标题： 带径向基函数网络的半参数模型的约束曲线拟合 显示英文标题

标题： Constrained curve fitting for semi-parametric models with radial basis function networks

摘要： 许多格点规范理论和更广泛的科学领域中的分析流程都涉及到将半参数模型拟合到数据中。 我们提出了一种拟合方法，该方法利用径向基函数网络来近似此类模型的非参数部分。 通过盆地跳跃全局优化算法将近似的参数模型拟合到数据中。 通过高斯先验来施加参数约束。 我们的方法的有效性通过检查其在$q$状态 Potts 模型和$p$状态时钟模型的有限尺寸标度分析中的应用来测试，这些模型具有$q=2,3$和$p=4,\infty$。 显示英文摘要

摘要： Common to many analysis pipelines in lattice gauge theory and the broader scientific discipline is the need to fit a semi-parametric model to data. We propose a fit method that utilizes a radial basis function network to approximate the non-parametric component of such models. The approximate parametric model is fit to data using the basin hopping global optimization algorithm. Parameter constraints are enforced through Gaussian priors. The viability of our method is tested by examining its use in a finite-size scaling analysis of the $q$-state Potts model and $p$-state clock model with $q=2,3$ and $p=4,\infty$.