Ronald P. White

Lower and upper bounds for the absolute free energy by the hypothetical scanning Monte Carlo method: Application to liquid argon and water

The hypothetical scanning (HS) method is a general approach for calculating the absolute entropy S and free energy F by analyzing Boltzmann samples obtained by Monte Carlo or molecular dynamics techniques. With HS applied to a fluid, each configuration i of the sample is reconstructed by gradually placing the molecules in their positions at i using transition probabilities (TPs). At each step of the process the system is divided into two parts, the already treated molecules (the past), which are fixed, and the as yet unspecified (mobile) future molecules. Obtaining the TP exactly requires calculating partition functions over all positions of the future molecules in the presence of the frozen past, thus it is customary to invoke various approximations to best represent these quantities. In a recent publication [Proc. Natl. Acad. Sci. USA 101, 9235 (2004)] we developed a version of HS called complete HSMC, where each TP is calculated from an MC simulation involving all of the future molecules (the complete future); the method was applied very successfully to Lennard-Jones systems (liquid argon) and a box of TIP3P water molecules. In its basic implementation the method provides lower and upper bounds for F, where the latter can be evaluated only for relatively small systems. Here we introduce a new expression for an upper bound, which can be evaluated for larger systems. We also propose a new exact expression for F and verify its effectiveness. These free energy functionals lead to significantly improved accuracy (as applied to the liquid systems above) which is comparable to our thermodynamic integration results. We formalize and discuss theoretical aspects of HSMC that have not been addressed in previous studies. Additionally, several functionals are developed and shown to provide the free energy through the analysis of a single configuration.

Absolute entropy and free energy of fluids using the hypothetical scanning method. I. Calculation of transition probabilities from local grand canonical partition functions

The hypothetical scanning (HS) method provides the absolute entropy and free energy from a Boltzmann sample generated by Monte Carlo, molecular dynamics or any other exact simulation procedure. Thus far HS has been applied successfully to magnetic and polymer chain models; in this paper and the following one it is extended to fluid systems by treating a Lennard-Jones model of argon. With HS a probability Pi approximating the Boltzmann probability of system configuration i is calculated with a stepwise reconstruction procedure, based on adding atoms gradually layer-by-layer to an initially empty volume, where they are replaced in their positions at i. At each step a transition probability (TP) is obtained from local grand canonical partition functions calculated over a limited space of the still unvisited (future) volume, the larger this space the better the approximation. Pi is the product of the step TPs, where lnu200aPi is an upper bound of the absolute entropy, which leads to upper and lower bounds for the...

Absolute entropy and free energy of fluids using the hypothetical scanning method. II. Transition probabilities from canonical Monte Carlo simulations of partial systems

A variant of the hypothetical scanning (HS) method for calculating the absolute entropy and free energy of fluids is developed, as applied to systems of Lennard-Jones atoms (liquid argon). As in the preceding paper (Paper I), a probability Pi approximating the Boltzmann probability of system configuration i, is calculated with a reconstruction procedure based on adding the atoms gradually to an initially empty volume, where they are placed in their positions at i; in this process the volume is divided into cubic cells, which are visited layer-by-layer, line-by-line. At each step a transition probability (TP) is calculated and the product of all the TPs leads to Pi. At step k, k−1 cells have already been treated, where among them Nk are occupied by an atom. A canonical metropolis Monte Carlo (MC) simulation is carried out over a portion of the still unvisited (future) volume thus providing an approximate representation of the N−Nk as yet untreated (future) atoms. The TP of target cell k is determined from ...

Calculation of the entropy of random coil polymers with the hypothetical scanning Monte Carlo method

Hypothetical scanning Monte Carlo (HSMC) is a method for calculating the absolute entropy S and free energy F from a given MC trajectory developed recently and applied to liquid argon, TIP3P water, and peptides. In this paper HSMC is extended to random coil polymers by applying it to self-avoiding walks on a square lattice--a simple but difficult model due to strong excluded volume interactions. With HSMC the probability of a given chain is obtained as a product of transition probabilities calculated for each bond by MC simulations and a counting formula. This probability is exact in the sense that it is based on all the interactions of the system and the only approximation is due to finite sampling. The method provides rigorous upper and lower bounds for F, which can be obtained from a very small sample and even from a single chain conformation. HSMC is independent of existing techniques and thus constitutes an independent research tool. The HSMC results are compared to those obtained by other methods, and its application to complex lattice chain models is discussed; we emphasize its ability to treat any type of boundary conditions for which a reference state (with known free energy) might be difficult to define for a thermodynamic integration process. Finally, we stress that the capability of HSMC to extract the absolute entropy from a given sample is important for studying relaxation processes, such as protein folding.

Phase changes in Lennard-Jones mixed clusters with composition ArnXe6−n(n=0,1,2)

We have carried out parallel tempering Monte Carlo calculations on the binary six-atom mixed Lennard-Jones clusters, Ar(n)Xe(6-n) (n=0,1,2). We have looked at the classical configurational heat capacity C(V)(T) as a probe of phase behavior. All three clusters show a feature in the heat capacity in the region of 15-20 K. The Ar(2)Xe(4) cluster exhibits a further peak in the heat capacity near 7 K. We have also investigated dynamical properties of the Ar(2)Xe(4) cluster as a function of temperature using molecular dynamics. We report the interbasin isomerization rate and the bond fluctuation parameter obtained from these calculations. At 7 K, the isomerization rate is on the order of 0.01 ns(-1); at 20 K, the isomerization rate is greater than 10 ns(-1). Furthermore, at 7 K, the bond fluctuation parameter is less than 3%; at 20 K, it is in the range of 10-15% (depending on the sampling time used). Using this information, together with Monte Carlo quenching data, we assign the 15-20 K feature in the heat capacity to a solid-liquid phase change and the 7-K peak to a solid-solid phase change. We believe this is the smallest Lennard-Jones cluster system yet shown to exhibit solid-solid phase change behavior.

Free volume hypothetical scanning molecular dynamics method for the absolute free energy of liquids.

The hypothetical scanning (HS) method is a general approach for calculating the absolute entropy, S, and free energy, F, by analyzing Boltzmann samples obtained by Monte Carlo (MC) or molecular dynamics (MD) techniques. With HS applied to a fluid, each configuration i of the sample is reconstructed by gradually placing the molecules in their positions at i using transition probabilities (TPs). With our recent version of HS, called HSMC-EV, each TP is calculated from MC simulations, where the simulated particles are excluded from the volume reconstructed in previous steps. In this paper we remove the excluded volume (EV) restriction, replacing it by a free volume (FV) approach. For liquid argon, HSMC-FV leads to an improvement in efficiency over HSMC-EV by a factor of 2-3. Importantly, the FV treatment greatly simplifies the HS implementation for liquids, allowing a much more natural application of the method for MD simulations. Given the success and popularity of MD, the present development of the HSMD method for liquids is an important advancement for HS methodology. Results for the HSMD-FV approach presented here agree well with our HSMC and thermodynamic integration results. The efficiency of HSMD-FV is equivalent to HSMC-EV. The potential use of HSMC(MD)-FV in protein systems with explicit water is discussed.