Long-time convergence of an Adaptive Biasing Force method: the bi-channel case
Tony Lelievre (CERMICS), Kimiya Minoukadeh (CERMICS)

TL;DR
This paper proves that the adaptive biasing force (ABF) method converges efficiently in bi-channel molecular systems, overcoming previous limitations caused by metastable states, under certain conditions.
Contribution
It extends convergence analysis of the ABF method to bi-channel cases, showing it is not hindered by metastability if channels exchange and the bias is effective.
Findings
Convergence of ABF is not limited by metastabilities in bi-channel systems.
Exchange between channels enables effective biasing and convergence.
The method performs well under specific assumptions about channel exchange and bias effectiveness.
Abstract
We present convergence results for an adaptive algorithm to compute free energies, namely the adaptive biasing force (ABF) method. The free energy is the effective potential associated to a so-called reaction coordinate (RC). Computing free energy differences remains an important challenge in molecular dynamics due to the presence of meta-stable regions in the potential energy surface. The ABF method uses an on-the-fly estimate of the free energy to bias dynamics and overcome metastability. Using entropy arguments and logarithmic Sobolev inequalities, previous results have shown that the rate of convergence of the ABF method is limited by the metastable features of the canonical measures conditioned to being at fixed values of the RC. In this paper, we present an improvement on the existing results, in the presence of such metastabilities, which is a generic case encountered in…
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Taxonomy
TopicsProtein Structure and Dynamics · Quantum chaos and dynamical systems · Statistical Mechanics and Entropy
