{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2026:ON5BIHUBFTAQKZ5CANK2GHHVIQ","short_pith_number":"pith:ON5BIHUB","schema_version":"1.0","canonical_sha256":"737a141e812cc10567a20355a31cf5442be8aa73771e342cd257ad1d8e727f19","source":{"kind":"arxiv","id":"2607.28275","version":1},"attestation_state":"computed","paper":{"title":"Synchronization, Kinematic Waves and Spike-Phase-Separation in Feedback Ising Neural Networks on Heterogeneous Graphs","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["physics.bio-ph"],"primary_cat":"cond-mat.stat-mech","authors_text":"Anna Poggialini, Daniele De Martino, Fabrizio Lombardi, Irem Topal","submitted_at":"2026-07-30T14:27:18Z","abstract_excerpt":"Structural heterogeneity constrains collective dynamics in complex systems. However, its analytical tractability out of equilibrium remains limited. In this work, we study a class of kinetic Ising neural networks driven out of equilibrium by a homeostatic feedback loop between the neuronal excitability and the population firing rate. Using a Curie-Weiss heterogeneous mean-field approximation validated by Monte Carlo simulations, we provide an analytical characterization of how a macroscopic synchronized limit cycle emerges via an Andronov-Hopf bifurcation on heterogeneous networks. We derive c"},"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":false},"canonical_record":{"source":{"id":"2607.28275","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cond-mat.stat-mech","submitted_at":"2026-07-30T14:27:18Z","cross_cats_sorted":["physics.bio-ph"],"title_canon_sha256":"380551152eac66f687a2efc8b63e942effe49c73ec014c4b2a9227c4ce532fd7","abstract_canon_sha256":"9e1f4232944fd35397b6386e9194d0c9630fcdb10fbeb180094f77b04b64ec84"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"737a141e812cc10567a20355a31cf5442be8aa73771e342cd257ad1d8e727f19","last_reissued_at":"2026-07-31T01:37:07.495319Z","signature_status":"unsigned_v0","first_computed_at":"2026-07-31T01:37:07.495319Z"},"graph_snapshot":{"paper":{"title":"Synchronization, Kinematic Waves and Spike-Phase-Separation in Feedback Ising Neural Networks on Heterogeneous Graphs","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["physics.bio-ph"],"primary_cat":"cond-mat.stat-mech","authors_text":"Anna Poggialini, Daniele De Martino, Fabrizio Lombardi, Irem Topal","submitted_at":"2026-07-30T14:27:18Z","abstract_excerpt":"Structural heterogeneity constrains collective dynamics in complex systems. However, its analytical tractability out of equilibrium remains limited. In this work, we study a class of kinetic Ising neural networks driven out of equilibrium by a homeostatic feedback loop between the neuronal excitability and the population firing rate. Using a Curie-Weiss heterogeneous mean-field approximation validated by Monte Carlo simulations, we provide an analytical characterization of how a macroscopic synchronized limit cycle emerges via an Andronov-Hopf bifurcation on heterogeneous networks. We derive c"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2607.28275","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/2607.28275/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"},"aliases":[{"alias_kind":"arxiv","alias_value":"2607.28275","created_at":"2026-07-31T01:37:07.498531+00:00"},{"alias_kind":"arxiv_version","alias_value":"2607.28275v1","created_at":"2026-07-31T01:37:07.498531+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2607.28275","created_at":"2026-07-31T01:37:07.498531+00:00"},{"alias_kind":"pith_short_12","alias_value":"ON5BIHUBFTAQ","created_at":"2026-07-31T01:37:07.498531+00:00"},{"alias_kind":"pith_short_16","alias_value":"ON5BIHUBFTAQKZ5C","created_at":"2026-07-31T01:37:07.498531+00:00"},{"alias_kind":"pith_short_8","alias_value":"ON5BIHUB","created_at":"2026-07-31T01:37:07.498531+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":0,"internal_anchor_count":0,"sample":[]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/ON5BIHUBFTAQKZ5CANK2GHHVIQ","json":"https://pith.science/pith/ON5BIHUBFTAQKZ5CANK2GHHVIQ.json","graph_json":"https://pith.science/api/pith-number/ON5BIHUBFTAQKZ5CANK2GHHVIQ/graph.json","events_json":"https://pith.science/api/pith-number/ON5BIHUBFTAQKZ5CANK2GHHVIQ/events.json","paper":"https://pith.science/paper/ON5BIHUB"},"agent_actions":{"view_html":"https://pith.science/pith/ON5BIHUBFTAQKZ5CANK2GHHVIQ","download_json":"https://pith.science/pith/ON5BIHUBFTAQKZ5CANK2GHHVIQ.json","view_paper":"https://pith.science/paper/ON5BIHUB","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2607.28275&json=true","fetch_graph":"https://pith.science/api/pith-number/ON5BIHUBFTAQKZ5CANK2GHHVIQ/graph.json","fetch_events":"https://pith.science/api/pith-number/ON5BIHUBFTAQKZ5CANK2GHHVIQ/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/ON5BIHUBFTAQKZ5CANK2GHHVIQ/action/timestamp_anchor","attest_storage":"https://pith.science/pith/ON5BIHUBFTAQKZ5CANK2GHHVIQ/action/storage_attestation","attest_author":"https://pith.science/pith/ON5BIHUBFTAQKZ5CANK2GHHVIQ/action/author_attestation","sign_citation":"https://pith.science/pith/ON5BIHUBFTAQKZ5CANK2GHHVIQ/action/citation_signature","submit_replication":"https://pith.science/pith/ON5BIHUBFTAQKZ5CANK2GHHVIQ/action/replication_record"}},"created_at":"2026-07-31T01:37:07.498531+00:00","updated_at":"2026-07-31T01:37:07.498531+00:00"}