UC Davis

Weak lensing cosmology surveys measure the light from distant galaxies as it undergoes a series of distortions, suffering from deflections by both the large scale structure of the universe and individual galaxies. As the number of galaxies used to measure cosmology have increased into the tens of millions, the myriad of pernicious systematic errors to dominate over random errors. Over time and through different generations of surveys, understanding of leading sources of systematic error—like model inaccuracies of the Point Spread Function (PSF), observation strategies, the brighter-fatter effect, and differed charge transfer—has matured, leaving other sources of systematic error to become dominant. One source of systematic error that still demands the community’s attention is accurately modeling the redshifts of weak lensing galaxies. Perhaps the most secure way to measure galaxy redshifts is by measuring spectroscopic redshifts. Obtaining spectra for millions of faint galaxies that make up weak lensing surveys is intractable, however. Instead, weak lensing surveys traditionally estimate galaxy redshifts by using their flux as measured through broad band photometric filters, resulting in photometric redshifts. In this work we will examine the effects of photometric redshift uncertainty have our ability to constrain cosmological parameters. First, we will utilize the Deep Lensing Survey to study the effect that the error in estimated redshift distribution widths, n(z), has on cosmology inference using the joint combination of galaxy clustering, galaxy-galaxy lensing, and cosmic shear. We present two end—to—end analyses from the catalog level to parameter estimation. We produce an initial cosmological inference using fiducial tomographic redshift bins derived from photometric redshifts, then compare this with a result where the redshift bins are empirically corrected using a set of spectroscopic redshifts. We find that the derived parameter S8 decreases from 0.841+0.062 to 0.810+0.039 upon 0.061 0.031 correcting the n(z) errors in the second method. Second, we study various approaches to estimate photometric redshift of the Dark Energy Science Collaboration (DESC)’s Data Challenge (DC) 2 catalogs and see how the blended objects affect the result of photo-z estimations. We also explore the subsequent effect these errors have on our ability to measure the dark matter equation of state, w, and find if used alone, blending related photo-z errors can induce up to a 160% error in w.