Euclid preparation. XCVII. Cosmology Likelihood for Observables in Euclid (CLOE). 4: Validation and performance

Q: What does this research mean for the field?

The Cosmology Likelihood for Observables in Euclid (CLOE) software accurately models and fits Euclid observables, producing summary statistics that differ by less than 0.1 sigma from established benchmark codes. Novelty: ClaimNovelty.METHODOLOGICAL. Consensus alignment: ConsensusAlignment.NEUTRAL.

M. Martinelli; A. Pezzotta; D. Sciotti; L. Blot; M. Bonici; S. Camera; G. Cañas-Herrera; V. F. Cardone; P. Carrilho; S. Casas; S. Davini; S. Di Domizio; S. Farrens; L. W. K. Goh; S. Gouyou Beauchamps; S. Ilić; S. Joudaki; F. Keil; A. M. C. Le Brun; C. Moretti; V. Pettorino; A. G. Sánchez; Z. Sakr; K. Tanidis; I. Tutusaus; V. Ajani; M. Crocce; C. Giocoli; L. Legrand; M. Lembo; G. F. Lesci; D. Navarro-Gironés; A. Nouri-Zonoz; S. Pamuk; M. Tsedrik; J. Bel; C. Carbone; C. A. J. Duncan; M. Kilbinger; F. Lacasa; M. Lattanzi; D. Sapone; E. Sellentin; P. L. Taylor; N. Aghanim; B. Altieri; L. Amendola; S. Andreon; N. Auricchio; C. Baccigalupi; M. Baldi; A. Balestra; S. Bardelli; P. Battaglia; R. Bender; A. Biviano; A. Bonchi; D. Bonino; E. Branchini; M. Brescia; J. Brinchmann; V. Capobianco; J. Carretero; M. Castellano; G. Castignani; S. Cavuoti; K. C. Chambers; A. Cimatti; C. Colodro-Conde; G. Congedo; C. J. Conselice; L. Conversi; Y. Copin; H. M. Courtois; A. Da Silva; H. Degaudenzi; S. de la Torre; G. De Lucia; A. M. Di Giorgio; H. Dole; F. Dubath; X. Dupac; S. Dusini; A. Ealet; S. Escoffier; M. Farina; R. Farinelli; F. Faustini; S. Ferriol; F. Finelli; P. Fosalba; S. Fotopoulou; N. Fourmanoit; M. Frailis; E. Franceschi; M. Fumana; S. Galeotta; K. George; W. Gillard; B. Gillis

doi:10.1051/0004-6361/202556864/pdf

May 12, 2026

Euclid preparation. XCVII. Cosmology Likelihood for Observables in Euclid (CLOE). 4: Validation and performance

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Key Points

This work aims to validate the Cosmology Likelihood for Observables in Euclid software by comparing its outputs with other benchmark codes.
Compared calculations from the CLOE software with external benchmark codes for observables in Euclid.
Analyzed both photometric and spectroscopic survey outputs across a range of cases.
Evaluated correlation functions and summary statistics for accuracy assessment.
All summary statistics deviated less than 0.1σ from the benchmarks.
Predictions remained statistically compatible with simulated data from benchmark codes.
Comparison of correlation function accuracy for both photometric and spectroscopic observables showed similar results.

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Implication

Validates calculations for Euclid observables, highlighting high accuracy compared to benchmarks.

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Cite This Study

Martinelli et al. (2026) studied this question.

synapsesocial.com/papers/6a0d4ec0f03e14405aa9a01a https://doi.org/10.1051/0004-6361/202556864/pdf

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Euclid preparation. XCVII. Cosmology Likelihood for Observables in Euclid (CLOE). 4: Validation and performance

Key Points

No abstract yet

Implication

Discussion

Cite This Study

Euclid preparation. XCVII. Cosmology Likelihood for Observables in Euclid (CLOE). 4: Validation and performance

Key Points

No abstract yet

Implication

Discussion

Cite This Study

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