33,210 research outputs found
Non-Perturbative U(1) Gauge Theory at Finite Temperature
For compact U(1) lattice gauge theory (LGT) we have performed a finite size
scaling analysis on lattices for fixed by
extrapolating spatial volumes of size to . Within the
numerical accuracy of the thus obtained fits we find for , 5 and~6
second order critical exponents, which exhibit no obvious
dependence. The exponents are consistent with 3d Gaussian values, but not with
either first order transitions or the universality class of the 3d XY model. As
the 3d Gaussian fixed point is known to be unstable, the scenario of a yet
unidentified non-trivial fixed point close to the 3d Gaussian emerges as one of
the possible explanations.Comment: Extended version after referee reports. 6 pages, 6 figure
Configuration Space for Random Walk Dynamics
Applied to statistical physics models, the random cost algorithm enforces a
Random Walk (RW) in energy (or possibly other thermodynamic quantities). The
dynamics of this procedure is distinct from fixed weight updates. The
probability for a configuration to be sampled depends on a number of unusual
quantities, which are explained in this paper. This has been overlooked in
recent literature, where the method is advertised for the calculation of
canonical expectation values. We illustrate these points for the Ising
model. In addition, we proof a previously conjectured equation which relates
microcanonical expectation values to the spectral density.Comment: Various minor changes, appendix added, Fig. 2 droppe
Structure of the Energy Landscape of Short Peptides
We have simulated, as a showcase, the pentapeptide Met-enkephalin
(Tyr-Gly-Gly-Phe-Met) to visualize the energy landscape and investigate the
conformational coverage by the multicanonical method. We have obtained a
three-dimensional topographic picture of the whole energy landscape by plotting
the histogram with respect to energy(temperature) and the order parameter,
which gives the degree of resemblance of any created conformation with the
global energy minimum (GEM).Comment: 17 pages, 4 figure
Exchange Monte Carlo Method and Application to Spin Glass Simulations
We propose an efficient Monte Carlo algorithm for simulating a
``hardly-relaxing" system, in which many replicas with different temperatures
are simultaneously simulated and a virtual process exchanging configurations of
these replica is introduced. This exchange process is expected to let the
system at low temperatures escape from a local minimum. By using this algorithm
the three-dimensional Ising spin glass model is studied. The ergodicity
time in this method is found much smaller than that of the multi-canonical
method. In particular the time correlation function almost follows an
exponential decay whose relaxation time is comparable to the ergodicity time at
low temperatures. It suggests that the system relaxes very rapidly through the
exchange process even in the low temperature phase.Comment: 10 pages + uuencoded 5 Postscript figures, REVTe
Generalized-ensemble Monte carlo method for systems with rough energy landscape
We present a novel Monte Carlo algorithm which enhances equilibrization of
low-temperature simulations and allows sampling of configurations over a large
range of energies. The method is based on a non-Boltzmann probability weight
factor and is another version of the so-called generalized-ensemble techniques.
The effectiveness of the new approach is demonstrated for the system of a small
peptide, an example of the frustrated system with a rugged energy landscape.Comment: Latex; ps-files include
Rugged Metropolis Sampling with Simultaneous Updating of Two Dynamical Variables
The Rugged Metropolis (RM) algorithm is a biased updating scheme, which aims
at directly hitting the most likely configurations in a rugged free energy
landscape. Details of the one-variable (RM) implementation of this
algorithm are presented. This is followed by an extension to simultaneous
updating of two dynamical variables (RM). In a test with Met-Enkephalin in
vacuum RM improves conventional Metropolis simulations by a factor of about
four. Correlations between three or more dihedral angles appear to prevent
larger improvements at low temperatures. We also investigate a multi-hit
Metropolis scheme, which spends more CPU time on variables with large
autocorrelation times.Comment: 8 pages, 5 figures. Revisions after referee reports. Additional
simulations for temperatures down to 220
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