{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2026:G4QDRWU4Y6MMA2TUFAPF7AFTBW","short_pith_number":"pith:G4QDRWU4","canonical_record":{"source":{"id":"2608.06131","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"math.NA","submitted_at":"2026-08-06T15:05:43Z","cross_cats_sorted":["cs.NA"],"title_canon_sha256":"a6fc64d9f1439a8a63036aadacb4bf758d13d47e2dc2500a0c22d4fb85ea2bed","abstract_canon_sha256":"3f4b6013a41a586e57ed53e796b5c8fca9c2e26a17619b4a8dcc646d3eab982e"},"schema_version":"1.0"},"canonical_sha256":"372038da9cc798c06a74281e5f80b30d840d97b715005a08d7a50a23ecac9fa0","source":{"kind":"arxiv","id":"2608.06131","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2608.06131","created_at":"2026-08-07T01:40:36Z"},{"alias_kind":"arxiv_version","alias_value":"2608.06131v1","created_at":"2026-08-07T01:40:36Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2608.06131","created_at":"2026-08-07T01:40:36Z"},{"alias_kind":"pith_short_12","alias_value":"G4QDRWU4Y6MM","created_at":"2026-08-07T01:40:36Z"},{"alias_kind":"pith_short_16","alias_value":"G4QDRWU4Y6MMA2TU","created_at":"2026-08-07T01:40:36Z"},{"alias_kind":"pith_short_8","alias_value":"G4QDRWU4","created_at":"2026-08-07T01:40:36Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2026:G4QDRWU4Y6MMA2TUFAPF7AFTBW","target":"record","payload":{"canonical_record":{"source":{"id":"2608.06131","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"math.NA","submitted_at":"2026-08-06T15:05:43Z","cross_cats_sorted":["cs.NA"],"title_canon_sha256":"a6fc64d9f1439a8a63036aadacb4bf758d13d47e2dc2500a0c22d4fb85ea2bed","abstract_canon_sha256":"3f4b6013a41a586e57ed53e796b5c8fca9c2e26a17619b4a8dcc646d3eab982e"},"schema_version":"1.0"},"canonical_sha256":"372038da9cc798c06a74281e5f80b30d840d97b715005a08d7a50a23ecac9fa0","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-08-07T01:40:36.581743Z","signature_b64":"XSZ6/wLuS9Jz2mJOL+Pu5FJvFO7CkN4t9d2H3gQGIoD/zE6i8WVg1Qk0g7eZ7SkA3LJm/UNgh3j66hG7LOSTDw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"372038da9cc798c06a74281e5f80b30d840d97b715005a08d7a50a23ecac9fa0","last_reissued_at":"2026-08-07T01:40:36.579983Z","signature_status":"signed_v1","first_computed_at":"2026-08-07T01:40:36.579983Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2608.06131","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":"2026-08-07T01:40:36Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"deW7/BY1HGe853mbW4Lq8OPCz0YBnMSQBDS63Il0/vy8nKflp1l+zMLFBvwj7FCNCagq/jA7HYaGh35F2H0xBg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-09T03:25:28.161719Z"},"content_sha256":"48c6e8c4349a42c644ab9d73f795e78cde450a742e75423193490e775452283c","schema_version":"1.0","event_id":"sha256:48c6e8c4349a42c644ab9d73f795e78cde450a742e75423193490e775452283c"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2026:G4QDRWU4Y6MMA2TUFAPF7AFTBW","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"ChromOps.jl: High-order simulation and discrete forward sensitivity analysis for chromatography models","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.NA"],"primary_cat":"math.NA","authors_text":"Christopher Rackauckas, Kristian Meyer, Maksym Ratajczyk","submitted_at":"2026-08-06T15:05:43Z","abstract_excerpt":"Mechanistic chromatography models are valuable for process development, but gradient-based parameter estimation and optimization can be hindered by computational cost and the effort of deriving objective-function gradients. To address this concern, a fully differentiable Julia chromatography solver, ChromOps.jl, is presented that combines high-order spatial discretization with discrete forward sensitivity analysis (DFSA). Two high-order spatial discretizations, finite difference summation-by-parts (FD-SBP) and the discontinuous Galerkin spectral element method (DG-SEM), are compared on a 6-com"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2608.06131","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/2608.06131/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":"2026-08-07T01:40:36Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"xbE+uHm/de1u1ujjRANZT+0In83q62Bh/P6itSrpWOvpOWSzOeXivalfIE590knkh+WOupri7/Qp7Wgac660Dg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-09T03:25:28.162246Z"},"content_sha256":"2e93c316127a2bd15e233ffcbd1ce764b62e59ce69d017e620719a5a1d46d961","schema_version":"1.0","event_id":"sha256:2e93c316127a2bd15e233ffcbd1ce764b62e59ce69d017e620719a5a1d46d961"},{"event_type":"integrity_finding","subject_pith_number":"pith:2026:G4QDRWU4Y6MMA2TUFAPF7AFTBW","target":"integrity","payload":{"note":"Identifier '10.1016/j.future.2003' is syntactically valid but the DOI registry (doi.org) returned 404, and Crossref / OpenAlex / internal corpus also have no record. The cited work could not be located through any authoritative source.","snippet":"Solving unsymmetric sparse systems of linear equations with pardiso. Future Gener. Comput. Syst. 20, 475–487. URL:https://doi.org/10.1016/j.future.2003. 07.011. Schenk, O., Gärtner, K.,","arxiv_id":"2608.06131","detector":"doi_compliance","evidence":{"doi":"10.1016/j.future.2003","arxiv_id":null,"ref_index":32,"raw_excerpt":"Solving unsymmetric sparse systems of linear equations with pardiso. Future Gener. Comput. Syst. 20, 475–487. URL:https://doi.org/10.1016/j.future.2003. 07.011. Schenk, O., Gärtner, K.,","parse_status":"well_formed","verdict_class":"cross_source","checked_sources":["crossref_by_doi","openalex_by_doi","doi_org_head"],"resolution_status":"hard_miss"},"severity":"critical","ref_index":32,"audited_at":"2026-08-07T14:28:15.570201Z","event_type":"pith.integrity.v1","detected_doi":"10.1016/j.future.2003","detector_url":"https://pith.science/pith-integrity-protocol#doi_compliance","external_url":null,"finding_type":"unresolvable_identifier","evidence_hash":"61beda8006253e214250a2430ef26dbc69e4aed1e27a97e3441cde0fdfa3d9bb","paper_version":1,"verdict_class":"cross_source","resolved_title":null,"detector_version":"1.1.0","detected_arxiv_id":null,"integrity_event_id":18482,"payload_sha256":"c23eeda851d4089c37db41fb535198fa4733930f439664fc08e77d32e478a632","signature_b64":"4UUATk1krwSVOJG46CwYEQ5NRXyfGx1kjTCSZp8O9F1x4VLj6ydYVNjT8xZVZMihpWSp4Fx7GFwhxqZKWaPMCw==","signing_key_id":"pith-v1-2026-05"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-08-07T14:28:29Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"v01RiMIpl+qJU0xJcQu6MVSnrDWwwuF8cDz9du3+MNkwswY0+bhHqCVc8DDkEVKUvz3Ys5lmYEGv5HuJAyjDBA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-09T03:25:28.166263Z"},"content_sha256":"9c0b0e84bd7ad0419cdc2fb67c2d0252966fc1d9c7ed00cbca9408de52453bfb","schema_version":"1.0","event_id":"sha256:9c0b0e84bd7ad0419cdc2fb67c2d0252966fc1d9c7ed00cbca9408de52453bfb"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/G4QDRWU4Y6MMA2TUFAPF7AFTBW/bundle.json","state_url":"https://pith.science/pith/G4QDRWU4Y6MMA2TUFAPF7AFTBW/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/G4QDRWU4Y6MMA2TUFAPF7AFTBW/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":"2026-08-09T03:25:28Z","links":{"resolver":"https://pith.science/pith/G4QDRWU4Y6MMA2TUFAPF7AFTBW","bundle":"https://pith.science/pith/G4QDRWU4Y6MMA2TUFAPF7AFTBW/bundle.json","state":"https://pith.science/pith/G4QDRWU4Y6MMA2TUFAPF7AFTBW/state.json","well_known_bundle":"https://pith.science/.well-known/pith/G4QDRWU4Y6MMA2TUFAPF7AFTBW/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2026:G4QDRWU4Y6MMA2TUFAPF7AFTBW","merge_version":"pith-open-graph-merge-v1","event_count":3,"valid_event_count":3,"invalid_event_count":0,"equivocation_count":0,"current":{"canonical_record":{"metadata":{"abstract_canon_sha256":"3f4b6013a41a586e57ed53e796b5c8fca9c2e26a17619b4a8dcc646d3eab982e","cross_cats_sorted":["cs.NA"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"math.NA","submitted_at":"2026-08-06T15:05:43Z","title_canon_sha256":"a6fc64d9f1439a8a63036aadacb4bf758d13d47e2dc2500a0c22d4fb85ea2bed"},"schema_version":"1.0","source":{"id":"2608.06131","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2608.06131","created_at":"2026-08-07T01:40:36Z"},{"alias_kind":"arxiv_version","alias_value":"2608.06131v1","created_at":"2026-08-07T01:40:36Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2608.06131","created_at":"2026-08-07T01:40:36Z"},{"alias_kind":"pith_short_12","alias_value":"G4QDRWU4Y6MM","created_at":"2026-08-07T01:40:36Z"},{"alias_kind":"pith_short_16","alias_value":"G4QDRWU4Y6MMA2TU","created_at":"2026-08-07T01:40:36Z"},{"alias_kind":"pith_short_8","alias_value":"G4QDRWU4","created_at":"2026-08-07T01:40:36Z"}],"graph_snapshots":[{"event_id":"sha256:2e93c316127a2bd15e233ffcbd1ce764b62e59ce69d017e620719a5a1d46d961","target":"graph","created_at":"2026-08-07T01:40:36Z","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/2608.06131/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Mechanistic chromatography models are valuable for process development, but gradient-based parameter estimation and optimization can be hindered by computational cost and the effort of deriving objective-function gradients. To address this concern, a fully differentiable Julia chromatography solver, ChromOps.jl, is presented that combines high-order spatial discretization with discrete forward sensitivity analysis (DFSA). Two high-order spatial discretizations, finite difference summation-by-parts (FD-SBP) and the discontinuous Galerkin spectral element method (DG-SEM), are compared on a 6-com","authors_text":"Christopher Rackauckas, Kristian Meyer, Maksym Ratajczyk","cross_cats":["cs.NA"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"math.NA","submitted_at":"2026-08-06T15:05:43Z","title":"ChromOps.jl: High-order simulation and discrete forward sensitivity analysis for chromatography models"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2608.06131","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":"sha256:48c6e8c4349a42c644ab9d73f795e78cde450a742e75423193490e775452283c","target":"record","created_at":"2026-08-07T01:40:36Z","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":"3f4b6013a41a586e57ed53e796b5c8fca9c2e26a17619b4a8dcc646d3eab982e","cross_cats_sorted":["cs.NA"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"math.NA","submitted_at":"2026-08-06T15:05:43Z","title_canon_sha256":"a6fc64d9f1439a8a63036aadacb4bf758d13d47e2dc2500a0c22d4fb85ea2bed"},"schema_version":"1.0","source":{"id":"2608.06131","kind":"arxiv","version":1}},"canonical_sha256":"372038da9cc798c06a74281e5f80b30d840d97b715005a08d7a50a23ecac9fa0","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"372038da9cc798c06a74281e5f80b30d840d97b715005a08d7a50a23ecac9fa0","first_computed_at":"2026-08-07T01:40:36.579983Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-08-07T01:40:36.579983Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"XSZ6/wLuS9Jz2mJOL+Pu5FJvFO7CkN4t9d2H3gQGIoD/zE6i8WVg1Qk0g7eZ7SkA3LJm/UNgh3j66hG7LOSTDw==","signature_status":"signed_v1","signed_at":"2026-08-07T01:40:36.581743Z","signed_message":"canonical_sha256_bytes"},"source_id":"2608.06131","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:48c6e8c4349a42c644ab9d73f795e78cde450a742e75423193490e775452283c","sha256:2e93c316127a2bd15e233ffcbd1ce764b62e59ce69d017e620719a5a1d46d961","sha256:9c0b0e84bd7ad0419cdc2fb67c2d0252966fc1d9c7ed00cbca9408de52453bfb"],"state_sha256":"054c6587244d322d880ff7a0a81225fb401a08b607b520c3b4180585d4ffe816"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"pDO+L4BVHFC3QKzH+K465LUa61w0K+UP2v6TChLjj76ABbvPhyoXNHzs6VCGW6E0sLB/uYzo6Lc5psXbvHYuBQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-09T03:25:28.168632Z","bundle_sha256":"49d9bb7a3d857f312592d3fd8f726bedf37f0671a82cd2266d776340dafeff14"}}