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arxiv: 2605.03012 · v1 · submitted 2026-05-04 · 🌌 astro-ph.CO

Recognition: unknown

Euclid preparation. Three-dimensional galaxy clustering in configuration space: Three-point correlation function estimation

Euclid Collaboration: A. Veropalumbo (1 , 2 , 3) , M. Moresco (4 , 5) , F. Marulli (4 , 5 , 6)
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Authors on Pith no claims yet

Pith reviewed 2026-05-08 17:38 UTC · model grok-4.3

classification 🌌 astro-ph.CO
keywords three-point correlation functiongalaxy clusteringEuclid surveyspherical harmonicslarge-scale structurecosmological parameterscorrelation functions
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The pith

Euclid can estimate the galaxy three-point correlation function accurately enough for the full survey using an efficient approximate method and a faster random-sample technique.

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

This paper introduces and validates the estimators for the three-point correlation function that will be used in Euclid's data analysis pipeline. It presents a direct, exact triplet-counting algorithm suitable for any triangular configuration alongside a faster spherical harmonic decomposition that expands the correlation function in Legendre coefficients to a finite order. The work also describes a random split technique that lowers the cost of counting triplets in random reference catalogs by a factor of ten while preserving numerical accuracy. Validation tests on mocks demonstrate that both approaches deliver the precision and robustness needed for the survey, and scaling estimates confirm that processing the final Euclid dataset remains computationally practical.

Core claim

The central claim is that the three-point correlation function can be measured for Euclid-scale galaxy catalogs by combining an exact direct-counting estimator with an approximate spherical harmonic decomposition limited to finite order, plus a random-split method that reduces random-catalog triplet counting cost by a factor of ten. The spherical harmonic estimates satisfy the mission's scientific accuracy requirements across the relevant range of configurations despite the truncation. Extensive validation confirms robustness, precision, and accuracy, establishing that a complete three-point analysis of the final survey data set is computationally feasible.

What carries the argument

The spherical harmonic decomposition estimator that computes Legendre coefficients of the three-point correlation function up to a finite expansion order, together with the random split technique for efficient triplet counting in random reference samples.

If this is right

  • Direct counting yields exact three-point correlation values for arbitrary triangular configurations.
  • The spherical harmonic approach scales efficiently to the full Euclid data volume while remaining within scientific accuracy limits.
  • Random splitting reduces computational cost of random-catalog triplet counting by a factor of ten with negligible accuracy loss.
  • A complete three-point correlation analysis of the final Euclid survey becomes computationally achievable.
  • Higher-order statistics can be incorporated into the pipeline to extract additional information beyond two-point clustering.

Where Pith is reading between the lines

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

  • The validated methods could be directly ported to other forthcoming surveys facing similar data volumes for higher-order correlation measurements.
  • Joint two-point and three-point analyses enabled by these tools would help tighten constraints on cosmological parameters and tests of Gaussianity.
  • Further increases in expansion order or refinements to the split procedure might yield even tighter accuracy at modest extra cost for specific science cases.

Load-bearing premise

That truncating the spherical harmonic expansion at finite order and recombining results from split random samples still produces accuracy within Euclid's required tolerance for every triangle shape and redshift range in the survey.

What would settle it

Comparing the spherical-harmonic three-point function estimates directly against exact counts on the same large mock Euclid catalog and finding differences that exceed the mission's specified precision threshold for any significant fraction of triangular configurations.

Figures

Figures reproduced from arXiv: 2605.03012 by 00014 Helsinki, 00044 Frascati, 00078 Monteporzio Catone, 00100 Roma, 00133 Roma, 00185 Roma, 0315 Oslo, 06304 Nice cedex 4, 077125, 08010 Barcelona, 08028 Barcelona, 08193 Barcelona, 08193 Bellaterra (Barcelona), 08860 Castelldefels, 1, 1), 10, 10), 100, 10010, 10025 Pino Torinese (TO), (100) Satlantis, 101), 10125 Torino, (101) Instituto de Astrof\'isica e Ci\^encias do Espa\c{c}o, (102) Mullard Space Science Laboratory, (103) Cosmic Dawn Center (DAWN), 104), (104) Niels Bohr Institute, (105) Universidad Polit\'ecnica de Cartagena, (106) Kapteyn Astronomical Institute, (107) Caltech/IPAC, 108), (108) Dipartimento di Fisica e Scienze della Terra, 109, 109), 10900 Euclid Avenue, (109) Istituto Nazionale di Fisica Nucleare, (10) IFPU, 11, 11), (110) Universit\'e C\^ote d'Azur, (111) INAF, (112) Astronomical Observatory of the Autonomous Region of the Aosta Valley (OAVdA), (113) Department of Physics, (114) Instituto de F\'isica Te\'orica UAM-CSIC, (115) CEA Saclay, (116) Univ. 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Figure 1
Figure 1. Figure 1: Schematic overview of the 3PCF-GC processing function and its integration within the ESGS pipeline. The upstream SEL-ID module provides the galaxy and random catalogues. The four processing steps are: input reading, triplet counting (auto- and cross-triplets for the data and random samples), 3PCF estimation (computing ζ, ξ, and the reduced 3PCF Q), and generation of the output data products in FITS format.… view at source ↗
Figure 2
Figure 2. Figure 2: Convergence of the SHD method as a function of cos θ for two triangle configurations from the Flagship mock in the first redshift bin. Left: Isosceles case (r12 = r13 = 20 h −1 Mpc) with ℓmax = 10 (red), 20 (cyan), and 30 (blue), compared to the DC reference (black dashed). Right: Non-isosceles case (r12 = 20 h −1 Mpc, r13 = 40 h −1 Mpc) with ℓmax = 4 (red), 10 (cyan), and 20 (blue). The grey bands show th… view at source ↗
Figure 3
Figure 3. Figure 3: Null test: the mean 3PCF measured from 600 Gaussian mocks with the expected volume and density of DR1, for a scalene configu￾ration with r12 = 40 h −1 Mpc and r13 = 80 h −1 Mpc. The expected sig￾nal is zero by construction. The light-grey band represents the single￾realisation statistical error; the dark-grey band shows its 10 % ampli￾tude, corresponding to the Euclid systematic requirement. The solid blac… view at source ↗
Figure 4
Figure 4. Figure 4: Impact of the random split on the 3PCF accuracy. We show the difference between the split and reference (no-split) estimates, normalised to the expected statistical error, for all non-isosceles triangle configurations with sides in the range 20–150 h −1 Mpc. The measurement uses the SHD method applied to the Flagship 2 catalogue reproducing the DR1 of Euclid in the first redshift bin, with a random sample … view at source ↗
Figure 5
Figure 5. Figure 5: Comparison of the two edge-correction methods (direct sum ζˆDS and Slepian–Eisenstein estimator ζˆ SE) for the Flagship mock. The dif￾ference is shown in units of the expected statistical error as a function of the triangle index. Points are colour-coded by the ratio r13/r12, ranging from nearly isosceles configurations (warm colours) to more elongated ones (cool colours). The grey band marks the ±1σ regio… view at source ↗
Figure 6
Figure 6. Figure 6: Left: Computational cost in CPU–hours as a function of the sample number density for a single triangle configuration (r12 = 20 h −1 Mpc, r13 = 40 h −1 Mpc, ∆r = 5 h −1 Mpc). Symbols show measured run times; lines show the analytical models from Eqs. (18) and (20). The DC method (black) scales as ¯n 3 , while the SHD method scales as ¯n 2 , with a weak dependence on ℓmax (red: ℓmax = 5; blue: ℓmax = 10). Ri… view at source ↗
Figure 8
Figure 8. Figure 8: Computational time as a function of the split factor Nsplit, nor￾malised to the no-split case, for the DC (blue dashed) and SHD (red solid) methods. The vertical dashed line marks the reference choice Nsplit = 25. The split yields a factor of ∼ 10 gain for SHD and ∼ 500 for DC. slightly less efficient, with a scaling of around N −0.9 threads, and shows greater efficiency as a function of the value of ℓmax.… view at source ↗
Figure 9
Figure 9. Figure 9: Predicted computational times for measuring the 3PCF across all configurations up to rmax = 150 h −1 Mpc for the three Euclid data releases and four redshift bins. Predictions assume a random sample 50 times denser than the galaxy catalogue, a split factor of 25, 32 threads, and a clock frequency of 3 GHz, using the survey parameters from view at source ↗
read the original abstract

Higher-order correlation functions are firmly established as a fundamental tool for the statistical analysis of clustering in modern galaxy surveys. It was demonstrated that they greatly enrich the information content extracted by two-point statistics, allowing us to break the degeneracies between model parameters and constrain departures from Gaussianity. This paper presents the statistical estimators adopted to evaluate the galaxy three-point correlation function and its numerical implementation within the data analysis pipeline of the Euclid Science Ground Segment. Two different algorithms are adopted to count triplets: a direct and exact counting method capable of providing a robust three-point correlation function measurement for any triangular configuration, and a more efficient method based on spherical harmonic decomposition, designed to address the computational challenges of measuring the three-point statistics for data sets as large as those of the final Euclid survey. The spherical harmonic decomposition estimates the Legendre coefficients of the three-point correlation function up to a finite expansion order. Despite being an approximation, the three-point function measured with this approach satisfies the scientific requirements of the mission. We also introduce, implement, and validate the random split technique, which reduces the computational cost of counting triplets in the reference random sample by a factor of 10, without significantly compromising numerical accuracy. We evaluated the robustness, precision, and accuracy of the numerical estimates through an extensive campaign of validation tests, the results of which are presented. Finally, we quantify the computational requirements and their scaling with the expected size of Euclid data set, showing that a complete three-point analysis of the final Euclid survey is within computational reach.

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 / 0 minor

Summary. The manuscript presents statistical estimators for the three-point correlation function (3PCF) in configuration space for Euclid galaxy clustering data. It describes a direct triplet-counting algorithm for exact measurements on any triangle and an approximate method based on spherical-harmonic decomposition truncated at finite order. A random-split technique is introduced to reduce the cost of random-catalog triplet counting by a factor of ~10. The authors report an extensive validation campaign on mock catalogs showing that the approximate estimator meets Euclid's scientific requirements, and they demonstrate that the computational scaling permits a full 3PCF analysis of the final survey volume.

Significance. If the validation results hold across the full range of configurations and redshifts, the work provides a practical, computationally feasible route to include 3PCF measurements in the Euclid Science Ground Segment pipeline. This would enable higher-order statistics to break parameter degeneracies and constrain primordial non-Gaussianity, directly supporting one of the mission's core science goals. The random-split optimization is a concrete efficiency gain that could be adopted by other large-scale structure analyses.

major comments (1)
  1. [Abstract and validation section] Abstract and validation section: the central claim that the finite-order spherical-harmonic estimator (plus random-split recombination) satisfies mission requirements is load-bearing, yet the provided information does not specify whether the mock validation sampled the full Euclid redshift distribution and the complete space of triangular configurations (including squeezed and elongated triangles where higher multipoles become important). Without quantitative error budgets showing that truncation and recombination biases remain below the statistical uncertainty and the precision needed for cosmological inference across these regimes, the claim that the approximation is safe for the final survey does not yet follow from the evidence.

Simulated Author's Rebuttal

1 responses · 0 unresolved

We thank the referee for their careful reading of the manuscript and for the constructive feedback. The comment highlights an important point regarding the clarity and completeness of our validation presentation, which we address below.

read point-by-point responses
  1. Referee: [Abstract and validation section] Abstract and validation section: the central claim that the finite-order spherical-harmonic estimator (plus random-split recombination) satisfies mission requirements is load-bearing, yet the provided information does not specify whether the mock validation sampled the full Euclid redshift distribution and the complete space of triangular configurations (including squeezed and elongated triangles where higher multipoles become important). Without quantitative error budgets showing that truncation and recombination biases remain below the statistical uncertainty and the precision needed for cosmological inference across these regimes, the claim that the approximation is safe for the final survey does not yet follow from the evidence.

    Authors: We agree that the manuscript would benefit from greater explicitness on these points. The validation campaign described in the validation section was performed on mocks constructed to match the full Euclid redshift distribution and sampled a wide range of triangular configurations, including squeezed and elongated triangles. However, the text does not provide a dedicated quantitative error budget comparing truncation and random-split recombination biases against the expected statistical uncertainties for cosmological parameter inference. In the revised version we will add this information, including explicit statements on the redshift and configuration coverage together with tabulated or plotted error budgets demonstrating that the biases remain below the thresholds required by the mission. revision: yes

Circularity Check

0 steps flagged

No circularity: algorithmic validation of estimators with independent test-based claims

full rationale

The paper describes two triplet-counting algorithms (direct and spherical-harmonic) for the 3PCF, introduces a random-split technique for the random catalog, and reports that validation tests confirm the approximation meets Euclid requirements while cutting cost by ~10x. No physical prediction is derived from fitted parameters; the central statements are empirical statements about numerical accuracy and scaling, each tied to explicit test campaigns rather than reducing to the method definition by construction. Self-citations appear only for background context and are not invoked as uniqueness theorems or load-bearing justifications for the accuracy claims. The derivation chain is therefore self-contained and non-circular.

Axiom & Free-Parameter Ledger

0 free parameters · 1 axioms · 0 invented entities

This is a computational methods and implementation paper. No new physical free parameters, axioms, or invented entities are introduced; the work relies on standard properties of spherical harmonics and triplet counting.

axioms (1)
  • domain assumption Spherical harmonic decomposition can approximate the three-point correlation function to sufficient accuracy when truncated at finite order
    Invoked to justify the faster estimator meeting mission requirements

pith-pipeline@v0.9.0 · 12497 in / 1331 out tokens · 48361 ms · 2026-05-08T17:38:04.383928+00:00 · methodology

discussion (0)

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Reference graph

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