4.7 Article

Simultaneously constraining cosmology and baryonic physics via deep learning from weak lensing

Journal

MONTHLY NOTICES OF THE ROYAL ASTRONOMICAL SOCIETY
Volume 511, Issue 1, Pages 1518-1528

Publisher

OXFORD UNIV PRESS
DOI: 10.1093/mnras/stac161

Keywords

gravitational lensing: weak; cosmological parameters; cosmology: theory; large-scale structure of Universe

Funding

  1. NASA ATP grant [80NSSC18K1093]

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In this study, the researchers incorporated a baryonic correction model to account for baryonic effects and developed a convolutional neural network (CNN) to simultaneously learn and constrain cosmological and baryonic parameters from weak lensing convergence maps. They found that the CNN achieved tighter constraints in omega(m)-sigma(8) space compared to traditional methods, even while marginalizing over baryonic effects.
Ongoing and planned weak lensing (WL) surveys are becoming deep enough to contain information on angular scales down to a few arcmin. To fully extract information from these small scales, we must capture non-Gaussian features in the cosmological WL signal while accurately accounting for baryonic effects. In this work, we account for baryonic physics via a baryonic correction model that modifies the matter distribution in dark matter-only N-body simulations, mimicking the effects of galaxy formation and feedback. We implement this model in a large suite of ray-tracing simulations, spanning a grid of cosmological models in omega(m)-sigma(8) space. We then develop a convolutional neural network (CNN) architecture to learn and constrain cosmological and baryonic parameters simultaneously from the simulated WL convergence maps. We find that in a Hyper-Suprime Cam-like survey, our CNN achieves a 1.7x tighter constraint in omega(m)-sigma(8) space (1 sigma area) than the power spectrum and 2.1x tighter than the peak counts, showing that the CNN can efficiently extract non-Gaussian cosmological information even while marginalizing over baryonic effects. When we combine our CNN with the power spectrum, the baryonic effects degrade the constraint in omega(m)-sigma(8) space by a factor of 2.4, compared to the much worse degradation by a factor of 4.7 or 3.7 from either method alone.

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