A Bramble-Pasciak conjugate gradient method for discrete Stokes equations with random viscosity

We study the iterative solution of linear systems of equations arising from stochastic Galerkin finite element discretizations of saddle point problems. We focus on the Stokes model with random data parametrized by uniformly distributed random variables and discuss well-posedness of the variational formulations. We introduce a Bramble-Pasciak conjugate gradient method as a linear solver. It builds on a non-standard inner product associated with a block triangular preconditioner. The block triangular structure enables more sophisticated preconditioners than the block diagonal structure usually applied in MINRES methods. We show how the existence requirements of a conjugate gradient method can be met in our setting. We analyze the performance of the solvers depending on relevant physical and numerical parameters by means of eigenvalue estimates. For this purpose, we derive bounds for the eigenvalues of the relevant preconditioned sub-matrices. We illustrate our findings using the flow in a driven cavity as a numerical test case, where the viscosity is given by a truncated Karhunen-Lo\`eve expansion of a random field. In this example, a Bramble-Pasciak conjugate gradient method with block triangular preconditioner outperforms a MINRES method with block diagonal preconditioner in terms of iteration numbers.Comment: 19 pages, 1 figure, submitted to SIAM JU

Supernova neutrino physics with xenon dark matter detectors: A timely perspective

Dark matter detectors that utilize liquid xenon have now achieved tonne-scale targets, giving them sensitivity to all flavours of supernova neutrinos via coherent elastic neutrino-nucleus scattering. Considering for the first time a realistic detector model, we simulate the expected supernova neutrino signal for different progenitor masses and nuclear equations of state in existing and upcoming dual-phase liquid xenon experiments. We show that the proportional scintillation signal (S2) of a dual-phase detector allows for a clear observation of the neutrino signal and guarantees a particularly low energy threshold, while the backgrounds are rendered negligible during the supernova burst. XENON1T (XENONnT and LZ; DARWIN) experiments will be sensitive to a supernova burst up to 25 (35; 65) kpc from Earth at a significance of more than 5 sigma, observing approximately 35 (123; 704) events from a 27 Msun supernova progenitor at 10 kpc. Moreover, it will be possible to measure the average neutrino energy of all flavours, to constrain the total explosion energy, and to reconstruct the supernova neutrino light curve. Our results suggest that a large xenon detector such as DARWIN will be competitive with dedicated neutrino telescopes, while providing complementary information that is not otherwise accessible.Comment: 19 pages, 9 figures. Minor revisions compared to original version. Matches version published in Phys. Rev.

Cleaning the USNO-B Catalog through automatic detection of optical artifacts

The USNO-B Catalog contains spurious entries that are caused by diffraction spikes and circular reflection halos around bright stars in the original imaging data. These spurious entries appear in the Catalog as if they were real stars; they are confusing for some scientific tasks. The spurious entries can be identified by simple computer vision techniques because they produce repeatable patterns on the sky. Some techniques employed here are variants of the Hough transform, one of which is sensitive to (two-dimensional) overdensities of faint stars in thin right-angle cross patterns centered on bright (<13 \mag) stars, and one of which is sensitive to thin annular overdensities centered on very bright (<7 \mag) stars. After enforcing conservative statistical requirements on spurious-entry identifications, we find that of the 1,042,618,261 entries in the USNO-B Catalog, 24,148,382 of them (2.3 \percent) are identified as spurious by diffraction-spike criteria and 196,133 (0.02 \percent) are identified as spurious by reflection-halo criteria. The spurious entries are often detected in more than 2 bands and are not overwhelmingly outliers in any photometric properties; they therefore cannot be rejected easily on other grounds, i.e., without the use of computer vision techniques. We demonstrate our method, and return to the community in electronic form a table of spurious entries in the Catalog.Comment: published in A

Silicon Whisker and Carbon Nanofiber Composite Anode

Phase II Objectives: Demonstrate production levels of grams per batch; Achieve full cell anode capacity of greater than 1,000 mAh/g at a charge rate of 10 (C/10) and 0 degree C; Establish a full cell cycle life of over 300 cycles; Display an operating temperature of negative 30 degrees C to plus 30 degrees C; Demonstrate a rate capability of C/5 or higher; Deliver to NASA three 2.5 Ah cells (energy density greater than 220 Wh/kg); Exhibit the safety features of the anode and full cells; Design a 1 kWh prismatic battery pack

Targeting maps: An asset-based approach to geographic targeting

Proper targeting of policy interventions requires reasonable estimates of the benefits of the alternative options. To inform such decisions, we develop an integrated approach stemming from the small-area estimation literature that estimates the marginal returns to a range of assets across geographically defined subpopulations. We create a series of maps that can be overlaid with traditional poverty maps to identify strong candidate areas for intervention, though an efficiency/equity tradeoff sometimes exists. We apply our method using recent Ugandan data. Results are consistent with independent empirical findings and suggest asset specific transfer schemes would improve with a spatially targeted strategy

The unique and common effects of emotional intelligence dimensions on job satisfaction and facets of job performance:an exploratory study in three countries

Previous empirical studies have either used a unidimensional or a multidimensional analytical approach to examine the consequences of emotional intelligence (EI). In this exploratory study we integrate and extend these two approaches, using a novel perspective to better understand the structure of the EI-job satisfaction and the EI-job performance relationship. Using commonality analysis and data from Germany, India, as well as the U.S. we partition the explained variance for job satisfaction, in- role performance, and extra-role performance into the variance that is uniquely explained by the individual EI dimensions and the variance that is common to sets of EI dimensions. We provide evidence that the EI dimensions are differently related to job satisfaction and job performance facets. Furthermore, the findings offer insights on how unique and common effects vary across countries. Partitioning the unique and commonly shared variance allows us to assess the true predictive power of individual EI dimensions and of sets of EI dimensions. Based on these findings, we discuss implications for theory development and provide future research directions