Thermodynamic integration methods, infinite swapping, and the calculation of generalized averages.

In the present paper we examine the risk-sensitive and sampling issues associated with the problem of calculating generalized averages. By combining thermodynamic integration, stationary phase Monte Carlo, and infinite swapping techniques, we develop an approach for such problems and explore its utility for a prototypical class of applications.

On performance measures for infinite swapping Monte Carlo methods.

We introduce and illustrate a number of performance measures for rare-event sampling methods. These measures are designed to be of use in a variety of expanded ensemble techniques including parallel tempering as well as infinite and partial infinite swapping approaches. Using a variety of selected applications, we address questions concerning the variation of sampling performance with respect to key computational ensemble parameters.

Spatial Averaging: Sampling Enhancement for Exploring Configurational Space of Atomic Clusters and Biomolecules.

Spatial averaging Monte Carlo (SA-MC) is an efficient algorithm dedicated to the study of rare-event problems. At the heart of this method is the realization that from the equilibrium density a related, modified probability density can be constructed through a suitable transformation. This new density is more highly connected than the original density, which increases the probability for transitions between neighboring states, which in turn speeds up the sampling. The first successful investigations included the diffusion of small molecules in condensed phase environments and characterization of the metastable states of the migration of the CO ligand in myoglobin. In the present work, a general and robust implementation including rotational and torsional moves in the CHARMM molecular modeling software is introduced. Also, a procedure to estimate unbiased properties is proposed in order to compute thermodynamic observables. These procedures are suitable to study a range of topical systems including Lennard-Jones clusters of different sizes and the blocked alanine dipeptide (Ala)2 in implicit and explicit solvent. In all cases, SA-MC is found to outperform standard Metropolis simulations in sampling configurational space at little extra computational expense. The results for (Ala)2 in explicit solvent are in good agreement with previous umbrella sampling simulations.

Overcoming the Rare Event Sampling Problem in Biological Systems with Infinite Swapping.

Infinite swapping (INS) is a recently developed method to address the rare event sampling problem. For INS, an expanded computational ensemble composed of a number of replicas at different temperatures is used, similar to the widely used parallel tempering (PT) method. While the basic concept of PT is to sample various replicas of the system at different temperatures and exchange information between the replicas occasionally, INS uses the symmetrized distribution of configurations in temperature space, which corresponds to the infinite swapping limit of PT. The effect of this symmetrization and the enhanced information exchange between replicas is evaluated for three different biological systems representing different sampling problems in biology: (1) blocked alanine dipeptide, which is a small system and therefore optimal to evaluate sampling efficiency quantitatively, (2) Villin headpiece, which is used as a test case for the protein folding process, and (3) neuroglobin, which is used to evaluate the effects of enhanced information exchange between replicas for sampling the substate space of a folded protein. For these three test systems, PINS is compared to PT, and it is found that in all cases the sampling with PINS is substantially more efficient.

Rare-event sampling: occupation-based performance measures for parallel tempering and infinite swapping Monte Carlo methods.

In the present paper we identify a rigorous property of a number of tempering-based Monte Carlo sampling methods, including parallel tempering as well as partial and infinite swapping. Based on this property we develop a variety of performance measures for such rare-event sampling methods that are broadly applicable, informative, and straightforward to implement. We illustrate the use of these performance measures with a series of applications involving the equilibrium properties of simple Lennard-Jones clusters, applications for which the performance levels of partial and infinite swapping approaches are found to be higher than those of conventional parallel tempering.

Atomistic modeling of thermodynamic equilibrium and polymorphism of iron.

We develop two new modified embedded-atom method (MEAM) potentials for elemental iron, intended to reproduce the experimental phase stability with respect to both temperature and pressure. These simple interatomic potentials are fitted to a wide variety of material properties of bcc iron in close agreement with experiments. Numerous defect properties of bcc iron and bulk properties of the two close-packed structures calculated with these models are in reasonable agreement with the available first-principles calculations and experiments. Performance at finite temperatures of these models has also been examined using Monte Carlo simulations. We attempt to reproduce the experimental iron polymorphism at finite temperature by means of free energy computations, similar to the procedure previously pursued by Müller et al (2007 J. Phys.: Condens. Matter 19 326220), and re-examine the adequacy of the conclusion drawn in the study by addressing two critical aspects missing in their analysis: (i) the stability of the hcp structure relative to the bcc and fcc structures and (ii) the compatibility between the temperature and pressure dependences of the phase stability. Using two MEAM potentials, we are able to represent all of the observed structural phase transitions in iron. We discuss that the correct reproductions of the phase stability among three crystal structures of iron with respect to both temperature and pressure are incompatible with each other due to the lack of magnetic effects in this class of empirical interatomic potential models. The MEAM potentials developed in this study correctly predict, in the bcc structure, the self-interstitial in the (110) orientation to be the most stable configuration, and the screw dislocation to have a non-degenerate core structure, in contrast to many embedded-atom method potentials for bcc iron in the literature.

An infinite swapping approach to the rare-event sampling problem.

We describe a new approach to the rare-event Monte Carlo sampling problem. This technique utilizes a symmetrization strategy to create probability distributions that are more highly connected and, thus, more easily sampled than their original, potentially sparse counterparts. After discussing the formal outline of the approach and devising techniques for its practical implementation, we illustrate the utility of the technique with a series of numerical applications to Lennard-Jones clusters of varying complexity and rare-event character.

Convergence characteristics of the cumulant expansion for Fourier path integrals.

The cumulant representation of the Fourier path integral method is examined to determine the asymptotic convergence characteristics of the imaginary-time density matrix with respect to the number of path variables N included. It is proved that when the cumulant expansion is truncated at order p, the asymptotic convergence rate of the density matrix behaves like N(-(2p+1)). The complex algebra associated with the proof is simplified by introducing a diagrammatic representation of the contributing terms along with an associated linked-cluster theorem. The cumulant terms at each order are expanded in a series such that the asymptotic convergence rate is maintained without the need to calculate the full cumulant at order p. Using this truncated expansion of each cumulant at order p, the numerical cost in developing Fourier path integral expressions having convergence order N(-(2p+1)) is shown to be approximately linear in the number of required potential energy evaluations making the method promising for actual numerical implementation.

Spatial averaging for small molecule diffusion in condensed phase environments.

Spatial averaging is a new approach for sampling rare-event problems. The approach modifies the importance function which improves the sampling efficiency while keeping a defined relation to the original statistical distribution. In this work, spatial averaging is applied to multidimensional systems for typical problems arising in physical chemistry. They include (I) a CO molecule diffusing on an amorphous ice surface, (II) a hydrogen molecule probing favorable positions in amorphous ice, and (III) CO migration in myoglobin. The systems encompass a wide range of energy barriers and for all of them spatial averaging is found to outperform conventional Metropolis Monte Carlo. It is also found that optimal simulation parameters are surprisingly similar for the different systems studied, in particular, the radius of the point cloud over which the potential energy function is averaged. For H(2) diffusing in amorphous ice it is found that facile migration is possible which is in agreement with previous suggestions from experiment. The free energy barriers involved are typically lower than 1 kcal/mol. Spatial averaging simulations for CO in myoglobin are able to locate all currently characterized metastable states. Overall, it is found that spatial averaging considerably improves the sampling of configurational space.

Finite-temperature quantum simulations of mixed rare gas clusters.

Finite-temperature quantum Monte Carlo simulations are presented for mixed neon/argon rare gas clusters containing up to n=10 atoms. For the smallest clusters (n=3) comparison with rigorous bound state calculations and experiments shows that the present approach is accurate to within fractions of wavenumbers for energies and to within a few percent or better for rotational constants. For larger cluster sizes, for which no rigorous quantum calculations are available, comparison with experiment becomes even more favorable. In all simulations accurate pair potentials for the rare gas-rare gas interactions are employed and comparison with high-level electronic structure calculations suggest that many-body interactions play a minor role. For the largest clusters investigated (Ne(4)Ar(6)) gradual melting of the neon phase is observed while the argon-phase remains structurally intact.

Comparative Monte Carlo efficiency by Monte Carlo analysis.

We propose a modified power method for computing the subdominant eigenvalue λ{2} of a matrix or continuous operator. While useful both deterministically and stochastically, we focus on defining simple Monte Carlo methods for its application. The methods presented use random walkers of mixed signs to represent the subdominant eigenfunction. Accordingly, the methods must cancel these signs properly in order to sample this eigenfunction faithfully. We present a simple procedure to solve this sign problem and then test our Monte Carlo methods by computing λ{2} of various Markov chain transition matrices. As |λ{2}| of this matrix controls the rate at which Monte Carlo sampling relaxes to a stationary condition, its computation also enabled us to compare efficiencies of several Monte Carlo algorithms as applied to two quite different types of problems. We first computed λ{2} for several one- and two-dimensional Ising models, which have a discrete phase space, and compared the relative efficiencies of the Metropolis and heat-bath algorithms as functions of temperature and applied magnetic field. Next, we computed λ{2} for a model of an interacting gas trapped by a harmonic potential, which has a mutidimensional continuous phase space, and studied the efficiency of the Metropolis algorithm as a function of temperature and the maximum allowable step size Δ. Based on the λ{2} criterion, we found for the Ising models that small lattices appear to give an adequate picture of comparative efficiency and that the heat-bath algorithm is more efficient than the Metropolis algorithm only at low temperatures where both algorithms are inefficient. For the harmonic trap problem, we found that the traditional rule of thumb of adjusting Δ so that the Metropolis acceptance rate is around 50% is often suboptimal. In general, as a function of temperature or Δ , λ{2} for this model displayed trends defining optimal efficiency that the acceptance ratio does not. The cases studied also suggested that Monte Carlo simulations for a continuum model are likely more efficient than those for a discretized version of the model.

The thermodynamic and ground state properties of the TIP4P water octamer.

Several stochastic simulations of the TIP4P [W. L. Jorgensen, J. Chandrasekhar, J. D. Madura, R. W. Impey, and M. L. Klein, J. Chem. Phys. 79, 926 (1983)] water octamer are performed. Use is made of the stereographic projection path integral and the Green's function stereographic projection diffusion Monte Carlo techniques, recently developed in one of our groups. The importance sampling for the diffusion Monte Carlo algorithm is obtained by optimizing a simple wave function using variational Monte Carlo enhanced with parallel tempering to overcome quasiergodicity problems. The quantum heat capacity of the TIP4P octamer contains a pronounced melting peak at 160 K, about 50 K lower than the classical melting peak. The zero point energy of the TIP4P water octamer is 0.0348+/-0.0002 hartree. By characterizing several large samples of configurations visited by both guided and unguided diffusion walks, we determine that both the TIP4P and the SPC [H. J. C. Berendsen, J. P. Postma, W. F. von Gunsteren, and J. Hermans, (Intermolecular Forces, Reidel, 1981). p. 331] octamer have a ground state wave functions predominantly contained within the D(2d) basin of attraction. This result contrasts with the structure of the global minimum for the TIP4P potential, which is an S(4) cube. Comparisons of the thermodynamic and ground-state properties are made with the SPC octamer as well.

A stereographic projection path integral study of the coupling between the orientation and the bending degrees of freedom of water.

A Monte Carlo path integral method to study the coupling between the rotation and bending degrees of freedom for water is developed. It is demonstrated that soft internal degrees of freedom that are not stretching in nature can be mapped with stereographic projection coordinates. For water, the bending coordinate is orthogonal to the stereographic projection coordinates used to map its orientation. Methods are developed to compute the classical and quantum Jacobian terms so that the proper infinitely stiff spring constant limit is recovered in the classical limit, and so that the nonconstant nature of the Riemann Cartan curvature scalar is properly accounted in the quantum simulations. The theory is used to investigate the effects of the geometric coupling between the bending and the rotating degrees of freedom for the water monomer in an external field in the 250 to 500 K range. We detect no evidence of geometric coupling between the bending degree of freedom and the orientations.

A constant entropy increase model for the selection of parallel tempering ensembles.

The present paper explores a simple approach to the question of parallel tempering temperature selection. We argue that to optimize the performance of parallel tempering it is reasonable to require that the increase in entropy between successive temperatures be uniform over the entire ensemble. An estimate of the system's heat capacity, obtained either from experiment, a preliminary simulation, or a suitable physical model, thus provides a means for generating the desired tempering ensemble. Applications to the two-dimensional Ising problem indicate that the resulting method is effective, simple to implement, and robust with respect to its sensitivity to the quality of the underlying heat capacity model.

Rigid quantum Monte Carlo simulations of condensed molecular matter: water clusters in the n=2-->8 range.

The numerical advantage of quantum Monte Carlo simulations of rigid bodies relative to the flexible simulations is investigated for some simple systems. The results show that if high frequency modes in molecular condensed matter are predominantly in the ground state, the convergence of path integral simulations becomes nonuniform. Rigid body quantum parallel tempering simulations are necessary to accurately capture thermodynamic phenomena in the temperature range where the dynamics are influenced by intermolecular degrees of freedom; the stereographic projection path integral adapted for quantum simulations of asymmetric tops is a significantly more efficient strategy compared with Cartesian coordinate simulations for molecular condensed matter under these conditions. The reweighted random series approach for stereographic path integral Monte Carlo is refined and implemented for the quantum simulation of water clusters treated as an assembly of rigid asymmetric tops.

Pressure dependent study of the solid-solid phase change in 38-atom Lennard-Jones cluster.

Phase change phenomena in clusters are often modeled by augmenting physical interaction potentials with an external constraining potential to handle evaporation processes in finite temperature simulations. These external constraining potentials exert a pressure on the cluster. The influence of this constraining pressure on phase change phenomena in 38-atom Lennard-Jones clusters is investigated, and it is demonstrated that modest changes in the parameters of the constraining potential can lead to an order of magnitude change in the constraining pressure. At sufficiently high pressures the solid to solidlike phase change region in the 38-atom Lennard-Jones cluster is completely eliminated.

Combining smart darting with parallel tempering using Eckart space: application to Lennard-Jones clusters.

The smart-darting algorithm is a Monte Carlo based simulation method used to overcome quasiergodicity problems associated with disconnected regions of configurations space separated by high energy barriers. As originally implemented, the smart-darting method works well for clusters at low temperatures with the angular momentum restricted to zero and where there are no transitions to permutational isomers. If the rotational motion of the clusters is unrestricted or if permutational isomerization becomes important, the acceptance probability of darting moves in the original implementation of the method becomes vanishingly small. In this work the smart-darting algorithm is combined with the parallel tempering method in a manner where both rotational motion and permutational isomerization events are important. To enable the combination of parallel tempering with smart darting so that the smart-darting moves have a reasonable acceptance probability, the original algorithm is modified by using a restricted space for the smart-darting moves. The restricted space uses a body-fixed coordinate system first introduced by Eckart, and moves in this Eckart space are coupled with local moves in the full 3N-dimensional space. The modified smart-darting method is applied to the calculation of the heat capacity of a seven-atom Lennard-Jones cluster. The smart-darting moves yield significant improvement in the statistical fluctuations of the calculated heat capacity in the region of temperatures where the system isomerizes. When the modified smart-darting algorithm is combined with parallel tempering, the statistical fluctuations of the heat capacity of a seven-atom Lennard-Jones cluster using the combined method are smaller than parallel tempering when used alone.

Broken-symmetry unrestricted hybrid density functional calculations on nickel dimer and nickel hydride.

In the present work we investigate the adequacy of broken-symmetry unrestricted density functional theory for constructing the potential energy curve of nickel dimer and nickel hydride, as a model for larger bare and hydrogenated nickel cluster calculations. We use three hybrid functionals: the popular B3LYP, Becke's newest optimized functional Becke98, and the simple FSLYP functional (50% Hartree-Fock and 50% Slater exchange and LYP gradient-corrected correlation functional) with two basis sets: all-electron (AE) Wachters+f basis set and Stuttgart RSC effective core potential (ECP) and basis set. We find that, overall, the best agreement with experiment, comparable to that of the high-level CASPT2, is obtained with B3LYP/AE, closely followed by Becke98/AE and Becke98/ECP. FSLYP/AE and B3LYP/ECP give slightly worse agreement with experiment, and FSLYP/ECP is the only method among the ones we studied that gives an unacceptably large error, underestimating the dissociation energy of Ni(2) by 28%, and being in the largest disagreement with the experiment and the other theoretical predictions. We also find that for Ni(2), the spin projection for the broken-symmetry unrestricted singlet states changes the ordering of the states, but the splittings are less than 10 meV. All our calculations predict a deltadelta-hole ground state for Ni(2) and delta-hole ground state for NiH. Upon spin projection of the singlet state of Ni(2), almost all of our calculations: Becke98 and FSLYP both AE and ECP and B3LYP/AE predict (1)(d(A)(x(2)-y(2)d(B)(x(2)-y(2)) or (1)(d(A)(xy) (d)(B)(xy)) ground state, which is a mixture of (1)Sigma(g) (+) and (1)Gamma(g). B3LYP/ECP predicts a (3)(d(A)(x(2)-y(2))d(B)(xy) (mixture of (3)Sigma(g) (-) and (3)Gamma(u)) ground state virtually degenerate with the (1)(d(A)(x(2)-y(2)d(B)(x)(2)-y(2)/(1)(d(A)(xy)D(B)(xy) state. The doublet delta-hole ground state of NiH predicted by all our calculations is in agreement with the experimentally predicted (2)Delta ground state. For Ni(2), all our results are consistent with the experimentally predicted ground state of 0(g) (+) (a mixture of (1)Sigma(g) (+) and (3)Sigma(g) (-)) or 0(u) (-) (a mixture of (1)Sigma(u) (-) and (3)Sigma(u) (+)).

On the encapsulation of nickel clusters by molecular nitrogen.

The structures and energetic effects of molecular nitrogen adsorbates on nickel clusters are investigated using an extended Huckel model coupled with two models of the adsorbate-nickel interaction. The potential parameters for the adsorbates are chosen to mimic experimental information about the binding strength of nitrogen on both cluster and bulk surface phases of nickel. The first model potential is a simple Lennard-Jones interaction that leads to binding sites in holes defined by sets of near-neighbor nickel atoms. The second model potential has a simple three-body form that forces the model nitrogen adsorbates to bind directly to single nickel atoms. Significant rearrangement of the core nickel structures are found in both models. A disconnectivity graph analysis of the potential energy surfaces implies that the rearrangements arise from low transition state barriers and the small differences between available isomers in the nickel core.

Phase changes in selected Lennard-Jones X13-nYn clusters.

Detailed studies of the thermodynamic properties of selected binary Lennard-Jones clusters of the type X13-nYn (where n=1, 2, 3) are presented. The total energy, heat capacity, and first derivative of the heat capacity as a function of temperature are calculated by using the classical and path integral Monte Carlo methods combined with the parallel tempering technique. A modification in the phase change phenomena from the presence of impurity atoms and quantum effects is investigated.