{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2025:HX6XGDVVLHPODN2TQTTIWMQ7G7","short_pith_number":"pith:HX6XGDVV","canonical_record":{"source":{"id":"2506.14619","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2025-06-17T15:16:22Z","cross_cats_sorted":[],"title_canon_sha256":"123bfee9f43f56d34594c1117ec1f9b5c682b51299dd066f13a3090c28702a9c","abstract_canon_sha256":"1d892e071129de7d3bdee1e4d37de3063c98371856e70e4516144fef83b3b641"},"schema_version":"1.0"},"canonical_sha256":"3dfd730eb559dee1b75384e68b321f37f6711c9d9c44886e7f5fb1146266f0e3","source":{"kind":"arxiv","id":"2506.14619","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2506.14619","created_at":"2026-07-05T11:22:59Z"},{"alias_kind":"arxiv_version","alias_value":"2506.14619v1","created_at":"2026-07-05T11:22:59Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2506.14619","created_at":"2026-07-05T11:22:59Z"},{"alias_kind":"pith_short_12","alias_value":"HX6XGDVVLHPO","created_at":"2026-07-05T11:22:59Z"},{"alias_kind":"pith_short_16","alias_value":"HX6XGDVVLHPODN2T","created_at":"2026-07-05T11:22:59Z"},{"alias_kind":"pith_short_8","alias_value":"HX6XGDVV","created_at":"2026-07-05T11:22:59Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2025:HX6XGDVVLHPODN2TQTTIWMQ7G7","target":"record","payload":{"canonical_record":{"source":{"id":"2506.14619","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2025-06-17T15:16:22Z","cross_cats_sorted":[],"title_canon_sha256":"123bfee9f43f56d34594c1117ec1f9b5c682b51299dd066f13a3090c28702a9c","abstract_canon_sha256":"1d892e071129de7d3bdee1e4d37de3063c98371856e70e4516144fef83b3b641"},"schema_version":"1.0"},"canonical_sha256":"3dfd730eb559dee1b75384e68b321f37f6711c9d9c44886e7f5fb1146266f0e3","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T11:22:59.752386Z","signature_b64":"hXwL4SER+20VFNoHOwOcusl4xtgQfKe0Tctp+LHOqGNZvMI3DUyI3RCrFo5F52L/9tX9hXCG+gggnGNIpIKqDg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"3dfd730eb559dee1b75384e68b321f37f6711c9d9c44886e7f5fb1146266f0e3","last_reissued_at":"2026-07-05T11:22:59.751825Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T11:22:59.751825Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2506.14619","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":"2026-07-05T11:22:59Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"ngtEf8g20aQzyIygHdsgKiIMxdupHrYgXFNCsWIqxlkhii6m/TpBYw4KBmu4lQmYUN/LimS9E9zi30IbJd91Bg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-21T01:13:34.337964Z"},"content_sha256":"0f5808ec05c93ce3d1d11a63a86a91bac3f688be51d165a427e3f7a903d53576","schema_version":"1.0","event_id":"sha256:0f5808ec05c93ce3d1d11a63a86a91bac3f688be51d165a427e3f7a903d53576"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2025:HX6XGDVVLHPODN2TQTTIWMQ7G7","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Feasibility-Driven Trust Region Bayesian Optimization","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.LG","authors_text":"Elena Raponi, Fabian Duddeck, Paolo Ascia, Thomas B\\\"ack","submitted_at":"2025-06-17T15:16:22Z","abstract_excerpt":"Bayesian optimization is a powerful tool for solving real-world optimization tasks under tight evaluation budgets, making it well-suited for applications involving costly simulations or experiments. However, many of these tasks are also characterized by the presence of expensive constraints whose analytical formulation is unknown and often defined in high-dimensional spaces where feasible regions are small, irregular, and difficult to identify. In such cases, a substantial portion of the optimization budget may be spent just trying to locate the first feasible solution, limiting the effectiven"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2506.14619","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/2506.14619/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":"2026-07-05T11:22:59Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"3eZTbP7GEbJl7xAUEw+1MYbgIYrGNV8I5orxbwC6+TlX0fdJoyBojQGuqxroJvnf16T5df7zw5ywU8xz0cKhBQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-21T01:13:34.338514Z"},"content_sha256":"178c604191df575bbf132c307bacc13df90c4ea12cd3f6cfa8718f0f7902ee3c","schema_version":"1.0","event_id":"sha256:178c604191df575bbf132c307bacc13df90c4ea12cd3f6cfa8718f0f7902ee3c"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/HX6XGDVVLHPODN2TQTTIWMQ7G7/bundle.json","state_url":"https://pith.science/pith/HX6XGDVVLHPODN2TQTTIWMQ7G7/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/HX6XGDVVLHPODN2TQTTIWMQ7G7/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":"2026-08-21T01:13:34Z","links":{"resolver":"https://pith.science/pith/HX6XGDVVLHPODN2TQTTIWMQ7G7","bundle":"https://pith.science/pith/HX6XGDVVLHPODN2TQTTIWMQ7G7/bundle.json","state":"https://pith.science/pith/HX6XGDVVLHPODN2TQTTIWMQ7G7/state.json","well_known_bundle":"https://pith.science/.well-known/pith/HX6XGDVVLHPODN2TQTTIWMQ7G7/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:HX6XGDVVLHPODN2TQTTIWMQ7G7","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":"1d892e071129de7d3bdee1e4d37de3063c98371856e70e4516144fef83b3b641","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2025-06-17T15:16:22Z","title_canon_sha256":"123bfee9f43f56d34594c1117ec1f9b5c682b51299dd066f13a3090c28702a9c"},"schema_version":"1.0","source":{"id":"2506.14619","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2506.14619","created_at":"2026-07-05T11:22:59Z"},{"alias_kind":"arxiv_version","alias_value":"2506.14619v1","created_at":"2026-07-05T11:22:59Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2506.14619","created_at":"2026-07-05T11:22:59Z"},{"alias_kind":"pith_short_12","alias_value":"HX6XGDVVLHPO","created_at":"2026-07-05T11:22:59Z"},{"alias_kind":"pith_short_16","alias_value":"HX6XGDVVLHPODN2T","created_at":"2026-07-05T11:22:59Z"},{"alias_kind":"pith_short_8","alias_value":"HX6XGDVV","created_at":"2026-07-05T11:22:59Z"}],"graph_snapshots":[{"event_id":"sha256:178c604191df575bbf132c307bacc13df90c4ea12cd3f6cfa8718f0f7902ee3c","target":"graph","created_at":"2026-07-05T11:22:59Z","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/2506.14619/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Bayesian optimization is a powerful tool for solving real-world optimization tasks under tight evaluation budgets, making it well-suited for applications involving costly simulations or experiments. However, many of these tasks are also characterized by the presence of expensive constraints whose analytical formulation is unknown and often defined in high-dimensional spaces where feasible regions are small, irregular, and difficult to identify. In such cases, a substantial portion of the optimization budget may be spent just trying to locate the first feasible solution, limiting the effectiven","authors_text":"Elena Raponi, Fabian Duddeck, Paolo Ascia, Thomas B\\\"ack","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2025-06-17T15:16:22Z","title":"Feasibility-Driven Trust Region Bayesian Optimization"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2506.14619","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":"sha256:0f5808ec05c93ce3d1d11a63a86a91bac3f688be51d165a427e3f7a903d53576","target":"record","created_at":"2026-07-05T11:22:59Z","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":"1d892e071129de7d3bdee1e4d37de3063c98371856e70e4516144fef83b3b641","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2025-06-17T15:16:22Z","title_canon_sha256":"123bfee9f43f56d34594c1117ec1f9b5c682b51299dd066f13a3090c28702a9c"},"schema_version":"1.0","source":{"id":"2506.14619","kind":"arxiv","version":1}},"canonical_sha256":"3dfd730eb559dee1b75384e68b321f37f6711c9d9c44886e7f5fb1146266f0e3","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"3dfd730eb559dee1b75384e68b321f37f6711c9d9c44886e7f5fb1146266f0e3","first_computed_at":"2026-07-05T11:22:59.751825Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T11:22:59.751825Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"hXwL4SER+20VFNoHOwOcusl4xtgQfKe0Tctp+LHOqGNZvMI3DUyI3RCrFo5F52L/9tX9hXCG+gggnGNIpIKqDg==","signature_status":"signed_v1","signed_at":"2026-07-05T11:22:59.752386Z","signed_message":"canonical_sha256_bytes"},"source_id":"2506.14619","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:0f5808ec05c93ce3d1d11a63a86a91bac3f688be51d165a427e3f7a903d53576","sha256:178c604191df575bbf132c307bacc13df90c4ea12cd3f6cfa8718f0f7902ee3c"],"state_sha256":"13d2a00aae92f0ff806d7e7067ecddc602cf7a73aeda48f058945245fb8ede75"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"rr14vJBf6icm20UxAWmXXSl0zxw9yKjaZj7HGymDd92Gbw784IVRWP0cJ4OMgekaK5I7p0arcKh3wIfADEZdDQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-21T01:13:34.343340Z","bundle_sha256":"28cd4f401db1c6e0cd7ac24105227fddd864935bf027f8d5c6b281489fd67dbb"}}