Reducing Zero-point Systematics in Dark Energy Supernova Experiments

TL;DR

This paper demonstrates that fitting for calibration parameters simultaneously with supernova data significantly reduces zero-point systematic errors, improving the robustness of dark energy measurements in future supernova surveys.

Contribution

It introduces a method of simultaneous calibration fitting that enhances the accuracy of supernova-based dark energy experiments, easing calibration constraints.

Findings

Simultaneous fitting improves calibration accuracy over traditional methods.

The approach is robust across various experimental configurations.

Method is applicable to both space-based and ground-based surveys.

Abstract

We study the effect of filter zero-point uncertainties on future supernova dark energy missions. Fitting for calibration parameters using simultaneous analysis of all Type Ia supernova standard candles achieves a significant improvement over more traditional fit methods. This conclusion is robust under diverse experimental configurations (number of observed supernovae, maximum survey redshift, inclusion of additional systematics). This approach to supernova fitting considerably eases otherwise stringent mission calibration requirements. As an example we simulate a space-based mission based on the proposed JDEM satellite; however the method and conclusions are general and valid for any future supernova dark energy mission, ground or space-based.