{"slug": "boltzmann-mapreduce-a-partition-function-reduce-for-forkable-sandboxes", "title": "Boltzmann MapReduce: A Partition-Function Reduce for Forkable Sandboxes", "summary": "Researchers introduced Boltzmann MapReduce, a framework that treats confidence densities from distributed data chunks as Boltzmann factors and uses a partition-function reduce for precision-weighted pooling, achieving consistency in the zero-temperature limit.", "body_md": "# Computer Science > Artificial Intelligence\n\n[Submitted on 17 Jun 2026]\n\n# Title:Boltzmann MapReduce: A Partition-Function Reduce for Forkable Sandboxes\n\n[View PDF](/pdf/2607.09689)\n\n[HTML (experimental)](https://arxiv.org/html/2607.09689v1)\n\nAbstract:To leading order under local asymptotic normality (LAN), the confidence density a worker emits over a chunk of size $n$ is a Gibbs--Boltzmann measure $\\exp\\{-\\beta E(\\theta)\\}$ whose inverse temperature is the sample size, $\\beta=n$. Three consequences are exact in the Gaussian/linear case and first-order otherwise: disjoint chunks carry independent Boltzmann factors, so the MapReduce \\emph{reduce}, read literally, is a partition function $Z=\\int\\prod_k h_k\\,d\\theta$ whose mode is precision-weighted (inverse-variance) pooling; frequentist consistency is the zero-temperature limit $T=1/n\\to0$\n\n### Current browse context:\n\ncs.AI\n\n### References & Citations\n\nLoading...\n\n# Bibliographic and Citation Tools\n\nBibliographic Explorer\n\n*(*[What is the Explorer?](https://info.arxiv.org/labs/showcase.html#arxiv-bibliographic-explorer))\nConnected Papers\n\n*(*[What is Connected Papers?](https://www.connectedpapers.com/about))\nLitmaps\n\n*(*[What is Litmaps?](https://www.litmaps.co/))\nscite Smart Citations\n\n*(*[What are Smart Citations?](https://www.scite.ai/))# Code, Data and Media Associated with this Article\n\nalphaXiv\n\n*(*[What is alphaXiv?](https://alphaxiv.org/))\nCatalyzeX Code Finder for Papers\n\n*(*[What is CatalyzeX?](https://www.catalyzex.com))\nDagsHub\n\n*(*[What is DagsHub?](https://dagshub.com/))\nGotit.pub\n\n*(*[What is GotitPub?](http://gotit.pub/faq))\nHugging Face\n\n*(*[What is Huggingface?](https://huggingface.co/huggingface))\nScienceCast\n\n*(*[What is ScienceCast?](https://sciencecast.org/welcome))# Demos\n\n# Recommenders and Search Tools\n\nInfluence Flower\n\n*(*[What are Influence Flowers?](https://influencemap.cmlab.dev/))\nCORE Recommender\n\n*(*[What is CORE?](https://core.ac.uk/services/recommender))# arXivLabs: experimental projects with community collaborators\n\narXivLabs is a framework that allows collaborators to develop and share new arXiv features directly on our website.\n\nBoth individuals and organizations that work with arXivLabs have embraced and accepted our values of openness, community, excellence, and user data privacy. arXiv is committed to these values and only works with partners that adhere to them.\n\nHave an idea for a project that will add value for arXiv's community? [ Learn more about arXivLabs](https://info.arxiv.org/labs/index.html).", "url": "https://wpnews.pro/news/boltzmann-mapreduce-a-partition-function-reduce-for-forkable-sandboxes", "canonical_source": "https://arxiv.org/abs/2607.09689", "published_at": "2026-07-14 13:30:10+00:00", "updated_at": "2026-07-14 13:48:25.136636+00:00", "lang": "en", "topics": ["artificial-intelligence", "machine-learning", "ai-research"], "entities": [], "alternates": {"html": "https://wpnews.pro/news/boltzmann-mapreduce-a-partition-function-reduce-for-forkable-sandboxes", "markdown": "https://wpnews.pro/news/boltzmann-mapreduce-a-partition-function-reduce-for-forkable-sandboxes.md", "text": "https://wpnews.pro/news/boltzmann-mapreduce-a-partition-function-reduce-for-forkable-sandboxes.txt", "jsonld": "https://wpnews.pro/news/boltzmann-mapreduce-a-partition-function-reduce-for-forkable-sandboxes.jsonld"}}