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.
Publisher Copyright:
© 2019 The Author(s) Published by Oxford University Press on behalf of the Royal Astronomical Society.
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
UR - http://www.scopus.com/inward/record.url?scp=85074534358&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85074534358&partnerID=8YFLogxK
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 -