Accelerating BAO scale fitting using Taylor series

Abstract

ABSTRACT The Universe is currently undergoing accelerated expansion driven by dark energy. Dark energy’s essential nature remains mysterious: one means of revealing it is by measuring the Universe’s size at different redshifts. This may be done using the baryon acoustic oscillation (BAO) feature, a standard ruler in the galaxy two-point correlation function (2PCF). In order to measure the distance scale, one dilates and contracts a template for the 2PCF in a fiducial cosmology, using a scaling factor α. The standard method for finding the best-fitting α is to compute the likelihood over a grid of roughly 100 values of it. This approach is slow; in this work, we propose a significantly faster way. Our method writes the 2PCF as a polynomial in α by Taylor-expanding it about α = 1, exploiting that we know the fiducial cosmology sufficiently well that α is within a few per cent of unity. The likelihood resulting from this expansion may then be analytically solved for the best-fitting α. Our method is 48–85× faster than a directly comparable approach in which we numerically minimize α, and ∼12 000× faster than the standard iterative method. Our work will be highly enabling for upcoming large-scale structure redshift surveys such as that by Dark Energy Spectroscopic Instrument.