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Euclid preparation
R. Barnett
,
S. J. Warren
,
D. J. Mortlock
,
J.-G. Cuby
,
C. Conselice
et al.
Journal articles
cea-02334278v1
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Euclid preparation
H. Bretonnière
,
M. Huertas-Company
,
A. Boucaud
,
F. Lanusse
,
E. Jullo
et al.
Journal articles
hal-03533669v1
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Euclid preparation: XXII. Selection of Quiescent Galaxies from Mock Photometry using Machine Learning
A. Humphrey
,
L. Bisigello
,
P. A. C. Cunha
,
M. Bolzonella
,
S. Fotopoulou
et al.
Journal articles
hal-03866216v1
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Euclid preparation. XXI. Intermediate-redshift contaminants in the search for z > 6 galaxies within the Euclid Deep Survey (Corrigendum)
S. E. van Mierlo
,
K. I. Caputi
,
M. Ashby
,
H. Atek
,
M. Bolzonella
et al.
Journal articles
hal-03935710v1
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Euclid preparation
S. Ilić
,
N. Aghanim
,
C. Baccigalupi
,
J. R. Bermejo-Climent
,
G. Fabbian
et al.
Journal articles
hal-03533670v1
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Euclid preparation: XIX. Impact of magnification on photometric galaxy clustering
F. Lepori
,
I. Tutusaus
,
C. Viglione
,
C. Bonvin
,
S. Camera
et al.
Journal articles
hal-03447630v1
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Euclid: Forecasts from redshift-space distortions and the Alcock-Paczynski test with cosmic voids
N. Hamaus
,
M. Aubert
,
A. Pisani
,
S. Contarini
,
G. Verza
et al.
Journal articles
hal-03426564v1
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Euclid preparation: XVIII. Cosmic Dawn Survey. Spitzer observations of the Euclid deep fields and calibration fields
Andrea Moneti
,
H. J. Mccracken
,
M. Shuntov
,
O. B. Kauffmann
,
P. Capak
et al.
2021
Preprints, Working Papers, ...
hal-03451656v1
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Euclid: Calibrating photometric redshifts with spectroscopic cross-correlations
K. Naidoo
,
H. Johnston
,
B. Joachimi
,
J. L. van den Busch
,
H. Hildebrandt
et al.
2022
Preprints, Working Papers, ...
hal-03866242v1
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Euclid preparation: IX. EuclidEmulator2 -- Power spectrum emulation with massive neutrinos and self-consistent dark energy perturbations
Euclid Collaboration
,
M. Knabenhans
,
J. Stadel
,
D. Potter
,
J. Dakin
et al.
2020
Preprints, Working Papers, ...
hal-03027400v1
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Euclid preparation: XXIII. Derivation of galaxy physical properties with deep machine learning using mock fluxes and H-band images
L. Bisigello
,
C. J. Conselice
,
M. Baes
,
M. Bolzonella
,
M. Brescia
et al.
2022
Preprints, Working Papers, ...
hal-03866380v1
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Euclid preparation: XXIII. Derivation of galaxy physical properties with deep machine learning using mock fluxes and H-band images
L. Bisigello
,
C. J. Conselice
,
M. Baes
,
M. Bolzonella
,
M. Brescia
et al.
Journal articles
insu-03947319v1
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Euclid preparation. XVII. Cosmic Dawn Survey: Spitzer Space Telescope observations of the Euclid deep fields and calibration fields
A. Moneti
,
H. J. Mccracken
,
M. Shuntov
,
O. B. Kauffmann
,
P. Capak
et al.
Journal articles
hal-03565435v1
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