{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2022:YYUK5OZ5HKAWMACKL4ZJPBOA6Z","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":"83d7a0e2b3c38fdfefc74ae243b441cdad982cbe636e8984ab7fe08f69a71e05","cross_cats_sorted":["cond-mat.dis-nn"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cond-mat.str-el","submitted_at":"2022-02-27T02:11:36Z","title_canon_sha256":"f688e2e641c7f17a05f775799fb3706576fff5649e396c6ebe0d87d53c77c6d9"},"schema_version":"1.0","source":{"id":"2202.13268","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2202.13268","created_at":"2026-07-05T05:55:07Z"},{"alias_kind":"arxiv_version","alias_value":"2202.13268v2","created_at":"2026-07-05T05:55:07Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2202.13268","created_at":"2026-07-05T05:55:07Z"},{"alias_kind":"pith_short_12","alias_value":"YYUK5OZ5HKAW","created_at":"2026-07-05T05:55:07Z"},{"alias_kind":"pith_short_16","alias_value":"YYUK5OZ5HKAWMACK","created_at":"2026-07-05T05:55:07Z"},{"alias_kind":"pith_short_8","alias_value":"YYUK5OZ5","created_at":"2026-07-05T05:55:07Z"}],"graph_snapshots":[{"event_id":"sha256:29b7c857821c894dc1fa697a9c5108eb7a73cab826f4250bc4eff43157e09e10","target":"graph","created_at":"2026-07-05T05:55:07Z","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/2202.13268/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"We perform a data-driven dimensionality reduction of the scale-dependent 4-point vertex function characterizing the functional Renormalization Group (fRG) flow for the widely studied two-dimensional $t - t'$ Hubbard model on the square lattice. We demonstrate that a deep learning architecture based on a Neural Ordinary Differential Equation solver in a low-dimensional latent space efficiently learns the fRG dynamics that delineates the various magnetic and $d$-wave superconducting regimes of the Hubbard model. We further present a Dynamic Mode Decomposition analysis that confirms that a small ","authors_text":"Alessandro Toschi, Andrew J. Millis, Anirvan M. Sengupta, Cesare Franchini, Domenico Di Sante, Giorgio Sangiovanni, Matija Medvidovi\\'c","cross_cats":["cond-mat.dis-nn"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cond-mat.str-el","submitted_at":"2022-02-27T02:11:36Z","title":"Deep Learning the Functional Renormalization Group"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2202.13268","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":"sha256:3cf93f8b313a984196a983471f08fa9e2e4cc4ee2f88aa2e51bb4f3dd782e1fb","target":"record","created_at":"2026-07-05T05:55:07Z","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":"83d7a0e2b3c38fdfefc74ae243b441cdad982cbe636e8984ab7fe08f69a71e05","cross_cats_sorted":["cond-mat.dis-nn"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cond-mat.str-el","submitted_at":"2022-02-27T02:11:36Z","title_canon_sha256":"f688e2e641c7f17a05f775799fb3706576fff5649e396c6ebe0d87d53c77c6d9"},"schema_version":"1.0","source":{"id":"2202.13268","kind":"arxiv","version":2}},"canonical_sha256":"c628aebb3d3a8166004a5f329785c0f65a4aa6d96bae93fce1bd255d2ad924af","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"c628aebb3d3a8166004a5f329785c0f65a4aa6d96bae93fce1bd255d2ad924af","first_computed_at":"2026-07-05T05:55:07.582030Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T05:55:07.582030Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"maMOA/CVyduJ8rjofAlqtpS+If2P4qGUnYXIk1c/a4+FuZvKo5Dk0fO1BQKUKgXTXfbNgo/oglyMvanv8X+IBA==","signature_status":"signed_v1","signed_at":"2026-07-05T05:55:07.582490Z","signed_message":"canonical_sha256_bytes"},"source_id":"2202.13268","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:3cf93f8b313a984196a983471f08fa9e2e4cc4ee2f88aa2e51bb4f3dd782e1fb","sha256:29b7c857821c894dc1fa697a9c5108eb7a73cab826f4250bc4eff43157e09e10"],"state_sha256":"18da1a1c2c9aca0bf6ab07067a6c5d46e6795247041a47b1d18cbc9fcfa6f960"}