon_sha256":"fb912b29eca956e794857ce075f6c5864f223f62f77d304d79f009f27b00cf4f","abstract_canon_sha256":"f43370ddd94d3f14e59386f361240d3a752f099ce4e27c9dd5ec545e69bd8fe2"},"schema_version":"1.0"},"canonical_sha256":"d2a7c05edaae36f46a852f38f6a80811b153ee6e5c804ff45e4eccbb6e09076b","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T10:39:44.998337Z","signature_b64":"QKsbqlXbIVWaf3YWqP8rrpxYLvINnWvkeaGiFftU3+UuxXJQphmLE50iDmIfrLwsFR0yNvA1f834XQ7a7NwXBA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"d2a7c05edaae36f46a852f38f6a80811b153ee6e5c804ff45e4eccbb6e09076b","last_reissued_at":"2026-07-05T10:39:44.997850Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T10:39:44.997850Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2308.12339","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":"2026-07-05T10:39:44Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"sS+OoD1LKBx7eYgPRFcFIdw5OAFaiXi+tpAKMGWO+fI8khSiBQCJi0vwVbUB8OkMH0NtZkZdi62QJQPrUMVHCg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-03T08:37:47.187896Z"},"content_sha256":"cc1296f2262b72eb92e8307da907f7ea8e1657baff7ee430a3bd61bfbbd08472","schema_version":"1.0","event_id":"sha256:cc1296f2262b72eb92e8307da907f7ea8e1657baff7ee430a3bd61bfbbd08472"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2023:2KT4AXW2VY3PI2UFF44PNKAICG","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Refining Fast Calorimeter Simulations with a Schr\\\"{o}dinger Bridge","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["hep-ex","hep-ph"],"primary_cat":"physics.ins-det","authors_text":"Benjamin Nachman, Sascha Diefenbacher, Vinicius Mikuni","submitted_at":"2023-08-23T18:00:02Z","abstract_excerpt":"Machine learning-based simulations, especially calorimeter simulations, are promising tools for approximating the precision of classical high energy physics simulations with a fraction of the generation time. Nearly all methods proposed so far learn neural networks that map a random variable with a known probability density, like a Gaussian, to realistic-looking events. In many cases, physics events are not close to Gaussian and so these neural networks have to learn a highly complex function. We study an alternative approach: Schr\\\"{o}dinger bridge Quality Improvement via Refinement of Existi"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2308.12339","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/2308.12339/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":"2026-07-05T10:39:44Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"wKhXKPc7R2+/mQ2nnQNFR7C9RNgQf5EM65oglE7Yqv5Wn7VH+YTmkEjq/MDluta+ZnnS1pF+cZMrLRo+CILFCg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-03T08:37:47.188779Z"},"content_sha256":"f31afacdc9f6830423d67a2d873ddaf22a9d6e4e591043efb994a0ce4675a5e1","schema_version":"1.0","event_id":"sha256:f31afacdc9f6830423d67a2d873ddaf22a9d6e4e591043efb994a0ce4675a5e1"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/2KT4AXW2VY3PI2UFF44PNKAICG/bundle.json","state_url":"https://pith.science/pith/2KT4AXW2VY3PI2UFF44PNKAICG/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/2KT4AXW2VY3PI2UFF44PNKAICG/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":"2026-08-03T08:37:47Z","links":{"resolver":"https://pith.science/pith/2KT4AXW2VY3PI2UFF44PNKAICG","bundle":"https://pith.science/pith/2KT4AXW2VY3PI2UFF44PNKAICG/bundle.json","state":"https://pith.science/pith/2KT4AXW2VY3PI2UFF44PNKAICG/state.json","well_known_bundle":"https://pith.science/.well-known/pith/2KT4AXW2VY3PI2UFF44PNKAICG/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2023:2KT4AXW2VY3PI2UFF44PNKAICG","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":"f43370ddd94d3f14e59386f361240d3a752f099ce4e27c9dd5ec545e69bd8fe2","cross_cats_sorted":["hep-ex","hep-ph"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"physics.ins-det","submitted_at":"2023-08-23T18:00:02Z","title_canon_sha256":"fb912b29eca956e794857ce075f6c5864f223f62f77d304d79f009f27b00cf4f"},"schema_version":"1.0","source":{"id":"2308.12339","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2308.12339","created_at":"2026-07-05T10:39:44Z"},{"alias_kind":"arxiv_version","alias_value":"2308.12339v2","created_at":"2026-07-05T10:39:44Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2308.12339","created_at":"2026-07-05T10:39:44Z"},{"alias_kind":"pith_short_12","alias_value":"2KT4AXW2VY3P","created_at":"2026-07-05T10:39:44Z"},{"alias_kind":"pith_short_16","alias_value":"2KT4AXW2VY3PI2UF","created_at":"2026-07-05T10:39:44Z"},{"alias_kind":"pith_short_8","alias_value":"2KT4AXW2","created_at":"2026-07-05T10:39:44Z"}],"graph_snapshots":[{"event_id":"sha256:f31afacdc9f6830423d67a2d873ddaf22a9d6e4e591043efb994a0ce4675a5e1","target":"graph","created_at":"2026-07-05T10:39:44Z","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/2308.12339/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Machine learning-based simulations, especially calorimeter simulations, are promising tools for approximating the precision of classical high energy physics simulations with a fraction of the generation time. Nearly all methods proposed so far learn neural networks that map a random variable with a known probability density, like a Gaussian, to realistic-looking events. In many cases, physics events are not close to Gaussian and so these neural networks have to learn a highly complex function. We study an alternative approach: Schr\\\"{o}dinger bridge Quality Improvement via Refinement of Existi","authors_text":"Benjamin Nachman, Sascha Diefenbacher, Vinicius Mikuni","cross_cats":["hep-ex","hep-ph"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"physics.ins-det","submitted_at":"2023-08-23T18:00:02Z","title":"Refining Fast Calorimeter Simulations with a Schr\\\"{o}dinger Bridge"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2308.12339","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:cc1296f2262b72eb92e8307da907f7ea8e1657baff7ee430a3bd61bfbbd08472","target":"record","created_at":"2026-07-05T10:39:44Z","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":"f43370ddd94d3f14e59386f361240d3a752f099ce4e27c9dd5ec545e69bd8fe2","cross_cats_sorted":["hep-ex","hep-ph"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"physics.ins-det","submitted_at":"2023-08-23T18:00:02Z","title_canon_sha256":"fb912b29eca956e794857ce075f6c5864f223f62f77d304d79f009f27b00cf4f"},"schema_version":"1.0","source":{"id":"2308.12339","kind":"arxiv","version":2}},"canonical_sha256":"d2a7c05edaae36f46a852f38f6a80811b153ee6e5c804ff45e4eccbb6e09076b","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"d2a7c05edaae36f46a852f38f6a80811b153ee6e5c804ff45e4eccbb6e09076b","first_computed_at":"2026-07-05T10:39:44.997850Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T10:39:44.997850Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"QKsbqlXbIVWaf3YWqP8rrpxYLvINnWvkeaGiFftU3+UuxXJQphmLE50iDmIfrLwsFR0yNvA1f834XQ7a7NwXBA==","signature_status":"signed_v1","signed_at":"2026-07-05T10:39:44.998337Z","signed_message":"canonical_sha256_bytes"},"source_id":"2308.12339","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:cc1296f2262b72eb92e8307da907f7ea8e1657baff7ee430a3bd61bfbbd08472","sha256:f31afacdc9f6830423d67a2d873ddaf22a9d6e4e591043efb994a0ce4675a5e1"],"state_sha256":"7e7a520562e18622839bbbe55015052b1e4bb5eb2a34df5b6fcf6d4731e459a8"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"9+zWUX6mjeARKlv4fAp5RRM4J1PZdbakdaGDevpCPayXPytdqndbI9iNHU9L0juTxKHGYq3eLTBMltlu/iV/DQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-03T08:37:47.195441Z","bundle_sha256":"ee8880ce21dd920d935db74f872b0d522344d3772f1751d1a2eb706e94297c02"}}