{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2026:6FXJC4DIAI7EWSFAAMLHIRIFD4","short_pith_number":"pith:6FXJC4DI","schema_version":"1.0","canonical_sha256":"f16e917068023e4b48a003167445051f24f53056bb4140a6586529c3ab36e08a","source":{"kind":"arxiv","id":"2605.11138","version":2},"attestation_state":"computed","paper":{"title":"Field Theory of Data: Anomaly Detection via the Functional Renormalization Group. The 2D Ising Model as a Benchmark","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"Anomaly detection maps to renormalization group flows where the noise-to-signal ratio acts as temperature in an effective equilibrium field theory.","cross_cats":["cs.IT","hep-th","math.IT","stat.ME"],"primary_cat":"cond-mat.stat-mech","authors_text":"Dine Ousmane Samary, Parham Radpay, Riccardo Finotello, Vincent Lahoche","submitted_at":"2026-05-11T18:43:14Z","abstract_excerpt":"We establish a correspondence between anomaly detection in high-noise regimes and the renormalization group flow of non-equilibrium field theories. We provide a physical grounding for this framework by proving that the detection of phase transitions in interacting non-equilibrium systems maps to the study of an effective equilibrium field theory near its Gaussian fixed point, which we identify with the universal Marchenko-Pastur distribution. Applying the Functional Renormalization Group to the two-dimensional Model A, we demonstrate that the noise-to-signal ratio acts as a physical temperatur"},"verification_status":{"content_addressed":true,"pith_receipt":true,"author_attested":false,"weak_author_claims":0,"strong_author_claims":0,"externally_anchored":false,"storage_verified":false,"citation_signatures":0,"replication_records":0,"graph_snapshot":true,"references_resolved":false,"formal_links_present":true},"canonical_record":{"source":{"id":"2605.11138","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cond-mat.stat-mech","submitted_at":"2026-05-11T18:43:14Z","cross_cats_sorted":["cs.IT","hep-th","math.IT","stat.ME"],"title_canon_sha256":"7c27cf7ae8183fd9329b35f53b689f01e342cf14cd523e5583a2348e084e6c7b","abstract_canon_sha256":"cbbc8b592393c677fe196c8419c31fe02f0353cfe338b46c6d96a13884d0ef1a"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-25T02:02:16.605642Z","signature_b64":"b7tSEy/ZZ1r4rY+hClnjZUr24FgfOP3pvttt7VpW7cK3H3hRVyT274mbq0NVghBOyXZlInx7mg9LDAD9IvxlAw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"f16e917068023e4b48a003167445051f24f53056bb4140a6586529c3ab36e08a","last_reissued_at":"2026-05-25T02:02:16.604999Z","signature_status":"signed_v1","first_computed_at":"2026-05-25T02:02:16.604999Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Field Theory of Data: Anomaly Detection via the Functional Renormalization Group. The 2D Ising Model as a Benchmark","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"Anomaly detection maps to renormalization group flows where the noise-to-signal ratio acts as temperature in an effective equilibrium field theory.","cross_cats":["cs.IT","hep-th","math.IT","stat.ME"],"primary_cat":"cond-mat.stat-mech","authors_text":"Dine Ousmane Samary, Parham Radpay, Riccardo Finotello, Vincent Lahoche","submitted_at":"2026-05-11T18:43:14Z","abstract_excerpt":"We establish a correspondence between anomaly detection in high-noise regimes and the renormalization group flow of non-equilibrium field theories. We provide a physical grounding for this framework by proving that the detection of phase transitions in interacting non-equilibrium systems maps to the study of an effective equilibrium field theory near its Gaussian fixed point, which we identify with the universal Marchenko-Pastur distribution. Applying the Functional Renormalization Group to the two-dimensional Model A, we demonstrate that the noise-to-signal ratio acts as a physical temperatur"},"claims":{"count":4,"items":[{"kind":"strongest_claim","text":"Applying the Functional Renormalization Group to the two-dimensional Model A, the noise-to-signal ratio acts as a physical temperature where the signal emerges as ordered domains, identifying critical thresholds with an error below 4% and outperforming Kullback-Leibler divergence.","source":"verdict.strongest_claim","status":"machine_extracted","claim_id":"C1","attestation":"unclaimed"},{"kind":"weakest_assumption","text":"That the detection of phase transitions in interacting non-equilibrium systems maps to the study of an effective equilibrium field theory near its Gaussian fixed point, which is identified with the universal Marchenko-Pastur distribution.","source":"verdict.weakest_assumption","status":"machine_extracted","claim_id":"C2","attestation":"unclaimed"},{"kind":"one_line_summary","text":"Anomaly detection is mapped to the RG flow of a non-equilibrium field theory, with the 2D Ising model benchmark showing critical threshold identification error below 4% by treating noise-to-signal as effective temperature.","source":"verdict.one_line_summary","status":"machine_extracted","claim_id":"C3","attestation":"unclaimed"},{"kind":"headline","text":"Anomaly detection maps to renormalization group flows where the noise-to-signal ratio acts as temperature in an effective equilibrium field theory.","source":"verdict.pith_extraction.headline","status":"machine_extracted","claim_id":"C4","attestation":"unclaimed"}],"snapshot_sha256":"fcb76bf656ac97176452d112f7de388c05a73e35492cd93dc7cba0da829a9e84"},"source":{"id":"2605.11138","kind":"arxiv","version":2},"verdict":{"id":"917eb344-bc9b-47a6-95b0-58199d54d97a","model_set":{"reader":"grok-4.3"},"created_at":"2026-05-13T00:55:21.140520Z","strongest_claim":"Applying the Functional Renormalization Group to the two-dimensional Model A, the noise-to-signal ratio acts as a physical temperature where the signal emerges as ordered domains, identifying critical thresholds with an error below 4% and outperforming Kullback-Leibler divergence.","one_line_summary":"Anomaly detection is mapped to the RG flow of a non-equilibrium field theory, with the 2D Ising model benchmark showing critical threshold identification error below 4% by treating noise-to-signal as effective temperature.","pipeline_version":"pith-pipeline@v0.9.0","weakest_assumption":"That the detection of phase transitions in interacting non-equilibrium systems maps to the study of an effective equilibrium field theory near its Gaussian fixed point, which is identified with the universal Marchenko-Pastur distribution.","pith_extraction_headline":"Anomaly detection maps to renormalization group flows where the noise-to-signal ratio acts as temperature in an effective equilibrium field theory."},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/2605.11138/integrity.json","findings":[],"available":true,"detectors_run":[{"name":"claim_evidence","ran_at":"2026-05-20T05:02:00.652609Z","status":"completed","version":"1.0.0","findings_count":0},{"name":"ai_meta_artifact","ran_at":"2026-05-19T13:34:44.758761Z","status":"completed","version":"1.0.0","findings_count":0},{"name":"doi_title_agreement","ran_at":"2026-05-19T10:31:16.723425Z","status":"completed","version":"1.0.0","findings_count":0},{"name":"doi_compliance","ran_at":"2026-05-19T08:45:14.151927Z","status":"completed","version":"1.0.0","findings_count":0}],"snapshot_sha256":"eedbc3895facb12dfb806c6e5f4738259c12e53347354e093c6dbe85a753ca89"},"references":{"count":0,"sample":[],"resolved_work":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","internal_anchors":0},"formal_canon":{"evidence_count":2,"snapshot_sha256":"6198ca22d693fdd82fb5fa3712d7f7daec142ba68f43be016a0fc204458a840a"},"author_claims":{"count":0,"strong_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"builder_version":"pith-number-builder-2026-05-17-v1"},"aliases":[{"alias_kind":"arxiv","alias_value":"2605.11138","created_at":"2026-05-25T02:02:16.605086+00:00"},{"alias_kind":"arxiv_version","alias_value":"2605.11138v2","created_at":"2026-05-25T02:02:16.605086+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2605.11138","created_at":"2026-05-25T02:02:16.605086+00:00"},{"alias_kind":"pith_short_12","alias_value":"6FXJC4DIAI7E","created_at":"2026-05-25T02:02:16.605086+00:00"},{"alias_kind":"pith_short_16","alias_value":"6FXJC4DIAI7EWSFA","created_at":"2026-05-25T02:02:16.605086+00:00"},{"alias_kind":"pith_short_8","alias_value":"6FXJC4DI","created_at":"2026-05-25T02:02:16.605086+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":0,"internal_anchor_count":0,"sample":[]},"formal_canon":{"evidence_count":2,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/6FXJC4DIAI7EWSFAAMLHIRIFD4","json":"https://pith.science/pith/6FXJC4DIAI7EWSFAAMLHIRIFD4.json","graph_json":"https://pith.science/api/pith-number/6FXJC4DIAI7EWSFAAMLHIRIFD4/graph.json","events_json":"https://pith.science/api/pith-number/6FXJC4DIAI7EWSFAAMLHIRIFD4/events.json","paper":"https://pith.science/paper/6FXJC4DI"},"agent_actions":{"view_html":"https://pith.science/pith/6FXJC4DIAI7EWSFAAMLHIRIFD4","download_json":"https://pith.science/pith/6FXJC4DIAI7EWSFAAMLHIRIFD4.json","view_paper":"https://pith.science/paper/6FXJC4DI","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2605.11138&json=true","fetch_graph":"https://pith.science/api/pith-number/6FXJC4DIAI7EWSFAAMLHIRIFD4/graph.json","fetch_events":"https://pith.science/api/pith-number/6FXJC4DIAI7EWSFAAMLHIRIFD4/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/6FXJC4DIAI7EWSFAAMLHIRIFD4/action/timestamp_anchor","attest_storage":"https://pith.science/pith/6FXJC4DIAI7EWSFAAMLHIRIFD4/action/storage_attestation","attest_author":"https://pith.science/pith/6FXJC4DIAI7EWSFAAMLHIRIFD4/action/author_attestation","sign_citation":"https://pith.science/pith/6FXJC4DIAI7EWSFAAMLHIRIFD4/action/citation_signature","submit_replication":"https://pith.science/pith/6FXJC4DIAI7EWSFAAMLHIRIFD4/action/replication_record"}},"created_at":"2026-05-25T02:02:16.605086+00:00","updated_at":"2026-05-25T02:02:16.605086+00:00"}