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Centro de Astrofísica da Universidade do Porto

Polychronis Papaderos
Investigador

Este investigador deixou o CAUP em 31 janeiro 2019

Telefone
+351 226 089 839

Email
papaderos@astro.up.pt
Página pessoal
http://www.observational-cosmology.eu/papaderos/

Publicações
ADS
Últimas publicações no CAUP/IA
M. G. del Valle-Espinosa, R. Sánchez-Janssen, R. O. Amorín, V. A. López Fernández, J. Sánchez Almeida, B. García-Lorenzo, P. Papaderos, 2023,
Spatially resolved chemodynamics of the starburst dwarf galaxy CGCG 007-025: evidence for recent accretion of metal-poor gas,
Monthly Notices of the Royal Astronomical Society, 522, 15
>> Abstract
P. Papaderos, G. Östlin, I. P. Breda, 2023,
Bulgeless disks, dark galaxies, inverted color gradients, and other expected phenomena at higher z
The chromatic surface brightness modulation (CMOD) effect
,
Astronomy & Astrophysics, 673, 39
>> Abstract
N. Roche, J. M. Vílchez, J. Iglesias-Páramo, P. Papaderos, S. F. Sánchez, C. Kehrig, S. Duarte Puertas, 2023,
Integral Field Spectroscopy of the cometary starburst galaxy NGC 4861,
Monthly Notices of the Royal Astronomical Society, 523, 15
>> Abstract
V. Fernández, R. O. Amorín, R. Sanchez-Janssen, M. G. del Valle-Espinosa, P. Papaderos, 2023,
The resolved chemical composition of the starburst dwarf galaxy CGCG007-025: direct method versus photoionization model fitting,
Monthly Notices of the Royal Astronomical Society, 520, 14
>> Abstract
A. Humphrey, P. A. C. Cunha, A. Paulino-Afonso, S. Amarantidis, R. Carvajal, J. M. Gomes, I. Matute, P. Papaderos, 2023,
Improving machine learning-derived photometric redshifts and physical property estimates using unlabelled observations,
Monthly Notices of the Royal Astronomical Society, 520, 305 - 313
>> Abstract
Euclid Collaboration, A. Humphrey, L. Bisigello, P. A. C. Cunha, M. Bolzonella, S. Fotopoulou, K. Caputi, C. Tortora, G. Zamorani, P. Papaderos et al. (including: J. Brinchmann, A. C. da Silva, I. Tereno, C. S. Carvalho), 2023,
Euclid preparation
XXII. Selection of quiescent galaxies from mock photometry using machine learning
,
Astronomy & Astrophysics, 671, 36
>> Abstract