TY - JOUR

T1 - Modelling baryonic physics in future weak lensing surveys

AU - Huang, Hung Jin

AU - Eifler, Tim

AU - Mandelbaum, Rachel

AU - Dodelson, Scott

N1 - Funding Information:
We thank Alex Hall for reviewing this paper and providing useful suggestions to improve the manuscript. We thank Sukhdeep Singh, Franc¸ois Lanusse, Qirong Zhu, Arya Farahi, Hy Trac, Phil Bull, Tiziana Di Matteo, Alexander Mead, Irshad Mohammed, and Ananth Tenneti for many constructive discussions and feedback. RM and HH are supported by the Department of Energy Cosmic Frontier program, grant DE-SC0010118. Part of the research was carried out at the Jet Propulsion Laboratory, California Institute of Technology, under a contract with the National Aeronautics and Space Administration and is supported by NASA ROSES ATP 16-ATP16-0084 grant.

PY - 2019/9/11

Y1 - 2019/9/11

N2 - 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 > 10 h−1 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.

AB - 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 > 10 h−1 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.

KW - Cosmological parameters

KW - Cosmology: theory

KW - Large-scale structure of Universe

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U2 - 10.1093/mnras/stz1714

DO - 10.1093/mnras/stz1714

M3 - Article

AN - SCOPUS:85074534358

VL - 488

SP - 1652

EP - 1678

JO - Monthly Notices of the Royal Astronomical Society

JF - Monthly Notices of the Royal Astronomical Society

SN - 0035-8711

IS - 2

ER -