{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2025:WMCH5PYDQDNLSPZ5PLVR4Z7VP7","short_pith_number":"pith:WMCH5PYD","canonical_record":{"source":{"id":"2504.18103","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"quant-ph","submitted_at":"2025-04-25T06:16:13Z","cross_cats_sorted":["cs.LG"],"title_canon_sha256":"b9c19f28c01312e016c8ca66d6f5da97f47998ed5fe925b35d2af984addc495b","abstract_canon_sha256":"00eecde46bbab34f1e0f2fe1cbcb55227d20e75e38a97591cbd62b519aaec5a8"},"schema_version":"1.0"},"canonical_sha256":"b3047ebf0380dab93f3d7aeb1e67f57ff5e5de4fa1580ab1f8dccf1be525eddd","source":{"kind":"arxiv","id":"2504.18103","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2504.18103","created_at":"2026-07-05T10:54:01Z"},{"alias_kind":"arxiv_version","alias_value":"2504.18103v1","created_at":"2026-07-05T10:54:01Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2504.18103","created_at":"2026-07-05T10:54:01Z"},{"alias_kind":"pith_short_12","alias_value":"WMCH5PYDQDNL","created_at":"2026-07-05T10:54:01Z"},{"alias_kind":"pith_short_16","alias_value":"WMCH5PYDQDNLSPZ5","created_at":"2026-07-05T10:54:01Z"},{"alias_kind":"pith_short_8","alias_value":"WMCH5PYD","created_at":"2026-07-05T10:54:01Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2025:WMCH5PYDQDNLSPZ5PLVR4Z7VP7","target":"record","payload":{"canonical_record":{"source":{"id":"2504.18103","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"quant-ph","submitted_at":"2025-04-25T06:16:13Z","cross_cats_sorted":["cs.LG"],"title_canon_sha256":"b9c19f28c01312e016c8ca66d6f5da97f47998ed5fe925b35d2af984addc495b","abstract_canon_sha256":"00eecde46bbab34f1e0f2fe1cbcb55227d20e75e38a97591cbd62b519aaec5a8"},"schema_version":"1.0"},"canonical_sha256":"b3047ebf0380dab93f3d7aeb1e67f57ff5e5de4fa1580ab1f8dccf1be525eddd","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T10:54:01.754813Z","signature_b64":"bhxMorgSsMYVhFPcH6iZGFUr94rU4tbzK+kLd534Z8Z+28fUrjgCqmy50U8e3DNcRjslhPve3kac3XPGKLQHAw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"b3047ebf0380dab93f3d7aeb1e67f57ff5e5de4fa1580ab1f8dccf1be525eddd","last_reissued_at":"2026-07-05T10:54:01.754321Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T10:54:01.754321Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2504.18103","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":"2026-07-05T10:54:01Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"9tlRrhc4NbWrL8XEmQHytTBHHuV4xXqla8Z/OeSsEehkEJguUfZbfIyjw9VhRkkW+Y5bidJhHZ8sXG0a1RkYCQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-18T19:31:54.810365Z"},"content_sha256":"89c954ba0274f0af673353ee3bc9f924db3b454c544a88e759601be2a391e939","schema_version":"1.0","event_id":"sha256:89c954ba0274f0af673353ee3bc9f924db3b454c544a88e759601be2a391e939"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2025:WMCH5PYDQDNLSPZ5PLVR4Z7VP7","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Bayesian Quantum Orthogonal Neural Networks for Anomaly Detection","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.LG"],"primary_cat":"quant-ph","authors_text":"Akshat Tandon, Brian Coyle, Jasper Simon Krauser, Natansh Mathur, Nishant Jain, Rainer Stoessel, Snehal Raj","submitted_at":"2025-04-25T06:16:13Z","abstract_excerpt":"Identification of defects or anomalies in 3D objects is a crucial task to ensure correct functionality. In this work, we combine Bayesian learning with recent developments in quantum and quantum-inspired machine learning, specifically orthogonal neural networks, to tackle this anomaly detection problem for an industrially relevant use case. Bayesian learning enables uncertainty quantification of predictions, while orthogonality in weight matrices enables smooth training. We develop orthogonal (quantum) versions of 3D convolutional neural networks and show that these models can successfully det"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2504.18103","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/2504.18103/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":"2026-07-05T10:54:01Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"fjrUlowoir+gcbxf7nWy3z3n8KrcSoMttwtSDVAVsMAOI7+ceZpBebjVMfn3XtgDIciyqNnHXIkQuUMjqwo+Bg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-18T19:31:54.810856Z"},"content_sha256":"1384c1f43407ee9b3ff797310c3c04e34610834d3d0593a97f28fc3825c24cf8","schema_version":"1.0","event_id":"sha256:1384c1f43407ee9b3ff797310c3c04e34610834d3d0593a97f28fc3825c24cf8"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/WMCH5PYDQDNLSPZ5PLVR4Z7VP7/bundle.json","state_url":"https://pith.science/pith/WMCH5PYDQDNLSPZ5PLVR4Z7VP7/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/WMCH5PYDQDNLSPZ5PLVR4Z7VP7/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":"2026-08-18T19:31:54Z","links":{"resolver":"https://pith.science/pith/WMCH5PYDQDNLSPZ5PLVR4Z7VP7","bundle":"https://pith.science/pith/WMCH5PYDQDNLSPZ5PLVR4Z7VP7/bundle.json","state":"https://pith.science/pith/WMCH5PYDQDNLSPZ5PLVR4Z7VP7/state.json","well_known_bundle":"https://pith.science/.well-known/pith/WMCH5PYDQDNLSPZ5PLVR4Z7VP7/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:WMCH5PYDQDNLSPZ5PLVR4Z7VP7","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":"00eecde46bbab34f1e0f2fe1cbcb55227d20e75e38a97591cbd62b519aaec5a8","cross_cats_sorted":["cs.LG"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"quant-ph","submitted_at":"2025-04-25T06:16:13Z","title_canon_sha256":"b9c19f28c01312e016c8ca66d6f5da97f47998ed5fe925b35d2af984addc495b"},"schema_version":"1.0","source":{"id":"2504.18103","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2504.18103","created_at":"2026-07-05T10:54:01Z"},{"alias_kind":"arxiv_version","alias_value":"2504.18103v1","created_at":"2026-07-05T10:54:01Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2504.18103","created_at":"2026-07-05T10:54:01Z"},{"alias_kind":"pith_short_12","alias_value":"WMCH5PYDQDNL","created_at":"2026-07-05T10:54:01Z"},{"alias_kind":"pith_short_16","alias_value":"WMCH5PYDQDNLSPZ5","created_at":"2026-07-05T10:54:01Z"},{"alias_kind":"pith_short_8","alias_value":"WMCH5PYD","created_at":"2026-07-05T10:54:01Z"}],"graph_snapshots":[{"event_id":"sha256:1384c1f43407ee9b3ff797310c3c04e34610834d3d0593a97f28fc3825c24cf8","target":"graph","created_at":"2026-07-05T10:54:01Z","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/2504.18103/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Identification of defects or anomalies in 3D objects is a crucial task to ensure correct functionality. In this work, we combine Bayesian learning with recent developments in quantum and quantum-inspired machine learning, specifically orthogonal neural networks, to tackle this anomaly detection problem for an industrially relevant use case. Bayesian learning enables uncertainty quantification of predictions, while orthogonality in weight matrices enables smooth training. We develop orthogonal (quantum) versions of 3D convolutional neural networks and show that these models can successfully det","authors_text":"Akshat Tandon, Brian Coyle, Jasper Simon Krauser, Natansh Mathur, Nishant Jain, Rainer Stoessel, Snehal Raj","cross_cats":["cs.LG"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"quant-ph","submitted_at":"2025-04-25T06:16:13Z","title":"Bayesian Quantum Orthogonal Neural Networks for Anomaly Detection"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2504.18103","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":"sha256:89c954ba0274f0af673353ee3bc9f924db3b454c544a88e759601be2a391e939","target":"record","created_at":"2026-07-05T10:54:01Z","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":"00eecde46bbab34f1e0f2fe1cbcb55227d20e75e38a97591cbd62b519aaec5a8","cross_cats_sorted":["cs.LG"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"quant-ph","submitted_at":"2025-04-25T06:16:13Z","title_canon_sha256":"b9c19f28c01312e016c8ca66d6f5da97f47998ed5fe925b35d2af984addc495b"},"schema_version":"1.0","source":{"id":"2504.18103","kind":"arxiv","version":1}},"canonical_sha256":"b3047ebf0380dab93f3d7aeb1e67f57ff5e5de4fa1580ab1f8dccf1be525eddd","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"b3047ebf0380dab93f3d7aeb1e67f57ff5e5de4fa1580ab1f8dccf1be525eddd","first_computed_at":"2026-07-05T10:54:01.754321Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T10:54:01.754321Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"bhxMorgSsMYVhFPcH6iZGFUr94rU4tbzK+kLd534Z8Z+28fUrjgCqmy50U8e3DNcRjslhPve3kac3XPGKLQHAw==","signature_status":"signed_v1","signed_at":"2026-07-05T10:54:01.754813Z","signed_message":"canonical_sha256_bytes"},"source_id":"2504.18103","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:89c954ba0274f0af673353ee3bc9f924db3b454c544a88e759601be2a391e939","sha256:1384c1f43407ee9b3ff797310c3c04e34610834d3d0593a97f28fc3825c24cf8"],"state_sha256":"8a39a1069c8aadcbbfa38056d26cf62b9c26300ce79a7ccf5fa1f2b1fa689099"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"+fPbcr8Cf+yIPGmROg3+cXnCWY6Uh0WPpdgqXbG/VmlBrGrARulfYds78Gg5bohAtfJ+PxnRpFuNKtsdyAvcAA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-18T19:31:54.814367Z","bundle_sha256":"253133e273fa2b28b4d20f122d2200b6c938363b3022fa2e082e7fcb1fddc12e"}}