Showing papers on "Monte Carlo molecular modeling published in 1995"
Book•
01 Jan 1995
TL;DR: In this article, Monte Carlo Methods for the Self-Avoiding Walk and Monte Carlo Simulation of Neutral and Charged Polymer Solutions: Effects of Long-range Interactions are presented.
Abstract: 1. Introduction. General Aspects of Computer Simulation Techniques and Their Applicaitons in Polymer Physics 2. Monte Carlo Methods for the Self-Avoiding Walk 3. Structure and Dynamics of Neutral and Charged Polymer Solutions: Effects of Long-Range Interactions 4. Entanglement Effects in Polymer Melts 5. Molecular Dynamics of Glassy Polymers 6. Monte Carlo Simulations of the Glass Transition of Polymers 7. Monte Carlo Studies of Polymer Blends and Block Copolymer Thermodynamics 9. Computer Simulations of Tethered Chains
870 citations
TL;DR: In this article, an approach is presented to solve the reverse problem of statistical mechanics: reconstruction of interaction potentials from radial distribution functions, consisting of the iterative adjustment of the interaction potential to known radial distribution function using a Monte Carlo simulation technique and statistical-mechanics relations to connect deviations of canonical averages with Hamiltonian parameters.
Abstract: An approach is presented to solve the reverse problem of statistical mechanics: reconstruction of interaction potentials from radial distribution functions. The method consists of the iterative adjustment of the interaction potential to known radial distribution functions using a Monte Carlo simulation technique and statistical-mechanics relations to connect deviations of canonical averages with Hamiltonian parameters. The method is applied to calculate the effective interaction potentials between the ions in aqueous NaCl solutions at two different concentrations. The reference ion-ion radial distribution functions, calculated in separate molecular dynamics simulations with water molecules, are reproduced in Monte Carlo simulations, using the effective interaction potentials for the hydrated ions. Application of the present method should provide an effective and economical way to simulate equilibrium properties for very large molecular systems (e.g., polyelectrolytes) in the presence of hydrated ions, as well as to offer an approach to reduce a complexity in studies of various associated and aggregated systems in solution.
772 citations
TL;DR: In this paper, the authors compared the performance of quasi-random and random Monte Carlo methods for multidimensional integrals with respect to variance, variation, smoothness, and dimension.
492 citations
01 Jan 1995
TL;DR: The book is mainly concerned with the mathematical foundations of Bayesian image analysis and its algorithms, which amounts to the study of Markov random fields and dynamic Monte Carlo algorithms like sampling, simulated annealing and stochastic gradient algorithms.
486 citations
03 Apr 1995
TL;DR: If the authority ascribed to Monte Carlo models of devices at 1/spl mu/m feature size is to be maintained, modelling of the fundamental physics must be further improved, and the device model must be made more realistic.
Abstract: There can be little doubt that the Monte Carlo method for semiconductor device simulation has enormous power as a research tool. It represents a detailed physical model of the semiconductor material(s), and provides a high degree of insight into the microscopic transport processes. However, if the authority ascribed to Monte Carlo models of devices at 1/spl mu/m feature size is to be maintained for devices below O.1/spl mu/m, modelling of the fundamental physics must be further improved. And if the Monte Carlo method is to be successful as a semiconductor device design tool, the device model must be made more realistic. Success in the industrial sector depends on this, but also on achieving fast run-times optimisation - where the scope and need for ingenuity is now greatest.
436 citations
TL;DR: A Monte Carlo EM algorithm that uses a Markov chain sampling technique in the calculation of the expectation in the E step of the EM algorithm is discussed, and it is shown that under suitable regularity conditions, an MCEM algorithm will get close to a maximizer of the likelihood of the observed data.
Abstract: The observations in parameter-driven models for time series of counts are generated from latent unobservable processes that characterize the correlation structure. These models result in very complex likelihoods, and even the EM algorithm, which is usually well suited for problems of this type, involves high-dimensional integration. In this article we discuss a Monte Carlo EM (MCEM) algorithm that uses a Markov chain sampling technique in the calculation of the expectation in the E step of the EM algorithm. We propose a stopping criterion for the algorithm and provide rules for selecting the appropriate Monte Carlo sample size. We show that under suitable regularity conditions, an MCEM algorithm will, with high probability, get close to a maximizer of the likelihood of the observed data. We also discuss the asymptotic efficiency of the procedure. We illustrate our Monte Carlo estimation method on a time series involving small counts: the polio incidence time series previously analyzed by Zeger.
314 citations
TL;DR: A simple model for biological aging is presented through computer simulations and it is finted to reflect some features of real populations to reflect the changes in real populations.
Abstract: We present a simple model for biological aging. We study it through computer simulations and fint it to reflect some features of real populations.
289 citations
TL;DR: In this article, a new Monte Carlo algorithm for the simulation of atomistically detailed polymer melts is presented, where the connectivity of the polymer is altered in Monte Carlo moves that satisfy the detailed constraints of molecular geometry.
Abstract: A new Monte Carlo algorithm for the simulation of atomistically detailed polymer melts is presented. The method introduces connectivity relationships as variables in the description of the polymer. The connectivity of the polymer is altered in Monte Carlo moves that satisfy the detailed constraints of molecular geometry. Connectivity-altering moves are seen to induce large jumps in the configuration space of the bulk polymer, thereby greatly enhancing the efficiency with which molecular configurations are sampled. Simulations are carried out in a semigrand ensemble in which the chain length distribution is controlled by a spectrum of chemical potentials. Limiting chain length distributions are derived and compared with simulation results. Volumetric and structural predictions of the method are found to be in agreement with previous work.
244 citations
TL;DR: In this article, the authors investigated three Ising models on the simple cubic lattice by means of Monte Carlo methods and finite-size scaling, and found that the correction-to-scaling amplitudes are strongly dependent on the introduction of further-neighbour interactions or a third spin state.
Abstract: We investigate three Ising models on the simple cubic lattice by means of Monte Carlo methods and finite-size scaling. These models are the spin-1/2 Ising model with nearest-neighbour interactions, a spin-1/2 model with nearest-neighbour and third-neighbour interactions, and a spin-1 model with nearest-neighbour interactions. The results are in accurate agreement with the hypothesis of universality. Analysis of the finite-size scaling behaviour reveals corrections beyond those caused by the leading irrelevant scaling field. We find that the correction-to-scaling amplitudes are strongly dependent on the introduction of further-neighbour interactions or a third spin state. In a spin-1 Ising model, these corrections appear to be very small. This is very helpful for the determination of the universal constants of the Ising model. The renormalization exponents of the Ising model are determined as yt=1.587 (2), yh=2.4815 (15) and yi=-0.82 (6). The universal ratio Q=(m2)2/(m4) is equal to 0.6233 (4) for periodic systems with cubic symmetry. The critical point of the nearest-neighbour spin-1/2 model is Kc=0.2216546 (10).
241 citations
TL;DR: In this paper, Woźniakowski et al. presented a program committee for the International Journal of Distributed Sensor Networks (GanIzerS) with the following members: Piotr krzyżanowski, Marek kwas, leszek Plaskota, and Grzegorz Wasilkowski.
Abstract: loCal orGanIzerS • Piotr krzyżanowski • Marek kwas • leszek Plaskota • Henryk Woźniakowski (chair) PROGRAM COMMITTEE • William Chen (australia) • ronald Cools (Belgium) • Josef dick (australia) • Henri Faure (France) • alan Genz (USa) • Paul Glasserman (USa) • Stefan Heinrich (Germany) • Fred J. Hickernell (USa) • Stephen Joe (new zealand) • aneta karaivanova (Bulgaria) • alexander keller (Germany) • Frances kuo (australia) • Gerhard larcher (austria) • Pierre l’ecuyer (Canada) • Christiane lemieux (Canada) • Makoto Matsumoto (Japan) • Peter Mathé (Germany) • thomas Müller-Gronbach (Germany) • Harald niederreiter (austria) • erich novak (Germany) • art B. owen (USa) • Friedrich Pillichshammer (austria) • leszek Plaskota (Poland) • klaus ritter (Germany) • Wolfgang Ch. Schmid (austria) • nikolai Simonov (russia) • Ian H. Sloan (australia) • Ilya M. Sobol’ (russia) • Jerome Spanier (USa) • Shu tezuka (Japan) • Xiaoqun Wang (China) • Grzegorz Wasilkowski (USa) • Henryk Woźniakowski (chair) (Poland/USa)
TL;DR: In this article, a Monte Carlo program is presented that computes all four-fermion processes in e+e− annihilation, and a systematic, modular and self-optimizing strategy is adopted for the Monte Carlo integration, which serves also as an example for further event generators in high energy particle physics.
TL;DR: In this article, an asymptotically efficient algorithm for the allocation of computing resources to the problem of Monte Carlo integration of continuous-time security prices is presented, where the tradeoff between increasing the number of time intervals per unit of time and increasing the simulation time is investigated.
Abstract: This paper provides an asymptotically efficient algorithm for the allocation of computing resources to the problem of Monte Carlo integration of continuous-time security prices The tradeoff between increasing the number of time intervals per unit of time and increasing the number of simulations, given a limited budget of computer time, is resolved for first-order discretization schemes (such as Euler) as well as second- and higher-order schemes (such as those of Milshtein or Talay)
TL;DR: In this paper, the authors examined the thermodynamic properties of 27 monomer lattice copolymer copolymers and found two independent transitions: a collapse transition to compact states and a folding transition from compact states to the native state.
Abstract: Using Monte Carlo dynamics and the Monte Carlo histogram method, the simple three‐dimensional 27 monomer lattice copolymer is examined in depth. The thermodynamic properties of various sequences are examined contrasting the behavior of good and poor folding sequences. The good (fast folding) sequences have sharp well‐defined thermodynamic transitions while the slow folding sequences have broad ones. We find two independent transitions: a collapse transition to compact states and a folding transition from compact states to the native state. The collapse transition is second‐order‐like, while folding is first‐order‐like. The system is also studied as a function of the energy parameters. In particular, as the average energetic drive toward compactness is reduced, the two transitions approach each other. At zero average drive, collapse and folding occur almost simultaneously; i.e., the chain collapses directly into the native state. At a specific value of this energy drive the folding temperature falls below ...
TL;DR: In this article, it was shown that the recently developed configurational-bias Monte Carlo technique can be used in a grand canonical Monte Carlo simulation to make the insertion of chain molecules possible, and the use of this technique is illustrated by calculations of the adsorption isotherms of butane and hexane in the zeolite silicate.
Abstract: Simulations of open systems are performed conveniently in the grand canonical ensemble. For chain molecules simulations of this type converge very poorly because of the very low probability of a successful insertion in the exchange step. Here, it is shown that the recently developed configurational-bias Monte Carlo technique can be used in a grand canonical Monte Carlo simulation to make the insertion of chain molecules possible. The use of this technique is illustrated by calculations of the adsorption isotherms of butane and hexane in the zeolite silicate.
TL;DR: The phase diagram is determined for the first time for a lattice system of biaxial particles interacting with a second rank anisotropic potential using Monte Carlo simulations for a number of values of the molecular biaXiality.
Abstract: We have determined the phase diagram for a lattice system of biaxial particles interacting with a second rank anisotropic potential using Monte Carlo simulations for a number of values of the molecular biaxiality. We find increasing differences from mean field theory as the biaxiality increases. We have also calculated for the first time the full set of second rank biaxial and uniaxial order parameters and their temperature dependence, and on this basis we comment on the difficulties of measuring phase biaxiality by NMR.
TL;DR: In this article, a theory for nonuniform polymer melts is presented, which combines density functional theory with Monte Carlo methods, treating the ideal gas functional exactly via a single chain simulation and using the weighted density approximation for the excess free energy functional.
Abstract: A theory for nonuniform polymer melts is presented, which combines density functional theory with Monte Carlo methods. The theory treats the ideal gas functional exactly via a single chain simulation and uses the weighted density approximation for the excess free energy functional. The bulk fluid properties required in the theory are obtained from a generalized Flory equation of state. The predictions of the theory are compared to Monte Carlo simulations for the density profiles of semiflexible polymer melts confined between flat plates. Good agreement between theory and simulation is found for 3mers and 20mers and for several densities and molecular stiffnesses.
TL;DR: In this paper, the authors present Monte Carlo methods with a correct real-time dependence for simulating chemical reactions on a surface that have reaction-rate constants that may vary in time.
TL;DR: A new ensemble for Monte Carlo simulations, in which each state is assigned a statistical weight $1/k$, where $k$ is the number of states with smaller or equal energy, which has robust ergodicity properties and gives significant weight to the ground state.
Abstract: We propose a new ensemble for Monte Carlo simulations, in which each state is assigned a statistical weight $1/k$, where $k$ is the number of states with smaller or equal energy. This ensemble has robust ergodicity properties and gives significant weight to the ground state, making it effective for hard optimization problems. It can be used to find free energies at all temperatures and picks up aspects of critical behaviour (if present) without any parameter tuning. We test it on the travelling salesperson problem, the Edwards-Anderson spin glass and the triangular antiferromagnet.
TL;DR: In this paper, a multi-canonical Monte Carlo method is proposed to sample across an extended space of macro-states, showing that a good approximation to this distribution may be generated efficiently by exploiting measurements of the transition rate between macro states, in simulations launched from sub-dominant macro states.
Abstract: We present a study of the multi-canonical Monte Carlo method which constructs and exploits Monte Carlo procedures that sample across an extended space of macrostates. We examine the strategies by which the sampling distribution can be constructed, showing, in particular, that a good approximation to this distribution may be generated efficiently by exploiting measurements of the transition rate between macrostates, in simulations launched from sub-dominant macrostates. We explore the utility of the method in the measurement of absolute free energies, and how it compares with traditional methods based on path integration. We present new results revealing the behaviour of the magnetization distribution of a critical finite-sized magnet, for magnetization values extending from the scaling region all the way to saturation.
TL;DR: In this paper, a new pressure coupling method is described that combines Monte Carlo volume-space sampling with traditional molecular dynamics calculations to simulate the physical properties of molecular systems under standard conditions, where the pressure is maintained by accepting or rejecting volume moves of newly propagated configurations using the Metropolis algorithm with probability P(ΔV) = min (1, exp (( −1 kT 0 ){ΔE + P 0 ΔV − NkT 0 ln [ (V + ΔV) V ]})).
TL;DR: In this paper, a class of Monte Carlo algorithms incorporating absorbing Markov chains is presented to study the escape from the metastable state in the two-dimensional square-lattice nearest-neighbor Ising ferromagnet in an unfavorable applied field.
Abstract: A class of Monte Carlo algorithms which incorporate absorbing Markov chains is presented. In a particular limit, the lowest order of these algorithms reduces to the $n$-fold way algorithm. These algorithms are applied to study the escape from the metastable state in the two-dimensional square-lattice nearest-neighbor Ising ferromagnet in an unfavorable applied field, and the agreement with theoretical predictions is very good. It is demonstrated that the higher-order algorithms can be many orders of magnitude faster than either the traditional Monte Carlo or $n$-fold way algorithms.
12 Jun 1995
TL;DR: A 5D tree structure to cache illumination information gained during Monte Carlo ray tracing is presented and it is adaptive and makes abstraction of the complexity of the input scene automatically.
Abstract: In this paper we present a 5D tree structure to cache illumination information gained during Monte Carlo ray tracing. The structure is elegant and simple to use. It is adaptive and makes abstraction of the complexity of the input scene automatically.
TL;DR: This work proposes a method which allows the parallel generation of MC moves, and which is especially useful for simulations with unavoidably low acceptance rates, such as for long chain molecules.
Abstract: The Monte Carlo (MC) method is an important tool in sampling the state space of a chosen statistical ensemble. It allows the study of thermodynamic averages of configurational properties by generating ``moves'' in a system and accepting or rejecting the thus generated new state depending on the energy of the new system and/or a random choice. These moves are intrinsically sequential and complicate parallel implementation. We propose a method which allows the parallel generation of MC moves, and which is especially useful for simulations with unavoidably low acceptance rates, such as for long chain molecules.
TL;DR: The proposed algorithm yields accurate results when it is applied to test problems such as the hydrogen atom and the hydrogen molecule and an excellent description of several properties of a fully many-body problem such as liquid $^{4}\mathrm{He}$ at zero temperature is achieved.
Abstract: A Monte Carlo algorithm for computing quantum-mechanical expectation values of coordinate operators in many-body problems is presented The algorithm, which relies on the forward walking method, fits naturally in a Green's function Monte Carlo calculation, ie, it does not require side walks or a bilinear sampling method Our method evidences stability regions large enough to accurately sample unbiased pure expectation values The proposed algorithm yields accurate results when it is applied to test problems such as the hydrogen atom and the hydrogen molecule An excellent description of several properties of a fully many-body problem such as liquid $^{4}\mathrm{He}$ at zero temperature is achieved
TL;DR: In this paper, a new method is proposed for calculation of the chemical potential of macromolecules by computer simulation, where simulations are performed in an expanded ensemble whose states are defined by the length of a tagged molecule of variable size.
Abstract: A new method is proposed for calculation of the chemical potential of macromolecules by computer simulation. Simulations are performed in an expanded ensemble whose states are defined by the length of a tagged molecule of variable size. A configurational‐bias sampling and a preweighting scheme are introduced to facilitate transitions between such states. The usefulness of the method is illustrated by calculations of the chemical potential of hard chain molecules over a wide range of densities. The method proposed here is shown to offer significant advantages over other available methods for calculation of chemical potentials, particularly for long chain molecules at high densities.
TL;DR: A Monte Carlo method generates optimum many-body basis states for diagonalizing the Hamiltonian consisting of one- and two-body terms, which ensures that not only the ground state but also low-lying excited states are obtained with their wave functions.
Abstract: We propose a Monte Carlo method for solving the quantum many-body interacting systems. Mean fields dominating the structure of low-lying states are selected by a Monte Carlo method, which generates optimum many-body basis states for diagonalizing the Hamiltonian consisting of one- and two-body terms. Not only the ground state but also low-lying excited states are obtained with their wave functions. Results are examined by comparison to exact values.
TL;DR: Based on the scaling relation for the dynamics at the early time, a new method is proposed to measure both the static and dynamic critical exponents in the two dimensional Ising model.
Abstract: Based on the scaling relation for the dynamics at the early time, a new method is proposed to measure both the static and dynamic critical exponents. The method is applied to the two-dimensional Ising model. The results are in good agreement with the existing results. Since the measurement is carried out in the initial stage of the relaxation process starting from independent initial configurations, our method is efficient.
TL;DR: In this article, a Monte Carlo algorithm is proposed to expand a CI expansion by randomly including new terms which interact with those terms already present in the expansion, and a solution of the variational problem is then performed for these randomly chosen configurations and a selection criterium for the resulting CI coefficients is applied.
Abstract: Full configuration interaction (FCI) calculations are useful as benchmarks for approximate techniques used in quantum chemistry: they are indeed the desired goal for all energy and wave function calculations in that they are the best solution to the Schrodinger equation within a finite basis Ansatz. Application of the method is limited due to the rapid increase in the number of configurations as the basis set size is increased. Many means have been applied to limit the number of terms in the expansion with the best known method being the singles and doubles expansion CI(SD). A Monte Carlo algorithm is proposed here whereby a CI expansion is allowed to expand by randomly including new terms which interact with those terms already present in the expansion. Solution of the variational problem is then performed for these randomly chosen configurations and a selection criterium for the resulting CI coefficients is applied. Repeated application of this method allows for estimates of the FCI energy. Calculations...
TL;DR: In this article, a Monte Carlo method for the simulation of spin models with ferromagnetic long-range interactions is introduced, in which the amount of time per spin-flip operation is independent of the system size, in spite of the fact that the interactions between each spin and all other spins are taken into account.
Abstract: We introduce a Monte Carlo method for the simulation of spin models with ferromagnetic long-range interactions in which the amount of time per spin-flip operation is independent of the system size, in spite of the fact that the interactions between each spin and all other spins are taken into account. We work out two algorithms for the q-state Potts model and discuss the generalization to systems with other interactions and to O(n) models. We illustrate the method with a simulation of the mean-field Ising model, for which we have also analytically calculated the leading finite-size correction to the dimensionless amplitude ratio 2/ at the critical temperature.