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Principal Component Analysis of Modified Gravity using Weak Lensing and Peculiar Velocity Measurements
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We perform a principal component analysis to assess ability of future observations to measure departures from General Relativity in predictions of the Poisson and anisotropy equations on linear scales. In particular, we focus on how the measurements of redshift-space distortions (RSD) observed from spectroscopic galaxy redshift surveys will improve the constraints when combined with lensing tomographic surveys. Assuming a Euclid-like galaxy imaging and redshift survey, we find that adding the 3D information decreases the statistical uncertainty by a factor between 3 and 10 compared to the case when only observables from lensing tomographic surveys are used. We also find that the number of well-constrained modes increases by a factor between 3 and 7. Our study indicates the importance of joint galaxy imaging and redshift surveys such as SuMIRe and Euclid to give more stringent tests of the {\Lambda}CDM model and to distinguish between various modified gravity and dark energy models.
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$\Lambda$CDM and early dark energy in latent space: a data-driven parametrization of the CMB temperature power spectrum
A variational autoencoder compresses CMB temperature spectra into 5 (LambdaCDM) or 8 (with early dark energy) latent parameters that reconstruct the data within Planck errors and can be constrained with Planck observations.
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