ABSTRACT
We examine the cosmological constraining power from two cross-correlation probes between galaxy and cosmic microwave background (CMB) surveys: the cross-correlation of lens galaxy density ...with CMB lensing convergence 〈δgκCMB〉, and source galaxy weak lensing shear with CMB lensing convergence 〈γκCMB〉. These two cross-correlation probes provide an independent cross-check of other large-scale structure constraints and are insensitive to galaxy-only or CMB-only systematic effects. In addition, when combined with other large-scale structure probes, the cross-correlations can break degeneracies in cosmological and nuisance parameters, improving both the precision and robustness of the analysis. In this work, we study how the constraining power of 〈δgκCMB〉 + 〈γκCMB〉 changes from Stage-III (ongoing) to Stage-IV (future) surveys. Given the flexibility in selecting the lens galaxy sample, we also explore systematically the impact on cosmological constraints when we vary the redshift range and magnitude limit of the lens galaxies using mock galaxy catalogs. We find that in our setup, the contribution to cosmological constraints from 〈δgκCMB〉 and 〈γκCMB〉 are comparable in the Stage-III data sets; but in Stage-IV surveys, the noise in 〈δgκCMB〉 becomes subdominant to cosmic variance, preventing 〈δgκCMB〉 to further improve the constraints. This implies that to maximize the cosmological constraints from future 〈δgκCMB〉 + 〈γκCMB〉 analyses, we should focus more on the requirements on 〈γκCMB〉 instead of 〈δgκCMB〉. Furthermore, the selection of the lens sample should be optimized in terms of our ability to characterize its redshift or galaxy bias instead of its number density.
We present optimal quadratic estimators for the Fourier analysis of cosmological surveys that detect several different types of tracers of large-scale structure. Our estimators can be used to ...simultaneously fit the matter power spectrum and the biases of the tracers – as well as redshift-space distortions (RSDs), non-Gaussianities (NGs), or any other effects that are manifested through differences between the clusterings of distinct species of tracers. Our estimators reduce to the one by Feldman, Kaiser & Peacock (FKP) in the case of a survey consisting of a single species of tracer. We show that the multitracer estimators are unbiased, and that their covariance is given by the inverse of the multitracer Fisher matrix. When the biases, RSDs and NGs are fixed to their fiducial values, and one is only interested in measuring the underlying power spectrum, our estimators are projected into the estimator found by Percival, Verde & Peacock. We have tested our estimators on simple (lognormal) simulated galaxy maps, and we show that it performs as expected, being either equivalent or superior to the FKP method in all cases we analysed. Finally, we have shown how to extend the multitracer technique to include the one-halo term of the power spectrum.
Self-interacting dark matter (SIDM) has long been proposed as a solution to small-scale problems posed by standard cold dark matter. We use numerical simulations to study the effect of dark matter ...interactions on the morphology of disk galaxies falling into galaxy clusters. The effective drag force on dark matter leads to offsets of the stellar disk with respect to the surrounding halo, causing distortions in the disk. For anisotropic scattering cross sections of 0.5 and , we show that potentially observable warps, asymmetries, and thickening of the disk occur in simulations. We discuss observational tests of SIDM with galaxy surveys and more realistic simulations needed to obtain detailed predictions.
ABSTRACT
Cosmological parameter constraints from recent galaxy imaging surveys are reaching percent-level accuracy on the effective amplitude of the lensing signal, S8. The upcoming Legacy Survey of ...Space and Time (LSST) of the Vera C. Rubin Observatory will produce subpercent level measurements of cosmological parameters, providing a milestone test of the ΛCDM model. To supply guidance to the upcoming LSST analysis, it is important to understand thoroughly the results from different recent galaxy imaging surveys and assess their consistencies. In this work, we perform a unified catalogue-level reanalysis of three cosmic shear data sets: the first year data from the Dark Energy Survey (DES-Y1), the 1000 deg2 data set from the Kilo-Degree Survey (KiDS-1000), and the first year data from the Hyper Suprime-Cam Subaru Strategic Program (HSC-Y1). We utilize a pipeline developed and rigorously tested by the LSST Dark Energy Science Collaboration to perform the reanalysis and assess the robustness of the results to analysis choices. We find the S8 constraint to be robust to two different small-scale modelling approaches, and varying choices of cosmological priors. Our unified analysis allows the consistency of the surveys to be rigorously tested, and we find the three surveys to be statistically consistent. Due to the partially overlapping footprint, we model the cross-covariance between KiDS-1000 and HSC-Y1 approximately when combining all three data sets, resulting in a 1.6–1.9 per cent constraint on S8 given different assumptions on the cross-covariance.
The intrinsic alignment (IA) of galaxies is potentially a major limitation in deriving cosmological constraints from weak lensing surveys. In order to investigate this effect, we assign intrinsic ...shapes and orientations to galaxies in the light-cone output of the MICE simulation, spanning ~ 5000 deg2 and reaching redshift Z = 1.4. This assignment is based on a semianalytic IA model that uses photometric properties of galaxies as well as the spin and shape of their host halos. Advancing on previous work, we include more realistic distributions of galaxy shapes and a luminosity-dependent galaxy-halo alignment. The IA model parameters are calibrated against COSMOS and BOSS LOWZ observations. The null detection of IA in observations of blue galaxies is accounted for by setting random orientations for these objects. We compare the two-point alignment statistics measured in the simulation against predictions from the analytical IA models NLA and TATT over a wide range of scales, redshifts, and luminosities for red and blue galaxies separately. We find that both models fit the measurements well at scales above 8h-1 Mpc, while TATT outperforms NLA at smaller scales. The IA parameters derived from our fits are in broad agreement with various observational constraints from red galaxies. Finally, we build a realistic source sample, mimicking DES Year 3 observations and use it to predict the IA contamination to the observed shear statistics. We find this prediction to be within the measurement uncertainty, which might be a consequence of the random alignment of blue galaxies in the simulation.
Abstract The Global Strategy for Plant Conservation (GSPC) was established by the Conference of Parties in 2002 to decrease the loss of plant diversity, reduce poverty and contribute to sustainable ...development. To achieve this overarching goal, the GSPC has established a series of targets, one of which is to ensure that plant diversity is well understood, so that it can be effectively conserved and used in a sustainable manner. Brazil hosts more than 46,000 species of plants, algae and fungi, representing one of the most biodiverse countries on Earth, and playing a key role in the GSPC. To meet the GSPC goals of Target 1 and facilitate access to plant diversity, Brazil committed to preparing the List of Species of the Brazilian Flora (2008-2015) and the Brazilian Flora 2020 (2016-present). Managing all the information associated with such great biodiversity has proven to be an extremely challenging task. Here, we synthesize the history of these projects, focusing on the multidisciplinary and collaborative approach adopted to develop and manage the inclusion of all the knowledge generated though digital information systems. We further describe the methods used, challenges faced, and strategies adopted, as well as summarize advances to date and prospects for completing the Brazilian flora in 2020.
Resumo A Estratégia Global para a Conservação das Plantas (GSPC) foi estabelecida pela Conferência das Partes em 2002 para diminuir a perda da diversidade vegetal, reduzir a pobreza e contribuir para o desenvolvimento sustentável. Para atingir um objetivo tão abrangente, a GSPC estabeleceu uma série de tarefas, uma das quais é assegurar um bom conhecimento da diversidade vegetal para que a mesma possa ser conservada de forma efetiva e utilizada de maneira sustentável. O Brasil possui mais de 46 mil espécies de plantas, algas e fungos, representando um dos países com maior biodiversidade no planeta, sendo um participante chave na GSPC. Para atingir os objetivos da GSPC e possibilitar o acesso à diversidade de plantas, o Brasil se comprometeu em preparar a Lista de Espécies da Flora do Brasil (2008-2015) e a Flora do Brasil 2020 (2016 até o presente). Gerenciar todas as informações relacionadas a esta enorme biodiversidade provou ser uma tarefa extremamente desafiadora. Neste artigo, sintetizamos a história destes projetos e a abordagem multidisciplinar e colaborativa adotada para desenvolver e gerenciar a inclusão de todo o conhecimento gerado em sistemas de informação digitais. Apresentamos ainda os métodos utilizados, desafios enfrentados, e estratégias adotadas, bem como sintetizamos os avanços até o momento e perspectivas para completar a flora do Brasil em 2020.
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