BU-MBAR：MBAR方程的混合求解策略
BU-MBAR: A hybrid solution strategy for the MBAR equations
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中文总结 AI 辅助
针对MBAR方程现有求解策略存在的收敛不稳定或缓慢问题，提出BU-MBAR方法，将其解释为WHAM的无限分箱极限，通过动态调整分箱宽度实现稳定高效收敛。
中文摘要 AI 辅助
多态Bennett接受率（MBAR）方程以统计最优方式整合不同热力学条件下采集的数据。鉴于其实际重要性，已开发多种求解策略以优化该耦合方程组的收敛性。然而即便借助图形处理器（GPU）加速，这些方法的收敛性仍可能不稳定或缓慢。我们提出一种新方法，将该方程解释为对应加权直方图分析方法（WHAM）的无限窄分箱极限。在提出的分箱转无分箱MBAR（BU-MBAR）方法中，分箱宽度被动态调整，以确保稳定且高效地收敛至渐近解。
英文摘要
The multi-state Bennett acceptance ratio (MBAR) equations combine the data collected under different thermodynamic conditions in a statistically optimal way. Due to their practical importance, several solution strategies have been devised to optimize the convergence of the resulting set of coupled equations. However, even with graphics processing unit (GPU) acceleration, the convergence of these methods can still be either unstable or slow. We propose a new approach where the equations are interpreted as the limit of infinitesimal bin width of the respective weighted histogram analysis method (WHAM). In the proposed binned-to-unbinned MBAR (BU-MBAR) method, the bin width is adapted dynamically to ensure a stable and efficient convergence to the asymptotic solution.
发表机构
- NEC Laboratories Europe GmbH（NEC欧洲实验室有限公司）
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