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authFullName_s : I. Tereno
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Euclid preparation

R. Barnett , S. J. Warren , D. J. Mortlock , J.-G. Cuby , C. Conselice et al.
Astronomy and Astrophysics - A&A, 2019, 631, pp.A85. ⟨10.1051/0004-6361/201936427⟩
Journal articles cea-02334278v1
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Euclid preparation

H. Bretonnière , M. Huertas-Company , A. Boucaud , F. Lanusse , E. Jullo et al.
Astronomy and Astrophysics - A&A, 2022, 657, pp.A90. ⟨10.1051/0004-6361/202141393⟩
Journal articles hal-03533669v1
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Joint cosmological parameters forecast from CFHTLS-cosmic shear and CMB data

I. Tereno , O. Doré , Ludovic van Waerbeke , Yannick Mellier
Astronomy and Astrophysics - A&A, 2005, 429, pp.383-398. ⟨10.1051/0004-6361:20041099⟩
Journal articles hal-03742173v1
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Euclid preparation

P. Paykari , T. Kitching , H. Hoekstra , R. Azzollini , V. F. Cardone et al.
Astronomy and Astrophysics - A&A, 2020, 635, pp.A139. ⟨10.1051/0004-6361/201936980⟩
Journal articles cea-02516435v1
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Euclid preparation

G. Desprez , S. Paltani , J. Coupon , I. Almosallam , A. Alvarez-Ayllon et al.
Astronomy and Astrophysics - A&A, 2020, 644, pp.A31. ⟨10.1051/0004-6361/202039403⟩
Journal articles hal-03026946v1

Euclid: Cosmology forecasts from the void-galaxy cross-correlation function with reconstruction

S. Radinovic , S. Nadathur , H.-A. Winther , W.J. Percival , A. Woodfinden et al.
2023
Preprints, Working Papers, ... hal-04006508v1

Euclid preparation. XXX. Evaluating the weak lensing cluster mass biases using the Three Hundred Project hydrodynamical simulations

C. Giocoli , M. Meneghetti , E. Rasia , S. Borgani , G. Despali et al.
2023
Preprints, Working Papers, ... hal-03991062v1

Euclid preparation. XXVII. Covariance model validation for the 2-point correlation function of galaxy clusters

A. Fumagalli , A. Saro , S. Borgani , T. Castro , M. Costanzi et al.
2022
Preprints, Working Papers, ... hal-03892184v1
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Euclid preparation: XXI. Intermediate-redshift contaminants in the search for $z>6$ galaxies within the Euclid Deep Survey

S. van Mierlo , K. Caputi , M. Ashby , H. Atek , M. Bolzonella et al.
Astronomy and Astrophysics - A&A, 2022, 666, pp.A200. ⟨10.1051/0004-6361/202243950⟩
Journal articles hal-03866172v1
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Euclid preparation. XVI. Exploring the ultra-low surface brightness Universe with Euclid/VIS

A. Borlaff , P. Gómez-Alvarez , B. Altieri , P. Marcum , R. Vavrek et al.
Astronomy and Astrophysics - A&A, 2022, 657, pp.A92. ⟨10.1051/0004-6361/202141935⟩
Journal articles hal-03542092v2

Euclid mission: building of a reference survey

J. Amiaux , R. Scaramella , Y. Mellier , B. Altieri , C. Burigana et al.
Space Telescopes and Instrumentation 2012: Optical, Infrared, and Millimeter Wave, Jul 2012, Amsterdam, Netherlands. pp.8442-32
Conference papers in2p3-00716748v1
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Euclid : Effects of sample covariance on the number counts of galaxy clusters

A. Fumagalli , A. Saro , S. Borgani , T. Castro , M. Costanzi et al.
Astron.Astrophys., 2021, 652, pp.A21. ⟨10.1051/0004-6361/202140592⟩
Journal articles hal-03210469v1
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Euclid : Constraining ensemble photometric redshift distributions with stacked spectroscopy

M. Cagliari , B. Granett , L. Guzzo , M. Bolzonella , L. Pozzetti et al.
Astronomy and Astrophysics - A&A, 2022, 660, pp.A9. ⟨10.1051/0004-6361/202142224⟩
Journal articles hal-03664785v1

Euclid: Calibrating photometric redshifts with spectroscopic cross-correlations

K. Naidoo , H. Johnston , B. Joachimi , J.L. van den Busch , H. Hildebrandt et al.
Astron.Astrophys., 2023, 670, pp.A149
Journal articles hal-03772761v1

Scalar-field quintessence by cosmic shear: CFHT data analysis and forecasts for DUNE

C. Schimd , I. Tereno
Journal of Physics A: Mathematical and Theoretical, 2007, 40, pp.7105-7112. ⟨10.1088/1751-8113/40/25/S69⟩
Journal articles hal-03646595v1
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Euclid preparation

S. Ilić , N. Aghanim , C. Baccigalupi , J. R. Bermejo-Climent , G. Fabbian et al.
Astronomy and Astrophysics - A&A, 2022, 657, pp.A91. ⟨10.1051/0004-6361/202141556⟩
Journal articles hal-03533670v1
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Euclid preparation

A. Blanchard , S. Camera , C. Carbone , V. F. Cardone , S. Casas et al.
Astronomy and Astrophysics - A&A, 2020, 642, pp.A191. ⟨10.1051/0004-6361/202038071⟩
Journal articles hal-02976446v1

Euclid: Forecasts for $k$-cut $3 \times 2$ Point Statistics

P.L. Taylor , T. Kitching , V.F. Cardone , A. Ferté , E.M. Huff et al.
Open J.Astrophys., 2021, 4 (1), pp.6. ⟨10.21105/astro.2012.04672⟩
Journal articles hal-03129526v1

Euclid Preparation XXIX: Forecasts for 10 different higher-order weak lensing statistics

V. Ajani , M. Baldi , A. Barthelemy , A. Boyle , P. Burger et al.
2023
Preprints, Working Papers, ... hal-03986111v1
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Euclid: Identification of asteroid streaks in simulated images using StreakDet software

M. Pöntinen , M. Granvik , A.A. Nucita , L. Conversi , B. Altieri et al.
Astronomy and Astrophysics - A&A, 2020, 644, pp.A35. ⟨10.1051/0004-6361/202037765⟩
Journal articles hal-03098892v1

Euclid Preparation. XIV. The Complete Calibration of the Color–Redshift Relation (C3R2) Survey: Data Release 3

S. Stanford , D. Masters , B. Darvish , D. Stern , J. Cohen et al.
The Astrophysical Journal Supplement, 2021, 256 (1), pp.9. ⟨10.3847/1538-4365/ac0833⟩
Journal articles hal-03413175v1

Euclid: Forecasts from the void-lensing cross-correlation

M. Bonici , C. Carbone , S. Davini , P. Vielzeuf , L. Paganin et al.
Astron.Astrophys., 2023, 670, pp.A47
Journal articles hal-03737493v1
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Euclid: Impact of non-linear and baryonic feedback prescriptions on cosmological parameter estimation from weak lensing cosmic shear

M. Martinelli , I. Tutusaus , M. Archidiacono , S. Camera , V.F. Cardone et al.
Astron.Astrophys., 2021, 649, pp.A100. ⟨10.1051/0004-6361/202039835⟩
Journal articles hal-02999590v1

Euclid: Modelling massive neutrinos in cosmology – a code comparison

J. Adamek , R.E. Angulo , C. Arnold , M. Baldi , M. Biagetti et al.
2022
Preprints, Working Papers, ... hal-03892198v1

Euclid: Testing the Copernican principle with next-generation surveys

D. Camarena , V. Marra , Z. Sakr , S. Nesseris , A. da Silva et al.
Astron.Astrophys., 2023, 671, pp.A68
Journal articles hal-03758826v1
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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.
Astronomy and Astrophysics - A&A, 2023, 671, pp.A99. ⟨10.1051/0004-6361/202244307⟩
Journal articles hal-03866216v1

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.
Astronomy and Astrophysics - A&A, 2022, 668, pp.C3. ⟨10.1051/0004-6361/202243950e⟩
Journal articles hal-03935710v1
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Euclid: Covariance of weak lensing pseudo-Cℓ estimates - Calculation, comparison to simulations, and dependence on survey geometry

R.E. Upham , M.L. Brown , L. Whittaker , A. Amara , N. Auricchio et al.
Astron.Astrophys., 2022, 660, pp.A114. ⟨10.1051/0004-6361/202142908⟩
Journal articles hal-03601240v1

Euclid: Searching for pair-instability supernovae with the Deep Survey

T.J. Moriya , C. Inserra , M. Tanaka , E. Cappellaro , M. Della Valle et al.
Astron.Astrophys., 2022, 666, pp.A157. ⟨10.1051/0004-6361/202243810⟩
Journal articles hal-03661327v1
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Euclid preparation

V. Guglielmo , R. Saglia , F. Castander , A. Galametz , S. Paltani et al.
Astronomy and Astrophysics - A&A, 2020, 642, pp.A192. ⟨10.1051/0004-6361/202038334⟩
Journal articles hal-03026941v1