The Age of the Universe and the Cosmological Constant Determined from Cosmic Microwave Background Anisotropy Measurements

If Omega_tot = 1 and structure formed from adiabatic initial conditions then the age of the Universe, as constrained by measurements of the cosmic microwave background (CMB), is t_0=14.0 +/- 0.5 Gyr. The uncertainty is surprisingly small given that CMB data alone constrain neither h nor Omega_Lambda significantly. It is due to the tight (and accidental) correlation, in these models, of the age with the angle subtended by the sound horizon on the last--scattering surface and thus with the well-determined acoustic peak locations. If we assume either the HST Key Project result h = 0.72 \pm .08 or simply that h > 0.55, we find Omega_Lambda > 0.4 at 95% confidence--another argument for dark energy, independent of supernovae observations. Our analysis is greatly simplified by the Monte Carlo Markov chain approach to Bayesian inference combined with a fast method for calculating angular power spectra.Comment: 5 pages, including 2 figures and one table final published versio

Ground-based time-guidance algorithm for control of airplanes in a time-metered air traffic control environment: A piloted simulation study

The rapidly increasing costs of flight operations and the requirement for increased fuel conservation have made it necessary to develop more efficient ways to operate airplanes and to control air traffic for arrivals and departures to the terminal area. One concept of controlling arrival traffic through time metering has been jointly studied and evaluated by NASA and ONERA/CERT in piloted simulation tests. From time errors attained at checkpoints, airspeed and heading commands issued by air traffic control were computed by a time-guidance algorithm for the pilot to follow that would cause the airplane to cross a metering fix at a preassigned time. These tests resulted in the simulated airplane crossing a metering fix with a mean time error of 1.0 sec and a standard deviation of 16.7 sec when the time-metering algorithm was used. With mismodeled winds representing the unknown in wind-aloft forecasts and modeling form, the mean time error attained when crossing the metering fix was increased and the standard deviation remained approximately the same. The subject pilots reported that the airspeed and heading commands computed in the guidance concept were easy to follow and did not increase their work load above normal levels

Standard Isotherm Fit Information for Dry CO2 on Sorbents for 4-Bed Molecular Sieve

Onboard the ISS, one of the systems tasked with removal of metabolic carbon dioxide (CO2) is a 4-bed molecular sieve (4BMS) system. In order to enable a 4-person mission to succeed, systems for removal of metabolic CO2 must reliably operate for several years while minimizing power, mass, and volume requirements. This minimization can be achieved through system redesign and/or changes to the separation material(s). A material screening process has identified the most reliable sorbent materials for the next 4BMS. Sorbent characterization will provide the information necessary to guide system design by providing inputs for computer simulations

Probing the equation of state of the early universe with a space laser interferometer

We propose a method to probe the equation of state of the early universe and its evolution, using the stochastic gravitational wave background from inflation. A small deviation from purely radiation dominated universe ($w= 1/3$) would be clearly imprinted on the gravitational wave spectrum $\Omega_{GW}(f)$ due to the nearly scale invariant nature of inflationary generated waves.Comment: 10 pages, 1 figur

Calibration and Uncertainty Analysis of a Fixed-Bed Adsorption Model for CO2 Separation

Fixed-bed adsorption is widely used in industrial gas separation and is the primary method for atmosphere revitalization in space. This paper analyzes the uncertainty of a one-dimensional, fixed-bed adsorption model due to uncertainty in several model inputs, namely, the linear-driving-force (LDF) mass transfer coefficient, axial dispersion, heat transfer coefficients, and adsorbent properties. The input parameter uncertainties are determined from a comprehensive survey of experimental data in the literature. The model is first calibrated against experimental data from intra-bed centerline concentration measurements to find the LDF coefficient. We then use this LDF coefficient to extract axial dispersion coefficients from mixed, downstream concentration measurements for both a small-diameter bed (dominated by wall-channeling) and a large-diameter bed (dominated by pellet-driven dispersion). The predicted effluent concentration and temperature profiles are most strongly affected by uncertainty in LDF coefficient, adsorbent density, and void fraction. The uncertainty analysis further reveals that ignoring the effect of wall-channeling on apparent axial dispersion can cause significant error in the predicted breakthrough times of small-diameter beds

Exploring Large-scale Structure with Billions of Galaxies

We consider cosmological applications of galaxy number density correlations to be inferred from future deep and wide multi-band optical surveys. We mostly focus on very large scales as a probe of possible features in the primordial power spectrum. We find the proposed survey of the Large Synoptic Survey Telescope may be competitive with future all-sky CMB experiments over a broad range of scales. On very large scales the inferred power spectrum is robust to photometric redshift errors, and, given a sufficient number density of galaxies, to angular variations in dust extinction and photometric calibration errors. We also consider other applications, such as constraining dark energy with the two CMB-calibrated standard rulers in the matter power spectrum, and controlling the effect of photometric redshift errors to facilitate the interpretation of cosmic shear data. We find that deep photometric surveys over wide area can provide constraints that are competitive with spectroscopic surveys in small volumes.Comment: 11 pages, 7 figures, ApJ accepted, references added, expanded discussion in Sec. 3.

Spatially-explicit and spectral soil carbon modeling in Florida.

Profound shifts have occurred over the last three centuries in which human actions have become the main driver to global environmental change. In this new epoch, the Anthropocene, human-driven changes such as population growth, climate and land use change, are pushing the Earth system well outside its normal operating range causing severe and abrupt environmental change. In this context, we present research highlights from Florida (150,000 km2) showing how anthropogenic-induced changes have had major impacts on carbon dynamics in soils, including (i) modeling of carbon and nutrient dynamics and soil carbon sequestration impacted by climate and land use change; (ii) geospatial assessment of soil carbon stocks and pools, and (iii) spectral-based soil carbon modeling. Our research is embedded in the STEP-AWBH modeling concept which explicitly incorporates Human forcings and time-dependent evolution of Atmospheric, Water, and Biotic factors into the modeling process. Spatially-explicit soil carbon observations were fused with ancillary environmental data and various statistical and geostatistical methods were used to upscale soil carbon across the region. Our results suggest that soil hydrologic and taxonomic, biotic (vegetation and land use), and climatic properties show complex interactions explaining the variation of soil carbon within this heterogeneous subtropical landscape

Comparing Cosmic Microwave Background Datasets

To extract reliable cosmic parameters from cosmic microwave background datasets, it is essential to show that the data are not contaminated by residual non-cosmological signals. We describe general statistical approaches to this problem, with an emphasis on the case in which there are two datasets that can be checked for consistency. A first visual step is the Wiener filter mapping from one set of data onto the pixel basis of another. For more quantitative analyses we develop and apply both Bayesian and frequentist techniques. We define the ``contamination parameter'' and advocate the calculation of its probability distribution as a means of examining the consistency of two datasets. The closely related ``probability enhancement factor'' is shown to be a useful statistic for comparison; it is significantly better than a number of chi-squared quantities we consider. Our methods can be used: internally (between different subsets of a dataset) or externally (between different experiments); for observing regions that completely overlap, partially overlap or overlap not at all; and for observing strategies that differ greatly. We apply the methods to check the consistency (internal and external) of the MSAM92, MSAM94 and Saskatoon Ring datasets. From comparing the two MSAM datasets, we find that the most probable level of contamination is 12%, with no contamination only 1.05 times less probable, and 100% contamination strongly ruled out at over 2 X 10^5 times less probable. From comparing the 1992 MSAM flight with the Saskatoon data we find the most probable level of contamination to be 50%, with no contamination only 1.6 times less probable and 100% contamination 13 times less probable. [Truncated]Comment: LaTeX, 16 pages which include 16 figures, submitted to Phys. Rev.