341 research outputs found
General heatbath algorithm for pure lattice gauge theory
A heatbath algorithm is proposed for pure SU(N) lattice gauge theory based on
the Manton action of the plaquette element for general gauge group N.
Comparison is made to the Metropolis thermalization algorithm using both the
Wilson and Manton actions. The heatbath algorithm is found to outperform the
Metropolis algorithm in both execution speed and decorrelation rate. Results,
mostly in D=3, for N=2 through 5 at several values for the inverse coupling are
presented.Comment: 9 pages, 10 figures, 1 table, major revision, final version, to
appear in PR
Application of Bryan's algorithm to the mobility spectrum analysis of semiconductor devices
A powerful method for mobility spectrum analysis is presented, based on Bryan's maximum entropy algorithm. The Bayesian analysis central to Bryan's algorithm ensures that we avoid overfitting of data, resulting in a physically reasonable solution. The algorithm is fast, and allows the analysis of large quantities of data, removing the bias of data selection inherent in all previous techniques. Existing mobility spectrum analysis systems are reviewed, and the performance of the Bryan's algorithm mobility spectrum (BAMS) approach is demonstrated using synthetic data sets. Analysis of experimental data is briefly discussed. We find that BAMS performs well compared to existing mobility spectrum methods
Differential cross section analysis in kaon photoproduction using associated legendre polynomials
Angular distributions of differential cross sections from the latest CLAS
data sets \cite{bradford}, for the reaction have been analyzed using associated Legendre polynomials. This
analysis is based upon theoretical calculations in Ref. \cite{fasano} where all
sixteen observables in kaon photoproduction can be classified into four
Legendre classes. Each observable can be described by an expansion of
associated Legendre polynomial functions. One of the questions to be addressed
is how many associated Legendre polynomials are required to describe the data.
In this preliminary analysis, we used data models with different numbers of
associated Legendre polynomials. We then compared these models by calculating
posterior probabilities of the models. We found that the CLAS data set needs no
more than four associated Legendre polynomials to describe the differential
cross section data. In addition, we also show the extracted coefficients of the
best model.Comment: Talk given at APFB08, Depok, Indonesia, August, 19-23, 200
A Bayesian approach to the follow-up of candidate gravitational wave signals
Ground-based gravitational wave laser interferometers (LIGO, GEO-600, Virgo
and Tama-300) have now reached high sensitivity and duty cycle. We present a
Bayesian evidence-based approach to the search for gravitational waves, in
particular aimed at the followup of candidate events generated by the analysis
pipeline. We introduce and demonstrate an efficient method to compute the
evidence and odds ratio between different models, and illustrate this approach
using the specific case of the gravitational wave signal generated during the
inspiral phase of binary systems, modelled at the leading quadrupole Newtonian
order, in synthetic noise. We show that the method is effective in detecting
signals at the detection threshold and it is robust against (some types of)
instrumental artefacts. The computational efficiency of this method makes it
scalable to the analysis of all the triggers generated by the analysis
pipelines to search for coalescing binaries in surveys with ground-based
interferometers, and to a whole variety of signal waveforms, characterised by a
larger number of parameters.Comment: 9 page
Symmetrization and enhancement of the continuous Morlet transform
The forward and inverse wavelet transform using the continuous Morlet basis
may be symmetrized by using an appropriate normalization factor. The loss of
response due to wavelet truncation is addressed through a renormalization of
the wavelet based on power. The spectral density has physical units which may
be related to the squared amplitude of the signal, as do its margins the mean
wavelet power and the integrated instant power, giving a quantitative estimate
of the power density with temporal resolution. Deconvolution with the wavelet
response matrix reduces the spectral leakage and produces an enhanced wavelet
spectrum providing maximum resolution of the harmonic content of a signal.
Applications to data analysis are discussed.Comment: 12 pages, 8 figures, 2 tables, minor revision, final versio
The history of mass assembly of faint red galaxies in 28 galaxy clusters since z=1.3
We measure the relative evolution of the number of bright and faint (as faint
as 0.05 L*) red galaxies in a sample of 28 clusters, of which 16 are at 0.50<=
z<=1.27, all observed through a pair of filters bracketing the 4000 Angstrom
break rest-frame. The abundance of red galaxies, relative to bright ones, is
constant over all the studied redshift range, 0<z<1.3, and rules out a
differential evolution between bright and faint red galaxies as large as
claimed in some past works. Faint red galaxies are largely assembled and in
place at z=1.3 and their deficit does not depend on cluster mass, parametrized
by velocity dispersion or X-ray luminosity. Our analysis, with respect to
previous one, samples a wider redshift range, minimizes systematics and put a
more attention to statistical issues, keeping at the same time a large number
of clusters.Comment: MNRAS, 386, 1045. Half a single sentence (in sec 4.4) change
Fitting the Phenomenological MSSM
We perform a global Bayesian fit of the phenomenological minimal
supersymmetric standard model (pMSSM) to current indirect collider and dark
matter data. The pMSSM contains the most relevant 25 weak-scale MSSM
parameters, which are simultaneously fit using `nested sampling' Monte Carlo
techniques in more than 15 years of CPU time. We calculate the Bayesian
evidence for the pMSSM and constrain its parameters and observables in the
context of two widely different, but reasonable, priors to determine which
inferences are robust. We make inferences about sparticle masses, the sign of
the parameter, the amount of fine tuning, dark matter properties and the
prospects for direct dark matter detection without assuming a restrictive
high-scale supersymmetry breaking model. We find the inferred lightest CP-even
Higgs boson mass as an example of an approximately prior independent
observable. This analysis constitutes the first statistically convergent pMSSM
global fit to all current data.Comment: Added references, paragraph on fine-tunin
Bayesian coherent analysis of in-spiral gravitational wave signals with a detector network
The present operation of the ground-based network of gravitational-wave laser
interferometers in "enhanced" configuration brings the search for gravitational
waves into a regime where detection is highly plausible. The development of
techniques that allow us to discriminate a signal of astrophysical origin from
instrumental artefacts in the interferometer data and to extract the full range
of information are some of the primary goals of the current work. Here we
report the details of a Bayesian approach to the problem of inference for
gravitational wave observations using a network of instruments, for the
computation of the Bayes factor between two hypotheses and the evaluation of
the marginalised posterior density functions of the unknown model parameters.
The numerical algorithm to tackle the notoriously difficult problem of the
evaluation of large multi-dimensional integrals is based on a technique known
as Nested Sampling, which provides an attractive alternative to more
traditional Markov-chain Monte Carlo (MCMC) methods. We discuss the details of
the implementation of this algorithm and its performance against a Gaussian
model of the background noise, considering the specific case of the signal
produced by the in-spiral of binary systems of black holes and/or neutron
stars, although the method is completely general and can be applied to other
classes of sources. We also demonstrate the utility of this approach by
introducing a new coherence test to distinguish between the presence of a
coherent signal of astrophysical origin in the data of multiple instruments and
the presence of incoherent accidental artefacts, and the effects on the
estimation of the source parameters as a function of the number of instruments
in the network.Comment: 22 page
Bayesian feedback control of a two-atom spin-state in an atom-cavity system
We experimentally demonstrate real-time feedback control of the joint
spin-state of two neutral Caesium atoms inside a high finesse optical cavity.
The quantum states are discriminated by their different cavity transmission
levels. A Bayesian update formalism is used to estimate state occupation
probabilities as well as transition rates. We stabilize the balanced two-atom
mixed state, which is deterministically inaccessible, via feedback control and
find very good agreement with Monte-Carlo simulations. On average, the feedback
loops achieves near optimal conditions by steering the system to the target
state marginally exceeding the time to retrieve information about its state.Comment: 4 pages, 4 figure
Multisite Weather Generators Using Bayesian Networks: An Illustrative Case Study for Precipitation Occurrence
ABSTRACT: Many existing approaches for multisite weather generation try to capture several statistics of the observed data (e.g. pairwise correlations) in order to generate spatially and temporarily consistent series. In this work we analyse the application of Bayesian networks to this problem, focusing on precipitation occurrence and considering a simple case study to illustrate the potential of this new approach. We use Bayesian networks to approximate the multi-variate (-site) probability distribution of observed gauge data, which is factorized according to the relevant (marginal and conditional) dependencies. This factorization allows the simulation of synthetic samples from the multivariate distribution, thus providing a sound and promising methodology for multisite precipitation series generation.We acknowledge funding provided by the project MULTI‐SDM (CGL2015‐ 66583‐R, MINECO/FEDER)
- …