Pöntinen, M. and Granvik, M. and Nucita, A. A. and Conversi, L. and Altieri, B. and Auricchio, N. and Bodendorf, C. and Bonino, D. and Brescia, M. and Capobianco, V. and Carretero, J. and Carry, B. and Castellano, M. and Cledassou, R. and Congedo, G. and Corcione, L. and Cropper, M. and Dusini, S. and Frailis, M. and Franceschi, E. and Fumana, M. and Garilli, B. and Grupp, F. and Hormuth, F. and Israel, H. and Jahnke, K. and Kermiche, S. and Kitching, T. and Kohley, R. and Kubik, B. and Kunz, M. and Laureijs, R. and Lilje, P. B. and Lloro, I. and Maiorano, E. and Marggraf, O. and Massey, R. and Meneghetti, M. and Meylan, G. and Moscardini, L. and Padilla, C. and Paltani, S. and Pasian, F. and Pires, S. and Polenta, G. and Raison, F. and Roncarelli, M. and Rossetti, E. and Saglia, R. and Schneider, P. and Secroun, A. and Serrano, S. and Sirri, G. and Taylor, A. N. and Tereno, I. and Toledo-Moreo, R. and Valenziano, L. and Wang, Y. and Wetzstein, M. and Zoubian, J. (2020) Euclid: Identification of asteroid streaks in simulated images using StreakDet software. Astronomy and Astrophysics, 644 . Art. No. A35. ISSN 0004-6361. doi:10.1051/0004-6361/202037765. https://resolver.caltech.edu/CaltechAUTHORS:20201130-095336338
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Abstract
Context. The ESA Euclid space telescope could observe up to 150 000 asteroids as a side product of its primary cosmological mission. Asteroids appear as trailed sources, that is streaks, in the images. Owing to the survey area of 15 000 square degrees and the number of sources, automated methods have to be used to find them. Euclid is equipped with a visible camera, VIS (VISual imager), and a near-infrared camera, NISP (Near-Infrared Spectrometer and Photometer), with three filters. Aims. We aim to develop a pipeline to detect fast-moving objects in Euclid images, with both high completeness and high purity. Methods. We tested the StreakDet software to find asteroids from simulated Euclid images. We optimized the parameters of StreakDet to maximize completeness, and developed a post-processing algorithm to improve the purity of the sample of detected sources by removing false-positive detections. Results. StreakDet finds 96.9% of the synthetic asteroid streaks with apparent magnitudes brighter than 23rd magnitude and streak lengths longer than 15 pixels (10 arcsec h⁻¹), but this comes at the cost of finding a high number of false positives. The number of false positives can be radically reduced with multi-streak analysis, which utilizes all four dithers obtained by Euclid. Conclusions. StreakDet is a good tool for identifying asteroids in Euclid images, but there is still room for improvement, in particular, for finding short (less than 13 pixels, corresponding to 8 arcsec h⁻¹) and/or faint streaks (fainter than the apparent magnitude of 23).
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Additional Information: | © ESO 2020. Article published by EDP Sciences. This paper is published on behalf of the Euclid Consortium. Received 18 February 2020; Accepted 26 October 2020; Published online 25 November 2020. We thank the anonymous referee for constructive comments. M.P. and M.G. acknowledge funding from the Academy of Finland (projects #316292 and #299543). The Euclid Consortium acknowledges the European Space Agency and the support of a number of agencies and institutes that have supported the development of Euclid. A detailed complete list is available on the Euclid web site (http://www.euclid-ec.org). In particular, the Academy of Finland, the Agenzia Spaziale Italiana, the Belgian Science Policy, the Canadian Euclid Consortium, the Centre National d’Etudes Spatiales, the Deutsches Zentrum für Luft- und Raumfahrt, the Danish Space Research Institute, the Fundação para a Ciência e a Tecnologia, the Ministerio de Economia y Competitividad, the National Aeronautics and Space Administration, the Netherlandse Onderzoekschool Voor Astronomie, the Norwegian Space Agency, the Romanian Space Agency, the State Secretariat for Education, Research and Innovation (SERI) at the Swiss Space Office (SSO), and the United Kingdom Space Agency. | ||||||||||||||||||||||||||||||||||||||
Group: | Infrared Processing and Analysis Center (IPAC) | ||||||||||||||||||||||||||||||||||||||
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Subject Keywords: | methods: data analysis – techniques: image processing – minor planets, asteroids: general – space vehicles – surveys – methods: numerical | ||||||||||||||||||||||||||||||||||||||
DOI: | 10.1051/0004-6361/202037765 | ||||||||||||||||||||||||||||||||||||||
Record Number: | CaltechAUTHORS:20201130-095336338 | ||||||||||||||||||||||||||||||||||||||
Persistent URL: | https://resolver.caltech.edu/CaltechAUTHORS:20201130-095336338 | ||||||||||||||||||||||||||||||||||||||
Official Citation: | Euclid: Identification of asteroid streaks in simulated images using StreakDet software. M. Pöntinen, M. Granvik, A. A. Nucita, L. Conversi, B. Altieri, N. Auricchio, C. Bodendorf, D. Bonino, M. Brescia, V. Capobianco, J. Carretero, B. Carry, M. Castellano, R. Cledassou, G. Congedo, L. Corcione, M. Cropper, S. Dusini, M. Frailis, E. Franceschi, M. Fumana, B. Garilli, F. Grupp, F. Hormuth, H. Israel, K. Jahnke, S. Kermiche, T. Kitching, R. Kohley, B. Kubik, M. Kunz, R. Laureijs, P. B. Lilje, I. Lloro, E. Maiorano, O. Marggraf, R. Massey, M. Meneghetti, G. Meylan, L. Moscardini, C. Padilla, S. Paltani, F. Pasian, S. Pires, G. Polenta, F. Raison, M. Roncarelli, E. Rossetti, R. Saglia, P. Schneider, A. Secroun, S. Serrano, G. Sirri, A. N. Taylor, I. Tereno, R. Toledo-Moreo, L. Valenziano, Y. Wang, M. Wetzstein and J. Zoubian. A&A, 644 (2020) A35; DOI: https://doi.org/10.1051/0004-6361/202037765 | ||||||||||||||||||||||||||||||||||||||
Usage Policy: | No commercial reproduction, distribution, display or performance rights in this work are provided. | ||||||||||||||||||||||||||||||||||||||
ID Code: | 106841 | ||||||||||||||||||||||||||||||||||||||
Collection: | CaltechAUTHORS | ||||||||||||||||||||||||||||||||||||||
Deposited By: | Tony Diaz | ||||||||||||||||||||||||||||||||||||||
Deposited On: | 02 Dec 2020 20:21 | ||||||||||||||||||||||||||||||||||||||
Last Modified: | 16 Nov 2021 18:57 |
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