{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:LF4LSY7OI4WGL4FMEBPCFC3ODF","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":"481b5cdb2e149eba0aef9f1761b79c374fc33e015056c924fae959085f0306b9","cross_cats_sorted":["math-ph","math.FA","math.MP"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"math.PR","submitted_at":"2024-12-17T09:36:50Z","title_canon_sha256":"1ef9309bab4bfc4c101ecb26401f713a606583b4f0d9c052a817ee440359cbbb"},"schema_version":"1.0","source":{"id":"2412.12720","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2412.12720","created_at":"2026-07-05T10:16:40Z"},{"alias_kind":"arxiv_version","alias_value":"2412.12720v2","created_at":"2026-07-05T10:16:40Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2412.12720","created_at":"2026-07-05T10:16:40Z"},{"alias_kind":"pith_short_12","alias_value":"LF4LSY7OI4WG","created_at":"2026-07-05T10:16:40Z"},{"alias_kind":"pith_short_16","alias_value":"LF4LSY7OI4WGL4FM","created_at":"2026-07-05T10:16:40Z"},{"alias_kind":"pith_short_8","alias_value":"LF4LSY7O","created_at":"2026-07-05T10:16:40Z"}],"graph_snapshots":[{"event_id":"sha256:7ac7ec0a5be0493e3107f301ef52d034b99d95d1543b0e2118a22974573a64ca","target":"graph","created_at":"2026-07-05T10:16:40Z","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/2412.12720/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"We present generalizations and modifications of Eldan's Stochastic Localization process, extending it to incorporate non-Gaussian tilts, making it useful for a broader class of measures. As an application, we introduce new processes that enable the decomposition and analysis of non-quadratic potentials on the Boolean hypercube, with a specific focus on quartic polynomials. Using this framework, we derive new spectral gap estimates for tensor Ising models under Glauber dynamics, resulting in rapid mixing.","authors_text":"Arianna Piana, Dan Mikulincer","cross_cats":["math-ph","math.FA","math.MP"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"math.PR","submitted_at":"2024-12-17T09:36:50Z","title":"Stochastic Localization with Non-Gaussian Tilts and Applications to Tensor Ising Models"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2412.12720","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:c0e7eeea4172d3d04e44e9ec90aa6f3124de006201fef79aba902d4497711546","target":"record","created_at":"2026-07-05T10:16:40Z","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":"481b5cdb2e149eba0aef9f1761b79c374fc33e015056c924fae959085f0306b9","cross_cats_sorted":["math-ph","math.FA","math.MP"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"math.PR","submitted_at":"2024-12-17T09:36:50Z","title_canon_sha256":"1ef9309bab4bfc4c101ecb26401f713a606583b4f0d9c052a817ee440359cbbb"},"schema_version":"1.0","source":{"id":"2412.12720","kind":"arxiv","version":2}},"canonical_sha256":"5978b963ee472c65f0ac205e228b6e197cfc074b5fe1f4094e306251ddc1a432","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"5978b963ee472c65f0ac205e228b6e197cfc074b5fe1f4094e306251ddc1a432","first_computed_at":"2026-07-05T10:16:40.312411Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T10:16:40.312411Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"cUI4yyEmcUluUFX6CasEDkG06uXGjn7NIou3l1dnW1Q5YBNbSGxXdQfKMi1VsIHHv0oISkBsPvVLg5c6qW8PBg==","signature_status":"signed_v1","signed_at":"2026-07-05T10:16:40.313008Z","signed_message":"canonical_sha256_bytes"},"source_id":"2412.12720","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:c0e7eeea4172d3d04e44e9ec90aa6f3124de006201fef79aba902d4497711546","sha256:7ac7ec0a5be0493e3107f301ef52d034b99d95d1543b0e2118a22974573a64ca"],"state_sha256":"16723c85a8e948aef13b9c83d8ba85b10f3dce33d741a832b96c1eb9a42357c7"}