Lumping analysis for the prediction of long-time dynamics: from monomolecular reaction systems to inherent structure dynamics of glassy materials.

In this work we develop, test, and implement a methodology that is able to perform, in an automated manner, "lumping" of a high-dimensional, discrete dynamical system onto a lower-dimensional space. Our aim is to develop an algorithm which, without any assumption about the nature of the system's slow dynamics, is able to reproduce accurately the long-time dynamics with minimal loss of information. Both the original and the lumped systems conform to master equations, related via the "lumping" analysis introduced by Wei and Kuo [Ind. Eng. Chem. Fundam. 8, 114 (1969)], and have the same limiting equilibrium probability distribution. The proposed method can be used in a variety of processes that can be modeled via a first order kinetic reaction scheme. Lumping affords great savings in the computational cost and reveals the characteristic times governing the slow dynamics of the system. Our goal is to approach the best lumping scheme with respect to three criteria, in order for the lumped system to be able to fully describe the long-time dynamics of the original system. The criteria used are: (a) the lumping error arising from the reduction process; (b) a measure of the magnitude of singular values associated with long-time evolution of the lumped system; and (c) the size of the lumped system. The search for the optimum lumping proceeds via Monte Carlo simulation based on the Wang-Landau scheme, which enables us to overcome entrapment in local minima in the above criteria and therefore increases the probability of encountering the global optimum. The developed algorithm is implemented to reproduce the long-time dynamics of a glassy binary Lennard-Jones mixture based on the idea of "inherent structures," where the rate constants for transitions between inherent structures have been evaluated via hazard plot analysis of a properly designed ensemble of molecular dynamics trajectories.

[1]  Nikolaos Lempesis,et al.  On the role of inherent structures in glass-forming materials: I. The vitrification process. , 2008, The journal of physical chemistry. B.

[2]  James Wei,et al.  The Structure and Analysis of Complex Reaction Systems , 1962 .

[3]  Georgios C Boulougouris,et al.  Dynamical integration of a Markovian web: a first passage time approach. , 2007, The Journal of chemical physics.

[4]  Kenneth B. Bischoff,et al.  Lumping strategy. 1. Introductory techniques and applications of cluster analysis , 1987 .

[5]  Nikolaos Lempesis,et al.  Temperature accelerated dynamics in glass-forming materials. , 2010, The journal of physical chemistry. B.

[6]  M. Chou,et al.  Continuum theory for lumping nonlinear reactions , 1988 .

[7]  N. Metropolis,et al.  Equation of State Calculations by Fast Computing Machines , 1953, Resonance.

[8]  Raffaella Ocone,et al.  Lumping nonlinear kinetics , 1988 .

[9]  Nikolaos Lempesis,et al.  On the role of inherent structures in glass-forming materials: II. Reconstruction of the mean square displacement by rigorous lifting of the inherent structure dynamics. , 2008, The journal of physical chemistry. B.

[10]  Pablo G. Debenedetti,et al.  A conformal solution theory for the energy landscape and glass transition of mixtures , 2006 .

[11]  James Wei,et al.  On the structure and analysis of complex systems of first-order chemical reactions containing irreversible steps—I general properties , 1967 .

[12]  B. Nadler,et al.  Diffusion maps, spectral clustering and reaction coordinates of dynamical systems , 2005, math/0503445.

[13]  Nikolaos Lempesis,et al.  Efficient Parallel Decomposition of Dynamical Sampling in Glass-Forming Materials Based on an “On the Fly” Definition of Metabasins , 2010 .

[14]  Andersen,et al.  Testing mode-coupling theory for a supercooled binary Lennard-Jones mixture I: The van Hove correlation function. , 1995, Physical review. E, Statistical physics, plasmas, fluids, and related interdisciplinary topics.

[15]  Ernesto C. Martinez LUMPING OF COMPONENTS AND REACTIONS IN COMPLEX REACTION NETWORKS , 1990 .

[16]  Herschel Rabitz,et al.  A general analysis of approximate lumping in chemical kinetics , 1990 .

[17]  Herschel Rabitz,et al.  A general analysis of approximate nonlinear lumping in chemical kinetics. II. Constrained lumping , 1994 .

[19]  D. Landau,et al.  Determining the density of states for classical statistical models: a random walk algorithm to produce a flat histogram. , 2001, Physical review. E, Statistical, nonlinear, and soft matter physics.

[20]  Gerhard Stock,et al.  Improved Wang-Landau sampling through the use of smoothed potential-energy surfaces. , 2006, The Journal of chemical physics.

[21]  D. Landau,et al.  Efficient, multiple-range random walk algorithm to calculate the density of states. , 2000, Physical review letters.

[22]  Andersen,et al.  Scaling behavior in the beta -relaxation regime of a supercooled Lennard-Jones mixture. , 1994, Physical review letters.

[23]  Georgios C Boulougouris,et al.  Probing subglass relaxation in polymers via a geometric representation of probabilities, observables, and relaxation modes for discrete stochastic systems. , 2009, The Journal of chemical physics.

[24]  Y. A. Liu,et al.  Observer theory for lumping analysis of monomolecular reaction systems , 1973 .

[25]  Herschel Rabitz,et al.  A general analysis of exact lumping in chemical kinetics , 1989 .

[26]  A. Hoffman,et al.  Lower bounds for the partitioning of graphs , 1973 .

[27]  Yuichi Ozawa The Structure of a Lumpable Monomolecular System for Reversible Chemical Reactions , 1973 .

[28]  Wang-Landau Sampling in Three-Dimensional Polymers , 2006, cond-mat/0603562.

[29]  Jian Chu,et al.  7-lump kinetic model for residual oil catalytic cracking , 2006 .

[30]  Kenneth B. Bischoff,et al.  Lumping strategy. II: A system theoretic approach , 1987 .

[31]  David Chandler,et al.  Statistical mechanics of isomerization dynamics in liquids and the transition state approximation , 1978 .

[32]  Andrei Zinovyev,et al.  Principal Manifolds for Data Visualization and Dimension Reduction , 2007 .