Chemical potential,Helmholtz free energy and entropy of argon with kinetic Monte Carlo simulation

We present a method based on kinetic Monte Carlo (kMC) to determine the chemical potential, Helmholtz free energy and entropy of a fluid within the course of a simulation. The procedure requires no recourse to auxiliary methods to determine the chemical potential, such as the implementation of a Widom scheme in Metropolis Monte Carlo simulations, as it is determined within the course of the simulation. The equation for chemical potential is proved, for the first time in the literature, to have a direct connection with inverse Widom potential theory in using real molecules rather than ghost molecules. We illustrate this new procedure by several examples, including fluid argon and adsorption of argon as a non-uniform fluid on a graphite surface and in slit pores.     

Application of the kinetic Monte Carlo method in the microscopic description of argon adsorption on graphite

We present an application of kinetic Monte Carlo (kMC) in the canonical ensemble to a calculation of vapour liquid equilibrium and to describe the adsorption of argon on a flat graphite surface and in a slit-like graphitic pore. Simulations at 77 and 87.3?K accurately describe the experimental data. The kMC method is simple to implement and, unlike conventional Monte Carlo, no rejection trials are necessary. The only move is a uniform sampling of the volume space, which makes the determination of the chemical potential straightforward using real particles in the simulation, in the same spirit as the Widom inverse potential distribution. This avoids the need to freeze the real particles before the trial insertion of test particles as is necessary in other methods, such as the Widom method and its variants.     

Cavity-bias sampling in reaction ensemble Monte Carlo simulations

A methodology is presented to sample efficiently configurations of reacting mixtures in the reaction ensemble Monte Carlo simulation technique. A cavity-biasing scheme is used, which more effectively samples configurations than conventional random sampling. Akin to other biasing schemes that are implemented into insertion-based Monte Carlo methods such as Gibbs ensemble Monte Carlo, the method presented here searches for space in the reacting mixture whereby the insertion of a product molecule is energetically favoured. This sampling bias is then corrected in the acceptance criteria. The approach allows for the study of reacting mixtures at high density as well as for polyatomic molecular species. For some cases, the method is shown to increase the efficiency of the reaction steps by a factor greater than 20. The approach is shown to be readily generalized to other biasing schemes such as orientational-biasing of polar molecules and configurational-biasing of chain-like molecules.     

Quantative measure of efficiency of Monte Carlo simulations

An easily applied, physically motivated algorithm for determining the efficiency of Monte Carlo simulations is introduced. The theoretical basis for the algorithm is developed. As an illustration we apply the method to the Lennard-Jones liquid near the triple point. We show that an acceptance ratio of 0.2 is twice as efficient for the purpose of generating a satisfactory sample as is an acceptance ratio of 0.5. There is a strong correlation between the efficiency measure and the diffusion rate of liquid particles during the simulation. We argue that the optimal value of the acceptance ratio is calculable from short Monte Carlo simulations. The method is very general and is applicable to Monte Carlo simulations involving arbitrary potentials.     

Next-to-next-to-leading-order subtraction formalism in hadron collisions and its application to Higgs-boson production at the large hadron collider

We consider higher-order QCD corrections to the production of colorless high-mass systems (lepton pairs, vector bosons, Higgs bosons, etc.) in hadron collisions. We propose a new formulation of the subtraction method to numerically compute arbitrary infrared-safe observables for this class of processes. To cancel the infrared divergences, we exploit the universal behavior of the associated transverse-momentum (qT) distributions in the small-qT region. The method is illustrated in general terms up to the next-to-next-to-leading order in QCD perturbation theory. As a first explicit application, we study Higgs-boson production through gluon fusion. Our calculation is implemented in a parton level Monte Carlo program that includes the decay of the Higgs boson into two photons. We present selected numerical results at the CERN Large Hadron Collider.     

Structural properties of low-density liquid alkali metals

The static structure factors of liquid alkali metals have been modelled at temperatures close to their melting points and a few higher temperatures using the reverse Monte Carlo (RMC) method. The positions of 5000 atoms in a box, with full periodicity, were altered until the experimental diffraction data of the structure factor agrees with the associated model structure factor within the errors. The model generated is then analysed. The position of the first peak of the pair distribution function g(r) does not show any significant temperature dependence and the mean bond lengths can be approximated within an interval of 3.6–5.3 Å, 4.5–6.6 Å, 4.8–6.7 Å and 5.1–7.3 Å for Na, K, Rb and Cs respectively. The cosine bond distributions show similar trend with the flattening up of the first peak with increase in temperature. In addition, the coordination numbers of these liquid metals are high due to the presence of non-covalent bonding between them. On the average, we surmise that the coordination number decreases with increase in temperature     

Application of Tube Dynamics to Non-Statistical Reaction Processes

A technique based on dynamical systems theory is introduced for the computation of lifetime distributions and rates of chemical reactions and scattering phenomena, even in systems that exhibit non-statistical behavior. In particular, we merge invariant manifold tube dynamics with Monte Carlo volume determination for accurate rate calculations. This methodology is applied to a three-degree-of-freedom model problem and some ideas on how it might be extended to higher-degree-of-freedom systems are presented.     

Structure of polymer solutions at interfaces: a Monte Carlo simulation study

The canonical ensemble Monte Carlo method is applied to study the structure of polymer solutions confined between surfaces. The polymer molecules are modeled as fused-sphere freely rotating chains with fixed bond length and bond angles and the solvent as hard spheres. The simulation results for the configurational and conformational properties of the chains are presented with varying interfacial distances, chain concentrations, and chain lengths. The chains are depleted at the wall at lower density, which, however, becomes less at higher density. With an increase in the interfacial distance, the enhancement/depletion of the chains at the wall becomes more marked. At all interfacial distances and chain lengths, increasing the concentration of the solvent makes the oscillation in the density profile of the chains more pronounced. Conformational properties provide important indications regarding the behaviour of chains as they approach surfaces.     

Grand Canonical Ensemble Monte Carlo Simulation of Depletion Interactions in Colloidal Suspensions

Depletion interactions in colloidal suspensions confined between two parallel plates are investigated by using acceptance ratio method with grand canonical ensemble Monte Carlo simulation. The numerical results show that both the depletion potential and depletion force are affected by the confinement from the two parallel plates. Furthermore, it is found that in the grand canonical ensemble Monte Carlo simulation, the depletion interactions are strongly affected by the generalized chemical potential.     

Convergence properties of Monte Carlo functional expansion tallies

The functional expansion tally (FET) is a method for constructing functional estimates of unknown tally distributions via Monte Carlo simulation. This technique uses a Monte Carlo calculation to estimate expansion coefficients of the tally distribution with respect to a set of orthogonal basis functions. The rate at which the FET approximation converges to the true distribution as the expansion order is increased is developed. For sufficiently smooth distributions the FET is shown to converge faster, and achieve a lower residual error, than a histogram approximation.     

An algorithm for calculating the chemical potential in associating and reacting fluids

We present a Monte Carlo algorithm to determine the chemical potential of associating and reacting fluids. The algorithm is based on the fact that the chemical potential of a component is the same in the monomer (unbonded) state as in any bonded state. We demonstrate that the chemical potential of the unbonded specie can be calculated at relatively low cost and with high accuracy. The algorithm is applicable to both homogeneous as well as inhomogeneous systems. We compare the results of the presented algorithm against the findings of Widom's single stage particle insertion method for four commonly encountered inhomogeneous systems of associating fluids in phase equilibria studies. The constancy of the chemical potential throughout an inhomogeneous system under equilibrium is used as an independent test of the algorithm. The uncertainty in chemical potential values over the system for the cases studied was on an average 30 times smaller in the new algorithm, with at least 5 times fewer insertions than in the traditional Widom's method.     

The structure of para-hydrogen clusters

The path integral Monte Carlo calculated radial distributions of para-hydrogen clusters $({\rm p}\text{-}{\rm H}_2)_N$ consisting of N = 4-40 molecules interacting via a Lennard-Jones potential at $T=1.5~{\rm K}$ show evidence for additional peaks compared to radial distributions calculated by diffusion Monte Carlo ( $T=0~{\rm K}$ ) and path integral Monte Carlo at $T \leq 0.5~{\rm K}$ . The difference in structures is attributed to quantum delocalization at the lowest temperature. The new structures at finite temperatures appear to be consistent with classical structures calculated for an effective Morse potential, which in order to account for the large zero point energy, is substantially softer than the Lennard-Jones potential.     

Helical structures from an isotropic homopolymer model

We present Monte Carlo simulation results for square-well homopolymers at a series of bond lengths. Although the model contains only isotropic pairwise interactions, under appropriate conditions this system shows spontaneous chiral symmetry breaking, where the chain exists in either a left- or a right-handed helical structure. We investigate how this behavior depends upon the ratio between bond length and monomer radius.     

Anomalous high resolution N.M.R. line-widths in plastic crystals

An optimized version of the force bias scheme is presented for the Monte Carlo simulation of water in which the random walk of the individual molecule is biased in the direction of the force and torque acting on the molecule. A new criterion is developed to judge the efficiency of sampling the configuration space by studying the translational and rotational diffusion of individual molecules during the random walk. The force bias method is compared with the uniform sampling method using ST2 water as an example, and with molecular dynamics. Similarities and differences between molecular dynamics and Monte Carlo are discussed with respect to pair correlations and energy distributions.     

Long jumps in the surface diffusion of large molecules

We have studied the diffusion of the two organic molecules DC and HtBDC on the Cu(110) surface by scanning tunneling microscopy. Surprisingly, we find that long jumps, spanning multiple lattice spacings, play a dominating role in the diffusion of these molecules--the root-mean-square jump lengths are as large as 3.9 and 6.8 lattice spacings, respectively. The presence of long jumps is revealed by a new and simple method of analysis, which is tested by kinetic Monte Carlo simulations.     

Quantum correlations of bosons and fermions produced in heavy ion collisions

A quantum statistical approach to simulate Bose-Einstein correlations of many boson systems is presented. The extension to fermions and Coulomb-interacting bosons is discussed. This approach appears to be very efficient and is applicable also to cases with very high multiplicities. A technique to analyze pion correlations via their counting distributions is developed. The exact counting distributions for bosons as well as for fermions are derived. The problem of incomplete data occuring in detectors with an acceptance angle <> is studied. The application to Monte Carlo generated pion distributions show that this technique offers a valuable supplement to the usual Hanbury-Brown, Twiss method.     

Monte Carlo simulations in the isothermal—isobaric ensemble: the requirement of a ‘shell’ molecule and simulations of small systems

A modification of the widely used Monte Carlo method for determining thermophysical properties in the isothermal-isobaric ensemble is presented. The new Monte Carlo method, now consistent with recent derivations describing the proper statistical mechanical formulation of the constant pressure ensemble for small systems, requires a ‘shell’ molecule to uniquely identify the volume of the system, thereby avoiding the redundant counting of configurations. Ensemble averages obtained with the new algorithm differ from averages calculated with the old Monte Carlo method, particularly for small system sizes, although both sets of averages become equal in the thermodynamic limit. Monte Carlo simulations in the constant pressure ensemble applied to the Lennard-Jones fluid demonstrate these differences for small systems. Peculiarities of small systems are also discussed, revealing that ‘shape’ is an important thermodynamic variable. Finally, an extension of the Monte Carlo method to mixtures is presented.     

(3 1)-Dimensional Quantum Mechanics from Monte Carlo Hamiltonian: Harmonic Oscillator

In Lagrangian formulation, it is extremely difficult to compute the excited spectrum and wavefunctions ora quantum theory via Monte Carlo methods. Recently, we developed a Monte Carlo Hamiltonian method for investigating this hard problem and tested the algorithm in quantum-mechanical systems in 1 1 and 2t1 dimensions. In this paper we apply it to the study of thelow-energy quantum physics of the (3 1)-dimensional harmonic oscillator.``     

Stark-potential evaporative cooling of polar molecules in a novel optical-access opened electrostatic trap

We propose a novel optical-access opened electrostatic trap to study the Stark-potential evaporative cooling of polar molecules by using two charged disk electrodes with a central hole of radius r0= 1.5 mm, and derive a set of new analytical equations to calculate the spatial distributions of the electrostatic field in the above charged-disk layout. Afterwards, we calculate the electric-field distributions of our electrostatic trap and the Stark potential for cold ND3 molecules, and analyze the dependences of both the electric field and the Stark potential on the geometric parameters of our charged-disk scheme,and find an optimal condition to form a desirable trap with the same trap depth in the x, y, and z directions. Also, we propose a desirable scheme to realize an efficient loading of cold polar molecules in the weak-field-seeking states, and investigate the dependences of the loading efficiency on both the initial forward velocity of the incident molecular beam and the loading time by Monte Carlo simulations. Our study shows that the maximal loading efficiency of our trap scheme can reach about 95%, and the corresponding temperature of the trapped cold molecules is about 28.8 m K. Finally, we study the Stark-potential evaporative cooling for cold polar molecules in our trap by the Monte Carlo method, and find that our simulated evaporative cooling results are consistent with our developed analytical model based on trapping-potential evaporative cooling.