Reconstructing features in the primordial power spectrum

Potential features in the primordial power spectrum, such as oscillatory patterns, have been searched for in galaxy surveys in recent years, since these features can assist in understanding the nature of inflation and distinguishing between different scenarios of inflation. The null detection to date suggests that any such features should be fairly weak, and next-generation galaxy surveys, with their unprecedented sizes and precisions, are in a position to place stronger constraints than before. However, even if such primordial features once existed in the early Universe, they would have been significantly weakened or even wiped out on small scales in the late Universe due to nonlinear structure formation, which makes them difficult to be directly detected in real observations. A potential way to tackle this challenge for probing the features is to undo the cosmological evolution, i.e., using reconstruction to obtain an approximate linear density field. By employing a suite of large N-body simulations, we show that a recently-proposed nonlinear reconstruction algorithm can effectively retrieve lost oscillatory features from the mock galaxy catalogues and improve the accuracy of the measurement of feature parameters (assuming such primordial features do exist). We do a Fisher analysis to forecast how reconstruction affects the constraining power, and find that it can lead to significantly more robust constraints on the oscillation amplitude for a DESI-like survey. In particular, we compare the application of reconstruction with other ways of improving constraints, such as increasing the survey volume and range of scales, and show that it can achieve what the latter do, but at a much lower cost.