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Recent papers have shown that a small systematic redshift shift ($Delta zsim 10^{-5}$) in measurements of type Ia supernovae can cause a significant bias ($sim$1%) in the recovery of cosmological parameters. Such a redshift shift could be caused, for example, by a gravitational redshift due to the density of our local environment. The sensitivity of supernova data to redshift shifts means supernovae make excellent probes of inhomogeneities. We therefore invert the analysis, and try to diagnose the nature of our local gravitational environment by fitting for $Delta z$ as an extra free parameter alongside the usual cosmological parameters.
We examine the possibility of soft cosmology, namely small deviations from the usual framework due to the effective appearance of soft-matter properties in the Universe sectors. One effect of such a case would be the dark energy to exhibit a differen
Cosmological surveys aim to use the evolution of the abundance of galaxy clusters to accurately constrain the cosmological model. In the context of LCDM, we show that it is possible to achieve the required percent level accuracy in the halo mass func
Measurements of the equation of state of dark energy from surveys of thousands of Type Ia Supernovae (SNe Ia) will be limited by spectroscopic follow-up and must therefore rely on photometric identification, increasing the chance that the sample is c
Accurate inference of cosmology from weak lensing shear requires an accurate shear power spectrum covariance matrix. Here, we investigate this accuracy requirement and quantify the relative importance of the Gaussian (G), super-sample covariance (SSC
We present a new Bayesian hierarchical model (BHM) named Steve for performing type Ia supernova (SNIa) cosmology fits. This advances previous works by including an improved treatment of Malmquist bias, accounting for additional sources of systematic