论文标题
用标准化的流程跳过复制式交换阶梯
Skipping the Replica Exchange Ladder with Normalizing Flows
论文作者
论文摘要
我们将复制交换（平行回火）与标准化流量（一类深入生成模型）相结合。这两种抽样策略相互补充，从而产生了采样以罕见事件为特征的分子系统的有效策略，我们称之为学习的副本交换（LREX）。在LREX中，训练了归一化的流量，以将最快混合副本的配置映射到属于目标分布的配置中，从而允许两者之间的直接交换无需模拟中间复制品。与标准副本交换相比，这可以大大降低计算成本。提出的方法还提供了有关Boltzmann发电机的几个优势，这些发电机直接使用标准化流量来采样目标分布。我们将LREX应用于某些典型的分子动力学系统，突出了对先前方法的改进。
We combine replica exchange (parallel tempering) with normalizing flows, a class of deep generative models. These two sampling strategies complement each other, resulting in an efficient strategy for sampling molecular systems characterized by rare events, which we call learned replica exchange (LREX). In LREX, a normalizing flow is trained to map the configurations of the fastest-mixing replica into configurations belonging to the target distribution, allowing direct exchanges between the two without the need to simulate intermediate replicas. This can significantly reduce the computational cost compared to standard replica exchange. The proposed method also offers several advantages with respect to Boltzmann generators that directly use normalizing flows to sample the target distribution. We apply LREX to some prototypical molecular dynamics systems, highlighting the improvements over previous methods.
