具有非保守力的自适应偏置力算法及相关问题
The Adaptive Biasing Force algorithm with non-conservative forces and related topics
摘要：
我们提出了一个自适应偏置力方法的鲁棒性通用（可能是非保守）的力量下的研究。我们首先确保在所有情况下都满足平坦直方图属性。然后，我们引入一个不动点问题，产生的自适应偏置力和投影自适应偏置力算法的稳态的存在，依赖于通用的均匀扩散不变的概率测度的界限。使用经典的熵技术，我们证明了指数收敛的偏置力和法律随着时间的推移到无穷大，无论是自适应偏置力和投影自适应偏置力的方法。
英文摘要：
We propose a study of the Adaptive Biasing Force method's robustness under generic (possibly non-conservative) forces. We first ensure the flat histogram property is satisfied in all cases. We then introduce a fixed point problem yielding the existence of a stationary state for both the Adaptive Biasing Force and Projected Adapted Biasing Force algorithms, relying on generic bounds on the invariant probability measures of homogeneous diffusions. Using classical entropy techniques, we prove the exponential convergence of both biasing force and law as time goes to infinity, for both the Adaptive Biasing Force and the Projected Adaptive Biasing Force methods.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
