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    Emulating galaxy clustering and galaxy–galaxy lensing into the deeply non-linear regime: methodology, information, and forecasts

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    Author
    Wibking, Benjamin D
    Salcedo, Andrés N
    Weinberg, David H
    Garrison, Lehman H
    Ferrer, Douglas
    Tinker, Jeremy
    Eisenstein, Daniel
    Metchnik, Marc
    Pinto, Philip
    Affiliation
    Univ Arizona, Steward Observ
    Issue Date
    2019-03
    Keywords
    gravitational lensing: weak
    cosmological parameters
    arge-scale structure of Universe
    
    Metadata
    Show full item record
    Publisher
    Oxford University Press (OUP)
    Citation
    Benjamin D Wibking, Andrés N Salcedo, David H Weinberg, Lehman H Garrison, Douglas Ferrer, Jeremy Tinker, Daniel Eisenstein, Marc Metchnik, Philip Pinto, Emulating galaxy clustering and galaxy–galaxy lensing into the deeply non-linear regime: methodology, information, and forecasts, Monthly Notices of the Royal Astronomical Society, Volume 484, Issue 1, March 2019, Pages 989–1006, https://doi.org/10.1093/mnras/sty2258
    Journal
    MONTHLY NOTICES OF THE ROYAL ASTRONOMICAL SOCIETY
    Rights
    © 2018 The Author(s). Published by Oxford University Press on behalf of the Royal Astronomical Society.
    Collection Information
    This item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at repository@u.library.arizona.edu.
    Abstract
    The combination of galaxy-galaxy lensing (GGL) with galaxy clustering is one of the most promising routes to determining the amplitude of matter clustering at low redshifts. We show that extending clustering+GGL analyses from the linear regime down to similar to 0.5 h(-1) Mpc scales increases their constraining power considerably, even after marginalizing over a flexible model of non-linear galaxy bias. Using a grid of cosmological N-body simulations, we construct a Taylor-expansion emulator that predicts the galaxy autocorrelation xi(gg)(r) and galaxy-matter cross-correlation xi(gm) (r) as a function of sigma(8), Omega(m), and halo occupation distribution (HOD) parameters, which are allowed to vary with large-scale environment to represent possible effects of galaxy assembly bias. We present forecasts for a fiducial case that corresponds to BOSS LOWZ galaxy clustering and SDSS-depth weak lensing (effective source density similar to 0.3 arcmin(-2)). Using tangential shear and projected correlation function measurements over 0.5 <= r(p) <= 30h(-1) Mpc yields a 2 per cent constraint on the parameter combination sigma(8)Omega(0.6)(m), a factor of two better than a constraint that excludes non-linear scales (r(p) > 2 h(-1) Mpc, 4 h(-1) Mpc for gamma(t) , omega(p)). Much of this improvement comes from the non-linear clustering information, which breaks degeneracies among HOD parameters. Increasing the effective source density to 3 arcmin(-2) sharpens the constraint on sigma(8)Omega(0.6 )(m)by a further factor of two. With robust modelling into the non-linear regime, low-redshift measurements of matter clustering at the 1-per cent level with clustering+GGL alone are well within reach of current data sets such as those provided by the Dark Energy Survey.
    ISSN
    0035-8711
    EISSN
    1365-2966
    DOI
    10.1093/mnras/sty2258
    Version
    Final published version
    Sponsors
    National Science Foundation Graduate Research Fellowship Program [DGE-1343012]; Department of Energy Computational Science Graduate Fellowship Program of the Office of Science; National Nuclear Security Administration in the Department of Energy [DE-FG02-97ER25308]; National Science Foundation [AST-1516997, AST-1313285, 1228509]; Department of Energy Office of Science grant [DOE-SC0013718]; Simons Foundation Investigator; Center for Cosmology and AstroParticle Physics at the Ohio State University; Faculty of Arts and Sciences Division of Science, Research Computing Group at Harvard University
    ae974a485f413a2113503eed53cd6c53
    10.1093/mnras/sty2258
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