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  1. ABSTRACT

    In order to prepare for the upcoming wide-field cosmological surveys, large simulations of the Universe with realistic galaxy populations are required. In particular, the tendency of galaxies to naturally align towards overdensities, an effect called intrinsic alignments (IA), can be a major source of systematics in the weak lensing analysis. As the details of galaxy formation and evolution relevant to IA cannot be simulated in practice on such volumes, we propose as an alternative a Deep Generative Model. This model is trained on the IllustrisTNG-100 simulation and is capable of sampling the orientations of a population of galaxies so as to recover the correct alignments. In our approach, we model the cosmic web as a set of graphs, where the graphs are constructed for each halo, and galaxy orientations as a signal on those graphs. The generative model is implemented on a Generative Adversarial Network architecture and uses specifically designed Graph-Convolutional Networks sensitive to the relative 3D positions of the vertices. Given (sub)halo masses and tidal fields, the model is able to learn and predict scalar features such as galaxy and dark matter subhalo shapes; and more importantly, vector features such as the 3D orientation of the major axismore »of the ellipsoid and the complex 2D ellipticities. For correlations of 3D orientations the model is in good quantitative agreement with the measured values from the simulation, except for at very small and transition scales. For correlations of 2D ellipticities, the model is in good quantitative agreement with the measured values from the simulation on all scales. Additionally, the model is able to capture the dependence of IA on mass, morphological type, and central/satellite type.

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  2. ABSTRACT In the era of precision cosmology and ever-improving cosmological simulations, a better understanding of different galaxy components such as bulges and discs will give us new insight into galactic formation and evolution. Based on the fact that the stellar populations of the constituent components of galaxies differ by their dynamical properties, we develop two simple models for galaxy decomposition using the TNG100 cosmological hydrodynamical simulation from the IllustrisTNG project. The first model uses a single dynamical parameter and can distinguish four components: thin disc, thick disc, counter-rotating disc, and bulge. The second model uses one more dynamical parameter, was defined in a probabilistic manner, and distinguishes two components: bulge and disc. We demonstrate the improved robustness of these models compared to a widely used method in literature involving cuts on the circularity parameter. The number fraction of disc-dominated galaxies at a given stellar mass obtained by our models agrees well with observations for masses exceeding log10(M*/M⊙) = 10. The galaxies classified as bulge-dominated by the second model are mostly red; however, the population classified as disc-dominated contains significant number of red galaxies alongside the blue population. The contributions of the different galaxy components to the total stellar mass budget exhibitsmore »similar trends with stellar mass compared to the observational data, although there is a quantitative disagreement at high and low masses. The Sérsic indices and half-mass radii for the bulge and disc components agree well with those of real galaxies.« less
  3. ABSTRACT

    Weak gravitational lensing is one of the most powerful tools for cosmology, while subject to challenges in quantifying subtle systematic biases. The point spread function (PSF) can cause biases in weak lensing shear inference when the PSF model does not match the true PSF that is convolved with the galaxy light profile. Although the effect of PSF size and shape errors – i.e. errors in second moments – is well studied, weak lensing systematics associated with errors in higher moments of the PSF model require further investigation. The goal of our study is to estimate their potential impact for LSST weak lensing analysis. We go beyond second moments of the PSF by using image simulations to relate multiplicative bias in shear to errors in the higher moments of the PSF model. We find that the current level of errors in higher moments of the PSF model in data from the Hyper Suprime-Cam survey can induce a ∼0.05 per cent shear bias, making this effect unimportant for ongoing surveys but relevant at the precision of upcoming surveys such as LSST.

  4. ABSTRACT Image simulations are essential tools for preparing and validating the analysis of current and future wide-field optical surveys. However, the galaxy models used as the basis for these simulations are typically limited to simple parametric light profiles, or use a fairly limited amount of available space-based data. In this work, we propose a methodology based on deep generative models to create complex models of galaxy morphologies that may meet the image simulation needs of upcoming surveys. We address the technical challenges associated with learning this morphology model from noisy and point spread function (PSF)-convolved images by building a hybrid Deep Learning/physical Bayesian hierarchical model for observed images, explicitly accounting for the PSF and noise properties. The generative model is further made conditional on physical galaxy parameters, to allow for sampling new light profiles from specific galaxy populations. We demonstrate our ability to train and sample from such a model on galaxy postage stamps from the HST/ACS COSMOS survey, and validate the quality of the model using a range of second- and higher order morphology statistics. Using this set of statistics, we demonstrate significantly more realistic morphologies using these deep generative models compared to conventional parametric models. To help makemore »these generative models practical tools for the community, we introduce galsim-hub, a community-driven repository of generative models, and a framework for incorporating generative models within the galsim image simulation software.« less
  5. ABSTRACT We explore synergies between the Nancy Grace Roman Space Telescope and the Vera Rubin Observatory’s Legacy Survey of Space and Time (LSST). Specifically, we consider scenarios where the currently envisioned survey strategy for the Roman Space Telescope’s High Latitude Survey (HLS reference), i.e. 2000 deg2 in four narrow photometric bands is altered in favour of a strategy of rapid coverage of the LSST area (to full LSST depth) in one band. We find that in only five months, a survey in the W-band can cover the full LSST survey area providing high-resolution imaging for >95 per cent of the LSST Year 10 gold galaxy sample. We explore a second, more ambitious scenario where the Roman Space Telescope spends 1.5 yr covering the LSST area. For this second scenario, we quantify the constraining power on dark energy equation-of-state parameters from a joint weak lensing and galaxy clustering analysis. Our survey simulations are based on the Roman Space Telescope exposure-time calculator and redshift distributions from the CANDELS catalogue. Our statistical uncertainties account for higher order correlations of the density field, and we include a wide range of systematic effects, such as uncertainties in shape and redshift measurements, and modelling uncertainties of astrophysical systematics, such asmore »galaxy bias, intrinsic galaxy alignment, and baryonic physics. We find a significant increase in constraining power for the joint LSST + HLS wide survey compared to LSST Y10 (FoMHLSwide = 2.4 FoMLSST) and compared to LSST + HLS (FoMHLSwide = 5.5 FoMHLSref).« less
  6. ABSTRACT We investigate the redshift evolution of the intrinsic alignments (IAs) of galaxies in the MassiveBlackII (MBII) simulation. We select galaxy samples above fixed subhalo mass cuts ($M_h\gt 10^{11,12,13}\,\mathrm{M}_{\odot }\, h^{-1}$) at z = 0.6 and trace their progenitors to z = 3 along their merger trees. Dark matter components of z = 0.6 galaxies are more spherical than their progenitors while stellar matter components tend to be less spherical than their progenitors. The distribution of the galaxy–subhalo misalignment angle peaks at ∼10 deg with a mild increase with time. The evolution of the ellipticity–direction (ED) correlation amplitude ω(r) of galaxies (which quantifies the tendency of galaxies to preferentially point towards surrounding matter overdensities) is governed by the evolution in the alignment of underlying dark matter (DM) subhaloes to the matter density of field, as well as the alignment between galaxies and their DM subhaloes. At scales $\sim 1~\mathrm{Mpc}\, h^{-1}$, the alignment between DM subhaloes and matter overdensity gets suppressed with time, whereas the alignment between galaxies and DM subhaloes is enhanced. These competing tendencies lead to a complex redshift evolution of ω(r) for galaxies at $\sim 1~\mathrm{Mpc}\, h^{-1}$. At scales $\gt 1~\mathrm{Mpc}\, h^{-1}$, alignment between DM subhaloes and matter overdensity does not evolve significantly; the evolutionmore »of the galaxy–subhalo misalignment therefore leads to an increase in ω(r) for galaxies by a factor of ∼4 from z = 3 to 0.6 at scales $\gt 1~\mathrm{Mpc}\, h^{-1}$. The balance between competing physical effects is scale dependent, leading to different conclusions at much smaller scales ($\sim 0.1~\mathrm{Mpc}\, h^{-1}$).« less
  7. Abstract Modifications of the matter power spectrum due to baryonic physics are one of the major theoretical uncertainties in cosmological weak lensing measurements. Developing robust mitigation schemes for this source of systematic uncertainty increases the robustness of cosmological constraints, and may increase their precision if they enable the use of information from smaller scales. Here we explore the performance of two mitigation schemes for baryonic effects in weak lensing cosmic shear: the principal component analysis (PCA) method and the halo-model approach in hmcode. We construct mock tomographic shear power spectra from four hydrodynamical simulations, and run simulated likelihood analyses with cosmolike assuming LSST-like survey statistics. With an angular scale cut of ℓmax < 2000, both methods successfully remove the biases in cosmological parameters due to the various baryonic physics scenarios, with the PCA method causing less degradation in the parameter constraints than hmcode. For a more aggressive ℓmax = 5000, the PCA method performs well for all but one baryonic physics scenario, requiring additional training simulations to account for the extreme baryonic physics scenario of Illustris; hmcode exhibits tensions in the 2D posterior distributions of cosmological parameters due to lack of freedom in describing the power spectrum for $k \gt 10\more »h^{-1}\, \mathrm{Mpc}$. We investigate variants of the PCA method and improve the bias mitigation through PCA by accounting for the noise properties in the data via Cholesky decomposition of the covariance matrix. Our improved PCA method allows us to retain more statistical constraining power while effectively mitigating baryonic uncertainties even for a broad range of baryonic physics scenarios.« less
  8. Abstract Vera C. Rubin Observatory is a ground-based astronomical facility under construction, a joint project of the National Science Foundation and the U.S. Department of Energy, designed to conduct a multipurpose 10 yr optical survey of the Southern Hemisphere sky: the Legacy Survey of Space and Time. Significant flexibility in survey strategy remains within the constraints imposed by the core science goals of probing dark energy and dark matter, cataloging the solar system, exploring the transient optical sky, and mapping the Milky Way. The survey’s massive data throughput will be transformational for many other astrophysics domains and Rubin’s data access policy sets the stage for a huge community of potential users. To ensure that the survey science potential is maximized while serving as broad a community as possible, Rubin Observatory has involved the scientific community at large in the process of setting and refining the details of the observing strategy. The motivation, history, and decision-making process of this strategy optimization are detailed in this paper, giving context to the science-driven proposals and recommendations for the survey strategy included in this Focus Issue.