publication . Article . Preprint . 2021

Reducing Ground-based Astrometric Errors with Gaia and Gaussian Processes

Name: Reducing Ground-based Astrometric Errors with Gaia and Gaussian Processes
Keywords: Astronometry, Sky noise, Astronomy data analysis, Astronometry, Sky noise, Astronomy data analysis, Astrophysics - Instrumentation and Methods for Astrophysics, Space and Planetary Science, Astronomy and Astrophysics

W. F. Fortino; Gary Bernstein; Pedro H. Bernardinelli; M. Aguena; Sahar S. Allam; James Annis; David Bacon; Keith Bechtol; S. Bhargava; D. Brooks; ...

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Open Access English

Published: 16 Aug 2021

Publisher: IOP Publishing

Country: Spain

Summary
References
29

Abstract

Stochastic field distortions caused by atmospheric turbulence are a fundamental limitation to the astrometric accuracy of ground-based imaging. This distortion field is measurable at the locations of stars with accurate positions provided by the Gaia DR2 catalog; we develop the use of Gaussian process regression (GPR) to interpolate the distortion field to arbitrary locations in each exposure. We introduce an extension to standard GPR techniques that exploits the knowledge that the 2D distortion field is curl-free. Applied to several hundred 90 s exposures from the Dark Energy Survey as a test bed, we find that the GPR correction reduces the variance of the turbulent astrometric distortions ≈12× , on average, with better performance in denser regions of the Gaia catalog. The rms per-coordinate distortion in the riz bands is typically ≈7 mas before any correction and ≈2 mas after application of the GPR model. The GPR astrometric corrections are validated by the observation that their use reduces, from 10 to 5 mas rms, the residuals to an orbit fit to riz-band observations over 5 yr of the r = 18.5 trans-Neptunian object Eris. We also propose a GPR method, not yet implemented, for simultaneously estimating the turbulence fields and the 5D stellar solutions in a stack of overlapping exposures, which should yield further turbulence reductions in future deep surveys.

The DES data management system is supported by the National Science Foundation under Grant Numbers AST-1138766 and AST-1536171. The DES participants from Spanish institutions are partially supported by MICINN under grants ESP2017-89838, PGC2018- 094773, PGC2018-102021, SEV-2016-0588, SEV-2016- 0597, and MDM-2015-0509, some of which include ERDF funds from the European Union. IFAE is partially funded by the CERCA program of the Generalitat de Catalunya. Research leading to these results has received funding from the European Research Council under the European Union’s Seventh Framework Program (FP7/2007-2013) including ERC grant agreements 240672, 291329, and 306478. We acknowledge support from the Brazilian Instituto Nacional de Ciˆencia e Tecnologia (INCT) do e-Universo (CNPq grant 465376/2014-2). This manuscript has been authored by Fermi Research Alliance, LLC under Contract No. DE-AC02- 07CH11359 with the U.S. Department of Energy, Office of Science, Office of High Energy Physics.

Fortino, W. F., et al. DES Collaboration

Peer reviewed

Persistent Identifiers

doi: 10.3847/1538-3881/ac0722

handle: 10261/254786

Subjects

free text keywords: Astronometry, Sky noise, Astronomy data analysis, Astronometry, Sky noise, Astronomy data analysis, Astrophysics - Instrumentation and Methods for Astrophysics, Space and Planetary Science, Astronomy and Astrophysics, Astrometry, Orbit (dynamics), Physics, Stars, Distortion, Gaussian process, symbols.namesake, symbols, Field (physics), Kriging, Ground-penetrating radar, Geodesy

Related Organizations

Max Planck Institute for Radio Astronomy
Germany
Raymond and Ruth Perelman School of Medicine at the University of Pennsylvania
United States
University of Illinois at Urbana Champaign
United States

Funded by

EC| COSMICDAWN, NSF| Collaborative Research: The Dark Energy Survey Data Management Operations, EC| TESTDE, EC| COGS

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Recolector de Ciencia Abierta, RECOLECTA; DIGITAL.CSIC

Article . 2021

Providers: Recolector de Ciencia Abierta, RECOLECTA; DIGITAL.CSIC

arXiv.org e-Print Archive

Preprint . 2020

Providers: arXiv.org e-Print Archive

The Astronomical Journal

Article . 2021

Providers: Crossref

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