Testing the interaction of dark energy to dark matter through the analysis of virial relaxation of clusters Abell Clusters A586 and A1689 using realistic density profiles

Interaction between dark energy and dark matter is probed through deviation from the virial equilibrium for two relaxed clusters: A586 and A1689. The evaluation of the virial equilibrium is performed using realistic density profiles. The virial ratios found for the more realistic density profiles are consistent with the absence of interaction.Comment: 16pp 1 fig; accepted by GeR

Electrostatic self-energy and Bekenstein entropy bound in the massive Schwinger model

We obtain the electrostatic energy of two opposite charges near the horizon of stationary black-holes in the massive Schwinger model. Besides the confining aspects of the model, we discuss the Bekenstein entropy upper bound of a charged object using the generalized second law. We show that despite the massless case, in the massive Schwinger model the entropy of the black hole and consequently the Bekenstein bound are altered by the vacuum polarization.Comment: 14 pages, accepted for publication in "Gen. Rel. Grav. (2005)

Highly damped quasinormal modes of Kerr black holes

Motivated by recent suggestions that highly damped black hole quasinormal modes (QNM's) may provide a link between classical general relativity and quantum gravity, we present an extensive computation of highly damped QNM's of Kerr black holes. We do not limit our attention to gravitational modes, thus filling some gaps in the existing literature. The frequency of gravitational modes with l=m=2 tends to \omega_R=2 \Omega, \Omega being the angular velocity of the black hole horizon. If Hod's conjecture is valid, this asymptotic behaviour is related to reversible black hole transformations. Other highly damped modes with m>0 that we computed do not show a similar behaviour. The real part of modes with l=2 and m<0 seems to asymptotically approach a constant value \omega_R\simeq -m\varpi, \varpi\simeq 0.12 being (almost) independent of a. For any perturbing field, trajectories in the complex plane of QNM's with m=0 show a spiralling behaviour, similar to the one observed for Reissner-Nordstrom (RN) black holes. Finally, for any perturbing field, the asymptotic separation in the imaginary part of consecutive modes with m>0 is given by 2\pi T_H (T_H being the black hole temperature). We conjecture that for all values of l and m>0 there is an infinity of modes tending to the critical frequency for superradiance (\omega_R=m) in the extremal limit. Finally, we study in some detail modes branching off the so--called ``algebraically special frequency'' of Schwarzschild black holes. For the first time we find numerically that QNM multiplets emerge from the algebraically special Schwarzschild modes, confirming a recent speculation.Comment: 19 pages, 11 figures. Minor typos corrected. Updated references to take into account some recent development

Transfer learning for galaxy morphology from one survey to another

© 2018 The Author(s). Published by Oxford University Press on behalf of the Royal Astronomical Society.Deep Learning (DL) algorithms for morphological classification of galaxies have proven very successful, mimicking (or even improving) visual classifications. However, these algorithms rely on large training samples of labelled galaxies (typically thousands of them). A key question for using DL classifications in future Big Data surveys is how much of the knowledge acquired from an existing survey can be exported to a new dataset, i.e. if the features learned by the machines are meaningful for different data. We test the performance of DL models, trained with Sloan Digital Sky Survey (SDSS) data, on Dark Energy survey (DES) using images for a sample of $\sim$5000 galaxies with a similar redshift distribution to SDSS. Applying the models directly to DES data provides a reasonable global accuracy ($\sim$ 90%), but small completeness and purity values. A fast domain adaptation step, consisting in a further training with a small DES sample of galaxies ($\sim$500-300), is enough for obtaining an accuracy > 95% and a significant improvement in the completeness and purity values. This demonstrates that, once trained with a particular dataset, machines can quickly adapt to new instrument characteristics (e.g., PSF, seeing, depth), reducing by almost one order of magnitude the necessary training sample for morphological classification. Redshift evolution effects or significant depth differences are not taken into account in this study.Peer reviewedFinal Accepted Versio

Effect of gas-to-liquid biosludge on soil properties and alfalfa yields in an arid soil

Soils in Qatar are relatively poor in fertility. Hence, imported top soils and soil enhancing materials are used to improve agricultural yields. Therefore, this work investigated the potential of using gas-to-liquid (GTL) biosludge as a soil conditioner. It sought to increase crop yields in an arid soil with positive environmental footprint in terms of fertilizer application savings, waste utilization and minimization of landfilling. A fodder crop, alfalfa (Medicago sativa), was grown under semi-controlled pot conditions for 12 months. The plant-growth media involved soil, soil + fertilizer, soil + 3% compost, and soil plus five (0.75–12%) biosludge contents. Pertinent properties of the soils, the resulting leachates, and plant growth parameters were analyzed at set periods. Biosludge content generally increased the total porosity and volumetric abundance of different pore types, which in turn affected plant performance, especially the plant height. Alfalfa yield in terms of plant height, aboveground fresh biomass weight and the number of tillers decreased with increasing biosludge content. Mixtures with 0.75–3% biosludge content showed comparable or better plant yield in contrast to the soil, fertilizer and compost controls. The concentration of chemical species in the leachate and plant biomass of biosludge treatments were either lower or similar to the fertilizer and compost controls. Regression modeling identified leachate phosphorus concentrations, soil iron concentration and clay content as the most influential variables for the aforementioned plant performance parameters. The results suggest that GTL biosludge could potentially enhance arid soil properties and improve alfalfa yields

Dataset on the influence of gas-to-liquid biosludge on arid soil properties and growth performance of alfalfa

The dataset presented here is related to our research article entitled “Effect of gas-to-liquid biosludge on soil properties and alfalfa yields in an arid soil” [1]. It relates to selected performance parameters of alfalfa grown in an arid soil amended with five different (0.75–12%) gas-to-liquid biosludge contents, and selected properties of the soil determined using several material characterization techniques. A detailed description of the raw data relating to figures on alfalfa performance parameters such as fresh biomass weight, plant height, the number of tillers, and biomass elemental content in the companion article is provided alongside additional data on the number of days to flowering. The underlying data for leachate from the soil and underlying spectra and diffractograms for the proton nuclear magnetic resonance (1H-NMR) and X-ray diffraction (XRD) data, respectively, shown in the companion article are presented. These show changes in the pore structure characteristics and the mineralogical composition of the soil, soil-fertilizer, soil-biosludge, and soil-compost mixtures tested over time. Additional data showing the effect of the amendments on the bulk and particle densities of the soil is presented. The dataset demonstrates the influence of the industrial biosludge on arid soil properties and alfalfa yields (Kogbara et al., [1])

Recycling industrial biosludge for buffel grass production in Qatar: impact on soil, leachate and plant characteristics

The agricultural industry in Qatar is highly dependent on using soil enhancing materials due to challenging soil and climatic conditions. Hence, this work investigated the potential of industrial biosludge from the wastewater treatment plant (WWTP) of a Gas-to-Liquids (GTL) plant to enhance an arid soil compared to fertilizer and compost. A fodder crop, buffel grass (Cenchrus ciliaris), was grown in semi-controlled pots containing a typical Qatari agricultural soil and admixtures over a 12-month period. The treatments included soil plus five biosludge percentage contents: 0.75, 1.5, 3, 6 and 12%. These were compared with soil only, soil plus 20-20-20 NPK fertilizer and soil plus 3% compost controls. Analyses of soil physical and chemical properties, the resulting leachate, and plant growth characteristics were conducted at set periods. The results indicate that up to 3% biosludge content led to better plant growth compared to the controls, with the optimum at 1.5% biosludge content for all growth characteristics studied. Biosludge addition to soil increased the volume of different pore types, especially micropores, which enhanced water retention and influenced plant growth. Regression modelling identified leachate Si and Fe concentrations, and biomass K content as the most influential variables for fresh biomass weight, plant height and the number of tillers, respectively. Biosludge addition to the soil around the optimum level did not cause detrimental changes to the resulting leachate and plant biomass. The findings of this work could lead to minimization of biosludge landfilling and allow for savings in fertilizers and irrigation water in arid regions

Dataset comparing the growth of fodder crops and soil structure dynamics in an industrial biosludge amended arid soil

The dataset in this work compares the response of two fodder crops, alfalfa (Medicago sativa) and buffel grass (Cenchrus ciliaris), to industrial biosludge amendment of an arid soil in the State of Qatar. It also evaluates the response of soil structure parameters in the biosludge-amended soils containing the different fodder crops. The dataset relates to our previously published works detailed subsequently. The underlying data comparing the water storage capacity and pore structure evolution of the planted soils treated with 0.75, 1.5, and 3% biosludge contents, which showed good outcomes in the companion articles, alongside soil only and soil-fertilizer controls, are presented. These are shown in terms of the percentage of irrigation water leached, and variations in the logarithmic mean T2 (i.e., T2LM - a proxy for mean pore size) and cumulative porosity, respectively. Data on plant growth parameters such as the number of days to flowering, plant height, and aboveground fresh biomass weight in individual replicates of the different treatments as a percentage of the soil-fertilizer control are also shown. The dataset shows the different responses of both plants and the planted soils to amendments with industrial biosludge from the wastewater treatment plant of a gas-to-liquid (GTL) plant

On the Construction of Quantum Field Theories with Factorizing S-Matrices

The subject of this thesis is a novel construction method for interacting relativistic quantum field theories on two-dimensional Minkowski space. The input in this construction is not a classical Lagrangian, but rather a prescribed factorizing S-matrix, i.e. the inverse scattering problem for such quantum field theories is studied. For a large class of factorizing S-matrices, certain associated quantum fields, which are localized in wedge-shaped regions of Minkowski space, are constructed explicitely. With the help of these fields, the local observable content of the corresponding model is defined and analyzed by employing methods from the algebraic framework of quantum field theory. The abstract problem in this analysis amounts to the question under which conditions an algebra of wedge-localized observables can be used to generate a net of local observable algebras with the right physical properties. The answer given here uses the so-called modular nuclearity condition, which is shown to imply the existence of local observables and the Reeh-Schlieder property. In the analysis of the concrete models, this condition is proven for a large family of S-matrices, including the scattering operators of the Sinh-Gordon model and the scaling Ising model as special examples. The so constructed models are then investigated with respect to their scattering properties. They are shown to solve the inverse scattering problem for the considered S-matrices, and a proof of asymptotic completeness is given.Comment: PhD thesis, Goettingen university, 2006 (advisor: D. Buchholz) 153 pages, 10 figure

DES13S2cmm: the first superluminous supernova from the Dark Energy Survey

We present DES13S2cmm, the first spectroscopically-confirmed superluminous supernova (SLSN) from the Dark Energy Survey (DES). We briefly discuss the data and search algorithm used to find this event in the first year of DES operations, and outline the spectroscopic data obtained from the European Southern Observatory (ESO) Very Large Telescope to confirm its redshift (z = 0.663 +/- 0.001 based on the host-galaxy emission lines) and likely spectral type (type I). Using this redshift, we find M_U_peak = -21.05 +0.10 -0.09 for the peak, rest-frame U-band absolute magnitude, and find DES13S2cmm to be located in a faint, low metallicity (sub-solar), low stellar-mass host galaxy (log(M/M_sun) = 9.3 +/- 0.3); consistent with what is seen for other SLSNe-I. We compare the bolometric light curve of DES13S2cmm to fourteen similarly well-observed SLSNe-I in the literature and find it possesses one of the slowest declining tails (beyond +30 days rest frame past peak), and is the faintest at peak. Moreover, we find the bolometric light curves of all SLSNe-I studied herein possess a dispersion of only 0.2-0.3 magnitudes between +25 and +30 days after peak (rest frame) depending on redshift range studied; this could be important for 'standardising' such supernovae, as is done with the more common type Ia. We fit the bolometric light curve of DES13S2cmm with two competing models for SLSNe-I - the radioactive decay of 56Ni, and a magnetar - and find that while the magnetar is formally a better fit, neither model provides a compelling match to the data. Although we are unable to conclusively differentiate between these two physical models for this particular SLSN-I, further DES observations of more SLSNe-I should break this degeneracy, especially if the light curves of SLSNe-I can be observed beyond 100 days in the rest frame of the supernova.Comment: Accepted by MNRAS (2015 January 23), 13 pages, 6 figures, 2 table