Euclid: Detecting Solar System objects in Euclid images and classifying them using Kohonen self-organising maps

A. A. Nucita; L. Conversi; A. Verdier; A. Franco; S. Sacquegna; M. Pöntinen; B. Altieri; B. Carry; F. De Paolis; F. Strafella; V. Orofino; M. Maiorano; V. Kansal; R. D. Vavrek; M. Miluzio; M. Granvik; V. Testa; N. Aghanim; S. Andreon; N. Auricchio; M. Baldi; S. Bardelli; E. Branchini; M. Brescia; J. Brinchmann; S. Camera; V. Capobianco; C. Carbone; J. Carretero; S. Casas; M. Castellano; G. Castignani; S. Cavuoti; A. Cimatti; G. Congedo; C. J. Conselice; Y. Copin; F. Courbin; H. M. Courtois; A. Da Silva; H. Degaudenzi; A. M. Di Giorgio; J. Dinis; F. Dubath; X. Dupac; S. Dusini; M. Farina; S. Farrens; S. Ferriol; M. Frailis; E. Franceschi; M. Fumana; S. Galeotta; B. Gillis; C. Giocoli; P. Gómez-Alvarez; A. Grazian; F. Grupp; S. V.H. Haugan; J. Hoar; W. Holmes; F. Hormuth; A. Hornstrup; P. Hudelot; K. Jahnke; M. Jhabvala; E. Keihänen; S. Kermiche; A. Kiessling; M. Kilbinger; R. Kohley; B. Kubik; M. Kümmel; H. Kurki-Suonio; R. Laureijs; S. Ligori; P. B. Lilje; V. Lindholm; I. Lloro; E. Maiorano; O. Mansutti; O. Marggraf; K. Markovic; N. Martinet; F. Marulli; R. Massey; D. C. Masters; E. Medinaceli; S. Mei; Y. Mellier; M. Meneghetti; G. Meylan; M. Moresco; L. Moscardini; R. Nakajima; S. M. Niemi; C. Padilla; S. Paltani; F. Pasian; K. Pedersen; V. Pettorino; S. Pires; G. Polenta; M. Poncet; L. A. Popa; L. Pozzetti; F. Raison; R. Rebolo; A. Renzi; J. Rhodes; G. Riccio; E. Romelli; M. Roncarelli; E. Rossetti; R. Saglia; D. Sapone; B. Sartoris; M. Schirmer; P. Schneider; A. Secroun; G. Seidel; S. Serrano; C. Sirignano; G. Sirri; J. Skottfelt; L. Stanco; J. Steinwagner; P. Tallada-Crespí; A. N. Taylor; I. Tereno; R. Toledo-Moreo; F. Torradeflot; I. Tutusaus; L. Valenziano; T. Vassallo; G. Verdoes Kleijn; A. Veropalumbo; Y. Wang; J. Weller; A. Zacchei; E. Zucca; M. Bolzonella; C. Burigana; V. Scottez

doi:10.1051/0004-6361/202451767

Euclid: Detecting Solar System objects in Euclid images and classifying them using Kohonen self-organising maps

A. A. Nucita^*
, L. Conversi
, A. Verdier
, A. Franco
, S. Sacquegna
, M. Pöntinen
, B. Altieri
, B. Carry
, F. De Paolis
, F. Strafella
, V. Orofino
, M. Maiorano
, V. Kansal
, R. D. Vavrek
, M. Miluzio
, M. Granvik
, V. Testa
, N. Aghanim
, S. Andreon
, N. Auricchio

M. Baldi, S. Bardelli, E. Branchini, M. Brescia, J. Brinchmann, S. Camera, V. Capobianco, C. Carbone, J. Carretero, S. Casas, M. Castellano, G. Castignani, S. Cavuoti, A. Cimatti, G. Congedo, C. J. Conselice, Y. Copin, F. Courbin, H. M. Courtois, A. Da Silva, H. Degaudenzi, A. M. Di Giorgio, J. Dinis, F. Dubath, X. Dupac, S. Dusini, M. Farina, S. Farrens, S. Ferriol, M. Frailis, E. Franceschi, M. Fumana, S. Galeotta, B. Gillis, C. Giocoli, P. Gómez-Alvarez, A. Grazian, F. Grupp, S. V.H. Haugan, J. Hoar, W. Holmes, F. Hormuth, A. Hornstrup, P. Hudelot, K. Jahnke, M. Jhabvala, E. Keihänen, S. Kermiche, A. Kiessling, M. Kilbinger, R. Kohley, B. Kubik, M. Kümmel, H. Kurki-Suonio, R. Laureijs, S. Ligori, P. B. Lilje, V. Lindholm, I. Lloro, E. Maiorano, O. Mansutti, O. Marggraf, K. Markovic, N. Martinet, F. Marulli, R. Massey, D. C. Masters, E. Medinaceli, S. Mei, Y. Mellier, M. Meneghetti, G. Meylan, M. Moresco, L. Moscardini, R. Nakajima, S. M. Niemi, C. Padilla, S. Paltani, F. Pasian, K. Pedersen, V. Pettorino, S. Pires, G. Polenta, M. Poncet, L. A. Popa, L. Pozzetti, F. Raison, R. Rebolo, A. Renzi, J. Rhodes, G. Riccio, E. Romelli, M. Roncarelli, E. Rossetti, R. Saglia, D. Sapone, B. Sartoris, M. Schirmer, P. Schneider, A. Secroun, G. Seidel, S. Serrano, C. Sirignano, G. Sirri, J. Skottfelt, L. Stanco, J. Steinwagner, P. Tallada-Crespí, A. N. Taylor, I. Tereno, R. Toledo-Moreo, F. Torradeflot, I. Tutusaus, L. Valenziano, T. Vassallo, G. Verdoes Kleijn, A. Veropalumbo, Y. Wang, J. Weller, A. Zacchei, E. Zucca, M. Bolzonella, C. Burigana, V. Scottez

^*Corresponding author for this work

National Institute for Nuclear Physics
European Space Astronomy Centre
Swiss Federal Institute of Technology Lausanne
University of Salento
University of Helsinki
Université Côte d'Azur
Swinburne University of Technology
European Space Agency - ESA
Osservatorio Astronomico Roma
Université Paris-Sud
Osservatorio Astronomico di Brera
Istituto di Astrofisica Spaziale e Fisica Cosmica di Bologna
University of Bologna
University of Genoa
University of Naples Federico II
University of Porto
University of Turin
National Institute for Astrophysics
Port d’Informació Científica
RWTH Aachen University
University of Edinburgh
University of Manchester
Universite Claude Bernard Lyon 1
Institut national de physique nucléaire et de physique des particules
University of Lisbon
University of Geneva
Université Paris-Saclay
Osservatorio Astronomico di Trieste
Astronomical Observatory of Padua
Ludwig Maximilian University of Munich
University of Oslo
California Institute of Technology
Felix Hormuth Engineering
Institut d’Astrophysique de Paris
Max Planck Institute for Astronomy
NASA Goddard Space Flight Center
CNRS
ESTEC
Netherlands Institute for Radio Astronomy
University of Bonn
Durham University
Université Paris 7
Institute for High Energy Physics
Aarhus University
Italian Space Agency
Centre national d'études spatiales
Institute of Space Science
Max Planck Institute for Extraterrestrial Physics
University of La Laguna
University of Padua
Osservatorio Astronomico di Capodimonte
Universidad de Chile
CSIC - Institute of Space Sciences
Open University Milton Keynes
Technical University of Cartagena
Université Paul Sabatier Toulouse III
University of Groningen
University of Trieste
Université catholique de Lille

Research output: Contribution to journal › Journal article › Research › peer-review

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Abstract

The ESA Euclid mission will survey more than 14 000 deg² of the sky in visible and near-infrared wavelengths, mapping the extragalactic sky to constrain our cosmological model of the Universe. Although the survey focusses on regions further than 15 from the ecliptic, it should allow for the detection of more than about 10⁵ Solar System objects (SSOs). After simulating the expected signal from SSOs in Euclid images acquired with the visible camera (VIS), we describe an automated pipeline developed to detect moving objects with an apparent velocity in the range of 0.1a-10″ h^-1, typically corresponding to sources in the outer Solar System (from Centaurs to Kuiper-belt objects). In particular, the proposed detection scheme is based on SExtractor software and on applying a new algorithm capable of associating moving objects amongst different catalogues. After applying a suite of filters to improve the detection quality, we study the expected purity and completeness of the SSO detections. We also show how a Kohonen self-organising neural network can be successfully trained (in an unsupervised fashion) to classify stars, galaxies, and SSOs. By implementing an early-stopping method in the training scheme, we show that the network can be used in a predictive way, allowing one to assign the probability of each detected object being a member of each considered class.

Original language	English
Article number	A116
Journal	Astronomy and Astrophysics
Volume	694
Number of pages	15
ISSN	0004-6361
DOIs	https://doi.org/10.1051/0004-6361/202451767
Publication status	Published - 2025

Keywords

Comets: general
Kuiper belt: general
Methods: data analysis
Methods: numerical
Minor planets, asteroids: general
Oort Cloud

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Nucita, A. A., Conversi, L., Verdier, A., Franco, A., Sacquegna, S., Pöntinen, M., Altieri, B., Carry, B., De Paolis, F., Strafella, F., Orofino, V., Maiorano, M., Kansal, V., Vavrek, R. D., Miluzio, M., Granvik, M., Testa, V., Aghanim, N., Andreon, S., ... Scottez, V. (2025). Euclid: Detecting Solar System objects in Euclid images and classifying them using Kohonen self-organising maps. Astronomy and Astrophysics, 694, Article A116. https://doi.org/10.1051/0004-6361/202451767

@article{7553ad80b7bf4ef8889ca8c6f0c49aa7,

title = "Euclid: Detecting Solar System objects in Euclid images and classifying them using Kohonen self-organising maps",

abstract = "The ESA Euclid mission will survey more than 14 000 deg2 of the sky in visible and near-infrared wavelengths, mapping the extragalactic sky to constrain our cosmological model of the Universe. Although the survey focusses on regions further than 15 from the ecliptic, it should allow for the detection of more than about 105 Solar System objects (SSOs). After simulating the expected signal from SSOs in Euclid images acquired with the visible camera (VIS), we describe an automated pipeline developed to detect moving objects with an apparent velocity in the range of 0.1a-10″ h-1, typically corresponding to sources in the outer Solar System (from Centaurs to Kuiper-belt objects). In particular, the proposed detection scheme is based on SExtractor software and on applying a new algorithm capable of associating moving objects amongst different catalogues. After applying a suite of filters to improve the detection quality, we study the expected purity and completeness of the SSO detections. We also show how a Kohonen self-organising neural network can be successfully trained (in an unsupervised fashion) to classify stars, galaxies, and SSOs. By implementing an early-stopping method in the training scheme, we show that the network can be used in a predictive way, allowing one to assign the probability of each detected object being a member of each considered class.",

keywords = "Comets: general, Kuiper belt: general, Methods: data analysis, Methods: numerical, Minor planets, asteroids: general, Oort Cloud",

author = "Nucita, \{A. A.\} and L. Conversi and A. Verdier and A. Franco and S. Sacquegna and M. P{\"o}ntinen and B. Altieri and B. Carry and \{De Paolis\}, F. and F. Strafella and V. Orofino and M. Maiorano and V. Kansal and Vavrek, \{R. D.\} and M. Miluzio and M. Granvik and V. Testa and N. Aghanim and S. Andreon and N. Auricchio and M. Baldi and S. Bardelli and E. Branchini and M. Brescia and J. Brinchmann and S. Camera and V. Capobianco and C. Carbone and J. Carretero and S. Casas and M. Castellano and G. Castignani and S. Cavuoti and A. Cimatti and G. Congedo and Conselice, \{C. J.\} and Y. Copin and F. Courbin and Courtois, \{H. M.\} and \{Da Silva\}, A. and H. Degaudenzi and \{Di Giorgio\}, \{A. M.\} and J. Dinis and F. Dubath and X. Dupac and S. Dusini and M. Farina and S. Farrens and S. Ferriol and M. Frailis and E. Franceschi and M. Fumana and S. Galeotta and B. Gillis and C. Giocoli and P. G{\'o}mez-Alvarez and A. Grazian and F. Grupp and Haugan, \{S. V.H.\} and J. Hoar and W. Holmes and F. Hormuth and A. Hornstrup and P. Hudelot and K. Jahnke and M. Jhabvala and E. Keih{\"a}nen and S. Kermiche and A. Kiessling and M. Kilbinger and R. Kohley and B. Kubik and M. K{\"u}mmel and H. Kurki-Suonio and R. Laureijs and S. Ligori and Lilje, \{P. B.\} and V. Lindholm and I. Lloro and E. Maiorano and O. Mansutti and O. Marggraf and K. Markovic and N. Martinet and F. Marulli and R. Massey and Masters, \{D. C.\} and E. Medinaceli and S. Mei and Y. Mellier and M. Meneghetti and G. Meylan and M. Moresco and L. Moscardini and R. Nakajima and Niemi, \{S. M.\} and C. Padilla and S. Paltani and F. Pasian and K. Pedersen and V. Pettorino and S. Pires and G. Polenta and M. Poncet and Popa, \{L. A.\} and L. Pozzetti and F. Raison and R. Rebolo and A. Renzi and J. Rhodes and G. Riccio and E. Romelli and M. Roncarelli and E. Rossetti and R. Saglia and D. Sapone and B. Sartoris and M. Schirmer and P. Schneider and A. Secroun and G. Seidel and S. Serrano and C. Sirignano and G. Sirri and J. Skottfelt and L. Stanco and J. Steinwagner and P. Tallada-Cresp{\'i} and Taylor, \{A. N.\} and I. Tereno and R. Toledo-Moreo and F. Torradeflot and I. Tutusaus and L. Valenziano and T. Vassallo and \{Verdoes Kleijn\}, G. and A. Veropalumbo and Y. Wang and J. Weller and A. Zacchei and E. Zucca and M. Bolzonella and C. Burigana and V. Scottez",

note = "Publisher Copyright: {\textcopyright} The Authors 2025.",

year = "2025",

doi = "10.1051/0004-6361/202451767",

language = "English",

volume = "694",

journal = "Astronomy and Astrophysics",

issn = "0004-6361",

publisher = "EDP Sciences",

}

Nucita, AA, Conversi, L, Verdier, A, Franco, A, Sacquegna, S, Pöntinen, M, Altieri, B, Carry, B, De Paolis, F, Strafella, F, Orofino, V, Maiorano, M, Kansal, V, Vavrek, RD, Miluzio, M, Granvik, M, Testa, V, Aghanim, N, Andreon, S, Auricchio, N, Baldi, M, Bardelli, S, Branchini, E, Brescia, M, Brinchmann, J, Camera, S, Capobianco, V, Carbone, C, Carretero, J, Casas, S, Castellano, M, Castignani, G, Cavuoti, S, Cimatti, A, Congedo, G, Conselice, CJ, Copin, Y, Courbin, F, Courtois, HM, Da Silva, A, Degaudenzi, H, Di Giorgio, AM, Dinis, J, Dubath, F, Dupac, X, Dusini, S, Farina, M, Farrens, S, Ferriol, S, Frailis, M, Franceschi, E, Fumana, M, Galeotta, S, Gillis, B, Giocoli, C, Gómez-Alvarez, P, Grazian, A, Grupp, F, Haugan, SVH, Hoar, J, Holmes, W, Hormuth, F, Hornstrup, A, Hudelot, P, Jahnke, K, Jhabvala, M, Keihänen, E, Kermiche, S, Kiessling, A, Kilbinger, M, Kohley, R, Kubik, B, Kümmel, M, Kurki-Suonio, H, Laureijs, R, Ligori, S, Lilje, PB, Lindholm, V, Lloro, I, Maiorano, E, Mansutti, O, Marggraf, O, Markovic, K, Martinet, N, Marulli, F, Massey, R, Masters, DC, Medinaceli, E, Mei, S, Mellier, Y, Meneghetti, M, Meylan, G, Moresco, M, Moscardini, L, Nakajima, R, Niemi, SM, Padilla, C, Paltani, S, Pasian, F, Pedersen, K, Pettorino, V, Pires, S, Polenta, G, Poncet, M, Popa, LA, Pozzetti, L, Raison, F, Rebolo, R, Renzi, A, Rhodes, J, Riccio, G, Romelli, E, Roncarelli, M, Rossetti, E, Saglia, R, Sapone, D, Sartoris, B, Schirmer, M, Schneider, P, Secroun, A, Seidel, G, Serrano, S, Sirignano, C, Sirri, G, Skottfelt, J, Stanco, L, Steinwagner, J, Tallada-Crespí, P, Taylor, AN, Tereno, I, Toledo-Moreo, R, Torradeflot, F, Tutusaus, I, Valenziano, L, Vassallo, T, Verdoes Kleijn, G, Veropalumbo, A, Wang, Y, Weller, J, Zacchei, A, Zucca, E, Bolzonella, M, Burigana, C & Scottez, V 2025, 'Euclid: Detecting Solar System objects in Euclid images and classifying them using Kohonen self-organising maps', Astronomy and Astrophysics, vol. 694, A116. https://doi.org/10.1051/0004-6361/202451767

TY - JOUR

T1 - Euclid

T2 - Detecting Solar System objects in Euclid images and classifying them using Kohonen self-organising maps

AU - Nucita, A. A.

AU - Conversi, L.

AU - Verdier, A.

AU - Franco, A.

AU - Sacquegna, S.

AU - Pöntinen, M.

AU - Altieri, B.

AU - Carry, B.

AU - De Paolis, F.

AU - Strafella, F.

AU - Orofino, V.

AU - Maiorano, M.

AU - Kansal, V.

AU - Vavrek, R. D.

AU - Miluzio, M.

AU - Granvik, M.

AU - Testa, V.

AU - Aghanim, N.

AU - Andreon, S.

AU - Auricchio, N.

AU - Baldi, M.

AU - Bardelli, S.

AU - Branchini, E.

AU - Brescia, M.

AU - Brinchmann, J.

AU - Camera, S.

AU - Capobianco, V.

AU - Carbone, C.

AU - Carretero, J.

AU - Casas, S.

AU - Castellano, M.

AU - Castignani, G.

AU - Cavuoti, S.

AU - Cimatti, A.

AU - Congedo, G.

AU - Conselice, C. J.

AU - Copin, Y.

AU - Courbin, F.

AU - Courtois, H. M.

AU - Da Silva, A.

AU - Degaudenzi, H.

AU - Di Giorgio, A. M.

AU - Dinis, J.

AU - Dubath, F.

AU - Dupac, X.

AU - Dusini, S.

AU - Farina, M.

AU - Farrens, S.

AU - Ferriol, S.

AU - Frailis, M.

AU - Franceschi, E.

AU - Fumana, M.

AU - Galeotta, S.

AU - Gillis, B.

AU - Giocoli, C.

AU - Gómez-Alvarez, P.

AU - Grazian, A.

AU - Grupp, F.

AU - Haugan, S. V.H.

AU - Hoar, J.

AU - Holmes, W.

AU - Hormuth, F.

AU - Hornstrup, A.

AU - Hudelot, P.

AU - Jahnke, K.

AU - Jhabvala, M.

AU - Keihänen, E.

AU - Kermiche, S.

AU - Kiessling, A.

AU - Kilbinger, M.

AU - Kohley, R.

AU - Kubik, B.

AU - Kümmel, M.

AU - Kurki-Suonio, H.

AU - Laureijs, R.

AU - Ligori, S.

AU - Lilje, P. B.

AU - Lindholm, V.

AU - Lloro, I.

AU - Maiorano, E.

AU - Mansutti, O.

AU - Marggraf, O.

AU - Markovic, K.

AU - Martinet, N.

AU - Marulli, F.

AU - Massey, R.

AU - Masters, D. C.

AU - Medinaceli, E.

AU - Mei, S.

AU - Mellier, Y.

AU - Meneghetti, M.

AU - Meylan, G.

AU - Moresco, M.

AU - Moscardini, L.

AU - Nakajima, R.

AU - Niemi, S. M.

AU - Padilla, C.

AU - Paltani, S.

AU - Pasian, F.

AU - Pedersen, K.

AU - Pettorino, V.

AU - Pires, S.

AU - Polenta, G.

AU - Poncet, M.

AU - Popa, L. A.

AU - Pozzetti, L.

AU - Raison, F.

AU - Rebolo, R.

AU - Renzi, A.

AU - Rhodes, J.

AU - Riccio, G.

AU - Romelli, E.

AU - Roncarelli, M.

AU - Rossetti, E.

AU - Saglia, R.

AU - Sapone, D.

AU - Sartoris, B.

AU - Schirmer, M.

AU - Schneider, P.

AU - Secroun, A.

AU - Seidel, G.

AU - Serrano, S.

AU - Sirignano, C.

AU - Sirri, G.

AU - Skottfelt, J.

AU - Stanco, L.

AU - Steinwagner, J.

AU - Tallada-Crespí, P.

AU - Taylor, A. N.

AU - Tereno, I.

AU - Toledo-Moreo, R.

AU - Torradeflot, F.

AU - Tutusaus, I.

AU - Valenziano, L.

AU - Vassallo, T.

AU - Verdoes Kleijn, G.

AU - Veropalumbo, A.

AU - Wang, Y.

AU - Weller, J.

AU - Zacchei, A.

AU - Zucca, E.

AU - Bolzonella, M.

AU - Burigana, C.

AU - Scottez, V.

PY - 2025

Y1 - 2025

N2 - The ESA Euclid mission will survey more than 14 000 deg2 of the sky in visible and near-infrared wavelengths, mapping the extragalactic sky to constrain our cosmological model of the Universe. Although the survey focusses on regions further than 15 from the ecliptic, it should allow for the detection of more than about 105 Solar System objects (SSOs). After simulating the expected signal from SSOs in Euclid images acquired with the visible camera (VIS), we describe an automated pipeline developed to detect moving objects with an apparent velocity in the range of 0.1a-10″ h-1, typically corresponding to sources in the outer Solar System (from Centaurs to Kuiper-belt objects). In particular, the proposed detection scheme is based on SExtractor software and on applying a new algorithm capable of associating moving objects amongst different catalogues. After applying a suite of filters to improve the detection quality, we study the expected purity and completeness of the SSO detections. We also show how a Kohonen self-organising neural network can be successfully trained (in an unsupervised fashion) to classify stars, galaxies, and SSOs. By implementing an early-stopping method in the training scheme, we show that the network can be used in a predictive way, allowing one to assign the probability of each detected object being a member of each considered class.

AB - The ESA Euclid mission will survey more than 14 000 deg2 of the sky in visible and near-infrared wavelengths, mapping the extragalactic sky to constrain our cosmological model of the Universe. Although the survey focusses on regions further than 15 from the ecliptic, it should allow for the detection of more than about 105 Solar System objects (SSOs). After simulating the expected signal from SSOs in Euclid images acquired with the visible camera (VIS), we describe an automated pipeline developed to detect moving objects with an apparent velocity in the range of 0.1a-10″ h-1, typically corresponding to sources in the outer Solar System (from Centaurs to Kuiper-belt objects). In particular, the proposed detection scheme is based on SExtractor software and on applying a new algorithm capable of associating moving objects amongst different catalogues. After applying a suite of filters to improve the detection quality, we study the expected purity and completeness of the SSO detections. We also show how a Kohonen self-organising neural network can be successfully trained (in an unsupervised fashion) to classify stars, galaxies, and SSOs. By implementing an early-stopping method in the training scheme, we show that the network can be used in a predictive way, allowing one to assign the probability of each detected object being a member of each considered class.

KW - Comets: general

KW - Kuiper belt: general

KW - Methods: data analysis

KW - Methods: numerical

KW - Minor planets, asteroids: general

KW - Oort Cloud

U2 - 10.1051/0004-6361/202451767

DO - 10.1051/0004-6361/202451767

M3 - Journal article

AN - SCOPUS:85217693752

SN - 0004-6361

VL - 694

JO - Astronomy and Astrophysics

JF - Astronomy and Astrophysics

M1 - A116

ER -

Euclid: Detecting Solar System objects in Euclid images and classifying them using Kohonen self-organising maps

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Keywords

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