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arxiv: 2605.23839 · v1 · pith:TJNABM72new · submitted 2026-05-22 · 🌌 astro-ph.CO · astro-ph.IM

cloelib: A Flexible Python Library for Computing Cosmological Observables in the Euclid Era

Marco Bonici , Guadalupe Ca\~nas-Herrera , Pedro Carrilho , Santiago Casas , Chiara Moretti , Andrea Pezzotta (cloe-org maintainers) , Michel Aguena , Giovanni Aric\'o
show 49 more authors
Zahra Baghkhani Matteo Baratto Emilio Bellini Jip de Buck Klara Bertmann Ben Bose Jeger C. Broxterman Pierre Burger Carmelita Carbone Chaitanya Chawak Jose Coloma-Nadal Martin Crocce Stefano Davini Christopher A. J. Duncan Samuel Farrens Lisa Goh Nastassia Grimm Alex Hall Ryusei R. Kano Martin K\"archer Felicitas Keil Rapha\"el Kou Laila Linke Arthur Loureiro Katarina Markovic David Navarro-Giron\'es Filippo Oppizzi Gabriele Parimbelli Anna Porredon Robert Reischke Jaime Ruiz Zapatero I\~nigo S\'aez-Casares Ziad Sakr Neel Shah Davide Sciotti Matthieu Schaller Ivan Sladoljev Arghavan Souki Sankarshana Srinivasan Konstantinos Tanidis Peter L. Taylor Nicolas Tessore Linus Thummel Maria Tsedrik Isaac Tutusaus Casper Vedder Angus H. Wright Miguel Zumalac\'arregui Joe Zuntz (cloe-org contributors)
This is my paper

Pith reviewed 2026-05-25 02:58 UTC · model grok-4.3

classification 🌌 astro-ph.CO astro-ph.IM
keywords cloelibEuclidcosmological observablesPython libraryJAXautomatic differentiationlarge-scale structureCMB cross-correlations
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The pith

cloelib is a modular Python library that computes cosmological observables for Euclid by interfacing with Boltzmann solvers and using JAX automatic differentiation.

A machine-rendered reading of the paper's core claim, the machinery that carries it, and where it could break.

The paper introduces cloelib as a Python library developed within the CLOE ecosystem to calculate cosmological observables for the Euclid mission. It features a modular architecture that connects to established Boltzmann solvers and adds JAX-based automatic differentiation to support gradient-based optimization in inference. The library defines protocols for background evolution, perturbations, and non-linear structure formation while covering photometric and spectroscopic large-scale structure probes plus CMB cross-correlations and galaxy clusters. A reader would care because Euclid demands flexible, efficient theory predictions that integrate with modern machine learning approaches to handle precision cosmology data. In final form the library is positioned as the reference infrastructure for the mission's first cosmological release.

Core claim

cloelib defines consistent protocols for background evolution, perturbations, and non-linear structure formation. It interfaces with Boltzmann solvers and incorporates JAX-based automatic differentiation to enable gradient-based methods. The library supports 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.

What carries the argument

The modular architecture that interfaces with Boltzmann solvers and incorporates JAX-based automatic differentiation for gradient-based inference.

If this is right

  • Supports gradient-based optimization methods in cosmological inference pipelines.
  • Covers the full range of photometric, spectroscopic, CMB cross-correlation and cluster observables needed for Euclid.
  • Bridges traditional numerical cosmology codes with modern optimization and machine learning inference techniques.
  • Provides the reference theory computation layer for Euclid's first cosmological data release.

Where Pith is reading between the lines

These are editorial extensions of the paper, not claims the author makes directly.

  • The differentiable interface could allow hybrid models that combine numerical solvers with neural network emulators for faster parameter scans.
  • Similar modular protocols might be adapted for other upcoming surveys that require consistent observable predictions across multiple probes.
  • Automatic differentiation opens the possibility of end-to-end gradient flow from theory parameters through to likelihood evaluations in joint analyses.
  • The library's design may reduce duplication of effort by letting different analysis teams share the same underlying observable computations.

Load-bearing premise

The modular architecture will interface with Boltzmann solvers and support all required observables without major accuracy or performance shortfalls.

What would settle it

A direct numerical comparison of cloelib outputs against established Boltzmann codes for a set of Euclid-like observables that reveals discrepancies exceeding the required precision.

read the original abstract

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.

Editorial analysis

A structured set of objections, weighed in public.

Desk editor's note, referee report, simulated authors' rebuttal, and a circularity audit. Tearing a paper down is the easy half of reading it; the pith above is the substance, this is the friction.

Referee Report

1 major / 2 minor

Summary. The manuscript describes cloelib, a Python library for computing cosmological observables in the Euclid context. It outlines a modular architecture with protocols for background evolution, perturbations, and non-linear structure formation; interfaces to Boltzmann solvers; and JAX-based automatic differentiation for gradient-based methods. The library supports photometric/spectroscopic large-scale structure, CMB cross-correlations, and cluster observables, with the intent to serve as reference infrastructure for Euclid's first cosmological release.

Significance. If the described features are realized, the library would offer a useful bridge between established numerical cosmology tools and modern differentiable/ML inference techniques, addressing needs in the Euclid precision era. The consistent protocol definitions and JAX integration are explicit strengths that enable the claimed flexibility.

major comments (1)
  1. Abstract: the assertion that the architecture 'interfaces seamlessly with established Boltzmann solvers' and supports the full range of observables 'without major accuracy or performance shortfalls' is presented without any benchmarks, validation tests, or error analysis. This is load-bearing for the central claim of serving as the reference infrastructure.
minor comments (2)
  1. The manuscript should include a diagram or explicit listing of the defined protocols to clarify the modular interfaces for readers.
  2. Consider adding references to prior differentiable cosmology libraries (e.g., those using JAX or similar) to better situate the contribution.

Simulated Author's Rebuttal

1 responses · 0 unresolved

We thank the referee for their constructive review. The single major comment correctly identifies that the abstract makes strong claims about seamless interfacing and performance without supporting evidence in the current manuscript. We address this below and will revise accordingly.

read point-by-point responses

  1. Referee: Abstract: the assertion that the architecture 'interfaces seamlessly with established Boltzmann solvers' and supports the full range of observables 'without major accuracy or performance shortfalls' is presented without any benchmarks, validation tests, or error analysis. This is load-bearing for the central claim of serving as the reference infrastructure.

    Authors: We agree that the abstract's claims require supporting evidence to be credible, particularly given the manuscript's positioning as reference infrastructure. The current version contains no benchmarks or validation tests. In the revised manuscript we will add a new section (provisionally Section 5) presenting direct comparisons against CLASS and CAMB for background quantities, linear power spectra, and selected observables (photometric and spectroscopic clustering, CMB cross-correlations). This section will include relative error plots, convergence tests, and wall-clock timing benchmarks on representative hardware. The abstract will be revised to reference these results or to qualify the performance claims. These additions directly address the load-bearing concern. revision: yes

Circularity Check

0 steps flagged

No significant circularity: software description paper with no derivations or predictions

full rationale

The manuscript is a library description paper whose central claim is the design and intended scope of cloelib as modular infrastructure for Euclid observables. No equations, fitted parameters, predictions, or load-bearing derivations are presented that could reduce to inputs by construction. Self-citations to cloe-org are descriptive of the ecosystem rather than justificatory of a physical result. The argument is self-contained as a statement of architectural choices and supported observables, with no internal reduction to fitted quantities or self-referential uniqueness theorems.

Axiom & Free-Parameter Ledger

0 free parameters · 0 axioms · 0 invented entities

This is a software library description paper with no scientific derivations, physical modeling, or new results; therefore the ledger contains no entries.

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discussion (0)

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Reference graph

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