论文标题
加权合奏：最近的数学发展
Weighted ensemble: Recent mathematical developments
论文作者
论文摘要
加权集合（WE）方法是一种基于一组平行模拟中定期复制和修剪轨迹的增强抽样方法，它在计算生物化学问题中越来越流行，部分原因是改善的硬件和现代软件的可用性。算法和分析改进也发挥了重要作用，近年来进步加速了。在这里，我们从数学角度讨论并详细介绍了我们的方法，并强调了最新的结果，这些结果已开始产生更高的计算效率。在这些创新中，值得注意的是减少方差方法，可优化任意维度系统的轨迹管理。
The weighted ensemble (WE) method, an enhanced sampling approach based on periodically replicating and pruning trajectories in a set of parallel simulations, has grown increasingly popular for computational biochemistry problems, due in part to improved hardware and the availability of modern software. Algorithmic and analytical improvements have also played an important role, and progress has accelerated in recent years. Here, we discuss and elaborate on the WE method from a mathematical perspective, highlighting recent results which have begun to yield greater computational efficiency. Notable among these innovations are variance reduction approaches that optimize trajectory management for systems of arbitrary dimensionality.
