{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2022:YQZZ3YKYDAEBYRFD3GXQBIPRTK","short_pith_number":"pith:YQZZ3YKY","canonical_record":{"source":{"id":"2202.09186","kind":"arxiv","version":3},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cond-mat.mtrl-sci","submitted_at":"2022-02-18T13:30:36Z","cross_cats_sorted":[],"title_canon_sha256":"80db548c31ae0923ac30df97fdf685b39529e225589a7c4d1b101168cde752f5","abstract_canon_sha256":"ff917bf99bab042b98f6894bdbbad63a63eaf3eb3717b2fcbbbf4ae8185bef71"},"schema_version":"1.0"},"canonical_sha256":"c4339de15818081c44a3d9af00a1f19a8f69fb87384c9e51d1686ad7331add56","source":{"kind":"arxiv","id":"2202.09186","version":3},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2202.09186","created_at":"2026-07-05T05:22:28Z"},{"alias_kind":"arxiv_version","alias_value":"2202.09186v3","created_at":"2026-07-05T05:22:28Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2202.09186","created_at":"2026-07-05T05:22:28Z"},{"alias_kind":"pith_short_12","alias_value":"YQZZ3YKYDAEB","created_at":"2026-07-05T05:22:28Z"},{"alias_kind":"pith_short_16","alias_value":"YQZZ3YKYDAEBYRFD","created_at":"2026-07-05T05:22:28Z"},{"alias_kind":"pith_short_8","alias_value":"YQZZ3YKY","created_at":"2026-07-05T05:22:28Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2022:YQZZ3YKYDAEBYRFD3GXQBIPRTK","target":"record","payload":{"canonical_record":{"source":{"id":"2202.09186","kind":"arxiv","version":3},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cond-mat.mtrl-sci","submitted_at":"2022-02-18T13:30:36Z","cross_cats_sorted":[],"title_canon_sha256":"80db548c31ae0923ac30df97fdf685b39529e225589a7c4d1b101168cde752f5","abstract_canon_sha256":"ff917bf99bab042b98f6894bdbbad63a63eaf3eb3717b2fcbbbf4ae8185bef71"},"schema_version":"1.0"},"canonical_sha256":"c4339de15818081c44a3d9af00a1f19a8f69fb87384c9e51d1686ad7331add56","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T05:22:28.570269Z","signature_b64":"FwGipAFYP2qz94u7Z5mPIUETHUI0OlZVNRd40wGnT7IITYm+vcxdMhnqIEXjs84jshKwhyTMSSrf62/ldAJ+Cw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"c4339de15818081c44a3d9af00a1f19a8f69fb87384c9e51d1686ad7331add56","last_reissued_at":"2026-07-05T05:22:28.569877Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T05:22:28.569877Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2202.09186","source_version":3,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T05:22:28Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"KzoA660plwLttcdzQ+N1eIn++TfMzshAMEd5rXD4eca5OB55/6GklrbchdvDQnH6J12wLZLnjSGmpfgVff3TAw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-23T22:01:08.929020Z"},"content_sha256":"afdea25f10f8528ffa540044049085b902007f8d8061efebfaff5c9782e476c4","schema_version":"1.0","event_id":"sha256:afdea25f10f8528ffa540044049085b902007f8d8061efebfaff5c9782e476c4"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2022:YQZZ3YKYDAEBYRFD3GXQBIPRTK","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Training-free hyperparameter optimization of neural networks for electronic structures in matter","license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","headline":"","cross_cats":[],"primary_cat":"cond-mat.mtrl-sci","authors_text":"Attila Cangi, Gabriel A. Popoola, J. Austin Ellis, Lenz Fiedler, Nils Hoffmann, Parvez Mohammed, Siva Rajamanickam, Tamar Yovell, Vladyslav Oles","submitted_at":"2022-02-18T13:30:36Z","abstract_excerpt":"A myriad of phenomena in materials science and chemistry rely on quantum-level simulations of the electronic structure in matter. While moving to larger length and time scales has been a pressing issue for decades, such large-scale electronic structure calculations are still challenging despite modern software approaches and advances in high-performance computing. The silver lining in this regard is the use of machine learning to accelerate electronic structure calculations -- this line of research has recently gained growing attention. The grand challenge therein is finding a suitable machine"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2202.09186","kind":"arxiv","version":3},"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/2202.09186/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":"2026-07-05T05:22:28Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"7yy4iPOsOKC+Pt3EhuwINJcs/v2Nh2xEA820iTl2DaJXAG/rqPmQcFdPi2eMUCwa0UQ3kMg3NJW3qzB4gP//BQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-23T22:01:08.929533Z"},"content_sha256":"8634b7ce7c71289c2e4723a26c1032f009d56aa38ccf0aa857f72efb5d1f1ba3","schema_version":"1.0","event_id":"sha256:8634b7ce7c71289c2e4723a26c1032f009d56aa38ccf0aa857f72efb5d1f1ba3"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/YQZZ3YKYDAEBYRFD3GXQBIPRTK/bundle.json","state_url":"https://pith.science/pith/YQZZ3YKYDAEBYRFD3GXQBIPRTK/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/YQZZ3YKYDAEBYRFD3GXQBIPRTK/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":"2026-08-23T22:01:08Z","links":{"resolver":"https://pith.science/pith/YQZZ3YKYDAEBYRFD3GXQBIPRTK","bundle":"https://pith.science/pith/YQZZ3YKYDAEBYRFD3GXQBIPRTK/bundle.json","state":"https://pith.science/pith/YQZZ3YKYDAEBYRFD3GXQBIPRTK/state.json","well_known_bundle":"https://pith.science/.well-known/pith/YQZZ3YKYDAEBYRFD3GXQBIPRTK/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2022:YQZZ3YKYDAEBYRFD3GXQBIPRTK","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":"ff917bf99bab042b98f6894bdbbad63a63eaf3eb3717b2fcbbbf4ae8185bef71","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cond-mat.mtrl-sci","submitted_at":"2022-02-18T13:30:36Z","title_canon_sha256":"80db548c31ae0923ac30df97fdf685b39529e225589a7c4d1b101168cde752f5"},"schema_version":"1.0","source":{"id":"2202.09186","kind":"arxiv","version":3}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2202.09186","created_at":"2026-07-05T05:22:28Z"},{"alias_kind":"arxiv_version","alias_value":"2202.09186v3","created_at":"2026-07-05T05:22:28Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2202.09186","created_at":"2026-07-05T05:22:28Z"},{"alias_kind":"pith_short_12","alias_value":"YQZZ3YKYDAEB","created_at":"2026-07-05T05:22:28Z"},{"alias_kind":"pith_short_16","alias_value":"YQZZ3YKYDAEBYRFD","created_at":"2026-07-05T05:22:28Z"},{"alias_kind":"pith_short_8","alias_value":"YQZZ3YKY","created_at":"2026-07-05T05:22:28Z"}],"graph_snapshots":[{"event_id":"sha256:8634b7ce7c71289c2e4723a26c1032f009d56aa38ccf0aa857f72efb5d1f1ba3","target":"graph","created_at":"2026-07-05T05:22:28Z","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/2202.09186/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"A myriad of phenomena in materials science and chemistry rely on quantum-level simulations of the electronic structure in matter. While moving to larger length and time scales has been a pressing issue for decades, such large-scale electronic structure calculations are still challenging despite modern software approaches and advances in high-performance computing. The silver lining in this regard is the use of machine learning to accelerate electronic structure calculations -- this line of research has recently gained growing attention. The grand challenge therein is finding a suitable machine","authors_text":"Attila Cangi, Gabriel A. Popoola, J. Austin Ellis, Lenz Fiedler, Nils Hoffmann, Parvez Mohammed, Siva Rajamanickam, Tamar Yovell, Vladyslav Oles","cross_cats":[],"headline":"","license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cond-mat.mtrl-sci","submitted_at":"2022-02-18T13:30:36Z","title":"Training-free hyperparameter optimization of neural networks for electronic structures in matter"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2202.09186","kind":"arxiv","version":3},"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:afdea25f10f8528ffa540044049085b902007f8d8061efebfaff5c9782e476c4","target":"record","created_at":"2026-07-05T05:22:28Z","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":"ff917bf99bab042b98f6894bdbbad63a63eaf3eb3717b2fcbbbf4ae8185bef71","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cond-mat.mtrl-sci","submitted_at":"2022-02-18T13:30:36Z","title_canon_sha256":"80db548c31ae0923ac30df97fdf685b39529e225589a7c4d1b101168cde752f5"},"schema_version":"1.0","source":{"id":"2202.09186","kind":"arxiv","version":3}},"canonical_sha256":"c4339de15818081c44a3d9af00a1f19a8f69fb87384c9e51d1686ad7331add56","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"c4339de15818081c44a3d9af00a1f19a8f69fb87384c9e51d1686ad7331add56","first_computed_at":"2026-07-05T05:22:28.569877Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T05:22:28.569877Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"FwGipAFYP2qz94u7Z5mPIUETHUI0OlZVNRd40wGnT7IITYm+vcxdMhnqIEXjs84jshKwhyTMSSrf62/ldAJ+Cw==","signature_status":"signed_v1","signed_at":"2026-07-05T05:22:28.570269Z","signed_message":"canonical_sha256_bytes"},"source_id":"2202.09186","source_kind":"arxiv","source_version":3}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:afdea25f10f8528ffa540044049085b902007f8d8061efebfaff5c9782e476c4","sha256:8634b7ce7c71289c2e4723a26c1032f009d56aa38ccf0aa857f72efb5d1f1ba3"],"state_sha256":"b7764f088074cf3d4af6cf6a09f29e5afe4c11a6bc18c9ef231940253d9861e3"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"Np1AKR0gDosfCPj8BUxsCb3g4oa/WNbUQkhbLz7sBTdW912jpK3BRaF6Q8iYIiQGdOCPSZOLiTteAse5VKa5Ag==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-23T22:01:08.933202Z","bundle_sha256":"7c9ec66ec7d7f86b96ae9cb7a81d48646a4c0704a4829464f8717ca8db33a943"}}