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Record W4414699266 · doi:10.1051/0004-6361/202556459

<i>Euclid</i> preparation

2025· preprint· en· W4414699266 on OpenAlexaff
Pierluigi Monaco, Gabriele Parimbelli, M.Y Elkhashab, J. Salvalaggio, T. Castro, M.D Lepinzan, E Sarpa, E Sefusatti, L. Stanco, L. Tornatore, Graeme E. Addison, S Bruton, C. Carbone, F. J. Castander, J. Carretero, S. de la Torre, P Fosalba, Guilhem Lavaux, S Lee, K. Markovič, F Passalacqua, Will J. Percival, I Risso, Claudia Scarlata, P. Tallada-Crespí, Matteo Viel, Yun Wang, B. Altieri, S. Andreon, N. Auricchio, C. Baccigalupi, M. Baldi, S. Bardelli, Francis Bernardeau, A. Biviano, E. Branchini, M. Brescia, J. Brinchmann, S. Camera, G Cañas-Herrera, V. Capobianco, V. F. Cardone, S Casas, M. Castellano, G. Castignani, S. Cavuoti, A. Cimatti, C Colodro-Conde, G. Congedo, Christopher J. Conselice, L Conversi, Y. Copin, F. Courbin, H. M. Courtois, A. Da Silva, H. Degaudenzi, G. De Lucia, A. M. Di Giorgio, F. Dubath, Franck Ducret, C. A. J. Duncan, S Dusini, A. Ealet, S. Escoffier, M. Farina, R. Farinelli, S Farrens, S Ferriol, F. Finelli⋆, N. Fourmanoit, M. Frailis, E. Franceschi, M. Fumana, S. Galeotta, Koshy George, B. Gillis, C. Giocoli, J Gracia-Carpio, A. Grazian, F Grupp, L. Guzzo, W. A. Holmes, F Hormuth, A. Hornstrup, K. Jahnkę, M. Jhabvala, B Joachimi, E. Keihänen, S. Kermiche, B. Kubik, M Kümmel, M. Kunz, H. Kurki‐Suonio, S. Ligori, V. Lindholm, I. Lloro, E. Maiorano, O. Mansutti, O. Marggraf, M. Martinelli, N. Martinet, F. Marulli, R. Massey, E. Medinaceli, S. Mei, M. Melchior, Y. Mellier, M. Meneghetti, E Merlin, G Meylan, A. Mora, M. Moresco, L. Moscardini, E. Munari, C. Neissner, C. Padilla Aranda, S Paltani, F. Pasian, Kim Steenstrup Pedersen, V. Pettorino, S. Pires, G. Polenta, M Poncet, L. Pozzetti, F. Raison, A. Renzi, J. Rhodes, G. Riccio, E. Romelli, R. P. Saglia, Z. Sakr, D. Sapone, B. Sartoris, P Schneider, T. Schrabback, M. Scodeggio, A. Secroun, G. Seidel, M. D. Seiffert, S. Serrano, C. Sirignano, G. Sirri, J Steinwagner, D. Tavagnacco, I. Tereno, N Tessore, Sune Toft, R. Toledo-Moreo, F Torradeflot, I. Tutusaus, L. Valenziano, J. Väliviita, T. Vassallo, G. Verdoes Kleijn, A. Veropalumbo, J. Weller, G. Zamorani, E. Zucca, V. Allevato, M. Ballardini, C. Burigana, R. Cabanac, M. Calabrese, A Cappi, D. Di Ferdinando, Giulio Fabbian, L. Gabarra, J Martín-Fleitas, S Matthew, N. Mauri, A Pezzotta, M. Pöntinen, C. Porciani, V Scottez, M. Sereno, M. Tenti, M. Wiesmann, Y. Akrami, S Anselmi, Maria Archidiacono, F. Atrio‐Barandela, S. Àvila, A. Balaguera-Antolínez, P. Bergamini, Daniele Bertacca, M. Béthermin, Alain Blanchard, L Blot, S. Borgani, Anthony Calabro, B. Camacho Quevedo, F Caro, F Cogato, Simon Conseil, S. Contarini, O. Cucciati, S. Davini, G. Desprez, A. Díaz‐Sánchez, S. Di Domizio, A Enia, A Finoguenov, Fabio Fontanot, A Franco, K. Ganga, J. García-Bellido, V Gautard, E. Gaztañaga, F. Giacomini, F. Gianotti, G. Gozaliasl, M Guidi, A Hall, Shoubaneh Hemmati, C. Hernández-Monteagudo, H. Hildebrandt, J. Hjorth, Shahab Joudaki, Y Kang, V. Kansal, D. Karagiannis, K. Kiiveri, Sandor Kruk, V. Le Brun, J Le Graet, L. Legrand, Maria Lembo, Julien Lesgourgues, J. F. Macías–Pérez, G. Maggio, M. Magliocchetti, C. Mancini, F. Mannucci, L. Maurin, M Miluzio, A Montoro, Claudio Moretti, G. Morgante, S. Nadathur, A Navarro-Alsina, Savvas Nesseris, K. Paterson, D. Potter, S Quai, M. Radovich, S Sacquegna, M Sahlén, D Sciotti, Elena Sellentin, C. Tao, G. Testera, Romain Teyssier, S. Tosi, A. Troja, C Valieri, A. Venhola, Filippo Vernizzi, G Verza, P Vielzeuf

Bibliographic record

VenueAstronomy and Astrophysics · 2025
Typepreprint
Languageen
FieldDecision Sciences
TopicScientific Computing and Data Management
Canadian institutionsPerimeter InstituteUniversity of Waterloo
FundersFundação para a Ciência e a TecnologiaNorsk RomsenterAgenția Spațială RomânăAgenzia Spaziale ItalianaMagyar Tudományos AkadémiaNational Astronomical Observatory of JapanEuropean CommissionEuropean Space AgencyNational Aeronautics and Space Administration
KeywordsGalaxyMilky WayHaloRADIUSDark matterSkyDark matter haloGalaxy formation and evolution

Abstract

fetched live from OpenAlex

We present two extensive sets of 3500+1000 simulations of dark matter haloes on the past light cone and two corresponding sets of simulated (mock) galaxy catalogues that represent the spectroscopic sample of Euclid . The simulations were produced with the latest version of the code Pinocchio and provide the largest public set of simulated skies. The mock galaxy catalogues were obtained by populating haloes with galaxies using an halo occupation distribution (HOD) model extracted from the Flagship galaxy catalogue provided by Euclid Collaboration. The Geppetto set of 3500 simulated skies was obtained by tiling a 1.2 h −1 Gpc box to cover a light cone whose sky footprint is a circle with a radius of 30° for an area of 2763 deg 2 and a minimum halo mass of 1.5 × 10 11 h −1 M ⊙ . The relatively small size of the box means that this set is unsuitable for measuring very large scales. The EuclidLargeBox set consists of 1000 simulations of 3.38 h −1 Gpc and has the same mass resolution and a footprint that covers half of the sky. It excludes the Milky Way zone of avoidance. From this, we produced a set of 1000 EuclidLargeMocks on the 30° radius footprint, whose comoving volume is fully contained in the simulation box. We validated the two sets of catalogues by analysing number densities, power spectra, and two-point correlation functions to show that the Flagship spectroscopic catalogue is consistent with being one of the realisations of the simulated sets. We noted small deviations, however, that are limited to the quadrupole at k &gt; 0.2 h Mpc −1 . We infer the cosmological parameters from these catalogues and demonstrate that using one realisation of EuclidLargeMocks in place of the Flagship mock produces the same posteriors to within the expected shift given by the sample variance. These simulated skies will be used for the galaxy clustering analysis of the Euclid Data Release 1 (DR1), and an even larger set of simulations is planned for the next releases.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScholarly communication
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.949
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0010.003
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.056
GPT teacher head0.351
Teacher spread0.294 · 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 teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreMethods

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

Citations3
Published2025
Admission routes1
Has abstractyes

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