{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2020:RRIFF5LJ7O5MJJ3ZPFROM7H3J2","short_pith_number":"pith:RRIFF5LJ","canonical_record":{"source":{"id":"2002.12388","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"math.NA","submitted_at":"2020-02-27T19:02:40Z","cross_cats_sorted":["cs.LG","cs.NA","math.DS","quant-ph","stat.ML"],"title_canon_sha256":"7bf2eceab8b3699e84349443054fe4ceafb9a65f799bf080b42ec1b95473ada9","abstract_canon_sha256":"b01055f4459e3d81485c0792a48bd79812de9b481598204968763611322aa863"},"schema_version":"1.0"},"canonical_sha256":"8c5052f569fbbac4a7797962e67cfb4ea86b845b8944deb00bca93443935eb52","source":{"kind":"arxiv","id":"2002.12388","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2002.12388","created_at":"2026-07-05T00:44:29Z"},{"alias_kind":"arxiv_version","alias_value":"2002.12388v1","created_at":"2026-07-05T00:44:29Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2002.12388","created_at":"2026-07-05T00:44:29Z"},{"alias_kind":"pith_short_12","alias_value":"RRIFF5LJ7O5M","created_at":"2026-07-05T00:44:29Z"},{"alias_kind":"pith_short_16","alias_value":"RRIFF5LJ7O5MJJ3Z","created_at":"2026-07-05T00:44:29Z"},{"alias_kind":"pith_short_8","alias_value":"RRIFF5LJ","created_at":"2026-07-05T00:44:29Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2020:RRIFF5LJ7O5MJJ3ZPFROM7H3J2","target":"record","payload":{"canonical_record":{"source":{"id":"2002.12388","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"math.NA","submitted_at":"2020-02-27T19:02:40Z","cross_cats_sorted":["cs.LG","cs.NA","math.DS","quant-ph","stat.ML"],"title_canon_sha256":"7bf2eceab8b3699e84349443054fe4ceafb9a65f799bf080b42ec1b95473ada9","abstract_canon_sha256":"b01055f4459e3d81485c0792a48bd79812de9b481598204968763611322aa863"},"schema_version":"1.0"},"canonical_sha256":"8c5052f569fbbac4a7797962e67cfb4ea86b845b8944deb00bca93443935eb52","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T00:44:29.495370Z","signature_b64":"Ex7U03jSNYJLji+GqtFjolBqtpX2B1CTSCEz1RldoAdYATz3q8teeddBSP3wdZ5HwaSKyGOdke20ovdkYVQMCA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"8c5052f569fbbac4a7797962e67cfb4ea86b845b8944deb00bca93443935eb52","last_reissued_at":"2026-07-05T00:44:29.494998Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T00:44:29.494998Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2002.12388","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":"2026-07-05T00:44:29Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"L7Y/JU5oAeeZwFMkusUCjTordmRq9LwzZ97wDS/n6sE3eB+EHrkbkmYCWjq7rSpXDnE5l4yPHL139JXfs8dSDA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-17T01:24:13.241567Z"},"content_sha256":"58ccf6ebd98ba1fc279bbc4d53867c26f29ef316a80b355b896dd7640f185877","schema_version":"1.0","event_id":"sha256:58ccf6ebd98ba1fc279bbc4d53867c26f29ef316a80b355b896dd7640f185877"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2020:RRIFF5LJ7O5MJJ3ZPFROM7H3J2","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Tensor network approaches for learning non-linear dynamical laws","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.LG","cs.NA","math.DS","quant-ph","stat.ML"],"primary_cat":"math.NA","authors_text":"A. Goe{\\ss}mann, G. Kutyniok, I. Roth, J. Eisert, M. G\\\"otte, R. Sweke","submitted_at":"2020-02-27T19:02:40Z","abstract_excerpt":"Given observations of a physical system, identifying the underlying non-linear governing equation is a fundamental task, necessary both for gaining understanding and generating deterministic future predictions. Of most practical relevance are automated approaches to theory building that scale efficiently for complex systems with many degrees of freedom. To date, available scalable methods aim at a data-driven interpolation, without exploiting or offering insight into fundamental underlying physical principles, such as locality of interactions. In this work, we show that various physical constr"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2002.12388","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/2002.12388/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":"2026-07-05T00:44:29Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"A6ozhFx3d5+V6HCcWvNNJut3z+PJ2UxoAQyh2y07KAa78DUEYTmKHskrMnGlg5F6rlROOnNii9KuFeNSthe3DQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-17T01:24:13.242181Z"},"content_sha256":"7e95e5fa4bf53ec9e66b0d5142806a8403d08f0290ad835d908c5b9547d3070c","schema_version":"1.0","event_id":"sha256:7e95e5fa4bf53ec9e66b0d5142806a8403d08f0290ad835d908c5b9547d3070c"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/RRIFF5LJ7O5MJJ3ZPFROM7H3J2/bundle.json","state_url":"https://pith.science/pith/RRIFF5LJ7O5MJJ3ZPFROM7H3J2/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/RRIFF5LJ7O5MJJ3ZPFROM7H3J2/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":"2026-08-17T01:24:13Z","links":{"resolver":"https://pith.science/pith/RRIFF5LJ7O5MJJ3ZPFROM7H3J2","bundle":"https://pith.science/pith/RRIFF5LJ7O5MJJ3ZPFROM7H3J2/bundle.json","state":"https://pith.science/pith/RRIFF5LJ7O5MJJ3ZPFROM7H3J2/state.json","well_known_bundle":"https://pith.science/.well-known/pith/RRIFF5LJ7O5MJJ3ZPFROM7H3J2/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2020:RRIFF5LJ7O5MJJ3ZPFROM7H3J2","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":"b01055f4459e3d81485c0792a48bd79812de9b481598204968763611322aa863","cross_cats_sorted":["cs.LG","cs.NA","math.DS","quant-ph","stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"math.NA","submitted_at":"2020-02-27T19:02:40Z","title_canon_sha256":"7bf2eceab8b3699e84349443054fe4ceafb9a65f799bf080b42ec1b95473ada9"},"schema_version":"1.0","source":{"id":"2002.12388","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2002.12388","created_at":"2026-07-05T00:44:29Z"},{"alias_kind":"arxiv_version","alias_value":"2002.12388v1","created_at":"2026-07-05T00:44:29Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2002.12388","created_at":"2026-07-05T00:44:29Z"},{"alias_kind":"pith_short_12","alias_value":"RRIFF5LJ7O5M","created_at":"2026-07-05T00:44:29Z"},{"alias_kind":"pith_short_16","alias_value":"RRIFF5LJ7O5MJJ3Z","created_at":"2026-07-05T00:44:29Z"},{"alias_kind":"pith_short_8","alias_value":"RRIFF5LJ","created_at":"2026-07-05T00:44:29Z"}],"graph_snapshots":[{"event_id":"sha256:7e95e5fa4bf53ec9e66b0d5142806a8403d08f0290ad835d908c5b9547d3070c","target":"graph","created_at":"2026-07-05T00:44:29Z","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/2002.12388/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Given observations of a physical system, identifying the underlying non-linear governing equation is a fundamental task, necessary both for gaining understanding and generating deterministic future predictions. Of most practical relevance are automated approaches to theory building that scale efficiently for complex systems with many degrees of freedom. To date, available scalable methods aim at a data-driven interpolation, without exploiting or offering insight into fundamental underlying physical principles, such as locality of interactions. In this work, we show that various physical constr","authors_text":"A. Goe{\\ss}mann, G. Kutyniok, I. Roth, J. Eisert, M. G\\\"otte, R. Sweke","cross_cats":["cs.LG","cs.NA","math.DS","quant-ph","stat.ML"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"math.NA","submitted_at":"2020-02-27T19:02:40Z","title":"Tensor network approaches for learning non-linear dynamical laws"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2002.12388","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":"sha256:58ccf6ebd98ba1fc279bbc4d53867c26f29ef316a80b355b896dd7640f185877","target":"record","created_at":"2026-07-05T00:44:29Z","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":"b01055f4459e3d81485c0792a48bd79812de9b481598204968763611322aa863","cross_cats_sorted":["cs.LG","cs.NA","math.DS","quant-ph","stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"math.NA","submitted_at":"2020-02-27T19:02:40Z","title_canon_sha256":"7bf2eceab8b3699e84349443054fe4ceafb9a65f799bf080b42ec1b95473ada9"},"schema_version":"1.0","source":{"id":"2002.12388","kind":"arxiv","version":1}},"canonical_sha256":"8c5052f569fbbac4a7797962e67cfb4ea86b845b8944deb00bca93443935eb52","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"8c5052f569fbbac4a7797962e67cfb4ea86b845b8944deb00bca93443935eb52","first_computed_at":"2026-07-05T00:44:29.494998Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T00:44:29.494998Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"Ex7U03jSNYJLji+GqtFjolBqtpX2B1CTSCEz1RldoAdYATz3q8teeddBSP3wdZ5HwaSKyGOdke20ovdkYVQMCA==","signature_status":"signed_v1","signed_at":"2026-07-05T00:44:29.495370Z","signed_message":"canonical_sha256_bytes"},"source_id":"2002.12388","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:58ccf6ebd98ba1fc279bbc4d53867c26f29ef316a80b355b896dd7640f185877","sha256:7e95e5fa4bf53ec9e66b0d5142806a8403d08f0290ad835d908c5b9547d3070c"],"state_sha256":"4b7025e7a90f9b9c92c45a77f29f977ea94d434b74f8e59e0069d3f599f3e3b4"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"fqhI8TwiuJimVycgGFFiFCFnmu2l6pRlrgcQ7b9CNu/Nt8G3YWul1JQwF4fgGcIFYRa3hGQLJOt9o8MXs/vVCQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-17T01:24:13.245802Z","bundle_sha256":"f3119f3af145ffea2ccd6ffc6b1bd8207f44018d21a44125485394a1930803e8"}}