The PAU survey: star-galaxy classification with multi narrow-band data

被引:18
|
作者
Cabayol, L. [1 ]
Sevilla-Noarbe, I. [2 ]
Fernandez, E. [1 ]
Carretero, J. [1 ,10 ]
Eriksen, M. [1 ,10 ]
Serrano, S. [3 ]
Alarcon, A. [3 ,4 ]
Amara, A. [5 ]
Casas, R. [3 ,4 ]
Castander, F. J. [3 ,4 ]
De Vicente, J. [2 ]
Folger, M. [3 ,4 ]
Garcia-Bellido, J. [6 ]
Gaztanaga, E. [3 ,4 ]
Hoekstra, H. [7 ]
Miquel, R. [1 ,8 ]
Padilla, C. [1 ]
Sanchez, E. [2 ]
Stothert, L. [9 ]
Tallada, P. [2 ,10 ]
Tortorelli, L. [5 ]
机构
[1] Barcelona Inst Sci & Technol, IFAE, E-08193 Bellaterra, Barcelona, Spain
[2] Ctr Invest Energet Medioambientales & Tecnol CIEM, E-28040 Madrid, Spain
[3] CSIC, Inst Space Sci ICE, Campus UAB,Carrer Can Magrans S-N, E-08193 Barcelona, Spain
[4] IEEC, E-08193 Barcelona, Spain
[5] Swiss Fed Inst Technol, Inst Particle Phys & Astrophys, Wolfgang Pauli Str 27, CH-8093 Zurich, Switzerland
[6] Univ Autonoma Madrid, CSIC, Inst Fis Teor, E-28049 Madrid, Spain
[7] Leiden Univ, Leiden Observ, NL-2333 CA Leiden, Netherlands
[8] Inst Catalana Recerca & Estudis Avancats, E-08010 Barcelona, Spain
[9] Univ Durham, Dept Phys, Inst Computat Cosmol, South Rd, Durham DH1 3LE, England
[10] PIC, Campus UAB,C Albareda S-N, E-08193 Bellaterra, Cerdanyola Del, Spain
关键词
methods: data analysis; techniques: photometric; PHOTOMETRIC REDSHIFTS; ALHAMBRA SURVEY; SEPARATION; IMAGES; COSMOS;
D O I
10.1093/mnras/sty3129
中图分类号
P1 [天文学];
学科分类号
0704 ;
摘要
Classification of stars and galaxies is a well-known astronomical problem that has been treated using different approaches, most of them relying on morphological information. In this paper, we tackle this issue using the low-resolution spectra from narrow-band photometry, provided by the Physics of the Accelerating Universe survey. We find that, with the photometric fluxes from the 40 narrow-band filters and without including morphological information, it is possible to separate stars and galaxies to very high precision, 98.4 per cent purity with a completeness of 98.8 per cent for objects brighter than I = 22.5. This precision is obtained with a convolutional neural network as a classification algorithm, applied to the objects' spectra. We have also applied the method to the ALHAMBRA photometric survey and we provide an updated classification for its Gold sample.
引用
收藏
页码:529 / 539
页数:11
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