{"paper":{"title":"Grouped Reverse Importance Sampling for the Partition Function","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cond-mat.stat-mech","math.IT"],"primary_cat":"cs.IT","authors_text":"Neri Merhav","submitted_at":"2026-06-25T08:33:22Z","abstract_excerpt":"We introduce and analyze several grouped variants of the method of reverse importance sampling (RIS) for estimating a partition function from samples of the Boltzmann distribution $p(x)=e^{ \\betaU(x)}/Z(\\beta)$. Ordinary RIS weighs each sample separately. By contrast, our proposed grouped RIS (GRIS) methods are based on assigning the samples into groups (or batches) of size $k\\ge 2$ and applying a joint weight function to each group. The focal point of the research is the quest for a tractable weight function that would yield the smallest possible mean squared error (MSE). A simple identity re"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2606.26748","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/2606.26748/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"}