14 research outputs found

    Cosmoparticle constraints with large-scale structure

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    Precisely measuring the large-scale structure of the universe is key to learning about fundamental physics. This thesis focuses on two of the most pressing problems in fundamental physics; massive neutrinos and dark energy, and explores what can be learnt from precise measurements of the large-scale structure of the universe. First, I examine the precision required for large-scale structure measurements to determine the neutrino hierarchy when combined with current particle physics results. The neutrino hierarchy refers to the ordering of the neutrino masses, and is a key question in neutrino physics. Particle physics and cosmology provide complementary information about neutrinos so a joint analysis is highly desirable. However, the method of incorporating prior knowledge about neutrinos into the analysis can strongly influence any results. I therefore developed a prior which is agnostic to the hierarchy by design, and used it to set a conclusive target precision for upcoming cosmological experiments. Second, I forecast whether including weak lensing magnification in future large-scale structure analyses can improve the constraints on dark energy and dark matter. Weak gravitational lensing is one of the key probes in forthcoming galaxy surveys, such as the Vera Rubin Observatory. Usually, the signal is detected by measuring distortions to the shapes of millions of galaxies - weak lensing shear. However, it can also be detected by measuring fluctuations in the number density of galaxies across the sky - weak lensing magnification. Weak lensing magnification only requires a count of galaxies to be made, as opposed to a measurement of their shape so is therefore traceable even for the very faint, small, and distant galaxies. In this thesis, I determined whether including weak lensing magnification in upcoming deep large-scale structure analyses improves the final cosmological constraints

    Forecasting the potential of weak lensing magnification to enhance LSST large-scale structure analyses

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    Recent works have shown that weak lensing magnification must be included in upcoming large-scale structure analyses, such as for the Vera C. Rubin Observatory Legacy Survey of Space and Time (LSST), to avoid biasing the cosmological results. In this work we investigate whether including magnification has a positive impact on the precision of the cosmological constraints, as well as being necessary to avoid bias. We forecast this using an LSST mock catalog and a halo model to calculate the galaxy power spectra. We find that including magnification has little effect on the precision of the cosmological parameter constraints for an LSST galaxy clustering analysis, where the halo model parameters are additionally constrained by the galaxy luminosity function. In particular, we find that for the LSST gold sample (i<25.3i < 25.3) including weak lensing magnification only improves the galaxy clustering constraint on Ωm\Omega_{\rm{m}} by a factor of 1.03, and when using a very deep LSST mock sample (i<26.5i<26.5) by a factor of 1.3. Since magnification predominantly contributes to the clustering measurement and provides similar information to that of cosmic shear, this improvement would be reduced for a combined galaxy clustering and shear analysis. We also confirm that not modelling weak lensing magnification will catastrophically bias the cosmological results from LSST. Magnification must therefore be included in LSST large-scale structure analyses even though it does not significantly enhance the precision of the cosmological constraints.Comment: v2: Version accepted in MNRAS. Minor clarifications, conclusions unchange

    KiDS-1000: Combined halo-model cosmology constraints from galaxy abundance, galaxy clustering and galaxy-galaxy lensing

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    We present constraints on the flat Λ\LambdaCDM cosmological model through a joint analysis of galaxy abundance, galaxy clustering and galaxy-galaxy lensing observables with the Kilo-Degree Survey. Our theoretical model combines a flexible conditional stellar mass function, to describe the galaxy-halo connection, with a cosmological N-body simulation-calibrated halo model to describe the non-linear matter field. Our magnitude-limited bright galaxy sample combines 9-band optical-to-near-infrared photometry with an extensive and complete spectroscopic training sample to provide accurate redshift and stellar mass estimates. Our faint galaxy sample provides a background of accurately calibrated lensing measurements. We constrain the structure growth parameter S8=σ8Ωm/0.3=0.773−0.030+0.028S_8=\sigma_8\sqrt{\Omega_{\mathrm{m}}/0.3}=0.773^{+0.028}_{-0.030}, and the matter density parameter Ωm=0.290−0.017+0.021\Omega_{\mathrm{m}}=0.290^{+0.021}_{-0.017}. The galaxy-halo connection model adopted in the work is shown to be in agreement with previous studies. Our constraints on cosmological parameters are comparable to, and consistent with, joint 3×2pt3\times2{\mathrm{pt}} clustering-lensing analyses that additionally include a cosmic shear observable. This analysis therefore brings attention to the significant constraining power in the often-excluded non-linear scales for galaxy clustering and galaxy-galaxy lensing observables. By adopting a theoretical model that accounts for non-linear halo bias, halo exclusion, scale-dependent galaxy bias and the impact of baryon feedback, this work demonstrates the potential and a way forward to include non-linear scales in cosmological analyses. Varying the width of the satellite galaxy distribution with an additional parameter yields a strong preference for sub-Poissonian variance, improving the goodness of fit by 0.18 in reduced χ2\chi^{2} value compared to a fixed Poisson distribution.Comment: 25 pages, 16 figures, accepted for publication in A&

    KiDS-1000: Combined halo-model cosmology constraints from galaxy abundance, galaxy clustering, and galaxy-galaxy lensing

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    We present constraints on the flat Λ cold dark matter cosmological model through a joint analysis of galaxy abundance, galaxy clustering, and galaxy-galaxy lensing observables with the Kilo-Degree Survey. Our theoretical model combines a flexible conditional stellar mass function, which describes the galaxy-halo connection, with a cosmological N-body simulation-calibrated halo model, which describes the non-linear matter field. Our magnitude-limited bright galaxy sample combines nine-band optical-to-near-infrared photometry with an extensive and complete spectroscopic training sample to provide accurate redshift and stellar mass estimates. Our faint galaxy sample provides a background of accurately calibrated lensing measurements. We constrain the structure growth parameter to S8 = σ8√Ωm/0.3 =√0.773−0.030+0.028 and the matter density parameter to Ωm = 0.290−0.017+0.021. The galaxy-halo connection model adopted in the work is shown to be in agreement with previous studies. Our constraints on cosmological parameters are comparable to, and consistent with, joint ‘3 × 2pt’ clustering-lensing analyses that additionally include a cosmic shear observable. This analysis therefore brings attention to the significant constraining power in the often excluded non-linear scales for galaxy clustering and galaxy-galaxy lensing observables. By adopting a theoretical model that accounts for non-linear halo bias, halo exclusion, scale-dependent galaxy bias, and the impact of baryon feedback, this work demonstrates the potential for, and a way towards, including non-linear scales in cosmological analyses. Varying the width of the satellite galaxy distribution with an additional parameter yields a strong preference for sub-Poissonian variance, improving the goodness of fit by 0.18 in terms of the reduced χ2 value (and increasing the p-value by 0.25) compared to a fixed Poisson distribution

    The halo model as a versatile tool to predict intrinsic alignments

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    Intrinsic alignments (IAs) of galaxies are an important contaminant for cosmic shear studies, but the modelling is complicated by the dependence of the signal on the source galaxy sample. In this paper, we use the halo model formalism to capture this diversity and examine its implications for Stage-III and Stage-IV cosmic shear surveys. We account for the different IA signatures at large and small scales, as well for the different contributions from central/satellite and red/blue galaxies, and we use realistic mocks to account for the characteristics of the galaxy populations as a function of redshift. We inform our model using the most recent observational findings: we include a luminosity dependence at both large and small scales and a radial dependence of the signal within the halo. We predict the impact of the total IA signal on the lensing angular power spectra, including the current uncertainties from the IA best-fits to illustrate the range of possible impact on the lensing signal: the lack of constraints for fainter galaxies is the main source of uncertainty for our predictions of the IA signal. We investigate how well effective models with limited degrees of freedom can account for the complexity of the IA signal. Although these lead to negligible biases for Stage-III surveys, we find that, for Stage-IV surveys, it is essential to at least include an additional parameter to capture the redshift dependence.Comment: 21 pages, 15 figure, accepted for publication in MNRA

    KiDS-1000: Combined halo-model cosmology constraints from galaxy abundance, galaxy clustering and galaxy-galaxy lensing

    Get PDF
    We present constraints on the flat Λ\LambdaCDM cosmological model through a joint analysis of galaxy abundance, galaxy clustering and galaxy-galaxy lensing observables with the Kilo-Degree Survey. Our theoretical model combines a flexible conditional stellar mass function, to describe the galaxy-halo connection, with a cosmological N-body simulation-calibrated halo model to describe the non-linear matter field. Our magnitude-limited bright galaxy sample combines 9-band optical-to-near-infrared photometry with an extensive and complete spectroscopic training sample to provide accurate redshift and stellar mass estimates. Our faint galaxy sample provides a background of accurately calibrated lensing measurements. We constrain the structure growth parameter S8=σ8Ωm/0.3=0.773−0.030+0.028S_8 = \sigma_8 \sqrt{\Omega_{\mathrm{m}}/0.3} = 0.773^{+0.028}_{-0.030}, and the matter density parameter Ωm=0.290−0.017+0.021\Omega_{\mathrm{m}} = 0.290^{+0.021}_{-0.017}. The galaxy-halo connection model adopted in the work is shown to be in agreement with previous studies. Our constraints on cosmological parameters are comparable to, and consistent with, joint '3×2pt3\times2{\mathrm{pt}}' clustering-lensing analyses that additionally include a cosmic shear observable. This analysis therefore brings attention to the significant constraining power in the often-excluded non-linear scales for galaxy clustering and galaxy-galaxy lensing observables. By adopting a theoretical model that accounts for non-linear halo bias, halo exclusion, scale-dependent galaxy bias and the impact of baryon feedback, this work demonstrates the potential and a way forward to include non-linear scales in cosmological analyses

    The halo model as a versatile tool to predict intrinsic alignments

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    Intrinsic alignments (IAs) of galaxies are an important contaminant for cosmic shear studies, but the modelling is complicated by the dependence of the signal on the source galaxy sample. In this paper, we use the halo model formalism to capture this diversity and examine its implications for Stage-III and Stage-IV cosmic shear surveys. We account for the different IA signatures at large and small scales, as well for the different contributions from central/satellite and red/blue galaxies, and we use realistic mocks to account for the characteristics of the galaxy populations as a function of redshift. We inform our model using the most recent observational findings: we include a luminosity dependence at both large and small scales and a radial dependence of the signal within the halo. We predict the impact of the total IA signal on the lensing angular power spectra, including the current uncertainties from the IA best-fits to illustrate the range of possible impact on the lensing signal: the lack of constraints for fainter galaxies is the main source of uncertainty for our predictions of the IA signal. We investigate how well effective models with limited degrees of freedom can account for the complexity of the IA signal. Although these lead to negligible biases for Stage-III surveys, we find that, for Stage-IV surveys, it is essential to at least include an additional parameter to capture the redshift dependence

    The halo model with beyond-linear halo bias: unbiasing cosmological constraints from galaxy-galaxy lensing and clustering

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    We determine the error introduced in a joint halo model analysis of galaxy-galaxy lensing and galaxy clustering observables when adopting the standard approximation of linear halo bias. Considering the Kilo-Degree Survey, we forecast that ignoring the non-linear halo bias would result in up to 5 sigma offsets in the recovered cosmological parameters describing structure growth, sigma_8 , and the matter density parameter, Ω_m. We include the scales 10 ^−1.3 < r_p /h−1 Mpc < 10 in the data vector, and the direction of these offsets are shown to depend on the freedom afforded to the halo model through other nuisance parameters. We conclude that a beyond-linear halo bias correction must therefore be included in future cosmological halo model analyses of large-scale structure observables on non-linear scales

    The halo model as a versatile tool to predict intrinsic alignments

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    Intrinsic alignments (IAs) of galaxies are an important contaminant for cosmic shear studies, but the modelling is complicated by the dependence of the signal on the source galaxy sample. In this paper, we use the halo model formalism to capture this diversity and examine its implications for Stage-III and Stage-IV cosmic shear surveys. We account for the different IA signatures at large and small scales, as well for the different contributions from central/satellite and red/blue galaxies, and we use realistic mocks to account for the characteristics of the galaxy populations as a function of redshift. We inform our model using the most recent observational findings: we include a luminosity dependence at both large and small scales and a radial dependence of the signal within the halo. We predict the impact of the total IA signal on the lensing angular power spectra, including the current uncertainties from the IA best-fits to illustrate the range of possible impact on the lensing signal: the lack of constraints for fainter galaxies is the main source of uncertainty for our predictions of the IA signal. We investigate how well effective models with limited degrees of freedom can account for the complexity of the IA signal. Although these lead to negligible biases for Stage-III surveys, we find that, for Stage-IV surveys, it is essential to at least include an additional parameter to capture the redshift dependence

    Forecasting the potential of weak lensing magnification to enhance LSST large-scale structure analyses

    Get PDF
    Recent works have shown that weak lensing magnification must be included in upcoming large-scale structure analyses, such as for the Vera C. Rubin Observatory Legacy Survey of Space and Time (LSST), to avoid biasing the cosmological results. In this work, we investigate whether including magnification has a positive impact on the precision of the cosmological constraints, as well as being necessary to avoid bias. We forecast this using an LSST mock catalogue and a halo model to calculate the galaxy power spectra. We find that including magnification has little effect on the precision of the cosmological parameter constraints for an LSST galaxy clustering analysis, where the halo model parameters are additionally constrained by the galaxy luminosity function. In particular, we find that for the LSST gold sample (i < 25.3) including weak lensing magnification only improves the galaxy clustering constraint on
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