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Importance sampling method

Figure 10 Sampling scheme in the importance sampling method. Each ellipse represents a conformation used in biased sampling. The lines indicate the connected network created through sampling. Adapted from Guo et al. with protein structures from Alonso and Daggett. Figure 10 Sampling scheme in the importance sampling method. Each ellipse represents a conformation used in biased sampling. The lines indicate the connected network created through sampling. Adapted from Guo et al. with protein structures from Alonso and Daggett.
The Sj 2 reaction, X + RY XR + Y", has been simulated with MC equilibrium calculations by Jorgensen and coworkers [81, 82]. The procedure used by these authors involves three steps i) the lowest energy reaction path is determined for the in vacuo system by using ab initio molecular orbital calculations ii) inter-molecular potential functions are obtained to describe the interactions between the substrate and a solvent molecule these potentials depend on the internal structure of the substrate iii) MC simulations are carried out to determine the free energy profile for the reaction in solution. This is a difficult computational task since importance sampling methods are required to explore all the values of the reaction coordinate. A similar technique was used by Madura and Jorgensen [83] in simulating the nucleophilic addition of hydroxide ion to formaldehyde in the gas phase and in aqueous solution. [Pg.452]

The simple difference scheme above may be combined with the importance sampling method of Grimm and Storer. A new difference function, corresponding to the difference between the products yyg and ygyo is defined as follows ... [Pg.163]

Equilibrium properties for a quantum particle in a classical solvent can be calculated by immersing the polymer in the classical solvent and treating the combined many-particle system by standard Monte Carlo or molecular dynamics techniques the latter often provide a viable alternative to importance sampling methods. [Pg.2024]

Fig. 8 Top variation of the average surface charge a) = Q)/A with potential, for a supercapacitor composed of a l-butyl-3-methylimidazolium hexafluorophosphate ionic liquid electrolyte and graphite electrodes. The points are raw data extracted from CGMD simulations while the lines are different polynomial fits of the data. Bottom Surfacic differential capacitance, which is either calculated by differentiating a = f(A ) (the colors match with the top panel plots), or from the fluctuations of the charge, using importance sampling methods (WHAM). °... Fig. 8 Top variation of the average surface charge a) = Q)/A with potential, for a supercapacitor composed of a l-butyl-3-methylimidazolium hexafluorophosphate ionic liquid electrolyte and graphite electrodes. The points are raw data extracted from CGMD simulations while the lines are different polynomial fits of the data. Bottom Surfacic differential capacitance, which is either calculated by differentiating a = f(A ) (the colors match with the top panel plots), or from the fluctuations of the charge, using importance sampling methods (WHAM). °...
To overcome this obstacle, different techniques have been proposed in order to reduce the number of simulations. One of the most commonly applied techniques is namely the importance sampling method, which is described in the next section. [Pg.2968]

Au and Beck (2001b) have also developed a very efficient importance sampling method for the first-excursion problem for linear dynamical systems under Gaussian stochastic excitation. However, for time-dependent problems, which are often characterized by a large number of uncertain parameters with complexity arising from their dynamic nature, the application of importance sampling is much more difficult (Au and Beck 2003a). [Pg.2969]

Wu, YT (1992) An adaptive importance sampling method for structural system reliability analysis. In Cruse TA (ed) Reliability technology 1992, ASME winter annual meeting, vol AD-28), Anaheim, pp 217-231... [Pg.3661]

In Chapter 4, it has already been stated that it is an advantage of the simple-sampling algorithms based on Rosenbluth sampling [33], compared to importance-sampling methods, that they allow for the approximation of the degeneracy ( density ) of states absolutely, i.e., free energy and entropy can be explicitly determined. [Pg.261]

Metropolis and Ulam determined how to generate these configurations that contribute to the sums in Eq. 15.5. The idea is simple instead of all microscopic states of phase space being sampled with uniform probability, more probable states are sampled more frequently than less probable ones. This is the importance sampling method, best described... [Pg.258]

What is remarkable is that there is no need to multiply by the probability density of each state, as in Eq. 15.5. The ensemble average is the arithmetic average because all states are generated in proportion to their probability density. Consequently, the major benefit of importance sampling methods is that they do not generate states that contribute nothing to the ensemble average. [Pg.266]

Historically, the first and most important capacitance method is the vibrating capacitor approach implemented by Lord Kelvin in 1897. In this technique (now called the Kelvin probe), the reference plate moves relative to the sample surface at some constant frequency and tlie capacitance changes as tlie interelectrode separation changes. An AC current thus flows in the external circuit. Upon reduction of the electric field to zero, the AC current is also reduced to zero. Originally, Kelvin detected the zero point manually using his quadrant electrometer. Nowadays, there are many elegant and sensitive versions of this technique. A piezoceramic foil can be used to vibrate the reference plate. To minimize noise and maximize sensitivity, a phase-locked... [Pg.1894]

In the preceding section, we presented principles of spectroscopy over the entire electromagnetic spectrum. The most important spectroscopic methods are those in the visible spectral region where food colorants can be perceived by the human eye. Human perception and the physical analysis of food colorants operate differently. The human perception with which we shall deal in Section 1.5 is difficult to normalize. However, the intention to standardize human color perception based on the abilities of most individuals led to a variety of protocols that regulate in detail how, with physical methods, human color perception can be simulated. In any case, a sophisticated instrumental set up is required. We present certain details related to optical spectroscopy here. For practical purposes, one must discriminate between measurements in the absorbance mode and those in the reflection mode. The latter mode is more important for direct measurement of colorants in food samples. To characterize pure or extracted food colorants the absorption mode should be used. [Pg.14]

API Serial Dilution Method. The API serial dilution method is the most widely used method for the detection of microorganisms. Field test methods for estimating bacterial populations have been standardized. A standard method dealing with the dose-response (time-kill) testing for evaluating biocides has been established. Sampling methods are of special importance because effective sampling is essential to any successful analysis. [Pg.69]

When considering libraries of spectra for identification purposes, the effect of sample preparation on spectral characteristics is also important. Two FUR sampling methods have been adopted for IR analysis of TLC eluates in the presence of a stationary phase, namely DRIFTS [741] and PAS [742], of comparable sensitivity. It is to be noted that in situ TLC-PA-FTIR and TLC-DRIFT spectra bear little resemblance to KBr disc or DR spectra [743,744]. This hinders spectral interpretation by fingerprinting. For unambiguous identification, the use of a reference library consisting of TLC-FTIR spectra of adsorbed species is necessary. [Pg.532]


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