Details

Autor(en) / Beteiligte

• Linker, Stephanie M.
• Weiß, R. Gregor
• Riniker, Sereina

Titel

Connecting dynamic reweighting Algorithms: Derivation of the dynamic reweighting family tree

Ist Teil von

• The Journal of chemical physics, 2020-12, Vol.153 (23), p.234106-234106

Ort / Verlag

United States: American Institute of Physics

Erscheinungsjahr

2020

Link zum Volltext

Quelle

AIP Journals Complete

Beschreibungen/Notizen

• Thermally driven processes of molecular systems include transitions of energy barriers on the microsecond timescales and higher. Sufficient sampling of such processes with molecular dynamics simulations is challenging and often requires accelerating slow transitions using external biasing potentials. Different dynamic reweighting algorithms have been proposed in the past few years to recover the unbiased kinetics from biased systems. However, it remains an open question if and how these dynamic reweighting approaches are connected. In this work, we establish the link between the two main reweighting types, i.e., path-based and energy-based reweighting. We derive a path-based correction factor for the energy-based dynamic histogram analysis method, thus connecting the previously separate reweighting types. We show that the correction factor can be used to combine the advantages of path-based and energy-based reweighting algorithms: it is integrator independent, more robust, and at the same time able to reweight time-dependent biases. We can furthermore demonstrate the relationship between two independently derived path-based reweighting algorithms. Our theoretical findings are verified on a one-dimensional four-well system. By connecting different dynamic reweighting algorithms, this work helps to clarify the strengths and limitations of the different methods and enables a more robust usage of the combined types.