Cluster Lenses

Clusters of galaxies are the most recently assembled, massive, bound structures in the Universe. As predicted by General Relativity, given their masses, clusters strongly deform space-time in their vicinity. Clusters act as some of the most powerful gravitational lenses in the Universe. Light rays traversing through clusters from distant sources are hence deflected, and the resulting images of these distant objects therefore appear distorted and magnified. Lensing by clusters occurs in two regimes, each with unique observational signatures. The strong lensing regime is characterized by effects readily seen by eye, namely, the production of giant arcs, multiple-images, and arclets. The weak lensing regime is characterized by small deformations in the shapes of background galaxies only detectable statistically. Cluster lenses have been exploited successfully to address several important current questions in cosmology: (i) the study of the lens(es) - understanding cluster mass distributions and issues pertaining to cluster formation and evolution, as well as constraining the nature of dark matter; (ii) the study of the lensed objects - probing the properties of the background lensed galaxy population - which is statistically at higher redshifts and of lower intrinsic luminosity thus enabling the probing of galaxy formation at the earliest times right up to the Dark Ages; and (iii) the study of the geometry of the Universe - as the strength of lensing depends on the ratios of angular diameter distances between the lens, source and observer, lens deflections are sensitive to the value of cosmological parameters and offer a powerful geometric tool to probe Dark Energy. In this review, we present the basics of cluster lensing and provide a current status report of the field.Comment: About 120 pages - Published in Open Access at: http://www.springerlink.com/content/j183018170485723/ . arXiv admin note: text overlap with arXiv:astro-ph/0504478 and arXiv:1003.3674 by other author

As desigualdades sociais e a saúde bucal nas capitais brasileiras

ResumoApesar da melhoria das condições de vida dos brasileiros, ainda persiste um panorama de iniquidades em saúde bucal. Este estudo ecológico avaliou a relação das condições socioeconômicas e de política de saúde pública com as de saúde bucal nas capitais brasileiras. Foi realizada análise fatorial com os indicadores de condições socioeconômicas, revelando dois fatores comuns: deprivação econômica e condição sociossanitária. Em seguida, executou-se análise de regressão linear múltipla para os indicadores de saúde bucal (média CPO-D 12 anos, média de dentes perdidos e taxa de população livre de cárie) com os dois fatores em comum e a fluoretação da água de abastecimento. A análise de regressão linear múltipla para o CPO-D das capitais foi estimado pelas condições sociossanitárias e fluoretação, ajustado pela deprivação econômica; enquanto que o modelo para a média de dentes perdidos foi estimado apenas pela fluoretação e deprivação econômica, e, por fim, o modelo para a taxa da população livre de cárie nas capitais brasileiras foi estimado pela condição econômica e sociossanitária ajustadas pelo abastecimento de água fluoretada. Portanto, os resultados apontam a necessidade de ações sociais que impactem nas condições de vida da população para redução da cárie dentária

The LSST-DESC 3x2pt tomography optimization challenge

This paper presents the results of the Rubin Observatory Dark Energy Science Collaboration (DESC) 3x2pt tomography challenge, which served as a first step toward optimizing the tomographic binning strategy for the main DESC analysis. The task of choosing an optimal tomographic binning scheme for a photometric survey is made particularly delicate in the context of a metacalibrated lensing catalogue, as only the photometry from the bands included in the metacalibration process (usually riz and potentially g) can be used in sample definition. The goal of the challenge was to collect and compare bin assignment strategies under various metrics of a standard 3x2pt cosmology analysis in a highly idealized setting to establish a baseline for realistically complex follow-up studies; in this preliminary study, we used two sets of cosmological simulations of galaxy redshifts and photometry under a simple noise model neglecting photometric outliers and variation in observing conditions, and contributed algorithms were provided with a representative and complete training set. We review and evaluate the entries to the challenge, finding that even from this limited photometry information, multiple algorithms can separate tomographic bins reasonably well, reaching figures-of-merit scores close to the attainable maximum. We further find that adding the g band to riz photometry improves metric performance by ~15% and that the optimal bin assignment strategy depends strongly on the science case: which figure-of-merit is to be optimized, and which observables (clustering, lensing, or both) are included