{"paper":{"title":"Dispersion of Gaussian Sources with Memory and an Extension to Abstract Sources","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["math.IT"],"primary_cat":"cs.IT","authors_text":"Eyyup Tasci, Victoria Kostina","submitted_at":"2026-02-09T20:33:18Z","abstract_excerpt":"We consider finite blocklength lossy compression of information sources whose components are independent but non-identically distributed. Crucially, Gaussian sources with memory can be cast in this form. We show that under the operational constraint of exceeding distortion $d$ with probability at most $\\epsilon$, the minimum achievable rate at blocklength $n$ satisfies $R(n, d, \\epsilon)=\\mathbb{R}_n(d)+\\sqrt{\\frac{\\mathbb{V}_n(d)}{n}}Q^{-1}(\\epsilon)+O \\left(\\frac{\\log n}{n}\\right)$, where $Q^{-1}(\\cdot)$ is the inverse $ Q$-function, while $\\mathbb{R}_n(d)$ and $\\mathbb{V}_n(d)$ are fundamen"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2602.09176","kind":"arxiv","version":2},"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/2602.09176/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"}