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We test the mutual consistency between the baryon acoustic oscillation measurements from the eBOSS SDSS final release, as well as the Pantheon supernova compilation in a model independent fashion using Gaussian process regression. We also test their joint consistency with the $Lambda$CDM model, also in a model independent fashion. We also use Gaussian process regression to reconstruct the expansion history that is preferred by these two datasets. While this methodology finds no significant preference for model flexibility beyond $Lambda$CDM, we are able to generate a number of reconstructed expansion histories that fit the data better than the best-fit $Lambda$CDM model. These example expansion histories may point the way towards modifications to $Lambda$CDM. We also constrain the parameters $Omega_k$ and $H_0r_d$ both with $Lambda$CDM and with Gaussian process regression. We find that $H_0r_d =10030 pm 130$ km/s and $Omega_k = 0.05 pm 0.10$ for $Lambda$CDM and that $H_0r_d = 10040 pm 140$ km/s and $Omega_k = 0.02 pm 0.20$ for the Gaussian process case.
The Integrated Sachs-Wolfe (ISW) effect is a large-angle modulation of the cosmic microwave background (CMB), generated when CMB photons traverse evolving potential wells associated with large scale structure (LSS). Recent efforts have been made to r
Reconstructing the Gaussian initial conditions at the beginning of the Universe from the survey data in a forward modeling framework is a major challenge in cosmology. This requires solving a high dimensional inverse problem with an expensive, non-li
We present an Effective Field Theory based reconstruction of quintessence models of dark energy directly from cosmological data. We show that current cosmological data possess enough constraining power to test several quintessence model properties fo
The observed dipole anisotropy of the cosmic microwave background (CMB) temperature is much larger than the fluctuations observed on smaller scales and is dominated by the kinematic contribution from the Doppler shifting of the monopole due to our mo
We develop an estimator for the correlation function which, in the ensemble average, returns the shape of the correlation function, even for signals that have significant correlations on the scale of the survey region. Our estimator is general and works in any number of dimensions. We devel