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| Format: | Preprint |
| Published: |
2026
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| Subjects: | |
| Online Access: | https://arxiv.org/abs/2605.23839 |
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| _version_ | 1866913157063114752 |
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| author | Bonici, Marco Cañas-Herrera, Guadalupe Carrilho, Pedro Casas, Santiago Moretti, Chiara Pezzotta, Andrea Aguena, Michel Aricó, Giovanni Baghkhani, Zahra Baratto, Matteo Bellini, Emilio de Buck, Jip Bertmann, Klara Bose, Ben Broxterman, Jeger C. Burger, Pierre Carbone, Carmelita Chawak, Chaitanya Coloma-Nadal, Jose Crocce, Martin Davini, Stefano Duncan, Christopher A. J. Farrens, Samuel Goh, Lisa Grimm, Nastassia Hall, Alex Kano, Ryusei R. Kärcher, Martin Keil, Felicitas Kou, Raphaël Linke, Laila Loureiro, Arthur Markovic, Katarina Navarro-Gironés, David Oppizzi, Filippo Parimbelli, Gabriele Porredon, Anna Reischke, Robert Zapatero, Jaime Ruiz Sáez-Casares, Iñigo Sakr, Ziad Shah, Neel Sciotti, Davide Schaller, Matthieu Sladoljev, Ivan Souki, Arghavan Srinivasan, Sankarshana Tanidis, Konstantinos Taylor, Peter L. Tessore, Nicolas Thummel, Linus Tsedrik, Maria Tutusaus, Isaac Vedder, Casper Wright, Angus H. Zumalacárregui, Miguel Zuntz, Joe |
| author_facet | Bonici, Marco Cañas-Herrera, Guadalupe Carrilho, Pedro Casas, Santiago Moretti, Chiara Pezzotta, Andrea Aguena, Michel Aricó, Giovanni Baghkhani, Zahra Baratto, Matteo Bellini, Emilio de Buck, Jip Bertmann, Klara Bose, Ben Broxterman, Jeger C. Burger, Pierre Carbone, Carmelita Chawak, Chaitanya Coloma-Nadal, Jose Crocce, Martin Davini, Stefano Duncan, Christopher A. J. Farrens, Samuel Goh, Lisa Grimm, Nastassia Hall, Alex Kano, Ryusei R. Kärcher, Martin Keil, Felicitas Kou, Raphaël Linke, Laila Loureiro, Arthur Markovic, Katarina Navarro-Gironés, David Oppizzi, Filippo Parimbelli, Gabriele Porredon, Anna Reischke, Robert Zapatero, Jaime Ruiz Sáez-Casares, Iñigo Sakr, Ziad Shah, Neel Sciotti, Davide Schaller, Matthieu Sladoljev, Ivan Souki, Arghavan Srinivasan, Sankarshana Tanidis, Konstantinos Taylor, Peter L. Tessore, Nicolas Thummel, Linus Tsedrik, Maria Tutusaus, Isaac Vedder, Casper Wright, Angus H. Zumalacárregui, Miguel Zuntz, Joe |
| contents | cloelib is a Python library developed to compute cosmological observables within the Cosmology Likelihood for Observables in Euclid (CLOE) ecosystem (cloe-org). As cosmology enters a precision era driven by galaxy survey missions such as Euclid, there is a growing need for flexible, efficient, and differentiable software capable of supporting next-generation inference pipelines. cloelib addresses these demands through a modular architecture that interfaces seamlessly with established Boltzmann solvers whilst incorporating JAX-based automatic differentiation to enable gradient-based methods. The library defines consistent protocols for background evolution, perturbations, and non-linear structure formation, and supports a wide range of observables, including photometric and spectroscopic large-scale structure probes, as well as cross-correlations with the Cosmic Microwave Background and galaxy clusters. In its finalised form, cloelib is intended to serve as the reference theory computation infrastructure for Euclid's first cosmological release, bridging traditional numerical cosmology with modern optimisation techniques and emerging machine learning approaches to inference. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2605_23839 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | cloelib: A Flexible Python Library for Computing Cosmological Observables in the Euclid Era Bonici, Marco Cañas-Herrera, Guadalupe Carrilho, Pedro Casas, Santiago Moretti, Chiara Pezzotta, Andrea Aguena, Michel Aricó, Giovanni Baghkhani, Zahra Baratto, Matteo Bellini, Emilio de Buck, Jip Bertmann, Klara Bose, Ben Broxterman, Jeger C. Burger, Pierre Carbone, Carmelita Chawak, Chaitanya Coloma-Nadal, Jose Crocce, Martin Davini, Stefano Duncan, Christopher A. J. Farrens, Samuel Goh, Lisa Grimm, Nastassia Hall, Alex Kano, Ryusei R. Kärcher, Martin Keil, Felicitas Kou, Raphaël Linke, Laila Loureiro, Arthur Markovic, Katarina Navarro-Gironés, David Oppizzi, Filippo Parimbelli, Gabriele Porredon, Anna Reischke, Robert Zapatero, Jaime Ruiz Sáez-Casares, Iñigo Sakr, Ziad Shah, Neel Sciotti, Davide Schaller, Matthieu Sladoljev, Ivan Souki, Arghavan Srinivasan, Sankarshana Tanidis, Konstantinos Taylor, Peter L. Tessore, Nicolas Thummel, Linus Tsedrik, Maria Tutusaus, Isaac Vedder, Casper Wright, Angus H. Zumalacárregui, Miguel Zuntz, Joe Cosmology and Nongalactic Astrophysics Instrumentation and Methods for Astrophysics cloelib is a Python library developed to compute cosmological observables within the Cosmology Likelihood for Observables in Euclid (CLOE) ecosystem (cloe-org). As cosmology enters a precision era driven by galaxy survey missions such as Euclid, there is a growing need for flexible, efficient, and differentiable software capable of supporting next-generation inference pipelines. cloelib addresses these demands through a modular architecture that interfaces seamlessly with established Boltzmann solvers whilst incorporating JAX-based automatic differentiation to enable gradient-based methods. The library defines consistent protocols for background evolution, perturbations, and non-linear structure formation, and supports a wide range of observables, including photometric and spectroscopic large-scale structure probes, as well as cross-correlations with the Cosmic Microwave Background and galaxy clusters. In its finalised form, cloelib is intended to serve as the reference theory computation infrastructure for Euclid's first cosmological release, bridging traditional numerical cosmology with modern optimisation techniques and emerging machine learning approaches to inference. |
| title | cloelib: A Flexible Python Library for Computing Cosmological Observables in the Euclid Era |
| topic | Cosmology and Nongalactic Astrophysics Instrumentation and Methods for Astrophysics |
| url | https://arxiv.org/abs/2605.23839 |