Back in the saddle: Large-deviation statistics of the cosmic log-density field C Uhlemann, S Codis, C Pichon, F Bernardeau, P Reimberg Monthly Notices of the Royal Astronomical Society 460 (2), 1529-1541, 2016 | 74 | 2016 |
Redshift-space distortions with wide angular separations P Reimberg, F Bernardeau, C Pitrou Journal of Cosmology and Astroparticle Physics 2016 (01), 048, 2016 | 60 | 2016 |
Euclid preparation-XVIII. The NISP photometric system M Schirmer, K Jahnke, G Seidel, H Aussel, C Bodendorf, F Grupp, ... Astronomy & Astrophysics 662, A92, 2022 | 41 | 2022 |
Large deviation principle at play in large scale structure cosmology F Bernardeau, P Reimberg Physical Review D 94 (6), 063520, 2016 | 36 | 2016 |
CMB in a box: Causal structure and the Fourier-Bessel expansion LR Abramo, PH Reimberg, HS Xavier Physical Review D 82 (4), 043510, 2010 | 21 | 2010 |
Large deviation principle at work: Computation of the statistical properties of the exact one-point aperture mass P Reimberg, F Bernardeau Physical Review D 97 (2), 023524, 2018 | 19 | 2018 |
Euclid preparation-XXVIII. Forecasts for ten different higher-order weak lensing statistics V Ajani, M Baldi, A Barthelemy, A Boyle, P Burger, VF Cardone, S Cheng, ... Astronomy & Astrophysics 675, A120, 2023 | 15 | 2023 |
CMB and random flights: temperature and polarization in position space PHF Reimberg, LR Abramo Journal of Cosmology and Astroparticle Physics 2013 (06), 043, 2013 | 14 | 2013 |
The Jacobi map for gravitational lensing: the role of the exponential map PHF Reimberg, LR Abramo Classical and Quantum Gravity 30 (6), 065020, 2013 | 14 | 2013 |
Euclid preparation – XXIII. Derivation of galaxy physical properties with deep machine learning using mock fluxes and H-band images Euclid Collaboration, L Bisigello, CJ Conselice, M Baes, M Bolzonella, ... Monthly Notices of the Royal Astronomical Society 520 (3), 3529-3548, 2023 | 11 | 2023 |
Euclid preparation-XXI. Intermediate-redshift contaminants in the search for z> 6 galaxies within the Euclid Deep Survey SE Van Mierlo, KI Caputi, M Ashby, H Atek, M Bolzonella, RAA Bowler, ... Astronomy & Astrophysics 666, A200, 2022 | 11 | 2022 |
Euclid preparation-XXV. The Euclid Morphology Challenge: Towards model-fitting photometry for billions of galaxies E Merlin, M Castellano, H Bretonnière, U Kuchner, D Tuccillo, F Buitrago, ... Astronomy & Astrophysics 671, A101, 2023 | 10 | 2023 |
Euclid preparation-XXVI. The Euclid Morphology Challenge: Towards structural parameters for billions of galaxies H Bretonnière, U Kuchner, E Merlin, M Castellano, D Tuccillo, F Buitrago, ... Astronomy & Astrophysics 671, A102, 2023 | 7 | 2023 |
Euclid preparation-XXII. Selection of quiescent galaxies from mock photometry using machine learning A Humphrey, L Bisigello, PAC Cunha, M Bolzonella, S Fotopoulou, ... Astronomy & Astrophysics 671, A99, 2023 | 6 | 2023 |
Random flights through spaces of different dimensions PHF Reimberg, LR Abramo Journal of Mathematical Physics 56 (1), 2015 | 5 | 2015 |
Euclid preparation-XX. The Complete Calibration of the Color–Redshift Relation survey: LBT observations and data release R Saglia, S De Nicola, M Fabricius, V Guglielmo, J Snigula, R Zöller, ... Astronomy & Astrophysics 664, A196, 2022 | 4 | 2022 |
Failures of Halofit model for computation of Fisher Matrices P Reimberg, F Bernardeau, T Nishimichi, M Rizzato arXiv preprint arXiv:1811.02976, 2018 | 4 | 2018 |
Euclid preparation-XXXII. Evaluating the weak-lensing cluster mass biases using the Three Hundred Project hydrodynamical simulations C Giocoli, M Meneghetti, E Rasia, S Borgani, G Despali, GF Lesci, ... Astronomy & Astrophysics 681, A67, 2024 | 2 | 2024 |
Euclid preparation TBD. Modelling spectroscopic clustering on mildly nonlinear scales in beyond-CDM models B Bose, P Carrilho, M Marinucci, C Moretti, M Pietroni, E Carella, L Piga, ... arXiv preprint arXiv:2311.13529, 2023 | 2 | 2023 |
Euclid preparation V Ajani, M Baldi, A Barthelemy, A Boyle, P Burger, VF Cardone, S Cheng, ... Astronomy & Astrophysics 675, 2023 | 2 | 2023 |