{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2025:ZD2Q6TV7WRDSAW4NQDU4G4JMF5","short_pith_number":"pith:ZD2Q6TV7","canonical_record":{"source":{"id":"2502.05735","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"eess.SY","submitted_at":"2025-02-09T01:05:58Z","cross_cats_sorted":["cs.CE","cs.LG","cs.SY","math.OC","stat.ML"],"title_canon_sha256":"798dc5f6cb4a4aacfa6644f6f50f995abd54823ba0a261cf73a61a52d92a3662","abstract_canon_sha256":"4bf0cb509d39f28fa6a986651cbfa096ffd01cb70a5b5859bca0f6084b78b6e6"},"schema_version":"1.0"},"canonical_sha256":"c8f50f4ebfb447205b8d80e9c3712c2f77dab536a6cdaef89efd8ccbfc94cdf8","source":{"kind":"arxiv","id":"2502.05735","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2502.05735","created_at":"2026-07-05T10:11:42Z"},{"alias_kind":"arxiv_version","alias_value":"2502.05735v1","created_at":"2026-07-05T10:11:42Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2502.05735","created_at":"2026-07-05T10:11:42Z"},{"alias_kind":"pith_short_12","alias_value":"ZD2Q6TV7WRDS","created_at":"2026-07-05T10:11:42Z"},{"alias_kind":"pith_short_16","alias_value":"ZD2Q6TV7WRDSAW4N","created_at":"2026-07-05T10:11:42Z"},{"alias_kind":"pith_short_8","alias_value":"ZD2Q6TV7","created_at":"2026-07-05T10:11:42Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2025:ZD2Q6TV7WRDSAW4NQDU4G4JMF5","target":"record","payload":{"canonical_record":{"source":{"id":"2502.05735","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"eess.SY","submitted_at":"2025-02-09T01:05:58Z","cross_cats_sorted":["cs.CE","cs.LG","cs.SY","math.OC","stat.ML"],"title_canon_sha256":"798dc5f6cb4a4aacfa6644f6f50f995abd54823ba0a261cf73a61a52d92a3662","abstract_canon_sha256":"4bf0cb509d39f28fa6a986651cbfa096ffd01cb70a5b5859bca0f6084b78b6e6"},"schema_version":"1.0"},"canonical_sha256":"c8f50f4ebfb447205b8d80e9c3712c2f77dab536a6cdaef89efd8ccbfc94cdf8","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T10:11:42.703267Z","signature_b64":"+QSmexp045SUwYm1mukE1HBoqhNmq4EF/0TQLOGJ2K7NHzoFlsI3rk7/xt0I/00ZsXifRCIKNjdc0AKZnOmpDQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"c8f50f4ebfb447205b8d80e9c3712c2f77dab536a6cdaef89efd8ccbfc94cdf8","last_reissued_at":"2026-07-05T10:11:42.702804Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T10:11:42.702804Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2502.05735","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":"2026-07-05T10:11:42Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"icp2M3S9jUtPaxgS6P9tifhKe74p/UyQJr5geBp5lYWQqsiE88oaSu6rxNHGNybO+WVWWaS9EZkCOXlIUXdlDg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-10T18:22:51.675682Z"},"content_sha256":"d7898bf03785bec86d45712b785c92ab7934ae3deab6542bd414436980f074f3","schema_version":"1.0","event_id":"sha256:d7898bf03785bec86d45712b785c92ab7934ae3deab6542bd414436980f074f3"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2025:ZD2Q6TV7WRDSAW4NQDU4G4JMF5","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Towards Autonomous Experimentation: Bayesian Optimization over Problem Formulation Space for Accelerated Alloy Development","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.CE","cs.LG","cs.SY","math.OC","stat.ML"],"primary_cat":"eess.SY","authors_text":"Brent Vela, Danial Khatamsaz, Douglas L. Allaire, Joseph Wagner, Raymundo Arroyave","submitted_at":"2025-02-09T01:05:58Z","abstract_excerpt":"Accelerated discovery in materials science demands autonomous systems capable of dynamically formulating and solving design problems. In this work, we introduce a novel framework that leverages Bayesian optimization over a problem formulation space to identify optimal design formulations in line with decision-maker preferences. By mapping various design scenarios to a multi attribute utility function, our approach enables the system to balance conflicting objectives such as ductility, yield strength, density, and solidification range without requiring an exact problem definition at the outset."},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2502.05735","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/2502.05735/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":"2026-07-05T10:11:42Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"iWVz41PGZaE1zqY//MYiWVFuiFh731uH22FgNDrQkdox8aFEdx0mitQARcBDZhcA/UqrVW+53O2/ePELXXFWAA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-10T18:22:51.676587Z"},"content_sha256":"f998836ea494d08fb073fcb4aff6f1668c60b9b164c73fa719131ba39c1e6494","schema_version":"1.0","event_id":"sha256:f998836ea494d08fb073fcb4aff6f1668c60b9b164c73fa719131ba39c1e6494"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/ZD2Q6TV7WRDSAW4NQDU4G4JMF5/bundle.json","state_url":"https://pith.science/pith/ZD2Q6TV7WRDSAW4NQDU4G4JMF5/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/ZD2Q6TV7WRDSAW4NQDU4G4JMF5/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":"2026-08-10T18:22:51Z","links":{"resolver":"https://pith.science/pith/ZD2Q6TV7WRDSAW4NQDU4G4JMF5","bundle":"https://pith.science/pith/ZD2Q6TV7WRDSAW4NQDU4G4JMF5/bundle.json","state":"https://pith.science/pith/ZD2Q6TV7WRDSAW4NQDU4G4JMF5/state.json","well_known_bundle":"https://pith.science/.well-known/pith/ZD2Q6TV7WRDSAW4NQDU4G4JMF5/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:ZD2Q6TV7WRDSAW4NQDU4G4JMF5","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":"4bf0cb509d39f28fa6a986651cbfa096ffd01cb70a5b5859bca0f6084b78b6e6","cross_cats_sorted":["cs.CE","cs.LG","cs.SY","math.OC","stat.ML"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"eess.SY","submitted_at":"2025-02-09T01:05:58Z","title_canon_sha256":"798dc5f6cb4a4aacfa6644f6f50f995abd54823ba0a261cf73a61a52d92a3662"},"schema_version":"1.0","source":{"id":"2502.05735","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2502.05735","created_at":"2026-07-05T10:11:42Z"},{"alias_kind":"arxiv_version","alias_value":"2502.05735v1","created_at":"2026-07-05T10:11:42Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2502.05735","created_at":"2026-07-05T10:11:42Z"},{"alias_kind":"pith_short_12","alias_value":"ZD2Q6TV7WRDS","created_at":"2026-07-05T10:11:42Z"},{"alias_kind":"pith_short_16","alias_value":"ZD2Q6TV7WRDSAW4N","created_at":"2026-07-05T10:11:42Z"},{"alias_kind":"pith_short_8","alias_value":"ZD2Q6TV7","created_at":"2026-07-05T10:11:42Z"}],"graph_snapshots":[{"event_id":"sha256:f998836ea494d08fb073fcb4aff6f1668c60b9b164c73fa719131ba39c1e6494","target":"graph","created_at":"2026-07-05T10:11:42Z","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/2502.05735/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Accelerated discovery in materials science demands autonomous systems capable of dynamically formulating and solving design problems. In this work, we introduce a novel framework that leverages Bayesian optimization over a problem formulation space to identify optimal design formulations in line with decision-maker preferences. By mapping various design scenarios to a multi attribute utility function, our approach enables the system to balance conflicting objectives such as ductility, yield strength, density, and solidification range without requiring an exact problem definition at the outset.","authors_text":"Brent Vela, Danial Khatamsaz, Douglas L. Allaire, Joseph Wagner, Raymundo Arroyave","cross_cats":["cs.CE","cs.LG","cs.SY","math.OC","stat.ML"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"eess.SY","submitted_at":"2025-02-09T01:05:58Z","title":"Towards Autonomous Experimentation: Bayesian Optimization over Problem Formulation Space for Accelerated Alloy Development"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2502.05735","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:d7898bf03785bec86d45712b785c92ab7934ae3deab6542bd414436980f074f3","target":"record","created_at":"2026-07-05T10:11:42Z","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":"4bf0cb509d39f28fa6a986651cbfa096ffd01cb70a5b5859bca0f6084b78b6e6","cross_cats_sorted":["cs.CE","cs.LG","cs.SY","math.OC","stat.ML"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"eess.SY","submitted_at":"2025-02-09T01:05:58Z","title_canon_sha256":"798dc5f6cb4a4aacfa6644f6f50f995abd54823ba0a261cf73a61a52d92a3662"},"schema_version":"1.0","source":{"id":"2502.05735","kind":"arxiv","version":1}},"canonical_sha256":"c8f50f4ebfb447205b8d80e9c3712c2f77dab536a6cdaef89efd8ccbfc94cdf8","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"c8f50f4ebfb447205b8d80e9c3712c2f77dab536a6cdaef89efd8ccbfc94cdf8","first_computed_at":"2026-07-05T10:11:42.702804Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T10:11:42.702804Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"+QSmexp045SUwYm1mukE1HBoqhNmq4EF/0TQLOGJ2K7NHzoFlsI3rk7/xt0I/00ZsXifRCIKNjdc0AKZnOmpDQ==","signature_status":"signed_v1","signed_at":"2026-07-05T10:11:42.703267Z","signed_message":"canonical_sha256_bytes"},"source_id":"2502.05735","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:d7898bf03785bec86d45712b785c92ab7934ae3deab6542bd414436980f074f3","sha256:f998836ea494d08fb073fcb4aff6f1668c60b9b164c73fa719131ba39c1e6494"],"state_sha256":"9a0695a2073b5ee14344c626d60501e814c4c9cfd534e1bdb565dfea907eed45"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"+c1lKBjr1EDsUxL23/AshhR4bdRihBQjuhZyvXX8jups92oFbWuEjd9frIzSS0XROm/sGrCbY2F1F4gDGXCiCw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-10T18:22:51.682358Z","bundle_sha256":"d6156da704ea8d0ca3b68e3318d47b88e65b1d52c9fcd9fc50b9a6ace7fba3cc"}}