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Record W4403597069 · doi:10.1051/0004-6361/202450996

<i>Euclid</i>

2024· article· en· W4403597069 on OpenAlexaff
M. Cropper, Ashraf Al-Bahlawan, J. Amiaux, M.S. Awan, R. Azzollini, K. Benson, Michel Berthé, J.-M. Boucher, E. Bozzo, C. Brockley-Blatt, Gian Paolo Candini, C. Cara, Rahil Chaudery, Pascale Danto, James Denniston, A. M. Di Giorgio, Ben Dryer, Julien Dubois, J. Endicott, M. Farina, Emanuele Galli, Ludovic Genolet, Jason Gow, P. Guttridge, M. Hailey, David Hall, Christofer Harper, H. Hoekstra, Andrew D. Holland, B. Horeau, D. Hu, Rachel James, Ali Kh. Khalil, Robbie King, T. Kitching, R. Kohley, C. Larchevêque, Alastair Lawrenson, P. Liebing, S.J Liu, J. Martignac, R. Massey, H. J. McCracken, L. Miller, Norman Murray, R. Nakajima, S.-M Niemi, J.W Nightingale, S. Paltani, Anand Pendem, A. Philippon, C. Plana, P. Pool, S. Pottinger, J. Rhodes, A. Rousseau, K. Ruane, Mario Salatti, J.-C Salvignol, Alice Sciortino, Anthony Short, J. Skottfelt, Samuel Smit, Ian Swindells, Magdalena Szafraniec, Peter Thomas, William R. Thomas, E. Tommasi, S. Tosti, François Visticot, D.M. Walton, G. Willis, B. Winter, N. Aghanim, B Altieri, A Amara, S. Andreon, N. Auricchio, C. Baccigalupi, M Baldi, A. Balestra, S. Bardelli, Alberto Basset, R. Bender, Francis Bernardeau, C. Bodendorf, Tobias Boenke, D. Bonino, E. Branchini, M. Brescia, J. Brinchmann, S. Camera, V. Capobianco, C. Carbone, V. F. Cardone, J. Carretero, R. Casas, Santiago Casas, F. J. Castander, M. Castellano, G. Castignani, S. Cavuoti, A. Cimatti, C Colodro-Conde, G. Congedo, C.J. Conselice, L. Conversi, Y. Copin, F. Courbin, H. M. Courtois, M. Crocce, Jean-Gabriel Cuby, J.-C. Cuillandre, A. Da Silva, H. Degaudenzi, G. De Lucia, J. Dinis, M. Douspis, C.A.J Duncan, X. Dupac, S. Dusini, A. Ealet, M. Fabricius, S. Farrens, S Ferriol, P. Fosalba, S. Fotopoulou, M. Frailis, E. Franceschi, P. Franzetti, Pierre-Antoine Frugier, M. Fumana, S. Galeotta, B. Garilli, Koshy George, W. Gillard, B. Gillis, C. Giocoli, P. G'omez-Alvarez, B. R. Granett, A. Grazian, F Grupp, L. Guzzo, S. V. H. Haugan, O. Hérent, J. Hoar, Mark Holliman, W. A. Holmes, I. Hook, F. Hormuth, A. Hornstrup, P. Hudelot, S. Ilić, K. Jahnkę, M. Jhabvala, Benjamin Joachimi, E. Keihänen, S. Kermiche, A. Kiessling, M. Kilbinger, B. Kubik, Konrad Kuijken, M. Kümmel, M. Kunz, H. Kurki‐Suonio, O. Lahav, R. Laureijs, S. Ligori, P. B. Lilje, V. Lindholm, I. Lloro, J. Lorenzo Alvarez, G Mainetti, E. Maiorano, O. Mansutti, S. Marcin, O. Marggraf, K. Markovič, M. Martinelli, N. Martinet, F. Marulli, Daniel Masters, S. Maurogordato, E. Medinaceli, S Mei, M. Melchior, Y. Mellier, M. Meneghetti, E. Merlin, G. Meylan, J. J. Mohr, M. Moresco, L. Moscardini, C. Neissner, R. C. Nichol, T. Nutma, C. Padilla Aranda, K. Paech, F. Pasian, J. A. Peacock, Will J. Percival, V. Pettorino, S. Pires, G. Polenta, M. Poncet, L. Popa, L. Pozzetti, F. Raison, R. Rébolo, Alexandre Réfrégier, A Renzi, G. Riccio, Hans-Walter Rix, E. Romelli, M. Roncarelli, C. Rosset, E. Rossetti, H. J. A. Röttgering, B. Rusholme, R. Saglia, Z. Sakr, A.G. S'anchez, D. Sapone, M. Sauvage, R. Scaramella, J.A Schewtschenko, M. Schirmer, Peter Schneider, T. Schrabback, A. Secroun, E. Sefusatti, G. Seidel, M. D. Seiffert, S. Serrano, C. Sirignano, G. Sirri, L. Stančo, Jean‐Luc Starck, J. Steinwagner, i, D. Tavagnacco, A.N. Taylor, H.I Teplitz, I. Tereno, R. Toledo-Moreo, F. Torradeflot, I. Tutusaus, E. A. Valentijn, L. Valenziano, T. Vassallo, A. Veropalumbo, S. Wachter, Yun Wang, J. Weller, G. Zamorani, J. Zoubian, A. Biviano, M. Bolzonella, A. Boucaud, C. Burigana, M. Calabrese, P Casenove, D. Di Ferdinando, J.A. Escartin Vigo, Giulio Fabbian, R. Farinelli, F. Finelli⋆, J. Gracia-Carpio, H. Israel, N. Mauri, H.N. Nguyen-Kim, A Pezzotta, C. Porciani, V Scottez, M. Tenti, Matteo Viel, M. Wiesmann, Y. Akrami, V. Allevato, S Anselmi, É. Aubourg, M. Ballardini, Daniele Bertacca, M. Béthermin, A. Blanchard, L Blot, S. Borgani, Alejandro S. Borlaff, S Bruton, R. Cabanac, Anthony Calabro, G. Calderone, G Cañas-Herrera, A. Cappi, C. S. Carvalho, T. Castro, K. C. Chambers, R. Chary, S. Contarini, A.R. Cooray, O. Cordes, M. Costanzi, O. Cucciati, S. Davini, Brian De, G. Desprez, A. Díaz‐Sánchez, S. Di Domizio, H. Dole, S. Escoffier, A.G Ferrari, P.G Ferreira, I. Ferrero, A. Finoguenov, F. Fornari, L. Gabarra, K. Ganga, J. García-Bellido, V Gautard, E. Gaztañaga, F. Giacomini, F. Gianotti, G. Gozaliasl, W.G Hartley, H. Hildebrandt, J Hjorth, O. Ilbert, A. Jiménez Muñoz, Shahab Joudaki, V. Kansal, D. Karagiannis, F. Lacasa, J Le Graet, L. Legrand, A. Loureiro, J. F. Macías–Pérez, M. Magliocchetti, C. Mancini, F. Mannucci, L. Maurin, M. Migliaccio, M Miluzio, Pierluigi Monaco, Claudio Moretti, G Morgante, S. Nadathur, N. A. Walton, J. Odier, M. Oguri, L. Patrizii, V. Popa, D. Potter, Alkistis Pourtsidou, P. Reimberg, I Risso, P.-F Rocci, M Sahlén, Claudia Scarlata, J. Schaye, Aurel Schneider, M. Schultheis, M. Sereno, F. Shankar, G. Sikkema, Alessandra Silvestri, P. Šimon, A. Spurio Mancini, Joachim Stadel, K Tanidis, C. Tao, N Tessore, G. Testera, M. Tewes, R. Teyssier, Sune Toft, S. Tosi, A. Troja, C Valieri, J. Väliviita, D. Vergani, Filippo Vernizzi, G Verza, P Vielzeuf, L. Zalesky, M. Archidiacono, F. Atrio‐Barandela, T. Bouvard, F Caro, Paola Dimauro, P.-A. Duc, Yuhong Fang, A Montoro, A. Mora, Clare Murray, L. Pagano, D. Paoletti, E Sarpa, A. Viitanen, J. Lesgourgues, J Martín-Fleitas, D. Scott

Bibliographic record

VenueAstronomy and Astrophysics · 2024
Typearticle
Languageen
FieldPhysics and Astronomy
TopicAstronomy and Astrophysical Research
Canadian institutionsUniversity of British ColumbiaSaint Mary's UniversityPerimeter InstituteUniversity of Waterloo
Fundersnot available
KeywordsPhysicsCosmologyDark energyRedshiftWeak gravitational lensingGravitational lensSkyAstronomyPlanckGalaxyAstrophysicsDark matterRemote sensingGeography

Abstract

fetched live from OpenAlex

This paper presents the specification, design, and development of the Visible Camera (VIS) on the European Space Agency’s Euclid mission. VIS is a large optical-band imager with a field of view of 0.54 deg 2 sampled at 0″.1 with an array of 609 Megapixels and a spatial resolution of 0″.18. It will be used to survey approximately 14 000 deg 2 of extragalactic sky to measure the distortion of galaxies in the redshift range z = 0.1–1.5 resulting from weak gravitational lensing, one of the two principal cosmology probes leveraged by Euclid . With photometric redshifts, the distribution of dark matter can be mapped in three dimensions, and the extent to which this has changed with look-back time can be used to constrain the nature of dark energy and theories of gravity. The entire VIS focal plane will be transmitted to provide the largest images of the Universe from space to date, specified to reach m AB ≥ 24.5 with a signal-to-noise ratio S/N ≥ 10 in a single broad I E ≃ ( r + i + z ) band over a six-year survey. The particularly challenging aspects of the instrument are the control and calibration of observational biases, which lead to stringent performance requirements and calibration regimes. With its combination of spatial resolution, calibration knowledge, depth, and area covering most of the extra-Galactic sky, VIS will also provide a legacy data set for many other fields. This paper discusses the rationale behind the conception of VIS and describes the instrument design and development, before reporting the prelaunch performance derived from ground calibrations and brief results from the inorbit commissioning. VIS should reach fainter than m AB = 25 with S/N ≥ 10 for galaxies with a full width at half maximum of 0″. 3 in a 1″.3 diameter aperture over the Wide Survey, and m AB ≥ 26.4 for a Deep Survey that will cover more than 50 deg 2 . The paper also describes how the instrument works with the Euclid telescope and survey, and with the science data processing, to extract the cosmological information.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.039
Threshold uncertainty score0.130

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.002
Science and technology studies0.0010.001
Scholarly communication0.0040.003
Open science0.0020.003
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0390.063

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.008
GPT teacher head0.252
Teacher spread0.243 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations71
Published2024
Admission routes1
Has abstractyes

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