251 research outputs found
Numerical implementation of some reweighted path integral methods
The reweighted random series techniques provide finite-dimensional
approximations to the quantum density matrix of a physical system that have
fast asymptotic convergence. We study two special reweighted techniques that
are based upon the Levy-Ciesielski and Wiener-Fourier series, respectively. In
agreement with the theoretical predictions, we demonstrate by numerical
examples that the asymptotic convergence of the two reweighted methods is cubic
for smooth enough potentials. For each reweighted technique, we propose some
minimalist quadrature techniques for the computation of the path averages.
These quadrature techniques are designed to preserve the asymptotic convergence
of the original methods.Comment: 15 pages, 10 figures, submitted to JC
Energy estimators for random series path-integral methods
We perform a thorough analysis on the choice of estimators for random series
path integral methods. In particular, we show that both the thermodynamic
(T-method) and the direct (H-method) energy estimators have finite variances
and are straightforward to implement. It is demonstrated that the agreement
between the T-method and the H-method estimators provides an important
consistency check on the quality of the path integral simulations. We
illustrate the behavior of the various estimators by computing the total,
kinetic, and potential energies of a molecular hydrogen cluster using three
different path integral techniques. Statistical tests are employed to validate
the sampling strategy adopted as well as to measure the performance of the
parallel random number generator utilized in the Monte Carlo simulation. Some
issues raised by previous simulations of the hydrogen cluster are clarified.Comment: 15 pages, 1 figure, 3 table
Heat capacity estimators for random series path-integral methods by finite-difference schemes
Previous heat capacity estimators used in path integral simulations either
have large variances that grow to infinity with the number of path variables or
require the evaluation of first and second order derivatives of the potential.
In the present paper, we show that the evaluation of the total energy by the
T-method estimator and of the heat capacity by the TT-method estimator can be
implemented by a finite difference scheme in a stable fashion. As such, the
variances of the resulting estimators are finite and the evaluation of the
estimators requires the potential function only. By comparison with the task of
computing the partition function, the evaluation of the estimators requires k +
1 times more calls to the potential, where k is the order of the difference
scheme employed. Quantum Monte Carlo simulations for the Ne_13 cluster
demonstrate that a second order central-difference scheme should suffice for
most applications.Comment: 11 pages, 4 figure
Reconstruction of thermally-symmetrized quantum autocorrelation functions from imaginary-time data
In this paper, I propose a technique for recovering quantum dynamical
information from imaginary-time data via the resolution of a one-dimensional
Hamburger moment problem. It is shown that the quantum autocorrelation
functions are uniquely determined by and can be reconstructed from their
sequence of derivatives at origin. A general class of reconstruction algorithms
is then identified, according to Theorem 3. The technique is advocated as
especially effective for a certain class of quantum problems in continuum
space, for which only a few moments are necessary. For such problems, it is
argued that the derivatives at origin can be evaluated by Monte Carlo
simulations via estimators of finite variances in the limit of an infinite
number of path variables. Finally, a maximum entropy inversion algorithm for
the Hamburger moment problem is utilized to compute the quantum rate of
reaction for a one-dimensional symmetric Eckart barrier.Comment: 15 pages, no figures, to appear in Phys. Rev.
Phase changes in selected Lennard-Jones X_{13-n}Y_n clusters
Detailed studies of the thermodynamic properties of selected binary
Lennard-Jones clusters of the type X_{13-n}Y_n (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.Comment: 14 pages, 13 figures. submitted to J. Chem. Phy
Moments of spectral functions: Monte Carlo evaluation and verification
The subject of the present study is the Monte Carlo path-integral evaluation
of the moments of spectral functions. Such moments can be computed by formal
differentiation of certain estimating functionals that are
infinitely-differentiable against time whenever the potential function is
arbitrarily smooth. Here, I demonstrate that the numerical differentiation of
the estimating functionals can be more successfully implemented by means of
pseudospectral methods (e.g., exact differentiation of a Chebyshev polynomial
interpolant), which utilize information from the entire interval . The algorithmic detail that leads to robust numerical
approximations is the fact that the path integral action and not the actual
estimating functional are interpolated. Although the resulting approximation to
the estimating functional is non-linear, the derivatives can be computed from
it in a fast and stable way by contour integration in the complex plane, with
the help of the Cauchy integral formula (e.g., by Lyness' method). An
interesting aspect of the present development is that Hamburger's conditions
for a finite sequence of numbers to be a moment sequence provide the necessary
and sufficient criteria for the computed data to be compatible with the
existence of an inversion algorithm. Finally, the issue of appearance of the
sign problem in the computation of moments, albeit in a milder form than for
other quantities, is addressed.Comment: 13 pages, 2 figure
Upon the existence of short-time approximations of any polynomial order for the computation of density matrices by path integral methods
In this article, I provide significant mathematical evidence in support of
the existence of short-time approximations of any polynomial order for the
computation of density matrices of physical systems described by arbitrarily
smooth and bounded from below potentials. While for Theorem 2, which is
``experimental'', I only provide a ``physicist's'' proof, I believe the present
development is mathematically sound. As a verification, I explicitly construct
two short-time approximations to the density matrix having convergence orders 3
and 4, respectively. Furthermore, in the Appendix, I derive the convergence
constant for the trapezoidal Trotter path integral technique. The convergence
orders and constants are then verified by numerical simulations. While the two
short-time approximations constructed are of sure interest to physicists and
chemists involved in Monte Carlo path integral simulations, the present article
is also aimed at the mathematical community, who might find the results
interesting and worth exploring. I conclude the paper by discussing the
implications of the present findings with respect to the solvability of the
dynamical sign problem appearing in real-time Feynman path integral
simulations.Comment: 19 pages, 4 figures; the discrete short-time approximations are now
treated as independent from their continuous version; new examples of
discrete short-time approximations of order three and four are given; a new
appendix containing a short review on Brownian motion has been added; also,
some additional explanations are provided here and there; this is the last
version; to appear in Phys. Rev.
Local Variational Principle
A generalization of the Gibbs-Bogoliubov-Feynman inequality for spinless
particles is proven and then illustrated for the simple model of a symmetric
double-well quartic potential. The method gives a pointwise lower bound for the
finite-temperature density matrix and it can be systematically improved by the
Trotter composition rule. It is also shown to produce groundstate energies
better than the ones given by the Rayleigh-Ritz principle as applied to the
groundstate eigenfunctions of the reference potentials. Based on this
observation, it is argued that the Local Variational Principle performs better
than the equivalent methods based on the centroid path idea and on the
Gibbs-Bogoliubov-Feynman variational principle, especially in the range of low
temperatures.Comment: 15 pages, 5 figures, one more section adde
Feedback-optimized parallel tempering Monte Carlo
We introduce an algorithm to systematically improve the efficiency of
parallel tempering Monte Carlo simulations by optimizing the simulated
temperature set. Our approach is closely related to a recently introduced
adaptive algorithm that optimizes the simulated statistical ensemble in
generalized broad-histogram Monte Carlo simulations. Conventionally, a
temperature set is chosen in such a way that the acceptance rates for replica
swaps between adjacent temperatures are independent of the temperature and
large enough to ensure frequent swaps. In this paper, we show that by choosing
the temperatures with a modified version of the optimized ensemble feedback
method we can minimize the round-trip times between the lowest and highest
temperatures which effectively increases the efficiency of the parallel
tempering algorithm. In particular, the density of temperatures in the
optimized temperature set increases at the "bottlenecks'' of the simulation,
such as phase transitions. In turn, the acceptance rates are now temperature
dependent in the optimized temperature ensemble. We illustrate the
feedback-optimized parallel tempering algorithm by studying the two-dimensional
Ising ferromagnet and the two-dimensional fully-frustrated Ising model, and
briefly discuss possible feedback schemes for systems that require
configurational averages, such as spin glasses.Comment: 12 pages, 14 figure
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