BARD: Better Automated Redistricting

BARD is the first (and at time of writing, only) open source software package for general redistricting and redistricting analysis. BARD provides methods to create, display, compare, edit, automatically refine, evaluate, and profile political districting plans. BARD aims to provide a framework for scientific analysis of redistricting plans and to facilitate wider public participation in the creation of new plans. BARD facilitates map creation and refinement through command-line, graphical user interface, and automatic methods. Since redistricting is a computationally complex partitioning problem not amenable to an exact optimization solution, BARD implements a variety of selectable metaheuristics that can be used to refine existing or randomly-generated redistricting plans based on user-determined criteria. Furthermore, BARD supports automated generation of redistricting plans and profiling of plans by assigning different weights to various criteria, such as district compactness or equality of population. This functionality permits exploration of trade-offs among criteria. The intent of a redistricting authority may be explored by examining these trade-offs and inferring which reasonably observable plans were not adopted. Redistricting is a computationally-intensive problem for even modest-sized states. Performance is thus an important consideration in BARD's design and implementation. The program implements performance enhancements such as evaluation caching, explicit memory management, and distributed computing across snow clusters.

Stripping of the Hot Gas Halos in Member Galaxies of Abell 1795

The nearby cluster Abell 1795 is used as a testbed to examine whether hot gas in cluster galaxies is stripped by the ram pressure of the intracluster medium (ICM). The expected X-ray emission in and around Abell 1795 galaxies is likely dominated by the ICM, low-mass X-ray binaries, active galactic nuclei, and hot gas halos. In order to constrain these components, we use archival Chandra X-ray Observatory and Sloan Digital Sky Survey (SDSS) observations of Abell 1795 and identify 58 massive (M_star>10^10 M_sun) spectroscopic cluster members within 5 arcmin of the Chandra optical axis. X-ray images at 0.5-1.5 keV and 4-8 keV were created for each cluster member and then stacked into two clustercentric radius bins: inner (0.25<R/R_500<1) and outer (1<R/R_500<2.5). Surface brightness profiles of inner and outer cluster members are fit using Markov chain Monte Carlo sampling in order to generate model parameters and measure the 0.5-1.5 keV luminosities of each model component. Leveraging effective total Chandra exposure times of 3.4 and 1.7 Msec for inner and outer cluster members, respectively, we report the detection of hot gas halos, in a statistical sense, around outer cluster members. Outer members have 0.5-1.5 keV hot halo luminosities (L_X = 8.1(-3.5/+5)x10^39 erg/s) that are six times larger than the upper limit for inner cluster members (L_X < 1.3x10^39 erg/s). This result suggests that the ICM is removing hot gas from the halos of Abell 1795 members as they fall into the cluster.Comment: 15 pages, nine figures, accepted for publication in The Astrophysical Journa

Matrix Roots of Eventually Positive Matrices

Eventually positive matrices are real matrices whose powers become and remain strictly positive. As such, eventually positive matrices are a fortiori matrix roots of positive matrices, which motivates us to study the matrix roots of primitive matrices. Using classical matrix function theory and Perron-Frobenius theory, we characterize, classify, and describe in terms of the real Jordan canonical form the $p$th-roots of eventually positive matrices.Comment: Accepted for publication in Linear Algebra and its Application

accuracy: Tools for Accurate and Reliable Statistical Computing

Most empirical social scientists are surprised that low-level numerical issues in software can have deleterious effects on the estimation process. Statistical analyses that appear to be perfectly successful can be invalidated by concealed numerical problems. We have developed a set of tools, contained in accuracy, a package for R and S-PLUS, to diagnose problems stemming from numerical and measurement error and to improve the accuracy of inferences. The tools included in accuracy include a framework for gauging the computational stability of model results, tools for comparing model results, optimization diagnostics, and tools for collecting entropy for true random numbers generation.

HST-COS Spectroscopy of the Cooling Flow in Abell 1795 - Evidence for Inefficient Star Formation in Condensing Intracluster Gas

We present far-UV spectroscopy from the Cosmic Origins Spectrograph on the Hubble Space Telescope of a cool, star-forming filament in the core of Abell 1795. These data, which span 1025A - 1700A, allow for the simultaneous modeling of the young stellar populations and the intermediate-temperature (10^5.5 K) gas in this filament, which is far removed (~30 kpc) from the direct influence of the central AGN. Using a combination of UV absorption line indices and stellar population synthesis modeling, we find evidence for ongoing star formation, with the youngest stars having ages of 7.5 +/- 2.0 Myr and metallicities of 0.4 +/- 0.2 Zsun. The latter is consistent with the local metallicity of the intracluster medium. We detect the O VI (1038) line, measuring a flux of 4.0 +/- 0.9 x 10^-17 erg s^-1 cm^-2. The O VI (1032) line is redshifted such that it is coincident with a strong Galactic H2 absorption feature, and is not detected. The measured O VI (1038) flux corresponds to a cooling rate of 0.85 +/- 0.2 (stat) +/- 0.15 (sys) Msun/yr at ~10^5.5 K, assuming that the cooling proceeds isochorically, which is consistent with the classical X-ray luminosity-derived cooling rate in the same region. We measure a star formation rate of 0.11 +/- 0.02 Msun/yr from the UV continuum, suggesting that star formation is proceeding at 13 +/- 3% efficiency in this filament. We propose that this inefficient star formation represents a significant contribution to the larger-scale cooling flow problem.Comment: 6 pages, 4 figures. Accepted for publication in ApJ Letter

New Constraints on the Escape of Ionizing Photons From Starburst Galaxies Using Ionization-Parameter Mapping

The fate of ionizing radiation in starburst galaxies is key to understanding cosmic reionization. However, the galactic parameters on which the escape fraction of ionizing radiation depend are not well understood. Ionization-parameter mapping provides a simple, yet effective, way to study the radiative transfer in starburst galaxies. We obtain emission-line ratio maps of [SIII]/[SII] for six, nearby, dwarf starbursts: NGC 178, NGC 1482, NGC 1705, NGC 3125, NGC 7126, and He 2-10. The narrow-band images are obtained with the Maryland-Magellan Tunable Filter at Las Campanas Observatory. Using these data, we previously reported the discovery of an optically thin ionization cone in NGC 5253, and here we also discover a similar ionization cone in NGC 3125. This latter cone has an opening angle of 40+/-5 degrees (0.4 ster), indicating that the passageways through which ionizing radiation may travel correspond to a small solid angle. Additionally, there are three sample galaxies that have winds and/or superbubble activity, which should be conducive to escaping radiation, yet they are optically thick. These results support the scenario that an orientation bias limits our ability to directly detect escaping Lyman continuum in many starburst galaxies. A comparison of the star-formation properties and histories of the optically thin and thick galaxies is consistent with the model that high escape fractions are limited to galaxies that are old enough (> 3 Myr) for mechanical feedback to have cleared optically thin passageways in the ISM, but young enough (< 5 Myr) that the ionizing stars are still present.Comment: Accepted for publication in Ap

Cool Core Bias in Sunyaev-Zel'dovich Galaxy Cluster Surveys

Sunyaev-Zeldovich (SZ) surveys find massive clusters of galaxies by measuring the inverse Compton scattering of cosmic microwave background off of intra-cluster gas. The cluster selection function from such surveys is expected to be nearly independent of redshift and cluster astrophysics. In this work, we estimate the effect on the observed SZ signal of centrally-peaked gas density profiles (cool cores) and radio emission from the brightest cluster galaxy (BCG) by creating mock observations of a sample of clusters that span the observed range of classical cooling rates and radio luminosities. For each cluster, we make simulated SZ observations by the South Pole Telescope and characterize the cluster selection function, but note that our results are broadly applicable to other SZ surveys. We find that the inclusion of a cool core can cause a change in the measured SPT significance of a cluster between 0.01% - 10% at z > 0.3, increasing with cuspiness of the cool core and angular size on the sky of the cluster (i.e., decreasing redshift, increasing mass). We provide quantitative estimates of the bias in the SZ signal as a function of a gas density cuspiness parameter, redshift, mass, and the 1.4 GHz radio luminosity of the central AGN. Based on this work, we estimate that, for the Phoenix cluster (one of the strongest cool cores known), the presence of a cool core is biasing the SZ significance high by ~ 6%. The ubiquity of radio galaxies at the centers of cool core clusters will offset the cool core bias to varying degrees.Comment: 8 pages, 4 figures, accepted to Ap

The challenging task of determining star formation rates: the case of a massive stellar burst in the brightest cluster galaxy of Phoenix galaxy cluster

Star formation in galaxies at the center of cooling-flow galaxy clusters is an important phenomenon in the context of formation and evolution of massive galaxies in the Universe. Yet, star formation rates (SFRs) in such systems continue to be elusive. We use our Bayesian-motivated spectral energy distribution (SED)-fitting code, BAYESCOOL, to estimate the plausible SFR values in the brightest cluster galaxy of a massive, X-ray luminous galaxy cluster, Phoenix. Previous studies of Phoenix have resulted in the highest measurement of SFR for any galaxy, with the estimates reaching up to 1000 solar masses/yr. However, a very small number of models have been considered in those studies. BAYESCOOL allows us to probe a large parameter space. We consider two models for star formation history, instantaneous bursts and continuous star formation, a wide range of ages for the old and the young stellar population, along with other discrete parameters, such as the initial mass function, metallicities, internal extinction and extinction law. We find that in the absence of any prior except that the maximum cooling rate < 3000 solar masses/yr, the SFR lies in the range (2230-2890) solar masses/yr. If we impose an observational prior on the internal extinction, E(B-V) < 0.6, the best-fit SFR lies in (454-494) solar masses/yr, and we consider this as the most probable range of SFR values for Phoenix. The SFR dependence on the extinction is a reflection of the standard age-extinction degeneracy, which can be overcome by using a prior on one of the two quantities in question.Comment: 12 pages, 4 figures, 1 Table, accepted for publication in MNRA

Wind Energy in Ireland - An Analysis of Percentage Error in Forecasting

This research aimed to examine the percentage error in forecasting of wind energy using datasets from a small wind farm in Ireland. Furthermore, the study aimed to compare this calculated data to the national forecasting percentage errors. Internationally, the electrical sector and society are undergoing a revolution in terms of \u27green economy\u27. This paradigm shift towards renewable energy technologies is recognised as a priority, with diminution of finite fossil fuels at its core. Renewable energy as a sector has provided significant financial stimulation to global economies in recent years. Moreover, wind energy has provided significant amounts of clean electricity throughout the world. However, due to its very nature, wind energy presents uncertainties which lead to errors in forecasting, which this study aimed to analyse. It is believed that accurate wind energy forecasting will allow establishment of an appropriate generation mix in future electrical networks. Thus, forecasting and percentage error is essential to wind energy integration, especially as installed capacity is estimated to increase substantially in the coming years. Using datasets based on various time series, this research collated, calculated and analysed the percentage error between predicted and actual wind energy output from a small wind farm (micro level) and at a national level (macro level). The findings of the research were that at the micro level there was a percentage error of -0.36% and at the macro level a percentage error of 5.7% over a twelve month period. The data in this study gives great insight into wind energy forecasting and the research discusses the effects of percentage errors in the renewable energy sector as wind capacity increases