Modelling the Transfer Function for the Dark Energy Survey

TL;DR

This paper introduces a forward-modelling simulation framework for the Dark Energy Survey, enabling realistic data product generation to study systematics and interpret measurements effectively.

Contribution

It presents a novel simulation framework that models DES data products from cosmological signals, aiding systematics analysis and future survey planning.

Findings

Simulated images and catalogs closely match DES data characteristics.

The framework effectively addresses systematics like star/galaxy classification.

Demonstrates the utility of simulations for interpreting survey measurements.

Abstract

We present a forward-modelling simulation framework designed to model the data products from the Dark Energy Survey (DES). This forward-model process can be thought of as a transfer function -- a mapping from cosmological and astronomical signals to the final data products used by the scientists. Using output from the cosmological simulations (the Blind Cosmology Challenge), we generate simulated images (the Ultra Fast Image Simulator, Berge et al. 2013) and catalogs representative of the DES data. In this work we simulate the 244 sq. deg coadd images and catalogs in 5 bands for the DES Science Verification (SV) data. The simulation output is compared with the corresponding data to show that major characteristics of the images and catalogs can be captured. We also point out several directions of future improvements. Two practical examples, star/galaxy classification and proximity effects on object detection, are then used to demonstrate how one can use the simulations to address systematics issues in data analysis. With clear understanding of the simplifications in our model, we show that one can use the simulations side-by-side with data products to interpret the measurements. This forward modelling approach is generally applicable for other upcoming and future surveys. It provides a powerful tool for systematics studies which is sufficiently realistic and highly controllable.