AI 中文总结
该研究开发了开源Julia包Newtrinos.jl，其模块化三层架构可灵活组合实验与模型，支持两类统计推理及并行、自动微分，用于中微子数据的全局分析。
AI 中文摘要
this http URL是一个开源Julia包，用于开展中微子数据的全局分析。它提供模块化的三层架构，将物理模型、实验描述和统计推理划分为独立模块，使研究人员可自由组合实验并针对多种理论模型进行测试，新增实验和物理模型无需修改核心代码。每个实验数据集均实现包含所有相关系统不确定度的完整统计前向模型，定义了似然和数据生成过程，支持现代统计推理工作流。该框架具备可组合性，可便捷构建多数据集的联合似然；物理和冗余参数可跨实验合并、关联或去关联，确保联合拟合的一致性。该包支持频率派和贝叶斯推理，可在CPU线程或分布式工作节点间并行运行；完全用Julia编写，所有模型均可自动微分，支持精确梯度计算。
英文摘要
Newtrinos.jl is an open-source Julia package for performing global analyses of neutrino data. It provides a modular, three-layer architecture that separates physics models, experiment descriptions, and statistical inference into independent modules. This allows researchers to freely combine experiments and test them against a variety of theoretical models. New experiments and physics models can be added without modifying core code. Full statistical forward models including all relevant systematic uncertainties are implemented for each experimental dataset, defining both the likelihood and the data-generating process and enabling modern statistical inference workflows. The framework is composable, making it straightforward to construct joint likelihoods over multiple datasets. Physics and nuisance parameters can be merged, correlated, or decorrelated across experiments to ensure consistency in the joint fit. The package supports Frequentist and Bayesian inference and is parallelizable across CPU threads or distributed workers. Written entirely in Julia, all models are automatically differentiable, enabling exact gradient computation.
