报告题目：Non-Negative Matrix Factorization for Self-Calibration of Photometric Redshift Scatter in Weak Lensing Surveys

报 告 人：Le Zhang(SJU)

报告时间：2017年5月18日下午2：00p

报告地点：蒙民伟科技南楼S727

报告摘要：In the next generation of proposed weak lensing surveys, it is necessary to calibrate the true redshift of galaxies at the level of 10^{-3} in order to reach their full potential for cosmology. However, the photo-z error, one of the major sources of systematics, can significantly degrade the accuracy of weak lensing cosmological inferences. Zhang et al. (2010) proposed a self-calibration method to eliminate such error by combining galaxy-galaxy correlations and galaxy-shear correlations between different photo-z bins. But implementing such calibration process suffers a numerical challenge, which requires solving a set of constrained nonlinear matrix equations. In this talk, I will introduce a new algorithm to overcome such numerical problem. Based on the techniques of fixed-point iteration and non-negative matrix factorization, the proposed algorithm can efficiently and robustly reconstruct the scattering probabilities between the true-z and photo-z bins. The algorithm can provide a successful recovery of the scatter rates at the level of 0.01-1%, and the true mean redshifts of photo-z bins at the level of 0.001, which may satisfy the requirements in future lensing surveys.