1,196 research outputs found
Statistically optimal analysis of samples from multiple equilibrium states
We present a new estimator for computing free energy differences and
thermodynamic expectations as well as their uncertainties from samples obtained
from multiple equilibrium states via either simulation or experiment. The
estimator, which we term the multistate Bennett acceptance ratio (MBAR)
estimator because it reduces to the Bennett acceptance ratio when only two
states are considered, has significant advantages over multiple histogram
reweighting methods for combining data from multiple states. It does not
require the sampled energy range to be discretized to produce histograms,
eliminating bias due to energy binning and significantly reducing the time
complexity of computing a solution to the estimating equations in many cases.
Additionally, an estimate of the statistical uncertainty is provided for all
estimated quantities. In the large sample limit, MBAR is unbiased and has the
lowest variance of any known estimator for making use of equilibrium data
collected from multiple states. We illustrate this method by producing a highly
precise estimate of the potential of mean force for a DNA hairpin system,
combining data from multiple optical tweezer measurements under constant force
bias.Comment: 13 pages (including appendices), 1 figure, LaTe
A Thermal Gradient Approach for the Quasi-Harmonic Approximation and its Application to Improved Treatment of Anisotropic Expansion
We present a novel approach to efficiently implement thermal expansion in the
quasi-harmonic approximation (QHA) for both isotropic and more importantly,
anisotropic expansion. In this approach, we rapidly determine a crystal's
equilibrium volume and shape at a given temperature by integrating along the
gradient of expansion from zero Kelvin up to the desired temperature. We
compare our approach to previous isotropic methods that rely on a brute-force
grid search to determine the free energy minimum, which is infeasible to carry
out for anisotropic expansion, as well as quasi-anisotropic approaches that
take into account the contributions to anisotropic expansion from the lattice
energy. We compare these methods for experimentally known polymorphs of
piracetam and resorcinol and show that both isotropic methods agree to within
error up to 300 K. Using the Gr\"{u}neisen parameter causes up to 0.04 kcal/mol
deviation in the Gibbs free energy, but for polymorph free energy differences
there is a cancellation in error with all isotropic methods within 0.025
kcal/mol at 300 K.
Anisotropic expansion allows the crystals to relax into lattice geometries
0.01-0.23 kcal/mol lower in energy at 300 K relative to isotropic expansion.
For polymorph free energy differences all QHA methods produced results within
0.02 kcal/mol of each other for resorcinol and 0.12 kcal/mol for piracetam, the
two molecules tested here, demonstrating a cancellation of error for isotropic
methods.
We also find that when expanding in more than a single volume variable, there
is a non-negligible rate of failure of the basic approximations of QHA.
Specifically, while expanding into new harmonic modes as the box vectors are
increased, the system often falls into alternate, structurally distinct
harmonic modes unrelated by continuous deformation from the original harmonic
mode.Comment: 38 pages, including 9 pages supporting informatio
Rapid Computation of Thermodynamic Properties Over Multidimensional Nonbonded Parameter Spaces using Adaptive Multistate Reweighting
We show how thermodynamic properties of molecular models can be computed over
a large, multidimensional parameter space by combining multistate reweighting
analysis with a linear basis function approach. This approach reduces the
computational cost to estimate thermodynamic properties from molecular
simulations for over 130,000 tested parameter combinations from over a thousand
CPU years to tens of CPU days. This speed increase is achieved primarily by
computing the potential energy as a linear combination of basis functions,
computed from either modified simulation code or as the difference of energy
between two reference states, which can be done without any simulation code
modification. The thermodynamic properties are then estimated with the
Multistate Bennett Acceptance Ratio (MBAR) as a function of multiple model
parameters without the need to define a priori how the states are connected by
a pathway. Instead, we adaptively sample a set of points in parameter space to
create mutual configuration space overlap. The existence of regions of poor
configuration space overlap are detected by analyzing the eigenvalues of the
sampled states' overlap matrix. The configuration space overlap to sampled
states is monitored alongside the mean and maximum uncertainty to determine
convergence, as neither the uncertainty or the configuration space overlap
alone is a sufficient metric of convergence.
This adaptive sampling scheme is demonstrated by estimating with high
precision the solvation free energies of charged particles of Lennard-Jones
plus Coulomb functional form. We also compute entropy, enthalpy, and radial
distribution functions of unsampled parameter combinations using only the data
from these sampled states and use the free energies estimates to examine the
deviation of simulations from the Born approximation to the solvation free
energy
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