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Comparisons between observed and predicted strong lensing properties of galaxy clusters have been routinely used to claim either tension or consistency with Λ cold dark matter cosmology. However, standard approaches to such cosmological tests are unable to quantify the preference for one cosmology over another.We advocate approximating the relevant Bayes factor using amarginal likelihood that is based on the following summary statistic: the posterior probability distribution function for the parameters of the scaling relation between Einstein radii and cluster mass, α and β. We demonstrate, for the first time, a method of estimating the marginal likelihood using the X-ray selected z > 0.5 Massive Cluster Survey clusters as a case in point and employing both N-body and hydrodynamic simulations of clusters. We investigate the uncertainty in this estimate and consequential ability to compare competing cosmologies, which arises from incomplete descriptions of baryonic processes, discrepancies in cluster selection criteria, redshift distribution and dynamical state. The relation between triaxial cluster masses at various overdensities provides a promising alternative to the strong lensing test. [ABSTRACT FROM AUTHOR]

We invoke a Gaussian mixture model (GMM) to jointly analyse two traditional emission-line classification schemes of galaxy ionization sources: the Baldwin-Phillips-Terlevich (BPT) and WHα versus [N II]/H α (WHAN) diagrams, using spectroscopic data from the Sloan Digital Sky Survey Data Release 7 and SEAGal/STARLIGHT data sets. We apply a GMM to empirically define classes of galaxies in a three-dimensional space spanned by the log [O III]/H β, log [NII]/H α and log EW(H α) optical parameters. The best-fitting GMM based on several statistical criteria suggests a solution around four Gaussian components (GCs), which are capable to explain up to 97 per cent of the data variance. Using elements of information theory, we compare each GC to their respective astronomical counterpart. GC1 and GC4 are associated with star-forming galaxies, suggesting the need to define a new starburst subgroup. GC2 is associated with BPT's active galactic nuclei (AGN) class and WHAN's weak AGN class. GC3 is associated with BPT's composite class and WHAN's strong AGN class. Conversely, there is no statistical evidence - based on four GCs - for the existence of a Seyfert/lowionization nuclear emission-line region (LINER) dichotomy in our sample. Notwithstanding, the inclusion of an additional GC5 unravels it. The GC5 appears associated with the LINER and passive galaxies on the BPT and WHAN diagrams, respectively. This indicates that if the Seyfert/LINER dichotomy is there, it does not account significantly to the global data variance and may be overlooked by standard metrics of goodness of fit. Subtleties aside, we demonstrate the potential of our methodology to recover/unravel different objects inside the wilderness of astronomical data sets, without lacking the ability to convey physically interpretable results. The probabilistic classifications from the GMM analysis are publicly available within the COINtoolbox at https://cointoolbox.github.io/GMM_Catalogue/. [ABSTRACT FROM AUTHOR]

In this paper, the third in a series illustrating the power of generalized linear models (GLMs) for the astronomical community, we elucidate the potential of the class of GLMs which handles count data. The size of a galaxy's globular cluster (GC) population (NGC) is a prolonged puzzle in the astronomical literature. It falls in the category of count data analysis, yet it is usually modelled as if it were a continuous response variable. We have developed a Bayesian negative binomial regression model to study the connection between NGC and the following galaxy properties: central black hole mass, dynamical bulge mass, bulge velocity dispersion and absolute visual magnitude. The methodology introduced herein naturally accounts for heteroscedasticity, intrinsic scatter, errors in measurements in both axes (either discrete or continuous) and allows modelling the population of GCs on their natural scale as a nonnegative integer variable. Prediction intervals of 99 per cent around the trend for expected NGC comfortably envelope the data, notably including the Milky Way, which has hitherto been considered a problematic outlier. Finally, we demonstrate how random intercept models can incorporate information of each particular galaxy morphological type. Bayesian variable selection methodology allows for automatically identifying galaxy types with different productions of GCs, suggesting that on average S0 galaxies have a GC population 35 per cent smaller than other types with similar brightness. [ABSTRACT FROM AUTHOR]

ABSTRACT The observed abundance of giant arcs produced by galaxy cluster lenses and the measured Einstein radii have presented a source of tension for Λ cold dark matter (ΛCDM), particularly at low redshifts ( z ∼ 0.2). Previous cosmological tests for high-redshift clusters ( z > 0.5) have suffered from small number statistics in the simulated sample and the implementation of baryonic physics is likely to affect the outcome. We analyse zoomed-in simulations of a fairly large sample of cluster-sized objects, with Mvir > 3 × 1014 h−1 M⊙, identified at z = 0.25 and 0.5, for a concordance ΛCDM cosmology. These simulations have been carried out by incrementally increasing the physics considered. We start with dark-matter-only simulations and then add gas hydrodynamics, with different treatments of baryonic processes: non-radiative cooling, radiative cooling with star formation and galactic winds powered by supernova explosions, and finally including the effect of active galactic nucleus (AGN) feedback. Our analysis of strong lensing properties is based on the computation of the cross-section for the formation of giant arcs and of the Einstein radii. We find that the addition of gas in non-radiative simulations does not change the strong lensing predictions significantly, but gas cooling and star formation together significantly increase the number of expected giant arcs and the Einstein radii, particularly for lower redshift clusters and lower source redshifts. Further inclusion of AGN feedback reduces the predicted strong lensing efficiencies such that the lensing probability distributions become closer to those obtained for simulations including only dark matter. Our results indicate that the inclusion of baryonic physics in simulations will not solve the arc-statistics problem at low redshifts, when the physical processes included provide a realistic description of cooling in the central regions of galaxy clusters. As outcomes of our analysis, we encourage the adoption of Einstein radii as a robust measure of strong lensing efficiency, and provide the ΛCDM predictions to be used for future comparisons with high-redshift cluster samples. [ABSTRACT FROM AUTHOR]

ABSTRACT High-redshift sources suffer from magnification or demagnification due to weak gravitational lensing by large-scale structure. One consequence of this is that the distance-redshift relation, in wide use for cosmological tests, suffers lensing-induced scatter which can be quantified by the magnification probability distribution. Predicting this distribution generally requires a method for ray tracing through cosmological N-body simulations. However, standard methods tend to apply the multiple-thin-lens approximation. In an effort to quantify the accuracy of these methods, we develop an innovative code that performs ray tracing without the use of this approximation. The efficiency and accuracy of this computationally challenging approach can be improved by careful choices of numerical parameters; therefore, the results are analysed for the behaviour of the ray-tracing code in the vicinity of Schwarzschild and Navarro-Frenk-White lenses. Preliminary comparisons are drawn with the multiple-lens-plane ray-bundle method in the context of cosmological mass distributions for a source redshift of zs= 0.5. [ABSTRACT FROM AUTHOR]

AIM: To identify the causes of childhood cataract in south India with emphasis on factors that might be potentially preventable. METHODS: A total of 514 consecutive children with cataract attending an eye hospital outpatient clinic were examined and their parents interviewed by a trained interviewer using a standardised questionnaire in the local language. Serology was performed on children under 1 year of age to detect congenital rubella syndrome (CRS). Other investigations were performed as clinically indicated. RESULTS: Of the 366 children with non-traumatic cataract 25% were hereditary, 15% were due to congenital rubella syndrome, and 51% were undetermined. In children under 1 year of age 25% were due to rubella and cataract of nuclear morphology had a 75% positive predictive value for CRS. Mothers of children in the undetermined group were more likely to have taken abortifacients than a group of age matched controls (p = 0.1) but use of other medications in pregnancy was similar in both groups. Of the 148 (29%) children with traumatic cataracts three quarters were over the age of 6 years. Stick injuries were responsible for 28%, thorn injuries for 21%, and firecrackers for 5%. CONCLUSION: Nearly half of non-traumatic cataract in south India is due to potentially preventable causes (CRS and autosomal dominant disease). There is need for further work to identify the factors leading to childhood cataract in at least half of the cases for which no definite cause can as yet be determined. [ABSTRACT FROM PUBLISHER]

Comparisons between observed and predicted strong lensing properties of galaxy clusters have been used to claim either tension or consistency with ΛCDM cosmology. However, standard approaches to such tests are unable to quantify the preference for one cosmology over another. We advocate a Bayesian approach whereby the parameters defining the scaling relation between Einstein radii and cluster mass are treated as the observables. We demonstrate a method of estimating the likelihood for observing these parameters under the ΛCDM framework, using the X-ray selected z > 0.5 MACS clusters as a case in point and employing both N-body and hydrodynamic simulations of clusters. We account for cluster lens triaxiality within the modelling of the likelihood function. Cluster selection criteria is found to play as important a role as the uncertainty related to the description of star formation and feedback. [ABSTRACT FROM PUBLISHER]