Hyperstaticity and loops in frictional granular packings

The hyperstatic nature of granular packings of perfectly rigid disks is analyzed algebraically and through numerical simulation. The elementary loops of grains emerge as a fundamental element in addressing hyperstaticity. Loops consisting of an odd number of grains behave differently than those with an even number. For odd loops, the latent stresses are exterior and are characterized by the sum of frictional forces around each loop. For even loops, the latent stresses are interior and are characterized by the alternating sum of frictional forces around each loop. The statistics of these two types of loop sums are found to be Gibbsian with a "temperature" that is linear with the friction coefficient mu when mu<1.Comment: 4 pages; Powders and Grains 2009, Golden, Colorado, US

The SBF Survey of Galaxy Distances. I. Sample Selection, Photometric Calibration, and the Hubble Constant

We describe a program of surface brightness fluctuation (SBF) measurements for determining galaxy distances. This paper presents the photometric calibration of our sample and of SBF in general. Basing our zero point on observations of Cepheid variable stars, we find that the absolute SBF magnitude in the Kron-Cousins I band correlates well with the mean (V-I)o color of a galaxy according to M_Ibar = (-1.74 +/- 0.07) + (4.5 +/- 0.25) [ (V-I)o - 1.15 ] for 1.0 < (V-I) < 1.3. This agrees well with theoretical estimates from stellar population models. Comparisons between SBF distances and a variety of other estimators, including Cepheid variable stars, the Planetary Nebula Luminosity Function (PNLF), Tully-Fisher (TF), Dn-sigma, SNII, and SNIa, demonstrate that the calibration of SBF is universally valid and that SBF error estimates are accurate. The zero point given by Cepheids, PNLF, TF (both calibrated using Cepheids), and SNII is in units of Mpc; the zero point given by TF (referenced to a distant frame), Dn-sigma and SNIa is in terms of a Hubble expansion velocity expressed in km/s. Tying together these two zero points yields a Hubble constant of H_0 = 81 +/- 6 km/s/Mpc. As part of this analysis, we present SBF distances to 12 nearby groups of galaxies where Cepheids, SNII, and SNIa have been observed.Comment: 29 pages plus 8 figures; LaTeX (AASTeX) uses aaspp4.sty (included); To appear in The Astrophysical Journal, 1997 February 1 issue; Compressed PostScript available from ftp://mars.tuc.noao.edu/sbf

The SBF Survey of Galaxy Distances. IV. SBF Magnitudes, Colors, and Distances

We report data for $I$ band Surface Brightness Fluctuation (SBF) magnitudes, V-I colors, and distance moduli for 300 galaxies. The Survey contains E, S0 and early-type spiral galaxies in the proportions of 49:42:9, and is essentially complete for E galaxies to Hubble velocities of 2000 km/s, with a substantial sampling of E galaxies out to 4000 km/s. The median error in distance modulus is 0.22 mag. We also present two new results from the Survey. (1) We compare the mean peculiar flow velocity (bulk flow) implied by our distances with predictions of typical cold dark matter transfer functions as a function of scale, and find very good agreement with cold, dark matter cosmologies if the transfer function scale parameter $\Gamma$, and the power spectrum normalization $\sigma_8$ are related by $\sigma_8 \Gamma^{-0.5} \approx 2\pm0.5$. Derived directly from velocities, this result is independent of the distribution of galaxies or models for biasing. The modest bulk flow contradicts reports of large-scale, large-amplitude flows in the $\sim200$ Mpc diameter volume surrounding our Survey volume. (2) We present a distance-independent measure of absolute galaxy luminosity, \Nbar, and show how it correlates with galaxy properties such as color and velocity dispersion, demonstrating its utility for measuring galaxy distances through large and unknown extinction.Comment: Accepted for publication in ApJ (10 January 2001); 23 page

Technical Research Priorities for Big Data

To drive innovation and competitiveness, organisations need to foster the development and broad adoption of data technologies, value-adding use cases and sustainable business models. Enabling an effective data ecosystem requires overcoming several technical challenges associated with the cost and complexity of management, processing, analysis and utilisation of data. This chapter details a community-driven initiative to identify and characterise the key technical research priorities for research and development in data technologies. The chapter examines the systemic and structured methodology used to gather inputs from over 200 stakeholder organisations. The result of the process identified five key technical research priorities in the areas of data management, data processing, data analytics, data visualisation and user interactions, and data protection, together with 28 sub-level challenges. The process also highlighted the important role of data standardisation, data engineering and DevOps for Big Data