Constraints on Dark Energy from Supernovae, Gamma Ray Bursts, Acoustic Oscillations, Nucleosynthesis and Large Scale Structure and the Hubble constant

The luminosity distance vs. redshift law is now measured using supernovae and gamma ray bursts, and the angular size distance is measured at the surface of last scattering by the CMB and at z = 0.35 by baryon acoustic oscillations. In this paper this data is fit to models for the equation of state with w = -1, w = const, and w(z) = w_0+w_a(1-a). The last model is poorly constrained by the distance data, leading to unphysical solutions where the dark energy dominates at early times unless the large scale structure and acoustic scale constraints are modified to allow for early time dark energy effects. A flat LambdaCDM model is consistent with all the data.Comment: 19 pages Latex with 8 Postscript figure files. A new reference and constraint, w vs w' contour plots updated. Version accepted by the the Ap

Testing flatness of the universe with probes of cosmic distances and growth

When using distance measurements to probe spatial curvature, the geometric degeneracy between curvature and dark energy in the distance-redshift relation typically requires either making strong assumptions about the dark energy evolution or sacrificing precision in a more model-independent approach. Measurements of the redshift evolution of the linear growth of perturbations can break the geometric degeneracy, providing curvature constraints that are both precise and model-independent. Future supernova, CMB, and cluster data have the potential to measure the curvature with an accuracy of sigma(Omega_K)=0.002, without specifying a particular dark energy phenomenology. In combination with distance measurements, the evolution of the growth function at low redshifts provides the strongest curvature constraint if the high-redshift universe is well approximated as being purely matter dominated. However, in the presence of early dark energy or massive neutrinos, the precision in curvature is reduced due to additional degeneracies, and precise normalization of the growth function relative to recombination is important for obtaining accurate constraints. Curvature limits from distances and growth compare favorably to other approaches to curvature estimation proposed in the literature, providing either greater accuracy or greater freedom from dark energy modeling assumptions, and are complementary due to the use of independent data sets. Model-independent estimates of curvature are critical for both testing inflation and obtaining unbiased constraints on dark energy parameters.Comment: 23 pages, 11 figures; submitted to Phys. Rev.

Probing the Primordial Power Spectrum with Cluster Number Counts

We investigate how well galaxy cluster number counts can constrain the primordial power spectrum. Measurements of the primary anisotropies in the cosmic microwave background (CMB) may be limited, by the presence of foregrounds from secondary sources, to probing the primordial power spectrum at wave numbers less than about 0.30 h Mpc^{-1}. We break up the primordial power spectrum into a number of nodes and interpolate linearly between each node. This allows us to show that cluster number counts could then extend the constraints on the form of the primordial power spectrum up to wave numbers of about 0.45 h Mpc^{-1}. We estimate combinations of constraints from PLANCK and SPT primary CMB and their respective SZ surveys. We find that their constraining ability is limited by uncertainties in the mass scaling relations. We also estimate the constraint from clusters detected from a SNAP like gravitational lensing survey. As there is an unambiguous and simple relationship between the filtered shear of the lensing survey and the cluster mass, it may be possible to obtain much tighter constraints on the primordial power spectrum in this case.Comment: Clarifications added and a few minor corrections made. Matches version to appear in PR

A domain-specific design architecture for composite material design and aircraft part redesign

Advanced composites have been targeted as a 'leapfrog' technology that would provide a unique global competitive position for U.S. industry. Composites are unique in the requirements for an integrated approach to designing, manufacturing, and marketing of products developed utilizing the new materials of construction. Numerous studies extending across the entire economic spectrum of the United States from aerospace to military to durable goods have identified composites as a 'key' technology. In general there have been two approaches to composite construction: build models of a given composite materials, then determine characteristics of the material via numerical simulation and empirical testing; and experience-directed construction of fabrication plans for building composites with given properties. The first route sets a goal to capture basic understanding of a device (the composite) by use of a rigorous mathematical model; the second attempts to capture the expertise about the process of fabricating a composite (to date) at a surface level typically expressed in a rule based system. From an AI perspective, these two research lines are attacking distinctly different problems, and both tracks have current limitations. The mathematical modeling approach has yielded a wealth of data but a large number of simplifying assumptions are needed to make numerical simulation tractable. Likewise, although surface level expertise about how to build a particular composite may yield important results, recent trends in the KBS area are towards augmenting surface level problem solving with deeper level knowledge. Many of the relative advantages of composites, e.g., the strength:weight ratio, is most prominent when the entire component is designed as a unitary piece. The bottleneck in undertaking such unitary design lies in the difficulty of the re-design task. Designing the fabrication protocols for a complex-shaped, thick section composite are currently very difficult. It is in fact this difficulty that our research will address

Model-Independent Constraints on Dark Energy Density from Flux-averaging Analysis of Type Ia Supernova Data

We reconstruct the dark energy density $\rho_X(z)$ as a free function from current type Ia supernova (SN Ia) data (Tonry et al. 2003; Barris et al. 2003; Knop et al. 2003), together with the Cosmic Microwave Background (CMB) shift parameter from CMB data (WMAP, CBI, and ACBAR), and the large scale structure (LSS) growth factor from 2dF galaxy survey data. We parametrize $\rho_X(z)$ as a continuous function, given by interpolating its amplitudes at equally spaced $z$ values in the redshift range covered by SN Ia data, and a constant at larger $z$ (where $\rho_X(z)$ is only weakly constrained by CMB data). We assume a flat universe, and use the Markov Chain Monte Carlo (MCMC) technique in our analysis. We find that the dark energy density $\rho_X(z)$ is constant for 0 \la z \la 0.5 and increases with redshift $z$ for 0.5 \la z \la 1 at 68.3% confidence level, but is consistent with a constant at 95% confidence level. For comparison, we also give constraints on a constant equation of state for the dark energy. Flux-averaging of SN Ia data is required to yield cosmological parameter constraints that are free of the bias induced by weak gravitational lensing \citep{Wang00b}. We set up a consistent framework for flux-averaging analysis of SN Ia data, based on \cite{Wang00b}. We find that flux-averaging of SN Ia data leads to slightly lower $\Omega_m$ and smaller time-variation in $\rho_X(z)$. This suggests that a significant increase in the number of SNe Ia from deep SN surveys on a dedicated telescope \citep{Wang00a} is needed to place a robust constraint on the time-dependence of the dark energy density.Comment: Slightly revised in presentation, ApJ accepted. One color figure shows rho_X(z) reconstructed from dat

The effects of a single dose of 7,12-dimethylbenz(a)-anthracene on the epidermis and hair follicles of mice, with notes on concurrent changes in the ovaries and adrenals.

IN spite of the fact that skin was the first tissue in which chemical carcinogenesis was demonstrated, and that it is possible to study all stages of the carcinogenic process by inspection, there is still much controversy over the mechanism. One factor that has given rise to much debate is the part played by the hair follicles. In a previous paper (Orr, 1955), results were described which appeared to show that with a potent carcinogen the original hair follicles were completely destroyed, and replaced by differentiation from the regenerating epidermis, and that neither the original nor the neogenetic hair follicles gave rise to tumours. The earlier experiment was done with outbred albino mice. The present paper seeks to confirm and expand the results using pure-strain mice. During necropsies on the animals, changes were observed in the ovaries and adrenals, and brief notes on the nature of such changes have been appended to the main object of this communication. MATERIAL AND METHODS Three pure-line strains of mice were used: BALB/cf/Sp, March (MAf/Sp), and C3H/Sp. All mice were female; this was originally because of availability, but when during the experiment changes were observed in the ovaries, it was decided to continue with this sex. Twenty-eight mice of each strain were used. They were housed in metal boxes, up to three in a box, and fed on Purina Laboratory Chow, with water ad libiturn. They received one application (circa 0.15 ml.) of a 0.5 % solution in acetone of 7,12-dimethylbenz(a)anthracene (DMBA), on the interscapular skin. Half of them received this on the first day of the experiment, the remainder 4 days later, to obviate the necessity for killing animals at the week-ends. One animal o