Convergence of simulated annealing by the generalized transition probability

We prove weak ergodicity of the inhomogeneous Markov process generated by the generalized transition probability of Tsallis and Stariolo under power-law decay of the temperature. We thus have a mathematical foundation to conjecture convergence of simulated annealing processes with the generalized transition probability to the minimum of the cost function. An explicitly solvable example in one dimension is analyzed in which the generalized transition probability leads to a fast convergence of the cost function to the optimal value. We also investigate how far our arguments depend upon the specific form of the generalized transition probability proposed by Tsallis and Stariolo. It is shown that a few requirements on analyticity of the transition probability are sufficient to assure fast convergence in the case of the solvable model in one dimension.Comment: 11 page

Inherent-Structure Dynamics and Diffusion in Liquids

The self-diffusion constant D is expressed in terms of transitions among the local minima of the potential (inherent structure, IS) and their correlations. The formulae are evaluated and tested against simulation in the supercooled, unit-density Lennard-Jones liquid. The approximation of uncorrelated IS-transition (IST) vectors, D_{0}, greatly exceeds D in the upper temperature range, but merges with simulation at reduced T ~ 0.50. Since uncorrelated IST are associated with a hopping mechanism, the condition D ~ D_{0} provides a new way to identify the crossover to hopping. The results suggest that theories of diffusion in deeply supercooled liquids may be based on weakly correlated IST.Comment: submitted to PR

The Potential Energy Landscape and Mechanisms of Diffusion in Liquids

The mechanism of diffusion in supercooled liquids is investigated from the potential energy landscape point of view, with emphasis on the crossover from high- to low-T dynamics. Molecular dynamics simulations with a time dependent mapping to the associated local mininum or inherent structure (IS) are performed on unit-density Lennard-Jones (LJ). New dynamical quantities introduced include r2_{is}(t), the mean-square displacement (MSD) within a basin of attraction of an IS, R2(t), the MSD of the IS itself, and g_{loc}(t) the mean waiting time in a cooperative region. At intermediate T, r2_{is}(t) posesses an interval of linear t-dependence allowing calculation of an intrabasin diffusion constant D_{is}. Near T_{c} diffusion is intrabasin dominated with D = D_{is}. Below T_{c} the local waiting time tau_{loc} exceeds the time, tau_{pl}, needed for the system to explore the basin, indicating the action of barriers. The distinction between motion among the IS below T_{c} and saddle, or border dynamics above T_{c} is discussed.Comment: submitted to pr

Generalized-ensemble Monte carlo method for systems with rough energy landscape

We present a novel Monte Carlo algorithm which enhances equilibrization of low-temperature simulations and allows sampling of configurations over a large range of energies. The method is based on a non-Boltzmann probability weight factor and is another version of the so-called generalized-ensemble techniques. The effectiveness of the new approach is demonstrated for the system of a small peptide, an example of the frustrated system with a rugged energy landscape.Comment: Latex; ps-files include

The Approach to Ergodicity in Monte Carlo Simulations

The approach to the ergodic limit in Monte Carlo simulations is studied using both analytic and numerical methods. With the help of a stochastic model, a metric is defined that enables the examination of a simulation in both the ergodic and non-ergodic regimes. In the non-ergodic regime, the model implies how the simulation is expected to approach ergodic behavior analytically, and the analytically inferred decay law of the metric allows the monitoring of the onset of ergodic behavior. The metric is related to previously defined measures developed for molecular dynamics simulations, and the metric enables the comparison of the relative efficiencies of different Monte Carlo schemes. Applications to Lennard-Jones 13-particle clusters are shown to match the model for Metropolis, J-walking and parallel tempering based approaches. The relative efficiencies of these three Monte Carlo approaches are compared, and the decay law is shown to be useful in determining needed high temperature parameters in parallel tempering and J-walking studies of atomic clusters.Comment: 17 Pages, 7 Figure

The Use of Experimental Structures to Model Protein Dynamics

The number of solved protein structures submitted in the Protein Data Bank (PDB) has increased dramatically in recent years. For some specific proteins, this number is very high—for example, there are over 550 solved structures for HIV-1 protease, one protein that is essential for the life cycle of human immunodeficiency virus (HIV) which causes acquired immunodeficiency syndrome (AIDS) in humans. The large number of structures for the same protein and its variants include a sample of different conformational states of the protein. A rich set of structures solved experimentally for the same protein has information buried within the dataset that can explain the functional dynamics and structural mechanism of the protein. To extract the dynamics information and functional mechanism from the experimental structures, this chapter focuses on two methods—Principal Component Analysis (PCA) and Elastic Network Models (ENM). PCA is a widely used statistical dimensionality reduction technique to classify and visualize high-dimensional data. On the other hand, ENMs are well-established simple biophysical method for modeling the functionally important global motions of proteins. This chapter covers the basics of these two. Moreover, an improved ENM version that utilizes the variations found within a given set of structures for a protein is described. As a practical example, we have extracted the functional dynamics and mechanism of HIV-1 protease dimeric structure by using a set of 329 PDB structures of this protein. We have described, step by step, how to select a set of protein structures, how to extract the needed information from the PDB files for PCA, how to extract the dynamics information using PCA, how to calculate ENM modes, how to measure the congruency between the dynamics computed from the principal components (PCs) and the ENM modes, and how to compute entropies using the PCs. We provide the computer programs or references to software tools to accomplish each step and show how to use these programs and tools. We also include computer programs to generate movies based on PCs and ENM modes and describe how to visualize them

Itineration of the Internet over Nonequilibrium Stationary States in Tsallis Statistics

The cumulative probability distribution of sparseness time interval in the Internet is studied by the method of data analysis. Round-trip time between a local host and a destination host through ten odd routers is measured using the Ping Command, i.e., doing echo experiment. It is found that the data are well described by the q-exponential destributions, which maximize the Tsallis entropy indexed by q less or larger than unity. The network is observed to itinerate over a series of the nonequilibrium stationary states characterized by Tsallis statistics.Comment: 15 pages, 5 figure

Absolute Single-Molecule Entropies from Quasi-Harmonic Analysis of Microsecond Molecular Dynamics: Correction Terms and Convergence Properties

The convergence properties of the absolute single-molecule configurational entropy and the correction terms used to estimate it are investigated using microsecond molecular dynamics simulation of a peptide test system and an improved methodology. The results are compared with previous applications for systems of diverse chemical nature. It is shown that (i) the effect of anharmonicity is small, (ii) the effect of pairwise correlation is typically large, and (iii) the latter affects to a larger extent the entropy estimate of thermodynamic states characterized by a higher motional correlation. The causes of such deviations from a quasi-harmonic behavior are explained. This improved approach provides entropies also for molecular systems undergoing conformational transitions and characterized by highly frustrated energy surfaces, thus not limited to systems sampling a single quasi-harmonic basin. Overall, this study emphasizes the need for extensive phase-space sampling in order to obtain a reliable estimation of entropic contributions

Neuer Kopf, alte Ideen? : "Normalisierung" des Front National unter Marine Le Pen

In this article, it is investigated whether vibrational entropy (VE) is an important contribution to the free energy of globular proteins at ambient conditions. VE represents the major configurational-entropy contribution of these proteins. By definition, it is an average of the configurational entropies of the protein within single minima of the energy landscape, weighted by their occupation probabilities. Its large part originates from thermal motion of flexible torsion angles giving rise to the finite peak widths observed in torsion angle distributions. While VE may affect the equilibrium properties of proteins, it is usually neglected in numerical calculations as its consideration is difficult. Moreover, it is sometimes believed that all well-packed conformations of a globular protein have similar VE anyway. Here, we measure explicitly the VE for six different conformations from simulation data of a test protein. Estimates are obtained using the quasi-harmonic approximation for three coordinate sets, Cartesian, bond-angle-torsion (BAT), and a new set termed rotamer-degeneracy lifted BAT coordinates by us. The new set gives improved estimates as it overcomes a known shortcoming of the quasi-harmonic approximation caused by multiply populated rotamer states, and it may serve for VE estimation of macromolecules in a very general context. The obtained VE values depend considerably on the type of coordinates used. However, for all coordinate sets we find large entropy differences between the conformations, of the order of the overall stability of the protein. This result may have important implications on the choice of free energy expressions used in software for protein structure prediction, protein design, and NMR refinement