{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2025:GBEK6UEASNLAZ4E2BFTMNRCZVR","short_pith_number":"pith:GBEK6UEA","canonical_record":{"source":{"id":"2506.15337","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2025-06-18T10:32:26Z","cross_cats_sorted":["cond-mat.mtrl-sci","physics.comp-ph"],"title_canon_sha256":"e9b43db1bf757490b8f2eac96bd65fe10316fe5650cd80aa5508612696c5001a","abstract_canon_sha256":"0eabd21c07afa0e0a10c17b26c0448de9db4dc99e72c42936416e1f5ebfaa31b"},"schema_version":"1.0"},"canonical_sha256":"3048af508093560cf09a0966c6c459ac6a31f684e2646811ed1493076f1627c1","source":{"kind":"arxiv","id":"2506.15337","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2506.15337","created_at":"2026-07-05T11:24:24Z"},{"alias_kind":"arxiv_version","alias_value":"2506.15337v2","created_at":"2026-07-05T11:24:24Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2506.15337","created_at":"2026-07-05T11:24:24Z"},{"alias_kind":"pith_short_12","alias_value":"GBEK6UEASNLA","created_at":"2026-07-05T11:24:24Z"},{"alias_kind":"pith_short_16","alias_value":"GBEK6UEASNLAZ4E2","created_at":"2026-07-05T11:24:24Z"},{"alias_kind":"pith_short_8","alias_value":"GBEK6UEA","created_at":"2026-07-05T11:24:24Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2025:GBEK6UEASNLAZ4E2BFTMNRCZVR","target":"record","payload":{"canonical_record":{"source":{"id":"2506.15337","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2025-06-18T10:32:26Z","cross_cats_sorted":["cond-mat.mtrl-sci","physics.comp-ph"],"title_canon_sha256":"e9b43db1bf757490b8f2eac96bd65fe10316fe5650cd80aa5508612696c5001a","abstract_canon_sha256":"0eabd21c07afa0e0a10c17b26c0448de9db4dc99e72c42936416e1f5ebfaa31b"},"schema_version":"1.0"},"canonical_sha256":"3048af508093560cf09a0966c6c459ac6a31f684e2646811ed1493076f1627c1","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T11:24:24.927657Z","signature_b64":"ilM38Z2EwwvyqdNMdznc4QyKrkZm5B22+TojkhQJOT1J4BBwsVoCQ0gh7MXbtwcGnZpDYNgbZjgsoLHzm391CQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"3048af508093560cf09a0966c6c459ac6a31f684e2646811ed1493076f1627c1","last_reissued_at":"2026-07-05T11:24:24.927068Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T11:24:24.927068Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2506.15337","source_version":2,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T11:24:24Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"P7dVnMM7BUAVPiVhxMc5j1ED0sLbH8RDDmTohW5AAJ3eFWGsK9fjM98bYKb/jk8MsYIjng+Upoa5e5qi2XslBg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-07T06:23:12.757837Z"},"content_sha256":"c0b23ddbb8eecb48dc844bcd14ea7154c266d9cabaf1161295afd8940a27570e","schema_version":"1.0","event_id":"sha256:c0b23ddbb8eecb48dc844bcd14ea7154c266d9cabaf1161295afd8940a27570e"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2025:GBEK6UEASNLAZ4E2BFTMNRCZVR","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Knowledge Distillation Framework for Accelerating High-Accuracy Neural Network-Based Molecular Dynamics Simulations","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cond-mat.mtrl-sci","physics.comp-ph"],"primary_cat":"cs.LG","authors_text":"Meguru Yamazaki, Naoki Matsumura, Yasufumi Sakai, Yuta Yoshimoto, Yuto Iwasaki","submitted_at":"2025-06-18T10:32:26Z","abstract_excerpt":"Neural network potentials (NNPs) offer a powerful alternative to traditional force fields for molecular dynamics (MD) simulations. Accurate and stable MD simulations, crucial for evaluating material properties, require training data encompassing both low-energy stable structures and high-energy structures. Conventional knowledge distillation (KD) methods fine-tune a pre-trained NNP as a teacher model to generate training data for a student model. However, in material-specific models, this fine-tuning process increases energy barriers, making it difficult to create training data containing high"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2506.15337","kind":"arxiv","version":2},"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/2506.15337/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":"2026-07-05T11:24:24Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"tlWKp2m+6dPOEW836zyRjFPy4KVUlSAUXDBSa3QnvTSmi/F0mX+c9ADhBeWTlni8q0W1DcQV4/vyQ+9JgbVpCA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-07T06:23:12.758435Z"},"content_sha256":"770e7b027b68ebdd5df1ef705776a6644e781ac47e12dd20cb26ee25222b4b4b","schema_version":"1.0","event_id":"sha256:770e7b027b68ebdd5df1ef705776a6644e781ac47e12dd20cb26ee25222b4b4b"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/GBEK6UEASNLAZ4E2BFTMNRCZVR/bundle.json","state_url":"https://pith.science/pith/GBEK6UEASNLAZ4E2BFTMNRCZVR/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/GBEK6UEASNLAZ4E2BFTMNRCZVR/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":"2026-08-07T06:23:12Z","links":{"resolver":"https://pith.science/pith/GBEK6UEASNLAZ4E2BFTMNRCZVR","bundle":"https://pith.science/pith/GBEK6UEASNLAZ4E2BFTMNRCZVR/bundle.json","state":"https://pith.science/pith/GBEK6UEASNLAZ4E2BFTMNRCZVR/state.json","well_known_bundle":"https://pith.science/.well-known/pith/GBEK6UEASNLAZ4E2BFTMNRCZVR/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:GBEK6UEASNLAZ4E2BFTMNRCZVR","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":"0eabd21c07afa0e0a10c17b26c0448de9db4dc99e72c42936416e1f5ebfaa31b","cross_cats_sorted":["cond-mat.mtrl-sci","physics.comp-ph"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2025-06-18T10:32:26Z","title_canon_sha256":"e9b43db1bf757490b8f2eac96bd65fe10316fe5650cd80aa5508612696c5001a"},"schema_version":"1.0","source":{"id":"2506.15337","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2506.15337","created_at":"2026-07-05T11:24:24Z"},{"alias_kind":"arxiv_version","alias_value":"2506.15337v2","created_at":"2026-07-05T11:24:24Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2506.15337","created_at":"2026-07-05T11:24:24Z"},{"alias_kind":"pith_short_12","alias_value":"GBEK6UEASNLA","created_at":"2026-07-05T11:24:24Z"},{"alias_kind":"pith_short_16","alias_value":"GBEK6UEASNLAZ4E2","created_at":"2026-07-05T11:24:24Z"},{"alias_kind":"pith_short_8","alias_value":"GBEK6UEA","created_at":"2026-07-05T11:24:24Z"}],"graph_snapshots":[{"event_id":"sha256:770e7b027b68ebdd5df1ef705776a6644e781ac47e12dd20cb26ee25222b4b4b","target":"graph","created_at":"2026-07-05T11:24:24Z","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/2506.15337/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Neural network potentials (NNPs) offer a powerful alternative to traditional force fields for molecular dynamics (MD) simulations. Accurate and stable MD simulations, crucial for evaluating material properties, require training data encompassing both low-energy stable structures and high-energy structures. Conventional knowledge distillation (KD) methods fine-tune a pre-trained NNP as a teacher model to generate training data for a student model. However, in material-specific models, this fine-tuning process increases energy barriers, making it difficult to create training data containing high","authors_text":"Meguru Yamazaki, Naoki Matsumura, Yasufumi Sakai, Yuta Yoshimoto, Yuto Iwasaki","cross_cats":["cond-mat.mtrl-sci","physics.comp-ph"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2025-06-18T10:32:26Z","title":"Knowledge Distillation Framework for Accelerating High-Accuracy Neural Network-Based Molecular Dynamics Simulations"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2506.15337","kind":"arxiv","version":2},"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:c0b23ddbb8eecb48dc844bcd14ea7154c266d9cabaf1161295afd8940a27570e","target":"record","created_at":"2026-07-05T11:24:24Z","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":"0eabd21c07afa0e0a10c17b26c0448de9db4dc99e72c42936416e1f5ebfaa31b","cross_cats_sorted":["cond-mat.mtrl-sci","physics.comp-ph"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2025-06-18T10:32:26Z","title_canon_sha256":"e9b43db1bf757490b8f2eac96bd65fe10316fe5650cd80aa5508612696c5001a"},"schema_version":"1.0","source":{"id":"2506.15337","kind":"arxiv","version":2}},"canonical_sha256":"3048af508093560cf09a0966c6c459ac6a31f684e2646811ed1493076f1627c1","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"3048af508093560cf09a0966c6c459ac6a31f684e2646811ed1493076f1627c1","first_computed_at":"2026-07-05T11:24:24.927068Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T11:24:24.927068Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"ilM38Z2EwwvyqdNMdznc4QyKrkZm5B22+TojkhQJOT1J4BBwsVoCQ0gh7MXbtwcGnZpDYNgbZjgsoLHzm391CQ==","signature_status":"signed_v1","signed_at":"2026-07-05T11:24:24.927657Z","signed_message":"canonical_sha256_bytes"},"source_id":"2506.15337","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:c0b23ddbb8eecb48dc844bcd14ea7154c266d9cabaf1161295afd8940a27570e","sha256:770e7b027b68ebdd5df1ef705776a6644e781ac47e12dd20cb26ee25222b4b4b"],"state_sha256":"c31e55bab70f70a2d7ab9efeddbbe806d1c71d810f49a911b1d773269977b1bf"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"PdLf3FRBhe9UnuL9RpLP8ldcaAqH31sFquY0ZNzDQPYDas4rSvxDG2lrlMqu/3+KmNnpqRExOW6Plymt/7MyDw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-07T06:23:12.763236Z","bundle_sha256":"3af1eb25c4c100ddd8a6aba25b7d2cc2646de1f407ab4e415386444f0e7925d6"}}