Theory of Adaptive Optimization for Umbrella Sampling
نویسندگان
چکیده
منابع مشابه
Theory of Adaptive Optimization for Umbrella Sampling
We present a theory of adaptive optimization for umbrella sampling. With the analytical bias force constant obtained from the constrained thermodynamic length along the reaction coordinate, the windows are distributed to optimize the overlap between neighbors. Combining with the replica exchange method, we propose a method of adaptive window exchange umbrella sampling. The efficiency gain in sa...
متن کاملEvaluation of the Adaptive Umbrella Sampling Method
(Received December, 1988) The adaptive umbrella sampling technique, introduced recently to improve the probability ratio method and found to perform more reliably then the customary harmonic umbrella sampling, is tested and compared with other free energy methods. One of the tests applies the method to a transition involving a chemical change: calculation of the hydration free energy difference...
متن کاملUmbrella sampling
The calculation of free-energy differences is one of the main challenges in computational biology and biochemistry. Umbrella sampling, biased molecular dynamics (MD), is one of the methods that provide free energy along a reaction coordinate. Here, the method is derived in a historic overview and is compared with related methods like thermodynamic integration, slow growth, steered MD, or the Ja...
متن کاملUmbrella sampling for nonequilibrium processes.
The authors introduce an algorithm for determining the steady-state probability distribution of an ergodic system arbitrarily far from equilibrium. By enforcing equal sampling of different regions of phase space, as in umbrella sampling simulations of systems at equilibrium, low probability regions are explored to a much greater extent than in physically weighted simulations. The algorithm can ...
متن کاملAdaptive Sampling Probabilities for Non-Smooth Optimization
Abstract Standard forms of coordinate and stochastic gradient methods do not adapt to structure in data; their good behavior under random sampling is predicated on uniformity in data. When gradients in certain blocks of features (for coordinate descent) or examples (for SGD) are larger than others, there is a natural structure that can be exploited for quicker convergence. Yet adaptive variants...
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ژورنال
عنوان ژورنال: Journal of Chemical Theory and Computation
سال: 2014
ISSN: 1549-9618,1549-9626
DOI: 10.1021/ct500504g