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Grand Canonical Generators 扩展 Boltzmann 生成器到巨正则系综

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2026-10-02，arXiv·Statistics Machine Learning 报道 Grand Canonical Generators（GCG）框架，将 Boltzmann 生成器扩展至巨正则系综。GCG 提供两种设计：一是直接以化学势为条件对粒子数与构型进行联合采样；二是将巨正则分布分解为粒子数分布与正则 Boltzmann 密度的乘积形式。该工作为统计机器学习中处理粒子数可变的系综采样提供了新方法。

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LatestOct 2
2026-10-02 arXiv 报道 GCG 框架，将 Boltzmann 生成器扩展至巨正则系综并给出两种采样设计。

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Oct 2, 2026
  1. arXiv · Statistics Machine Learning
    Grand Canonical Generators（GCG）生成框架

    Grand Canonical Generators（GCG）将 Boltzmann 生成器扩展至巨正则系综，提供两种设计：直接以化学势条件采样粒子数与构型，或将巨正则分布分解为粒子数分布与正则 Boltzmann 密度。

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