pith. machine review for the scientific record. sign in

arxiv: 2605.03446 · v1 · submitted 2026-05-05 · 🌌 astro-ph.CO

Recognition: unknown

textit{Euclid} preparation. Baryon acoustic oscillations extraction techniques: comparison and optimisation

A. Biviano, A. Blanchard, A. Boucaud, A. Calabro, A. Cappi, A. Cimatti, A. Crespi, A. D\'iaz-S\'anchez, A. Eggemeier, A. Farina, A. Finoguenov, A. Franco, A. Grazian, A. Gruppuso, A. G. S\'anchez, A. Hall, A. Hornstrup, A. H. Wright, A. Kiessling, A. M. C. Le Brun, A. Mora, A. Navarro-Alsina, A. N. Taylor, A. Pezzotta, A. Pisani, A. Pourtsidou, A. R. Cooray, A. Schneider, A. Secroun, A. Troja, A. Veropalumbo, A. Zacchei, B. Altieri, B. Camacho Quevedo, B. Gillis, B. Joachimi, B. Kubik, C. Baccigalupi, C. Burigana, C. Carbone, C. C. Kirkpatrick, C. Colodro-Conde, C. Garc\'ia-Garc\'ia, C. Giocoli, C. J. A. P. Martins, C. M. Gutierrez, C. Moretti, C. Neissner, C. Oliveri, C. Padilla, C. Pattison, C. S. Carvalho, C. Sirignano, C. Tao, C. Uhlemann, C. Valieri, D. Bertacca, D. B. Sanders, D. Eisenstein, D. Karagiannis, D. Paoletti, D. Potter, D. Sapone, D. Sciotti, D. Tavagnacco, E. Aubourg, E. Bozzo, E. Branchini, E. Franceschi, E. Gaztanaga, E. J. Gonzalez, E. Maragliano, E. Medinaceli, E. Merlin, E. Romelli, E. Sefusatti, E. Sellentin, E. Sihvola, Euclid Collaboration: E. Sarpa, E. Zucca, F. Atrio-Barandela, F. Beutler, F. Caro, F. Cogato, F. Courbin, F. De Paolis, F. Dubath, F. Faustini, F. Finelli, F. Giacomini, F. Gianotti, F. Grupp, F. Hormuth, F. J. Castander, F. Leclercq, F. Lepori, F. Marulli, F. M. Zerbi, F. Pace, F. Pasian, F. Raison, F. Rizzo, F. Tarsitano, F. Torradeflot, F. Vernizzi, G. Ca\~nas-Herrera, G. Castignani, G. Congedo, G. Degni, G. De Lucia, G. Desprez, G. Fabbian, G. F. Lesci, G. Gambardella, G. Gozaliasl, G. Leroy, G. Mainetti, G. Meylan, G. Morgante, G. Parimbelli, G. Piccirilli, G. Polenta, G. Riccio, G. Rodighiero, G. Sirri, G. Testera, G. Verdoes Kleijn, G. Verza, G. W. Pratt, G. Zamorani, H. Degaudenzi, H. Hildebrandt, H. Kurki-Suonio, H. M. Courtois, H. W. Yeung, I. Lloro, I. Risso, I. Szapudi, I. T. Andika, I. Tereno, I. Tutusaus, J. A. Escartin Vigo, J. Bautista, J. Bel, J. Carretero, J. Garc\'ia-Bellido, J. Gracia-Carpio, J. G. Sorce, J. Hjorth, J. J. E. Kajava, J. Kim, J. Lesgourgues, J. Macias-Perez, J. Mart\'in-Fleitas, J. M. Diego, J. Rhodes, J. Valiviita, J. Weller, K. C. Chambers, K. Ganga, K. George, K. Jahnke, K. Kiiveri, K. Koyama, K. Naidoo, K. Paterson, K. Pedersen, K. Tanidis, L. A. Popa, L. Bazzanini, L. Blot, L. Conversi, L. C. Smith, L. Guzzo, L. Legrand, L. Maurin, L. Moscardini, L. Patrizii, L. Stanco, L. Valenziano, M. Archidiacono, M. Baldi, M. Ballardini, M. Bethermin, M. Bonici, M. Brescia, M. Calabrese, M. Castellano, M. C. Lam, M. Crocce, M. Farina, M. Frailis, M. Fumana, M. Guidi, M. Jhabvala, M. K\"archer, M. K\"ummel, M. Kunz, M. L. Brown, M. Lembo, M. Magliocchetti, M. Martinelli, M. Melchior, M. Meneghetti, M. Migliaccio, M. Miluzio, M. Moresco, M. Poncet, M. P\"ontinen, M. Radovich, M. Roncarelli, M. Sahl\'en, M. Schirmer, M. Scodeggio, M. Sereno, M. Tenti, M. Tucci, M. Viel, M. von Wietersheim-Kramsta, M. Wiesmann, M. Y. Elkhashab, N. A. Walton, N. Fourmanoit, N. Martinet, N. Mauri, N. Tessore, O. Cucciati, O. Mansutti, O. Marggraf, P. Battaglia, P. B. Lilje, P. Fosalba, P. G. Ferreira, P. Monaco, P. Schneider, P. Tallada-Cresp\'i, R. B. Metcalf, R. Cabanac, R. Farinelli, R. J. Massey, R. Maoli, R. Saglia, R. Teyssier, R. Toledo-Moreo, S. Andreon, S. Bardelli, S. Borgani, S. Bruton, S. Camera, S. Cavuoti, S. Contarini, S. Davini, S. de la Torre, S. Di Domizio, S. Escoffier, S. Ferriol, S. Galeotta, S. J. Liu, S. Kermiche, S. Kruk, S. Ligori, S. Mei, S.-M. Niemi, S. Nadathur, S. Nesseris, S. Paltani, S. Pires, S. Quai, S. Radinovi\'c, S. Sacquegna, S. Toft, S. Tosi, S. V. H. Haugan, S. Vinciguerra, T. Castro, T. de Boer, T. Gasparetto, T. I. Liaudat, T. Schrabback, T. Vassallo, V. Capobianco, V. Duret, V. Kansal, V. Lindholm, V. Pettorino, V. Scottez, W. Gillard, W. Holmes, W. J. Percival, W. Roster, X. Dupac, Y. Akrami, Y. Copin, Y. Fang, Y. Kang, Y. Wang, Z. Ghaffari, Z. Sakr

Authors on Pith no claims yet

Pith reviewed 2026-05-07 13:49 UTC · model grok-4.3

classification 🌌 astro-ph.CO
keywords baryon acoustic oscillationsdensity field reconstructionEuclid surveymock cataloguescosmological parameterstwo-point correlation functionZel'dovich approximation
0
0 comments X

The pith

Density-field reconstruction triples the figure of merit for baryon acoustic oscillation parameters in Euclid-like mocks.

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

The paper performs an end-to-end validation of the Euclid BAO analysis pipeline on mock catalogues that match the statistical properties expected for the first data release. It compares two standard reconstruction methods based on the Zel'dovich approximation and demonstrates that both deliver unbiased measurements of the BAO scale at all tested redshifts and analysis settings. The work also introduces faster computational tools for model evaluation and covariance estimation that keep the full pipeline practical. These results show reconstruction can multiply the effective information extracted from the survey by a factor of three.

Core claim

Both reconstruction schemes yield unbiased BAO measurements across all redshifts and analysis choices, including smoothing scale and fiducial cosmology. In each snapshot, reconstruction enhances the figure of merit for {Ω_m, H_0 r_s} by ∼3, equivalent to tripling the effective survey volume. Combining the four redshift bins, the improvement remains substantial, with BAO-only constraints reaching ∼10% precision on Ω_m and ∼3% on H_0 r_s.

What carries the argument

Zel'dovich-approximation density-field reconstruction implemented as RecSym and RecIso, combined with an emulator-based evaluator and semi-analytical covariance estimator.

If this is right

  • Results from RecSym and RecIso remain consistent within uncertainties across all tested settings.
  • BAO-only constraints reach approximately 10 percent precision on Ω_m and 3 percent on H_0 r_s when all four redshift bins are combined.
  • The pipeline delivers more than a 500-fold speed-up in sampling while remaining stable under fiducial-cosmology variations.
  • Unbiased BAO measurements hold independent of smoothing scale and choice of fiducial cosmology.

Where Pith is reading between the lines

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

  • The demonstrated robustness suggests the pipeline can be applied to real Euclid data with minimal further tuning.
  • Similar reconstruction gains could be tested in other large-scale structure surveys measuring the expansion history.
  • The speed-up tools open the possibility of including additional nuisance parameters or cross-correlations without prohibitive cost.
  • Extending the validation to mocks that include extra systematics beyond those modeled here would strengthen readiness for later data releases.

Load-bearing premise

The eight Euclid-like mock catalogues from each of four Flagship I snapshots accurately reproduce the expected statistical properties of the first Euclid data release, including all relevant systematics and selection effects.

What would settle it

Running the validated pipeline on actual Euclid DR1 data and obtaining biased BAO scale measurements or no improvement in the figure of merit for Ω_m and H_0 r_s would falsify the claims.

Figures

Figures reproduced from arXiv: 2605.03446 by A. Biviano, A. Blanchard, A. Boucaud, A. Calabro, A. Cappi, A. Cimatti, A. Crespi, A. D\'iaz-S\'anchez, A. Eggemeier, A. Farina, A. Finoguenov, A. Franco, A. Grazian, A. Gruppuso, A. G. S\'anchez, A. Hall, A. Hornstrup, A. H. Wright, A. Kiessling, A. M. C. Le Brun, A. Mora, A. Navarro-Alsina, A. N. Taylor, A. Pezzotta, A. Pisani, A. Pourtsidou, A. R. Cooray, A. Schneider, A. Secroun, A. Troja, A. Veropalumbo, A. Zacchei, B. Altieri, B. Camacho Quevedo, B. Gillis, B. Joachimi, B. Kubik, C. Baccigalupi, C. Burigana, C. Carbone, C. C. Kirkpatrick, C. Colodro-Conde, C. Garc\'ia-Garc\'ia, C. Giocoli, C. J. A. P. Martins, C. M. Gutierrez, C. Moretti, C. Neissner, C. Oliveri, C. Padilla, C. Pattison, C. S. Carvalho, C. Sirignano, C. Tao, C. Uhlemann, C. Valieri, D. Bertacca, D. B. Sanders, D. Eisenstein, D. Karagiannis, D. Paoletti, D. Potter, D. Sapone, D. Sciotti, D. Tavagnacco, E. Aubourg, E. Bozzo, E. Branchini, E. Franceschi, E. Gaztanaga, E. J. Gonzalez, E. Maragliano, E. Medinaceli, E. Merlin, E. Romelli, E. Sefusatti, E. Sellentin, E. Sihvola, Euclid Collaboration: E. Sarpa, E. Zucca, F. Atrio-Barandela, F. Beutler, F. Caro, F. Cogato, F. Courbin, F. De Paolis, F. Dubath, F. Faustini, F. Finelli, F. Giacomini, F. Gianotti, F. Grupp, F. Hormuth, F. J. Castander, F. Leclercq, F. Lepori, F. Marulli, F. M. Zerbi, F. Pace, F. Pasian, F. Raison, F. Rizzo, F. Tarsitano, F. Torradeflot, F. Vernizzi, G. Ca\~nas-Herrera, G. Castignani, G. Congedo, G. Degni, G. De Lucia, G. Desprez, G. Fabbian, G. F. Lesci, G. Gambardella, G. Gozaliasl, G. Leroy, G. Mainetti, G. Meylan, G. Morgante, G. Parimbelli, G. Piccirilli, G. Polenta, G. Riccio, G. Rodighiero, G. Sirri, G. Testera, G. Verdoes Kleijn, G. Verza, G. W. Pratt, G. Zamorani, H. Degaudenzi, H. Hildebrandt, H. Kurki-Suonio, H. M. Courtois, H. W. Yeung, I. Lloro, I. Risso, I. Szapudi, I. T. Andika, I. Tereno, I. Tutusaus, J. A. Escartin Vigo, J. Bautista, J. Bel, J. Carretero, J. Garc\'ia-Bellido, J. Gracia-Carpio, J. G. Sorce, J. Hjorth, J. J. E. Kajava, J. Kim, J. Lesgourgues, J. Macias-Perez, J. Mart\'in-Fleitas, J. M. Diego, J. Rhodes, J. Valiviita, J. Weller, K. C. Chambers, K. Ganga, K. George, K. Jahnke, K. Kiiveri, K. Koyama, K. Naidoo, K. Paterson, K. Pedersen, K. Tanidis, L. A. Popa, L. Bazzanini, L. Blot, L. Conversi, L. C. Smith, L. Guzzo, L. Legrand, L. Maurin, L. Moscardini, L. Patrizii, L. Stanco, L. Valenziano, M. Archidiacono, M. Baldi, M. Ballardini, M. Bethermin, M. Bonici, M. Brescia, M. Calabrese, M. Castellano, M. C. Lam, M. Crocce, M. Farina, M. Frailis, M. Fumana, M. Guidi, M. Jhabvala, M. K\"archer, M. K\"ummel, M. Kunz, M. L. Brown, M. Lembo, M. Magliocchetti, M. Martinelli, M. Melchior, M. Meneghetti, M. Migliaccio, M. Miluzio, M. Moresco, M. Poncet, M. P\"ontinen, M. Radovich, M. Roncarelli, M. Sahl\'en, M. Schirmer, M. Scodeggio, M. Sereno, M. Tenti, M. Tucci, M. Viel, M. von Wietersheim-Kramsta, M. Wiesmann, M. Y. Elkhashab, N. A. Walton, N. Fourmanoit, N. Martinet, N. Mauri, N. Tessore, O. Cucciati, O. Mansutti, O. Marggraf, P. Battaglia, P. B. Lilje, P. Fosalba, P. G. Ferreira, P. Monaco, P. Schneider, P. Tallada-Cresp\'i, R. B. Metcalf, R. Cabanac, R. Farinelli, R. J. Massey, R. Maoli, R. Saglia, R. Teyssier, R. Toledo-Moreo, S. Andreon, S. Bardelli, S. Borgani, S. Bruton, S. Camera, S. Cavuoti, S. Contarini, S. Davini, S. de la Torre, S. Di Domizio, S. Escoffier, S. Ferriol, S. Galeotta, S. J. Liu, S. Kermiche, S. Kruk, S. Ligori, S. Mei, S.-M. Niemi, S. Nadathur, S. Nesseris, S. Paltani, S. Pires, S. Quai, S. Radinovi\'c, S. Sacquegna, S. Toft, S. Tosi, S. V. H. Haugan, S. Vinciguerra, T. Castro, T. de Boer, T. Gasparetto, T. I. Liaudat, T. Schrabback, T. Vassallo, V. Capobianco, V. Duret, V. Kansal, V. Lindholm, V. Pettorino, V. Scottez, W. Gillard, W. Holmes, W. J. Percival, W. Roster, X. Dupac, Y. Akrami, Y. Copin, Y. Fang, Y. Kang, Y. Wang, Z. Ghaffari, Z. Sakr.

Figure 1
Figure 1. Figure 1: demonstrates the impact of the smoothing scale Rs on the reconstructed power spectrum. As Rs varies, the rel￾ative amplitude of the reconstruction transfer function DZA(k) changes, affecting the recovery of BAO features. An optimal value, Rs,opt = 8.4 h −1 Mpc, emerges that best approaches the linear prediction by balancing noise suppression with minimal loss of physical information. However, Eq. (16) show… view at source ↗
Figure 2
Figure 2. Figure 2: Mean reconstructed galaxy-displacement amplitude as a func￾tion of the mesh resolution Ncell for three smoothing choices given by Rs = 0 h −1 Mpc (yellow), Rs = Ropt (light blue), and Rs = Req (blue), expressed in units of h −1 Mpc. Solid lines show results at z = 0.9, while dotted lines correspond to z = 1.8. Shaded bands, shown only for the case of z = 0.9 for visual clarity, represent the sample standar… view at source ↗
Figure 3
Figure 3. Figure 3: Normalised residuals of the theoretical (magenta, dashed) and BeXiCov (blue, dot-dashed) models with respect to the mean 2PCF multipoles at z = 0.9. The leftmost column shows PreRec, the middle RecSym, and RecIso is presented in the rightmost column. Residuals are computed as ∆ℓ = (ξ model ℓ − ξ data ℓ )/(σ data ℓ / √ Nmocks) with Nmocks = 8 and shaded bands indicate |∆ℓ | = 1 as well as |∆ℓ | = 2 view at source ↗
Figure 4
Figure 4. Figure 4: Mean values of the χ 2 red from fits to the 2PCF multipoles, av￾eraged over eight realisations at z = {0.9, 1.2, 1.5, 1.8}. Magenta cir￾cles (dashed line) denote the non-iterated theory covariance, while blue squares (dot-dashed) refer to the iterative BeXiCov+WinCov covariance. Panels in order from top to bottom present PreRec, RecSym, and Re￾cIso, respectively. Grey bands indicate the acceptance regions … view at source ↗
Figure 5
Figure 5. Figure 5: Impact of the smoothing scale Rs on RecSym at z = 0.9. Coloured lines show the mean monopole (top panel), quadrupole (mid￾dle panel), and hexadecapole (bottom panel) of the reconstructed 2PCF, averaged over eight sub-boxes. Different colours correspond to different Rs (expressed in units of h −1 Mpc). Shaded bands, shown only for the case of PreRec and Rs = 15h −1 Mpc for visual clarity, indicate the stan￾… view at source ↗
Figure 7
Figure 7. Figure 7: Effect of the smoothing scale Rs on post-reconstruction BAO fits at z = 0.9. Purple dashed and light-blue dot-dashed lines correspond to RecSym and RecIso, respectively. From top to bottom, the panels show the mean χ 2 red, averaged over the eight realisations at fixed Rs , the mean values of α∥ and α⊥, and their profile-likelihood uncertainties. Error bars indicate the standard deviation across the eight … view at source ↗
Figure 9
Figure 9. Figure 9: Impact of the fiducial cosmology on BAO constraints at z = 0.9. Posterior contours show the 68% and 95% credible regions in ∆α∥ and ∆α⊥, after subtracting the deterministic AP remapping. Colours refer to three fiducial cosmologies encoded also with different linestyles, where solid corresponds to Ωfid m , dashed to Ωlower m , and dotted to Ω upper m . fixed Rs 8 . The χ 2 red values remain within the stati… view at source ↗
Figure 10
Figure 10. Figure 10: Posterior constraints on Ωm and H0rs for pre-reconstruction (left), RecSym (middle), and RecIso (right). Coloured contours refer to the 68% and 95% credible regions for z ∈ {0.9, 1.2, 1.5, 1.8} and black curves show the combined constraints (assuming independence). Grey dashed lines denote the mock fiducial values of Ωm = 0.319 and H0rs = 98.6 × 100 km s−1 view at source ↗
read the original abstract

We present the first end-to-end validation of the Euclid baryon acoustic oscillation (BAO) analysis pipeline, encompassing density-field reconstruction, two-point correlation function measurement, and cosmological-parameter inference. Using eight Euclid-like mock catalogues from each of four Flagship I snapshots, designed to reproduce the expected statistical properties of the first Euclid data release (DR1), we assess the two standard BAO reconstruction methods based on the Zel'dovich approximation, RecSym and RecIso, across $0.9 \leq z \leq 1.8$. The pipeline introduces several methodological advances: an emulator-based model evaluator (Bora.jl) combined with a Hamiltonian Monte Carlo sampler (NUTS), achieving more than a 500-fold speed-up relative to standard Markov chain Monte Carlo, and a semi-analytical covariance estimator (BeXiCov+WinCov) that enables robust error estimates from only eight mock realisations while remaining stable under fiducial-cosmology variations. These components ensure computational efficiency while reducing the risk of underestimating parameter uncertainties. Both reconstruction schemes yield unbiased BAO measurements across all redshifts and analysis choices, including smoothing scale and fiducial cosmology. In each snapshot, reconstruction enhances the figure of merit for $\{\Omega_m, H_0 r_s\}$ by $\sim3$, equivalent to tripling the effective survey volume. Combining the four redshift bins, the improvement remains substantial, with BAO-only constraints reaching $\sim10\%$ precision on $\Omega_m$ and $\sim3\%$ on $H_0 r_s$. Results from RecSym and RecIso are consistent within uncertainties, though we recommend RecSym during testing due to its lower sensitivity to covariance variations. These findings establish the accuracy, robustness, and scalability of the Euclid BAO pipeline for DR1, providing a solid foundation for future cosmological analyses.

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

2 major / 3 minor

Summary. The manuscript presents the first end-to-end validation of the Euclid BAO analysis pipeline, including density-field reconstruction (RecSym and RecIso), two-point correlation function measurement, and cosmological parameter inference. Using eight Euclid-like mock catalogs from each of four Flagship I snapshots designed to match DR1 statistical properties, it demonstrates unbiased BAO scale recovery across redshifts 0.9 ≤ z ≤ 1.8, smoothing scales, and fiducial cosmologies. Methodological advances include the Bora.jl emulator with NUTS HMC sampler (>500× speedup) and the BeXiCov+WinCov semi-analytical covariance estimator stable with only eight realizations. Reconstruction improves the FoM for {Ω_m, H_0 r_s} by a factor of ~3 per snapshot (equivalent to tripling effective volume), with combined bins yielding ~10% precision on Ω_m and ~3% on H_0 r_s; RecSym is recommended for lower covariance sensitivity.

Significance. If the central claims hold, this work provides a critical foundation for Euclid DR1 BAO analyses by establishing pipeline accuracy, robustness to analysis choices, and substantial efficiency gains from the emulator and covariance tools. The reported FoM improvement quantifies the value of reconstruction for maximizing cosmological return from the survey volume. The methodological contributions (Bora.jl and BeXiCov+WinCov) are reusable beyond Euclid and address practical challenges of limited mocks and computational cost in large-scale structure analyses.

major comments (2)
  1. [Abstract and mock validation sections] The central claims of unbiased BAO recovery and ~3× FoM gain rest on the assumption that the eight Flagship I mocks per snapshot fully capture DR1 systematics (photometric redshift scatter, survey mask, selection function, scale-dependent bias). The abstract states the mocks are 'designed to reproduce the expected statistical properties,' but no quantitative fidelity tests or residual mismatch assessments appear in the validation sections; this is load-bearing because any unmodeled systematics would invalidate the lack-of-bias conclusion when applied to real data.
  2. [Covariance estimator description] The stability of the BeXiCov+WinCov estimator under fiducial-cosmology variations is asserted to enable robust errors from only eight realizations, yet the manuscript provides no explicit equations or tabulated tests quantifying how the semi-analytical terms respond to cosmology shifts or how they compare to direct mock covariances beyond the reported parameter uncertainties.
minor comments (3)
  1. [Figures] Figure captions and axis labels for the FoM and BAO scale plots could be expanded to explicitly state the smoothing scales and fiducial cosmologies used in each panel for easier cross-reference with the text.
  2. [Methods] The speed-up factor of >500 for Bora.jl + NUTS is stated in the abstract; a brief comparison table in the methods section showing wall-clock times versus standard MCMC on the same hardware would strengthen the claim.
  3. [Discussion] A short discussion of how the pipeline would adapt to the full Euclid survey mask and photometric redshift uncertainties (beyond the mocks) would help readers assess readiness for DR1.

Simulated Author's Rebuttal

2 responses · 0 unresolved

We thank the referee for their careful reading and constructive comments, which have helped us improve the clarity and completeness of the manuscript. We provide point-by-point responses to the major comments below.

read point-by-point responses

  1. Referee: [Abstract and mock validation sections] The central claims of unbiased BAO recovery and ~3× FoM gain rest on the assumption that the eight Flagship I mocks per snapshot fully capture DR1 systematics (photometric redshift scatter, survey mask, selection function, scale-dependent bias). The abstract states the mocks are 'designed to reproduce the expected statistical properties,' but no quantitative fidelity tests or residual mismatch assessments appear in the validation sections; this is load-bearing because any unmodeled systematics would invalidate the lack-of-bias conclusion when applied to real data.

    Authors: We agree that explicit demonstration of mock fidelity is important for linking the pipeline validation to real DR1 data. The mocks incorporate the main DR1-like systematics (photometric redshift scatter, survey mask, selection function, and scale-dependent bias) by construction from the Flagship I simulation, as described in the mock generation section. The primary focus of this work is end-to-end validation of the BAO pipeline within this controlled mock framework, where we demonstrate unbiased recovery and FoM gains. To address the referee's concern, we will add a new subsection summarizing quantitative fidelity metrics (e.g., comparisons of redshift distributions, clustering amplitude, and mask effects) and any noted residuals, with references to the mock construction details. We will also clarify that the lack-of-bias result holds for these mocks and that real-data validation will include additional checks. This is a partial revision that strengthens the manuscript without changing the core results. revision: partial

  2. Referee: [Covariance estimator description] The stability of the BeXiCov+WinCov estimator under fiducial-cosmology variations is asserted to enable robust errors from only eight realizations, yet the manuscript provides no explicit equations or tabulated tests quantifying how the semi-analytical terms respond to cosmology shifts or how they compare to direct mock covariances beyond the reported parameter uncertainties.

    Authors: We thank the referee for noting the need for greater transparency on the covariance estimator. In the revised manuscript we will insert the explicit equations defining the BeXiCov and WinCov terms, including how the semi-analytical contributions are combined with the window-function corrections. We will also add a table (or supplementary figure) that directly compares the semi-analytical covariance to the sample covariance computed from the eight mocks, evaluated at both the fiducial cosmology and at shifted cosmological parameters. This will quantify the response to cosmology variations and confirm stability with limited realizations. These additions make the methodological contribution more self-contained and reproducible. revision: yes

Circularity Check

0 steps flagged

No significant circularity in BAO validation or pipeline claims

full rationale

The paper validates its reconstruction methods (RecSym, RecIso) and inference pipeline by applying them to external Flagship I mock catalogs and comparing recovered BAO scales and FoM directly to the mocks' known input cosmology. No derivation steps, equations, or self-citations reduce the reported unbiased measurements or ~3x FoM gain to quantities fitted from the same data or to prior self-referential results. The methodological additions (Bora.jl emulator, NUTS sampler, BeXiCov+WinCov covariance) are presented as independent computational tools. Reliance on mocks reproducing DR1 properties is an external modeling assumption rather than an internal definitional loop or fitted-input prediction. The derivation chain remains self-contained against the provided benchmarks.

Axiom & Free-Parameter Ledger

2 free parameters · 1 axioms · 0 invented entities

The work rests on standard cosmological assumptions and the realism of Flagship mocks; no new physical entities are postulated.

free parameters (2)
  • smoothing scale
    Tested across multiple values in reconstruction step
  • fiducial cosmology
    Varied to check stability of covariance estimator
axioms (1)
  • domain assumption Zel'dovich approximation accurately captures large-scale displacement field for BAO reconstruction
    Invoked for both RecSym and RecIso methods

pith-pipeline@v0.9.0 · 7322 in / 1365 out tokens · 68652 ms · 2026-05-07T13:49:38.248192+00:00 · methodology

Review history (2 revisions) →

discussion (0)

Sign in with ORCID, Apple, or X to comment. Anyone can read and Pith papers without signing in.

Reference graph

Works this paper leans on

299 extracted references · 237 canonical work pages · 16 internal anchors

  1. [1]

    A&A, in press (Euclid Q1 SI),

    Euclid: Quick Data Release (Q1) -- The connection between galaxy close encounters and radio activity. A&A, in press (Euclid Q1 SI),

  2. [2]

    A&A, in press (Euclid Q1 SI),

    Euclid: Quick Data Release (Q1) – Secondary nuclei in early-type galaxies. A&A, in press (Euclid Q1 SI),

  3. [3]

    Euclid Quick Data Release (Q1). XXXVII. Searching for giant gravitational arcs in galaxy clusters with mask region-based convolutional neural networks. A&A, in press,

  4. [4]

    Quenching precedes bulge formation in dense environments but follows it in the field

    Euclid Quick Data Release (Q1). Quenching precedes bulge formation in dense environments but follows it in the field. A&A, in press (Euclid Q1 SI),

  5. [5]

    The average far-infrared properties of Euclid-selected star-forming galaxies

    Euclid Quick Data Release (Q1). The average far-infrared properties of Euclid-selected star-forming galaxies. A&A, in press (Euclid Q1 SI),

  6. [6]

    Spectroscopic unveiling of highly ionised lines at z = 2.48--3.88

    Euclid Quick Data Release (Q1). Spectroscopic unveiling of highly ionised lines at z = 2.48--3.88. A&A, submitted (Euclid Q1 SI) , keywords =

  7. [7]

    Hunting for luminous z > 6 galaxies in the Euclid Deep Fields – forecasts and first bright detections

    Euclid Quick Data Release (Q1). Hunting for luminous z > 6 galaxies in the Euclid Deep Fields – forecasts and first bright detections. A&A, in press (Euclid Q1 SI),

  8. [8]

    A&A, accepted (Euclid Q1 SI) , keywords =

    Euclid Quick Data Release (Q1) - Data release overview. A&A, accepted (Euclid Q1 SI) , keywords =

  9. [9]

    A&A, in press (Euclid Q1 SI),

    Euclid Quick Data Release (Q1): VIS processing and data products. A&A, in press (Euclid Q1 SI),

  10. [10]

    NIR processing and data products

    Euclid Quick Data Release (Q1). NIR processing and data products. A&A, in press (Euclid Q1 SI),

  11. [11]

    From images to multiwavelength catalogues: the Euclid MERge Processing Function

    Euclid Quick Data Release (Q1). From images to multiwavelength catalogues: the Euclid MERge Processing Function. A&A, in press (Euclid Q1 SI),

  12. [12]

    Photometric redshifts and physical properties of galaxies through the PHZ processing function

    Euclid Quick Data Release (Q1). Photometric redshifts and physical properties of galaxies through the PHZ processing function. A&A, in press (Euclid Q1 SI),

  13. [13]

    A&A, in press (Euclid Q1 SI),

    Euclid Quick Data Release (Q1): From spectrograms to spectra: the SIR spectroscopic Processing Function. A&A, in press (Euclid Q1 SI),

  14. [14]

    A&A, in press (Euclid Q1 SI),

    Euclid Quick Data Release (Q1) - Characteristics and limitations of the spectroscopic measurements. A&A, in press (Euclid Q1 SI),

  15. [15]

    Exploring galaxy morphology across cosmic time through Sersic fits

    Euclid Quick Data Release (Q1). Exploring galaxy morphology across cosmic time through Sersic fits. A&A, in press (Euclid Q1 SI),

  16. [16]

    A&A, accepted (Euclid Q1 SI) , keywords =

    Euclid Quick Data Release (Q1): First visual morphology catalogue. A&A, accepted (Euclid Q1 SI) , keywords =

  17. [17]

    A&A, in press (Euclid Q1 SI),

    Euclid Quick Data Release (Q1), A first look at the fraction of bars in massive galaxies at z<1. A&A, in press (Euclid Q1 SI),

  18. [18]

    A&A, in press (Euclid Q1 SI),

    Euclid Quick Data Release (Q1) Exploring galaxy properties with a multi-modal foundation model. A&A, in press (Euclid Q1 SI),

  19. [19]

    A&A, accepted , keywords =

    Euclid Quick Data Release (Q1): The evolution of the passive-density and morphology-density relations between z=0.25 and z=1. A&A, accepted , keywords =

  20. [20]

    A first view of the star-forming main sequence in the Euclid Deep Fields

    Euclid Quick Data Release (Q1). A first view of the star-forming main sequence in the Euclid Deep Fields. A&A, in press (Euclid Q1 SI),

  21. [21]

    A probabilistic classification of quenched galaxies

    Euclid Quick Data Release (Q1). A probabilistic classification of quenched galaxies. A&A, in press (Euclid Q1 SI),

  22. [22]

    Optical and near-infrared identification and classification of point-like X-ray selected sources

    Euclid Quick Data Release (Q1). Optical and near-infrared identification and classification of point-like X-ray selected sources. A&A, in press (Euclid Q1 SI),

  23. [23]

    A&A, in press (Euclid Q1 SI),

    Euclid Quick Data Release (Q1) -- First Euclid statistical study of galaxy mergers and their connection to active galactic nuclei. A&A, in press (Euclid Q1 SI),

  24. [24]

    First Euclid statistical study of the active galactic nuclei contribution fraction

    Euclid Quick Data Release (Q1). First Euclid statistical study of the active galactic nuclei contribution fraction. A&A, in press (Euclid Q1 SI),

  25. [25]

    A&A, in press (Euclid Q1 SI),

    Euclid Quick Data Release (Q1) First study of red quasars selection. A&A, in press (Euclid Q1 SI),

  26. [26]

    The active galaxies of Euclid

    Euclid Quick Data Release (Q1). The active galaxies of Euclid. A&A, in press (Euclid Q1 SI),

  27. [27]

    Euclid Quick Data Release (Q1): Euclid spectroscopy of QSOs. 1. Identification and redshift determination of 3500 bright QSOs. A&A, in press,. doi:10.48550/arXiv.2512.08803 , archivePrefix =. 2512.08803 , primaryClass =

    work page doi:10.48550/arxiv.2512.08803

  28. [28]

    Active galactic nuclei identification using diffusion-based inpainting of Euclid VIS images

    Euclid Quick Data Release (Q1). Active galactic nuclei identification using diffusion-based inpainting of Euclid VIS images. A&A, in press (Euclid Q1 SI),

  29. [29]

    An investigation of optically faint, red objects in the Euclid Deep Fields

    Euclid Quick Data Release (Q1). An investigation of optically faint, red objects in the Euclid Deep Fields. A&A, in press (Euclid Q1 SI),

  30. [30]

    Extending the quest for little red dots to z<4

    Euclid Quick Data Release (Q1). Extending the quest for little red dots to z<4. A&A, in press (Euclid Q1 SI),

  31. [31]

    arXiv e-prints , keywords =

    Euclid Quick Data Release (Q1): Identification of massive galaxy candidates at the end of the Epoch of Reionisation. A&A, submitted (Euclid Q1 SI) , keywords =. doi:10.48550/arXiv.2511.11943 , archivePrefix =. 2511.11943 , primaryClass =

    work page doi:10.48550/arxiv.2511.11943

  32. [32]

    A&A, accepted (Euclid Q1 SI) , keywords =

    Euclid Quick Data Release (Q1): The Strong Lensing Discovery Engine A -- System overview and lens catalogue. A&A, accepted (Euclid Q1 SI) , keywords =

  33. [33]

    A&A, in press (Euclid Q1 SI),

    Euclid Quick Data Release (Q1) The Strong Lensing Discovery Engine B -- Early strong lens candidates from visual inspection of high velocity dispersion galaxies. A&A, in press (Euclid Q1 SI),

  34. [34]

    The Strong Lensing Discovery Engine C -- Finding lenses with machine learning

    Euclid Quick Data Release (Q1). The Strong Lensing Discovery Engine C -- Finding lenses with machine learning. A&A, in press (Euclid Q1 SI),

  35. [35]

    The Strong Lensing Discovery Engine D -- Double-source-plane lens candidates

    Euclid Quick Data Release (Q1). The Strong Lensing Discovery Engine D -- Double-source-plane lens candidates. A&A, in press (Euclid Q1 SI),

  36. [36]

    The Strong Lensing Discovery Engine E - Ensemble classification of strong gravitational lenses: lessons for Data Release 1

    Euclid Quick Data Release (Q1). The Strong Lensing Discovery Engine E - Ensemble classification of strong gravitational lenses: lessons for Data Release 1. A&A, accepted (Euclid Q1 SI) , keywords =

  37. [37]

    LEMON -- Lens Modelling with Neural networks

    Euclid Quick Data Release (Q1). LEMON -- Lens Modelling with Neural networks. Automated and fast modelling of Euclid gravitational lenses with a singular isothermal ellipsoid mass profile. A&A, in press (Euclid Q1 SI),

  38. [38]

    From simulations to sky: Advancing machine-learning lens detection with real Euclid data

    Euclid Quick Data Release (Q1). From simulations to sky: Advancing machine-learning lens detection with real Euclid data. A&A, in press (Euclid Q1 SI),. doi:10.48550/arXiv.2512.05899 , archivePrefix =. 2512.05899 , primaryClass =

    work page doi:10.48550/arxiv.2512.05899

  39. [39]

    The first catalogue of strong-lensing galaxy clusters

    Euclid Quick Data Release (Q1). The first catalogue of strong-lensing galaxy clusters. A&A, in press (Euclid Q1 SI),

  40. [40]

    Combined and galaxy density catalogues at z> 1.3 and detection of significant passive galaxy overdensities in overdense regions

    Euclid Quick Data Release (Q1). Combined and galaxy density catalogues at z> 1.3 and detection of significant passive galaxy overdensities in overdense regions. A&A, submitted (Euclid Q1 SI) , keywords =

  41. [41]

    The Euclid view on Planck galaxy protocluster candidates: towards a probe of the highest sites of star formation at cosmic noon

    Euclid Quick Data Release (Q1). The Euclid view on Planck galaxy protocluster candidates: towards a probe of the highest sites of star formation at cosmic noon. A&A, submitted (Euclid Q1 SI) , keywords =. doi:10.48550/arXiv.2503.21304 , archivePrefix =. 2503.21304 , primaryClass =

    work page doi:10.48550/arxiv.2503.21304

  42. [42]

    First detections from the galaxy cluster workflow

    Euclid Quick Data Release (Q1). First detections from the galaxy cluster workflow. A&A, in press (Euclid Q1 SI),. doi:10.48550/arXiv.2503.19196 , archivePrefix =. 2503.19196 , primaryClass =

    work page doi:10.48550/arxiv.2503.19196

  43. [43]

    A&A, submittted (Euclid Q1 SI) , keywords =

    EMU and Euclid: Detection of a radio-optical galaxy clustering cross-correlation signal between the Evolutionary Map of the Universe and Euclid. A&A, submittted (Euclid Q1 SI) , keywords =. doi:10.48550/arXiv.2511.22732 , archivePrefix =. 2511.22732 , primaryClass =

    work page doi:10.48550/arxiv.2511.22732

  44. [44]

    The role of cosmic connectivity in shaping galaxy clusters

    Euclid Quick Data Release (Q1). The role of cosmic connectivity in shaping galaxy clusters. A&A, in press (Euclid Q1 SI),

  45. [45]

    Galaxy shapes and alignments in the cosmic web

    Euclid Quick Data Release (Q1). Galaxy shapes and alignments in the cosmic web. A&A, in press (Euclid Q1 SI),

  46. [46]

    A&A, in press (Euclid Q1 SI),

    Euclid Quick Data Release (Q1): A photometric search for ultracool dwarfs in the Euclid Deep Fields. A&A, in press (Euclid Q1 SI),

  47. [47]

    A&A, submitted (Euclid Q1 SI) , keywords =

    Euclid Quick Data Release (Q1) -- Spectroscopic search, classification and analysis of ultracool dwarfs in the Deep Fields. A&A, submitted (Euclid Q1 SI) , keywords =

  48. [48]

    A&A, submitted (Euclid Q1 SI) , keywords =

    Euclid Quick Data Release (Q1) Ultracool dwarfs in the Euclid Deep Field North. A&A, submitted (Euclid Q1 SI) , keywords =

  49. [49]

    A&A, in press (Euclid Q1 SI),

    Euclid: Quick Data Release (Q1) - Photometric studies of known transients. A&A, in press (Euclid Q1 SI),

  50. [50]

    A census of dwarf galaxies across a range of distances and environments

    Euclid Quick Data Release (Q1). A census of dwarf galaxies across a range of distances and environments. A&A, in press (Euclid Q1 SI),

  51. [51]

    Euclid Quick Data Release (Q1). AgileLens: A scalable CNN-based pipeline for strong gravitational lens identification

    Euclid Quick Data Release (Q1). AgileLens: A scalable CNN-based pipeline for strong gravitational lens identification. arXiv e-prints , keywords =. doi:10.48550/arXiv.2604.06648 , archivePrefix =. 2604.06648 , primaryClass =

    work page internal anchor Pith review Pith/arXiv arXiv doi:10.48550/arxiv.2604.06648

  52. [52]

    The Strong Lensing Discovery Engine F -- Bright and low-redshift strong lenses

    Euclid Quick Data Release (Q1). The Strong Lensing Discovery Engine F -- Bright and low-redshift strong lenses. A&A, submitted , keywords =. doi:10.48550/arXiv.2603.28580 , archivePrefix =. 2603.28580 , primaryClass =

    work page doi:10.48550/arxiv.2603.28580

  53. [53]

    and others

    Euclid - I. Overview of the Euclid mission , DOI= "10.1051/0004-6361/202450810", url= "https://doi.org/10.1051/0004-6361/202450810", journal =

    work page doi:10.1051/0004-6361/202450810

  54. [55]

    10.1051/0004-6361/202450786

    Euclid - III. The NISP Instrument , DOI= "10.1051/0004-6361/202450786", url= "https://doi.org/10.1051/0004-6361/202450786", journal =

    work page doi:10.1051/0004-6361/202450786

  55. [56]

    10.1051/0004-6361/202450345

    Euclid - IV. The NISP Calibration Unit , DOI= "10.1051/0004-6361/202450345", url= "https://doi.org/10.1051/0004-6361/202450345", journal =

    work page doi:10.1051/0004-6361/202450345

  56. [57]

    Astronomy & Astrophysics , author =

    Euclid - V. The Flagship galaxy mock catalogue: A comprehensive simulation for the Euclid , DOI= "10.1051/0004-6361/202450853", url= "https://doi.org/10.1051/0004-6361/202450853", journal =

    work page doi:10.1051/0004-6361/202450853

  57. [58]

    10.1051/0004-6361/202450803

    Euclid: Early Release Observations – Programme overview and pipeline for compact- and diffuse-emission photometry , DOI= "10.1051/0004-6361/202450803", url= "https://doi.org/10.1051/0004-6361/202450803", journal =

    work page doi:10.1051/0004-6361/202450803

  58. [59]

    10.1051/0004-6361/202450793

    Euclid: Early Release Observations – A glance at free-floating newborn planets in the σ Orionis cluster , DOI= "10.1051/0004-6361/202450793", url= "https://doi.org/10.1051/0004-6361/202450793", journal =

    work page doi:10.1051/0004-6361/202450793

  59. [60]

    10.1051/0004-6361/202449696

    Euclid: Early Release Observations – Unveiling the morphology of two Milky Way globular clusters out to their periphery , DOI= "10.1051/0004-6361/202449696", url= "https://doi.org/10.1051/0004-6361/202449696", journal =

    work page doi:10.1051/0004-6361/202449696

  60. [61]

    10.1051/0004-6361/202450781

    Euclid: Early Release Observations – Deep anatomy of nearby galaxies , DOI= "10.1051/0004-6361/202450781", url= "https://doi.org/10.1051/0004-6361/202450781", journal =

    work page doi:10.1051/0004-6361/202450781

  61. [62]

    10.1051/0004-6361/202450784

    Euclid: Early Release Observations – Globular clusters in the Fornax galaxy cluster, from dwarf galaxies to the intracluster field , DOI= "10.1051/0004-6361/202450784", url= "https://doi.org/10.1051/0004-6361/202450784", journal =

    work page doi:10.1051/0004-6361/202450784

  62. [63]

    A&A , volume =

    Euclid: Early Release Observations – Overview of the Perseus cluster and analysis of its luminosity and stellar mass functions , DOI= "10.1051/0004-6361/202450996", url= "https://doi.org/10.1051/0004-6361/202450996", journal =

    work page doi:10.1051/0004-6361/202450996

  63. [64]

    , keywords =

    Euclid: Early Release Observations – Dwarf galaxies in the Perseus galaxy cluster , DOI= "10.1051/0004-6361/202450799", url= "https://doi.org/10.1051/0004-6361/202450799", journal =

    work page doi:10.1051/0004-6361/202450799

  64. [65]

    arXiv , author =:2405.13503 , journal =

    Euclid: Early Release Observations – The intracluster light and intracluster globular clusters of the Perseus cluster , DOI= "10.1051/0004-6361/202450772", url= "https://doi.org/10.1051/0004-6361/202450772", journal =

    work page doi:10.1051/0004-6361/202450772

  65. [66]

    10.1051/0004-6361/202451868

    Euclid: The Early Release Observations Lens Search Experiment , DOI= "10.1051/0004-6361/202451868", url= "https://doi.org/10.1051/0004-6361/202451868", journal =

    work page doi:10.1051/0004-6361/202451868

  66. [67]

    10.1051/0004-6361/202450776

    Euclid: Early Release Observations – A preview of the Euclid era through a galaxy cluster magnifying lens , DOI= "10.1051/0004-6361/202450776", url= "https://doi.org/10.1051/0004-6361/202450776", journal =

    work page doi:10.1051/0004-6361/202450776

  67. [68]

    10.1051/0004-6361/202450794

    Euclid: Early Release Observations – NISP-only sources and the search for luminous z = 6–8 galaxies , DOI= "10.1051/0004-6361/202450794", url= "https://doi.org/10.1051/0004-6361/202450794", journal =

    work page doi:10.1051/0004-6361/202450794

  68. [69]

    Euclid Early Release Observations

  69. [70]

    Euclid Quick Release Q1

  70. [71]

    Euclid Quick Release Q2

  71. [72]

    Euclid Data Release 1

  72. [73]

    Space Data Management

    ESA Datalabs: Digital Innovation in Space Science. Space Data Management. Studies in Big Data , year = 2024, volume =. doi:10.1007/978-981-97-0041-7_1 , adsurl =

    work page doi:10.1007/978-981-97-0041-7_1 2024

  73. [74]

    Properties and performance of the NISP signal estimator

    Euclid. Properties and performance of the NISP signal estimator. A&A, submitted , keywords =. doi:10.48550/arXiv.2602.03574 , archivePrefix =. 2602.03574 , primaryClass =

    work page doi:10.48550/arxiv.2602.03574

  74. [75]

    A&A, submitted , keywords =

    Euclid: Galaxy SED reconstruction in the PHZ processing function: impact on the PSF and the role of medium-band filters. A&A, submitted , keywords =

  75. [76]

    NISP-P optical ghosts

    Euclid: VI. NISP-P optical ghosts. , keywords =. doi:10.1051/0004-6361/202555106 , archivePrefix =. 2507.11072 , primaryClass =

    work page doi:10.1051/0004-6361/202555106

  76. [77]

    Non-Gaussianity of 2-pt statistics likelihood: Parameter inference with a non-Gaussian likelihood in Fourier and configuration space

    Euclid preparation. Non-Gaussianity of 2-pt statistics likelihood: Parameter inference with a non-Gaussian likelihood in Fourier and configuration space. A&A, submitted , keywords =. doi:10.48550/arXiv.2604.01309 , archivePrefix =. 2604.01309 , primaryClass =

    work page doi:10.48550/arxiv.2604.01309

  77. [78]

    Impact of redshift distribution uncertainties on the joint analysis of photometric galaxy clustering and weak gravitational lensing

    Euclid preparation. Impact of redshift distribution uncertainties on the joint analysis of photometric galaxy clustering and weak gravitational lensing. A&A, submitted , keywords =. doi:10.48550/arXiv.2604.00805 , archivePrefix =. 2604.00805 , primaryClass =

    work page doi:10.48550/arxiv.2604.00805

  78. [79]

    Euclid preparation. Galaxy power spectrum and bispectrum modelling

    Euclid preparation. Galaxy power spectrum and bispectrum modelling. A&A, submitted , keywords =. doi:10.48550/arXiv.2603.27966 , archivePrefix =. 2603.27966 , primaryClass =

    work page internal anchor Pith review Pith/arXiv arXiv doi:10.48550/arxiv.2603.27966

  79. [80]

    Far-infrared predictions for Euclid galaxy catalogues: cluster, protocluster, and field

    Euclid preparation. Far-infrared predictions for Euclid galaxy catalogues: cluster, protocluster, and field. A&A, submitted , keywords =. doi:10.48550/arXiv.2603.13195 , archivePrefix =. 2603.13195 , primaryClass =

    work page doi:10.48550/arxiv.2603.13195

  80. [81]

    Simulated galaxy catalogues for non-standard cosmological models

    Euclid preparation. Simulated galaxy catalogues for non-standard cosmological models. A&A, submitted , keywords =. doi:10.48550/arXiv.2603.13148 , archivePrefix =. 2603.13148 , primaryClass =

    work page doi:10.48550/arxiv.2603.13148

Showing first 80 references.