Self-calibration of photometric redshift scatter from DECaLS DR8 power spectrum and validation with simulated catalogues

TL;DR

This paper improves a self-calibration algorithm for photometric redshift scatter, demonstrating its effectiveness on simulated and real DECaLS DR8 data to reduce biases in weak lensing cosmology.

Contribution

The authors enhance the stability and robustness of a self-calibration algorithm for photometric redshift errors, validated through simulations and real data.

Findings

Successfully reconstructs redshift scatter rates within 0.015

Reduces mean redshift bias by over 50%

Aligns well with expectations from simulations

Abstract

The uncertainty in the photometric redshift estimation is one of the major systematics in weak lensing cosmology. The self-calibration method is able to reduce this systematics without assuming strong priors. We improve the recently proposed self-calibration algorithm to enhance the stability and robustness with the noisy measurement. The improved algorithm is tested on the power spectra measured from the simulated catalogues constructed according to DECaLS DR8 photometric catalogue. For the fiducial analysis with 5 equal-width redshift bins over $0<z<1$ and 6 bands over scales $100 \leq \ell<1000$, we find that the improved algorithm successfully reconstructs the scatter rates and the auto power spectrum in true redshift bins at the level of $\sim0.015$ and $\sim4.4$ per cent, respectively. The bias of the mean redshift is reduced by more than 50 per cent compared to the photo-$z$ without self-calibration, especially for the cases with catastrophic photo-$z$ errors. The reconstructed results of DECaLS DR8 galaxy sample are in line with the expectations from the simulation validation. The self-calibration code is publicly available at https://github.com/PengHui-hub/FP-NMF.