Analytic calculation of the power spectrum covariance: speedup by four orders of magnitude

In order to infer cosmological parameters from galaxy survey data, we typically use summary statistics such as the power spectrum and we need an accurate estimate of their covariance matrix. The traditional process of obtaining the covariance involves simulating thousands of mocks. I will present an analytic approach for the covariance matrix which is more than four orders of magnitude faster than mocks and show its validation with an analysis of the BOSS DR12 data. Furthermore, our analytic approach is free of sampling noise which makes it useful for upcoming surveys like DESI and Euclid. Towards the end, I will change gears and talk about some recent work on the assembly bias of neutral hydrogen.