Revisiting large scale structure analysis techniques in the DESI era
131 Campbell Hall
Nikhil Padmanabhan (Yale)
Galaxy redshift surveys are powerful cosmological probes, and the next generations of these surveys, including DESI, Euclid and WFIRST, forecast sub-percent statistical errors on the expansion and growth rate of the Universe. I’ll aim to explore some of the analysis challenges that these surveys present, and possible approaches to address these. I’ll focus on two specific problems. The first of these introduces a redshift weighting, optimized to measure the expansion history without resorting to binning in redshift. The second is estimating covariance matrices, where I’ll discuss a few approaches that can help alleviate the difficulties in estimating covariance matrices via Monte Carlo techniques.