Title: Modeling the Transfer Function for the Dark Energy Survey

Abstract

We present a forward-modeling 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/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) and catalogs representative of the DES data. In this work we demonstrate the framework by simulating the 244 deg² coadd images and catalogs in five bands for the DES Science Verification 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 illustrate 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 modeling approach is generally applicable for other upcoming and future surveys. It provides a powerful tool for systematics studies that is sufficientlymore » realistic and highly controllable.« less

Authors:

Chang, C. ^[1]

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+ Show Author Affiliations

1. Wolfgang-Pauli-Strasse, Zurich (Switzerland). et al.

Publication Date:

Wed Mar 04 00:00:00 EST 2015

Research Org.:

Fermi National Accelerator Laboratory (FNAL), Batavia, IL (United States)

Sponsoring Org.:

USDOE Office of Science (SC), High Energy Physics (HEP)

Contributing Org.:

DES Collaboration

OSTI Identifier:

1226302

Report Number(s):

FERMILAB-PUB-14-479-AE
Journal ID: ISSN 1538-4357; arXiv eprint number arXiv:1411.0032

Grant/Contract Number:  

AC02-07CH11359

Resource Type:

Accepted Manuscript

Journal Name:

The Astrophysical Journal (Online)

Additional Journal Information:

Journal Name: The Astrophysical Journal (Online); Journal Volume: 801; Journal Issue: 2; Journal ID: ISSN 1538-4357

Publisher:

Institute of Physics (IOP)

Country of Publication:

United States

Language:

English

Subject:

79 ASTRONOMY AND ASTROPHYSICS; methods:data analysis; methods: numerical; surveys; techniques: image processing