Novel Methods to Leverage Spectroscopic Overlap of Imaging Surveys

Justin Myles (Stanford)

Title: Novel Methods to Leverage Spectroscopic Overlap of Imaging Surveys

Abstract:
Large galaxy imaging surveys promise to deliver extraordinary datasets to answer open questions about the nature of dark matter and dark energy, but these surveys suffer from challenges arising from the difficulty in constraining galaxy redshift. I will discuss projects that leverage spectroscopic observations of small, well selected subsets of galaxies observed in imaging surveys to improve the utility of photometric datasets for cosmological experiments. First, I will describe the new methodology used for the Dark Energy Survey Year 3 weak lensing source galaxy redshift calibration and the resulting DES Y3 cosmology constraints. Second, I will present an algorithm for accurately propagating uncertainties of probability distributions and illustrate the application of this algorithm to redshift calibration. Third, I will show results using archival spectroscopy of redMaPPer galaxy clusters to measure the impact of projection effects on these clusters and comment on how this measurement relates to the DES Y1 cluster cosmology results. I will conclude by presenting promising paths forward to take full advantage of forthcoming surveys to constrain the cosmological model.