The Hessian biased singular value decomposition method for optimization and analysis of force fields
نویسندگان
چکیده
We present methodology ~HBFF/SVD! for optimizing the form and parameters of force fields ~FF! for molecular dynamics simulations through utilizing information about properties such as the geometry, Hessian, polarizability, stress ~crystals!, and elastic constants ~crystals!. This method is based on singular value decomposition ~SVD! of the Jacobian describing the partial derivatives in various properties with respect to FF parameters. HBFF/SVD is effective for optimizing the parameters for accurate FFs of organic, inorganic, and transition metal compounds. In addition it provides information on the validity of the functional form of the FF for describing the properties of interest. This method is illustrated by application to organic molecules ~CH2O, C2H4, C4H6, C6H8, C6H6, and naphthalene! and inorganic molecules ~Cl2CrO2 and Cl2MoO2!. © 1996 American Institute of Physics. @S0021-9606~96!01208-8#
منابع مشابه
Noise Effects on Modal Parameters Extraction of Horizontal Tailplane by Singular Value Decomposition Method Based on Output Only Modal Analysis
According to the great importance of safety in aerospace industries, identification of dynamic parameters of related equipment by experimental tests in operating conditions has been in focus. Due to the existence of noise sources in these conditions the probability of fault occurrence may increases. This study investigates the effects of noise in the process of modal parameters identification b...
متن کاملModified Laplace Decomposition Method for Singular IVPs in the second-Order Ordinary Differential Equations
In this paper, we use modified Laplace decomposition method to solving initial value problems (IVP) of the second order ordinary differential equations. Theproposed method can be applied to linear and nonlinearproblems
متن کاملGraph Clustering by Hierarchical Singular Value Decomposition with Selectable Range for Number of Clusters Members
Graphs have so many applications in real world problems. When we deal with huge volume of data, analyzing data is difficult or sometimes impossible. In big data problems, clustering data is a useful tool for data analysis. Singular value decomposition(SVD) is one of the best algorithms for clustering graph but we do not have any choice to select the number of clusters and the number of members ...
متن کاملA Dimensionless Parameter Approach based on Singular Value Decomposition and Evolutionary Algorithm for Prediction of Carbamazepine Particles Size
The particle size control of drug is one of the most important factors affecting the efficiency of the nano-drug production in confined liquid impinging jets. In the present research, for this investigation the confined liquid impinging jet was used to produce nanoparticles of Carbamazepine. The effects of several parameters such as concentration, solution and anti-solvent flow rate and solvent...
متن کاملChange Point Estimation of the Stationary State in Auto Regressive Moving Average Models, Using Maximum Likelihood Estimation and Singular Value Decomposition-based Filtering
In this paper, for the first time, the subject of change point estimation has been utilized in the stationary state of auto regressive moving average (ARMA) (1, 1). In the monitoring phase, in case the features of the question pursue a time series, i.e., ARMA(1,1), on the basis of the maximum likelihood technique, an approach will be developed for the estimation of the stationary state’s change...
متن کامل