The BNT transform of cosmic shear data makes ℓ-space cuts behave like k-space cuts, reducing nonlinear scale leakage and preserving unbiased S8 constraints in Euclid-like forecasts.
Mapping luminous and dark matter in the Universe
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abstract
Our standard model of the Universe predicts the distribution of dark matter to $1\%$ at the scales needed for upcoming experiments, yet our predictions for how the luminous matter -- which has interactions besides gravity -- is distributed remain highly uncertain. Understanding how much gas and stars there are in the Universe and where they preferentially live is challenging, and the uncertainty affects how well we can understand the cosmological model itself. For example, it compromises our ability to tell apart different models for dark energy, the mysterious force driving the accelerated expansion of the Universe. In this Essay, I will touch upon many recent developments that suggest we will be able to overcome this limitation before data from new experiments become available. More excitingly, I will describe how our efforts to model luminous and dark matter jointly will create new possibilities for constraining the physics of supermassive black holes, galaxies, and gas over time.
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Mitigating Nonlinear Systematics in Weak Lensing Surveys: The Bernardeau-Nishimichi-Taruya Approach
The BNT transform of cosmic shear data makes ℓ-space cuts behave like k-space cuts, reducing nonlinear scale leakage and preserving unbiased S8 constraints in Euclid-like forecasts.