60,774 research outputs found
Normalized entropy density of the 3D 3-state Potts model
Using a multicanonical Metropolis algorithm we have performed Monte Carlo
simulations of the 3D 3-state Potts model on lattices with L=20, 30, 40,
50. Covering a range of inverse temperatures from to
we calculated the infinite volume limit of the entropy
density with its normalization obtained from . At the
transition temperature the entropy and energy endpoints in the ordered and
disordered phase are estimated employing a novel reweighting procedure. We also
evaluate the transition temperature and the order-disorder interface tension.
The latter estimate increases when capillary waves are taken into account.Comment: 5 pages, 4 figure
Clopper-Pearson Bounds from HEP Data Cuts
For the measurement of signals in events rigorous confidence bounds
on the true signal probability were established in a classical
paper by Clopper and Pearson [Biometrica 26, 404 (1934)]. Here, their bounds
are generalized to the HEP situation where cuts on the data tag signals with
probability and background data with likelihood . The Fortran
program which, on input of , , the number of tagged data and
the total number of data , returns the requested confidence bounds as well
as bounds on the entire cumulative signal distribution function, is available
on the web. In particular, the method is of interest in connection with the
statistical analysis part of the ongoing Higgs search at the LEP experiments
Biased Metropolis Sampling for Rugged Free Energy Landscapes
Metropolis simulations of all-atom models of peptides (i.e. small proteins)
are considered. Inspired by the funnel picture of Bryngelson and Wolyness, a
transformation of the updating probabilities of the dihedral angles is defined,
which uses probability densities from a higher temperature to improve the
algorithmic performance at a lower temperature. The method is suitable for
canonical as well as for generalized ensemble simulations. A simple
approximation to the full transformation is tested at room temperature for
Met-Enkephalin in vacuum. Integrated autocorrelation times are found to be
reduced by factors close to two and a similar improvement due to generalized
ensemble methods enters multiplicatively.Comment: Plenary talk at the Los Alamos conference, The Monte Carlo Method in
Physical Sciences: Celebrating the 50th Anniversary of the Metropolis
Algorithm, to appear in the proceedings, 11 pages, 4 figures, one table.
Inconsistencies corrected and references adde
New Algorithm to Investigate Neural Networks
Random cost simulations were introduced as a method to investigate
optimization problems in systems with conflicting constraints. Here I study the
approach in connection with the training of a feed-forward multilayer
perceptron, as used in high energy physics applications. It is suggested to use
random cost simulations for generating a set of selected configurations. On
each of those final minimization may then be performed by a standard algorithm.
For the training example at hand many almost degenerate local minima are thus
found. Some effort is spend to discuss whether they lead to equivalent
classifications of the data.Comment: 16 pages and 8 figures. Typos in eqn.(1) and various misleading
formulations eliminate
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