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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 deg 2 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 ismore » sufficiently realistic and highly controllable.« less

Authors:
 [1]
  1. Wolfgang-Pauli-Strasse, Zurich (Switzerland). et al.
Publication Date:
Research Org.:
Fermi National Accelerator Lab. (FNAL), Batavia, IL (United States)
Sponsoring Org.:
USDOE Office of Science (SC), High Energy Physics (HEP) (SC-25)
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:
Journal Article: Accepted Manuscript
Journal Name:
The Astrophysical Journal
Additional Journal Information:
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

Citation Formats

Chang, C. Modeling the Transfer Function for the Dark Energy Survey. United States: N. p., 2015. Web. doi:10.1088/0004-637X/801/2/73.
Chang, C. Modeling the Transfer Function for the Dark Energy Survey. United States. doi:10.1088/0004-637X/801/2/73.
Chang, C. Wed . "Modeling the Transfer Function for the Dark Energy Survey". United States. doi:10.1088/0004-637X/801/2/73. https://www.osti.gov/servlets/purl/1226302.
@article{osti_1226302,
title = {Modeling the Transfer Function for the Dark Energy Survey},
author = {Chang, C.},
abstractNote = {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 sufficiently realistic and highly controllable.},
doi = {10.1088/0004-637X/801/2/73},
journal = {The Astrophysical Journal},
number = 2,
volume = 801,
place = {United States},
year = {Wed Mar 04 00:00:00 EST 2015},
month = {Wed Mar 04 00:00:00 EST 2015}
}

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Cited by: 13 works
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