Ultraviolet Observations of Super-Chandrasekhar Mass Type Ia Supernova Candidates with Swift UVOT

Among Type Ia supernovae (SNe~Ia) exist a class of overluminous objects whose ejecta mass is inferred to be larger than the canonical Chandrasekhar mass. We present and discuss the UV/optical photometric light curves, colors, absolute magnitudes, and spectra of three candidate Super-Chandrasekhar mass SNe--2009dc, 2011aa, and 2012dn--observed with the Swift Ultraviolet/Optical Telescope. The light curves are at the broad end for SNe Ia, with the light curves of SN~2011aa being amongst the broadest ever observed. We find all three to have very blue colors which may provide a means of excluding these overluminous SNe from cosmological analysis, though there is some overlap with the bluest of "normal" SNe Ia. All three are overluminous in their UV absolute magnitudes compared to normal and broad SNe Ia, but SNe 2011aa and 2012dn are not optically overluminous compared to normal SNe Ia. The integrated luminosity curves of SNe 2011aa and 2012dn in the UVOT range (1600-6000 Angstroms) are only half as bright as SN~2009dc, implying a smaller 56Ni yield. While not enough to strongly affect the bolometric flux, the early time mid-UV flux makes a significant contribution at early times. The strong spectral features in the mid-UV spectra of SNe 2009dc and 2012dn suggest a higher temperature and lower opacity to be the cause of the UV excess rather than a hot, smooth blackbody from shock interaction. Further work is needed to determine the ejecta and 56Ni masses of SNe 2011aa and 2012dn and fully explain their high UV luminosities.Comment: 12 pages, 8 figures Accepted for publication in the Astrophysical Journal Data available on the Swift supernova website http://swift.gsfc.nasa.gov/docs/swift/sne/swift_sn.htm

An approach to model validation and model-based prediction -- polyurethane foam case study.

Enhanced software methodology and improved computing hardware have advanced the state of simulation technology to a point where large physics-based codes can be a major contributor in many systems analyses. This shift toward the use of computational methods has brought with it new research challenges in a number of areas including characterization of uncertainty, model validation, and the analysis of computer output. It is these challenges that have motivated the work described in this report. Approaches to and methods for model validation and (model-based) prediction have been developed recently in the engineering, mathematics and statistical literatures. In this report we have provided a fairly detailed account of one approach to model validation and prediction applied to an analysis investigating thermal decomposition of polyurethane foam. A model simulates the evolution of the foam in a high temperature environment as it transforms from a solid to a gas phase. The available modeling and experimental results serve as data for a case study focusing our model validation and prediction developmental efforts on this specific thermal application. We discuss several elements of the ''philosophy'' behind the validation and prediction approach: (1) We view the validation process as an activity applying to the use of a specific computational model for a specific application. We do acknowledge, however, that an important part of the overall development of a computational simulation initiative is the feedback provided to model developers and analysts associated with the application. (2) We utilize information obtained for the calibration of model parameters to estimate the parameters and quantify uncertainty in the estimates. We rely, however, on validation data (or data from similar analyses) to measure the variability that contributes to the uncertainty in predictions for specific systems or units (unit-to-unit variability). (3) We perform statistical analyses and hypothesis tests as a part of the validation step to provide feedback to analysts and modelers. Decisions on how to proceed in making model-based predictions are made based on these analyses together with the application requirements. Updating modifying and understanding the boundaries associated with the model are also assisted through this feedback. (4) We include a ''model supplement term'' when model problems are indicated. This term provides a (bias) correction to the model so that it will better match the experimental results and more accurately account for uncertainty. Presumably, as the models continue to develop and are used for future applications, the causes for these apparent biases will be identified and the need for this supplementary modeling will diminish. (5) We use a response-modeling approach for our predictions that allows for general types of prediction and for assessment of prediction uncertainty. This approach is demonstrated through a case study supporting the assessment of a weapons response when subjected to a hydrocarbon fuel fire. The foam decomposition model provides an important element of the response of a weapon system in this abnormal thermal environment. Rigid foam is used to encapsulate critical components in the weapon system providing the needed mechanical support as well as thermal isolation. Because the foam begins to decompose at temperatures above 250 C, modeling the decomposition is critical to assessing a weapons response. In the validation analysis it is indicated that the model tends to ''exaggerate'' the effect of temperature changes when compared to the experimental results. The data, however, are too few and to restricted in terms of experimental design to make confident statements regarding modeling problems. For illustration, we assume these indications are correct and compensate for this apparent bias by constructing a model supplement term for use in the model-based predictions. Several hypothetical prediction problems are created and addressed. Hypothetical problems are used because no guidance was provided concerning what was needed for this aspect of the analysis. The resulting predictions and corresponding uncertainty assessment demonstrate the flexibility of this approach

The arithmetic of genus two curves with (4,4)-split Jacobians

In this paper we study genus 2 curves whose Jacobians admit a polarized (4,4)-isogeny to a product of elliptic curves. We consider base fields of characteristic different from 2 and 3, which we do not assume to be algebraically closed. We obtain a full classification of all principally polarized abelian surfaces that can arise from gluing two elliptic curves along their 4-torsion and we derive the relation their absolute invariants satisfy. As an intermediate step, we give a general description of Richelot isogenies between Jacobians of genus 2 curves, where previously only Richelot isogenies with kernels that are pointwise defined over the base field were considered. Our main tool is a Galois theoretic characterization of genus 2 curves admitting multiple Richelot isogenies.Comment: 30 page

Acute response to a 2-minute isometric exercise test predicts the blood pressure lowering efficacy of isometric resistance training in young adults

This work aimed to explore whether different forms of a simple isometric exercise test could be used to predict the blood pressure (BP)-lowering efficacy of different types of isometric resistance training (IRT) in healthy young adults. In light of the emphasis on primary prevention of hypertension, identifying those with normal BP who will respond to IRT is important. Also, heightened BP reactivity increases hypertension risk, and as IRT reduces BP reactivity in patients with hypertension, it warrants further investigation in a healthy population. METHODS Forty-six young men and women (24 ± 5 years; 116 ± 10/ 68 ± 8 mm Hg) were recruited from 2 study sites: Windsor, Canada (n = 26; 13 women), and Northampton, United Kingdom (n = 20; 10 women). Resting BP and BP reactivity to an isometric exercise test were assessed prior to and following 10 weeks of thrice weekly IRT. Canadian participants trained on a handgrip dynamometer (isometric handgrip, IHG), while participants in the UK trained on an isometric leg extension dynamometer (ILE). RESULTS Men and women enrolled in both interventions demonstrated significant reductions in systolic BP (P < 0.001) and pulse pressure (P < 0.05). Additionally, test-induced systolic BP changes to IHG and ILE tests were associated with IHG and ILE training-induced reductions in systolic BP after 10 weeks of training, respectively (r = 0.58 and r = 0.77; for IHG and ILE; P < 0.05). CONCLUSIONS The acute BP response to an isometric exercise test appears to be a viable tool to identify individuals who may respond to traditional IRT prescription

The Peculiar SN 2005hk: Do Some Type Ia Supernovae Explode as Deflagrations?

We present extensive u'g'r'i'BVRIYJHKs photometry and optical spectroscopy of SN 2005hk. These data reveal that SN 2005hk was nearly identical in its observed properties to SN 2002cx, which has been called ``the most peculiar known type Ia supernova.'' Both supernovae exhibited high ionization SN 1991T-like pre-maximum spectra, yet low peak luminosities like SN 1991bg. The spectra reveal that SN 2005hk, like SN 2002cx, exhibited expansion velocities that were roughly half those of typical type Ia supernovae. The R and I light curves of both supernovae were also peculiar in not displaying the secondary maximum observed for normal type Ia supernovae. Our YJH photometry of SN 2005hk reveals the same peculiarity in the near-infrared. By combining our optical and near-infrared photometry of SN 2005hk with published ultraviolet light curves obtained with the Swift satellite, we are able to construct a bolometric light curve from ~10 days before to ~60 days after B maximum. The shape and unusually low peak luminosity of this light curve, plus the low expansion velocities and absence of a secondary maximum at red and near-infrared wavelengths, are all in reasonable agreement with model calculations of a 3D deflagration which produces ~0.25 M_sun of 56Ni.Comment: Accepted by PASP, to appear in April 2007 issue, 63 pages, 16 figures, 11 table

The landscape model: a model for exploring trade-offs between agricultural production and the environment

We describe a model framework that simulates spatial and temporal interactions in agricultural landscapes and that can be used to explore trade-offs between production and environment so helping to determine solutions to the problems of sustainable food production. Here we focus on models of agricultural production, water movement and nutrient flow in a landscape. We validate these models against data from two long-term experiments, (the first a continuous wheat experiment and the other a permanent grass-land experiment) and an experiment where water and nutrient flow are measured from isolated catchments. The model simulated wheat yield (RMSE 20.3–28.6%), grain N (RMSE 21.3–42.5%) and P (RMSE 20.2–29% excluding the nil N plots), and total soil organic carbon particularly well (RMSE 3.1 − 13.8 %), the simulations of water flow were also reasonable (RMSE 180.36 and 226.02%). We illustrate the use of our model framework to explore trade-offs between production and nutrient losses