{"paper":{"title":"Mittag-Leffler-Type Forecast-Error Growth as a Diagnostic Indicator of Fractional Dynamics","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"math.DS","authors_text":"Andrei Velichko, N'Gbo N'Gbo","submitted_at":"2026-07-09T15:24:39Z","abstract_excerpt":"Fractional calculus is a powerful framework for modeling nonlocal behavior in complex systems. However, the identification of fractional dynamics from measured time series remains challenging, as most existing approaches require knowledge of the underlying governing equations. In this work, we propose a data-driven diagnostic pipeline that detects fractional signatures directly from scalar observations using a multi-horizon k-nearest neighbors (kNN) forecast-error growth framework. The central idea is that fractional systems exhibit power-law or Mittag-Leffler error growth, in contrast to the "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2607.08588","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/2607.08588/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"}