Cosmology in the Non-Linear Regime with Weak Gravitational Lensing

Liu Jia, New York NY

Investigators

Abstract

Jia Liu is awarded an NSF Astronomy and Astrophysics Postdoctoral Fellowship to carry out a program of research and education at Princeton University. Liu will develop theoretical models and use them to interpret observations that could provide new insight into dark energy, as well as a way to measure the total mass of neutrinos. "Dark energy" is the term for the unknown form of energy that is accelerating the expansion of the Universe. By improving constraints on key cosmological parameters, the proposed research would significantly improve our understanding of the Universe. For the education component of her work, Liu will serve as a volunteer instructor for Princeton's Prison Teaching Initiative (PTI), where she will teach college level mathematics and science courses, including a new preparatory physics and astronomy course aimed at helping inmates discover their interest in science and acquire the skills and credentials to succeed in life outside prison. Liu will undertake N-body ray-tracing simulations to investigate non-Gaussian statistics that are essential for a proper interpretation of the weak lensing of galaxies and the cosmic microwave background. The proposed work has the potential to (1) improve constraints on the dark energy equation of state nearly twofold, thereby doubling the output of survey observations with Advanced Atacama Cosmology Telescope and the Hyper Suprime-Cam; and (2) shed light on the neutrino mass hierarchy, a long-standing problem in particle physics. It will also advance our understanding of weak lensing systematics, including photometric redshift, intrinsic alignment of galaxies, and shape measurements. Reducing noise from these systematics will further improve cosmological constraints. As a volunteer instructor at PTI, Liu will teach college level mathematics and science courses to inmates, design a new preparatory physics and astronomy course, and train other instructors to teach the newly designed course.