2,601 research outputs found
Space Shuttle Main Engine (SSME) Pogo testing and results
To effectively assess the Pogo stability of the space shuttle vehicle, it was necessary to characterize the structural, propellant, and propulsion dynamics subsystems. Extensive analyses and comprehensive testing programs were established early in the project as an implementation of management philosophy of Pogo prevention for space shuttle. The role of the space shuttle main engine (SSMF) in the Pogo prevention plans, the results obtained from engine ground testing with analysis, and measured data from STS-1 flight are discussed
Nonparametric inference for competing risks current status data with continuous, discrete or grouped observation times
New methods and theory have recently been developed to nonparametrically
estimate cumulative incidence functions for competing risks survival data
subject to current status censoring. In particular, the limiting distribution
of the nonparametric maximum likelihood estimator and a simplified "naive
estimator" have been established under certain smoothness conditions. In this
paper, we establish the large-sample behavior of these estimators in two
additional models, namely when the observation time distribution has discrete
support and when the observation times are grouped. These asymptotic results
are applied to the construction of confidence intervals in the three different
models. The methods are illustrated on two data sets regarding the cumulative
incidence of (i) different types of menopause from a cross-sectional sample of
women in the United States and (ii) subtype-specific HIV infection from a
sero-prevalence study in injecting drug users in Thailand.Comment: 16 pages, 3 figure
A Markov Chain Monte Carlo Algorithm for analysis of low signal-to-noise CMB data
We present a new Monte Carlo Markov Chain algorithm for CMB analysis in the
low signal-to-noise regime. This method builds on and complements the
previously described CMB Gibbs sampler, and effectively solves the low
signal-to-noise inefficiency problem of the direct Gibbs sampler. The new
algorithm is a simple Metropolis-Hastings sampler with a general proposal rule
for the power spectrum, C_l, followed by a particular deterministic rescaling
operation of the sky signal. The acceptance probability for this joint move
depends on the sky map only through the difference of chi-squared between the
original and proposed sky sample, which is close to unity in the low
signal-to-noise regime. The algorithm is completed by alternating this move
with a standard Gibbs move. Together, these two proposals constitute a
computationally efficient algorithm for mapping out the full joint CMB
posterior, both in the high and low signal-to-noise regimes.Comment: Submitted to Ap
Application of Monte Carlo Algorithms to the Bayesian Analysis of the Cosmic Microwave Background
Power spectrum estimation and evaluation of associated errors in the presence
of incomplete sky coverage; non-homogeneous, correlated instrumental noise; and
foreground emission is a problem of central importance for the extraction of
cosmological information from the cosmic microwave background. We develop a
Monte Carlo approach for the maximum likelihood estimation of the power
spectrum. The method is based on an identity for the Bayesian posterior as a
marginalization over unknowns. Maximization of the posterior involves the
computation of expectation values as a sample average from maps of the cosmic
microwave background and foregrounds given some current estimate of the power
spectrum or cosmological model, and some assumed statistical characterization
of the foregrounds. Maps of the CMB are sampled by a linear transform of a
Gaussian white noise process, implemented numerically with conjugate gradient
descent. For time series data with N_{t} samples, and N pixels on the sphere,
the method has a computational expense $KO[N^{2} +- N_{t} +AFw-log N_{t}],
where K is a prefactor determined by the convergence rate of conjugate gradient
descent. Preconditioners for conjugate gradient descent are given for scans
close to great circle paths, and the method allows partial sky coverage for
these cases by numerically marginalizing over the unobserved, or removed,
region.Comment: submitted to Ap
Marginal distributions for cosmic variance limited CMB polarization data
We provide computationally convenient expressions for all marginal
distributions of the polarization CMB power spectrum distribution
P(C_l|sigma_l), where C_l = {C_l^TT, C_l^TE, C_l^EE, C_l^BB} denotes the set of
ensemble averaged polarization CMB power spectra, and sigma_l = {sigma_l^TT,
sigma_l^TE, sigma_l^EE, sigma_l^BB} the set of the realization specific
polarization CMB power spectra. This distribution describes the CMB power
spectrum posterior for cosmic variance limited data. The expressions derived
here are general, and may be useful in a wide range of applications. Two
specific applications are described in this paper. First, we employ the derived
distributions within the CMB Gibbs sampling framework, and demonstrate a new
conditional CMB power spectrum sampling algorithm that allows for different
binning schemes for each power spectrum. This is useful because most CMB
experiments have very different signal-to-noise ratios for temperature and
polarization. Second, we provide new Blackwell-Rao estimators for each of the
marginal polarization distributions, which are relevant to power spectrum and
likelihood estimation. Because these estimators represent marginals, they are
not affected by the exponential behaviour of the corresponding joint
expression, but converge quickly.Comment: 8 pages, 3 figures; minor adjustment, accepted for publication in
ApJ
CMB likelihood approximation by a Gaussianized Blackwell-Rao estimator
We introduce a new CMB temperature likelihood approximation called the
Gaussianized Blackwell-Rao (GBR) estimator. This estimator is derived by
transforming the observed marginal power spectrum distributions obtained by the
CMB Gibbs sampler into standard univariate Gaussians, and then approximate
their joint transformed distribution by a multivariate Gaussian. The method is
exact for full-sky coverage and uniform noise, and an excellent approximation
for sky cuts and scanning patterns relevant for modern satellite experiments
such as WMAP and Planck. A single evaluation of this estimator between l=2 and
200 takes ~0.2 CPU milliseconds, while for comparison, a single pixel space
likelihood evaluation between l=2 and 30 for a map with ~2500 pixels requires
~20 seconds. We apply this tool to the 5-year WMAP temperature data, and
re-estimate the angular temperature power spectrum, , and likelihood,
L(C_l), for l<=200, and derive new cosmological parameters for the standard
six-parameter LambdaCDM model. Our spectrum is in excellent agreement with the
official WMAP spectrum, but we find slight differences in the derived
cosmological parameters. Most importantly, the spectral index of scalar
perturbations is n_s=0.973 +/- 0.014, 1.9 sigma away from unity and 0.6 sigma
higher than the official WMAP result, n_s = 0.965 +/- 0.014. This suggests that
an exact likelihood treatment is required to higher l's than previously
believed, reinforcing and extending our conclusions from the 3-year WMAP
analysis. In that case, we found that the sub-optimal likelihood approximation
adopted between l=12 and 30 by the WMAP team biased n_s low by 0.4 sigma, while
here we find that the same approximation between l=30 and 200 introduces a bias
of 0.6 sigma in n_s.Comment: 10 pages, 7 figures, submitted to Ap
Room-Temperature Continuous-Wave Vertical-Cavity Single-Quantum-Well Microlaser Diodes
Room-temperature continuous and pulsed lasing of vertical-cavity, single-quantum-well, surface-emitting microlasers is achieved at ~983nm. The active Ga[sub][0-8]In[sub][0-2]As single quantum well is 100 [angstroms] thick. These microlasers have the smallest gain medium volumes among lasers ever built. The entire laser structure is grown by molecular beam epitaxy and the microlasers are formed by chemically assisted ion-beam etching. The microlasers are 3-50-μm across. The minimum threshold currents are 1.1 mA (pulsed) and 1.5 mA (CW)
The joint large-scale foreground-CMB posteriors of the 3-year WMAP data
Using a Gibbs sampling algorithm for joint CMB estimation and component
separation, we compute the large-scale CMB and foreground posteriors of the
3-yr WMAP temperature data. Our parametric data model includes the cosmological
CMB signal and instrumental noise, a single power law foreground component with
free amplitude and spectral index for each pixel, a thermal dust template with
a single free overall amplitude, and free monopoles and dipoles at each
frequency. This simple model yields a surprisingly good fit to the data over
the full frequency range from 23 to 94 GHz. We obtain a new estimate of the CMB
sky signal and power spectrum, and a new foreground model, including a
measurement of the effective spectral index over the high-latitude sky. A
particularly significant result is the detection of a common spurious offset in
all frequency bands of ~ -13muK, as well as a dipole in the V-band data.
Correcting for these is essential when determining the effective spectral index
of the foregrounds. We find that our new foreground model is in good agreement
with template-based model presented by the WMAP team, but not with their MEM
reconstruction. We believe the latter may be at least partially compromised by
the residual offsets and dipoles in the data. Fortunately, the CMB power
spectrum is not significantly affected by these issues, as our new spectrum is
in excellent agreement with that published by the WMAP team. The corresponding
cosmological parameters are also virtually unchanged.Comment: 5 pages, 4 figures, submitted to ApJL. Background data are available
at http://www.astro.uio.no/~hke under the Research ta
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