26 research outputs found
A Parameterization Invariant Approach to the Statistical Estimation of the CKM Phase
In contrast to previous analyses, we demonstrate a Bayesian approach to the
estimation of the CKM phase that is invariant to parameterization. We
also show that in addition to {\em computing} the marginal posterior in a
Bayesian manner, the distribution must also be {\em interpreted} from a
subjective Bayesian viewpoint. Doing so gives a very natural interpretation to
the distribution. We also comment on the effect of removing information about
.Comment: 14 pages, 3 figures, 1 table, minor revision; to appear in JHE
Fitting a sum of exponentials to lattice correlation functions using a non-uniform prior
Excited states are extracted from lattice correlation functions using a
non-uniform prior on the model parameters. Models for both a single exponential
and a sum of exponentials are considered, as well as an alternate model for the
orthogonalization of the correlation functions. Results from an analysis of
torelon and glueball operators indicate the Bayesian methodology compares well
with the usual interpretation of effective mass tables produced by a
variational procedure. Applications of the methodology are discussed.Comment: 12 pages, 8 figures, 8 tables, major revision, final versio
MaxEnt power spectrum estimation using the Fourier transform for irregularly sampled data applied to a record of stellar luminosity
The principle of maximum entropy is applied to the spectral analysis of a
data signal with general variance matrix and containing gaps in the record. The
role of the entropic regularizer is to prevent one from overestimating
structure in the spectrum when faced with imperfect data. Several arguments are
presented suggesting that the arbitrary prefactor should not be introduced to
the entropy term. The introduction of that factor is not required when a
continuous Poisson distribution is used for the amplitude coefficients. We
compare the formalism for when the variance of the data is known explicitly to
that for when the variance is known only to lie in some finite range. The
result of including the entropic measure factor is to suggest a spectrum
consistent with the variance of the data which has less structure than that
given by the forward transform. An application of the methodology to example
data is demonstrated.Comment: 15 pages, 13 figures, 1 table, major revision, final version,
Accepted for publication in Astrophysics & Space Scienc
Cosmokinetics: A joint analysis of Standard Candles, Rulers and Cosmic Clocks
We study the accelerated expansion of the universe by using the kinematic
approach. In this context, we parameterize the deceleration parameter, q(z), in
a model independent way. Assuming three simple parameterizations we reconstruct
q(z). We do the joint analysis with combination of latest cosmological data
consisting of standard candles (Supernovae Union2 sample), standard ruler
(CMB/BAO), cosmic clocks (age of passively evolving galaxies) and Hubble (H(z))
data. Our results support the accelerated expansion of the universe.Comment: PDFLatex, 15 pages, 12 pdf figures, revised version to appear in JCA
Phase extension methods
Available from British Library Document Supply Centre- DSC:D59907 / BLDSC - British Library Document Supply CentreSIGLEGBUnited Kingdo
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Dynamics of the Anderson model for dilute magnetic alloys: A quantum Monte Carlo and maximum entropy study
In this article we describe the results of a new method for calculating the dynamical properties of the Anderson model. QMC generates data about the Matsubara Green's functions in imaginary time. To obtain dynamical properties, one must analytically continue these data to real time. This is an extremely ill-posed inverse problem similar to the inversion of a Laplace transform from incomplete and noisy data. Our method is a general one, applicable to the calculation of dynamical properties from a wide variety of quantum simulations. We use Bayesian methods of statistical inference to determine the dynamical properties based on both the QMC data and any prior information we may have such as sum rules, symmetry, high frequency limits, etc. This provides a natural means of combining perturbation theory and numerical simulations in order to understand dynamical many-body problems. Specifically we use the well-established maximum entropy (ME) method for image reconstruction. We obtain the spectral density and transport coefficients over the entire range of model parameters accessible by QMC, with data having much larger statistical error than required by other proposed analytic continuation methods