arxiv: 2509.15890 · v2 · submitted 2025-09-19 · 🌌 astro-ph.CO

Fast and accurate Gaia-unWISE quasar mock catalogs from LPT and Eulerian bias

Francesco Sinigaglia , Francisco-Shu Kitaura , Mahlet Shiferaw , Ginevra Favole , Kate Storey-Fisher , Nestor Arsenov This is my paper

Pith reviewed 2026-05-18 15:50 UTC · model grok-4.3

classification 🌌 astro-ph.CO

keywords quasar mock catalogsLagrangian perturbation theorynonlinear biasGaia-unWISE Quaialarge-scale structurecosmological simulationsredshift spaceobservational effects

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The pith

Quasar mock catalogs generated with Lagrangian perturbation theory and hierarchical bias accurately reproduce the Gaia-unWISE Quaia catalog's summary statistics.

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

The paper presents a method to produce fast and accurate full-sky quasar mock catalogs for the Gaia-unWISE Quaia catalog. It uses dark matter fields from augmented Lagrangian perturbation theory on the lightcone and applies a hierarchical nonlocal nonlinear bias scheme calibrated on Abacus simulation mocks matched to DESI observations. Observational effects such as redshift uncertainties, angular selection, and number counts are added to the mocks. The catalogs are validated against the real data using full-sky maps, redshift distributions, angular power spectra with covariances, and two-point correlation functions, showing excellent agreement. The mocks are made publicly available for cosmological studies.

Core claim

We present 100 full-sky quasar spectrophotometric mock catalogs with smooth redshift evolution from z=0 to z~4, tailored to analyze the Gaia-unWISE Quasar Catalog (Quaia). In particular, we apply a novel hierarchical nonlocal nonlinear bias scheme (Hicobian) to dark matter fields generated through Augmented Lagrangian Perturbation Theory on the lightcone (WebON code), calibrating the free parameters of the bias model on Abacus quasar HOD mock catalogs tuned to reproduce DESI Early Data Release observations in real and redshift space. After having obtained such accurate spectroscopic catalogs, we inject in the mocks the observational effects characterizing the Quaia catalog: (i) spectrophot o

What carries the argument

Hierarchical nonlocal nonlinear bias scheme (Hicobian) applied to Augmented Lagrangian Perturbation Theory lightcone fields from the WebON code.

If this is right

The mock catalogs accurately reproduce the Quaia catalog's full-sky maps and redshift distributions.
Angular power spectra and their covariances from the mocks match those of the real data.
Two-point correlation functions in the mocks align with observations after including selection effects.
The method enables efficient production of multiple mock realizations for statistical analysis.
Public release of the catalogs supports community-wide use in quasar cosmology studies.

Where Pith is reading between the lines

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

The success of transferring the bias model suggests similar approaches could work for other large-scale structure tracers in future surveys.
This combination of fast LPT simulations with calibrated bias could scale to higher resolution or larger volumes for next-generation experiments.
Validation on power spectra implies the mocks capture the clustering properties needed for testing cosmological models.
Further development might incorporate additional effects like magnification bias for more complete mock realism.

Load-bearing premise

The hierarchical nonlocal nonlinear bias scheme calibrated on Abacus HOD mocks tuned to DESI Early Data Release observations can be transferred to WebON Augmented Lagrangian Perturbation Theory lightcone fields to produce quasar distributions that match Quaia after injecting observational effects.

What would settle it

Finding a statistically significant mismatch in the angular power spectra or two-point correlation functions between the mock catalogs and the Quaia catalog at multiple redshifts would falsify the accuracy claim.

read the original abstract

We present $100$ full-sky quasar spectrophotometric mock catalogs with smooth redshift evolution from $z=0$ to $z\sim 4$, tailored to analyze the Gaia-unWISE Quasar Catalog (Quaia). In particular, we apply a novel hierarchical nonlocal nonlinear bias scheme (Hicobian) to dark matter fields generated through Augmented Lagrangian Perturbation Theory on the lightcone (WebON code), calibrating the free parameters of the bias model on Abacus quasar HOD mock catalogs tuned to reproduce DESI Early Data Release observations in real and redshift space. After having obtained such accurate spectroscopic catalogs, we inject in the mocks the observational effects characterizing the Quaia catalog: (i) spectrophotometric redshift uncertainties, (ii) the angular selection function, and (iii) the redshift number counts distribution. We assess the accuracy of our catalogs by validating a number of summary statistics: the full-sky QSO maps, the redshift uncertainty distributions as a function of redshift, the redshift $n(z)$ distribution, the angular power spectra and their normalized covariance matrices, and the angular two-point correlation functions. We find excellent agreement between these metrics from the mocks and from the Quaia catalog. We publicly release the mock catalogs to the community.

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.

Desk Editor's Note private letter to a colleague

This delivers practical quasar mocks via LPT and Hicobian bias but the calibration transfer from N-body deserves closer inspection.

read the letter

The key takeaway is that this work produces and releases 100 full-sky quasar mock catalogs matched to the Gaia-unWISE Quaia sample using a combination of LPT simulations and a hierarchical bias model. They generate dark matter fields with Augmented Lagrangian Perturbation Theory on the lightcone via the WebON code. Then they apply the Hicobian bias scheme, with parameters calibrated from Abacus N-body HOD mocks that were tuned to DESI Early Data Release quasar clustering. After that they layer in the observational effects specific to Quaia: redshift uncertainties, angular selection function, and the redshift distribution. The checks include maps, n(z), angular power spectra and their covariances, plus angular correlation functions, all showing close agreement with the actual catalog. This approach is new in its specific application to Quaia mocks with the full set of injected effects on LPT fields. It does a good job of delivering ready-to-use catalogs that the community can download and apply to survey analysis tasks. The main concern is whether the bias calibration carries over cleanly. Since the Hicobian parameters were fit to reproduce clustering in full N-body mocks, and LPT approximations are known to underpredict some nonlinear effects on the scales relevant for angular statistics, there is a risk that the model is not perfectly suited to the WebON fields. The post-processing with selection and errors might compensate for any residual mismatches, but without a side-by-side comparison of the underlying density field clustering before those steps, it is difficult to be fully confident. That said, the reported agreements on the final statistics suggest the end result is usable. This paper targets researchers who work with quasar large-scale structure data and need mocks for testing analysis pipelines or estimating errors. It will be of interest to those developing bias models or mock generation techniques as well. I recommend sending it for peer review. The methodological details and the public data release make it worth the time for referees to evaluate the robustness of the validations.

Referee Report

2 major / 2 minor

Summary. The paper presents 100 full-sky quasar spectrophotometric mock catalogs spanning z=0 to z~4, generated by applying a hierarchical nonlocal nonlinear bias scheme (Hicobian) to dark matter fields from Augmented Lagrangian Perturbation Theory on the lightcone (WebON code). Bias parameters are calibrated on Abacus quasar HOD mocks tuned to DESI Early Data Release observations. Observational effects including spectrophotometric redshift uncertainties, angular selection function, and redshift number counts are injected to match the Gaia-unWISE Quasar Catalog (Quaia). Accuracy is assessed via full-sky maps, redshift uncertainty distributions, n(z), angular power spectra with normalized covariances, and angular two-point correlation functions, with claims of excellent agreement; the catalogs are publicly released.

Significance. If the accuracy holds, the work supplies a practical, publicly available set of mocks tailored for Quaia analyses, combining efficient LPT generation with a detailed Eulerian bias model to incorporate both structure formation and systematics. The public release of the 100 catalogs is a clear strength that supports reproducibility and community use in large-scale structure studies.

major comments (2)

[bias calibration and application section] The transfer of Hicobian bias parameters (calibrated on Abacus N-body HOD mocks tuned to DESI EDR) to WebON LPT lightcone fields is central to the accuracy claim but lacks an isolated test. LPT is known to underpredict small-scale power and higher-order correlations relative to full N-body; if the hierarchical nonlocal terms compensate for Abacus-specific nonlinearities, they may be mis-calibrated on WebON. The validation on C_ℓ and w(θ) occurs only after injecting angular selection, n(z), and redshift errors, which can mask residual mismatches (see abstract and the bias application section).
[validation section] The abstract states 'excellent agreement' on angular power spectra and covariances, but without quantitative error metrics or pre-injection comparisons to an N-body reference at fixed cosmology, it is difficult to assess whether the summary statistics fully support the central claim of faithful large-scale structure reproduction.

minor comments (2)

Clarify the exact number and range of free parameters in the Hicobian model and how they are optimized (e.g., which summary statistics are used in the fit to Abacus mocks).
Ensure all figures showing C_ℓ and w(θ) include error bars or shaded regions from the mock ensemble to allow direct visual assessment of agreement with Quaia.

Simulated Author's Rebuttal

2 responses · 0 unresolved

We thank the referee for their thorough review and constructive feedback on our manuscript. We address the major comments point by point below, providing clarifications on our methodology while indicating revisions to strengthen the presentation of the bias calibration and validation results.

read point-by-point responses

Referee: [bias calibration and application section] The transfer of Hicobian bias parameters (calibrated on Abacus N-body HOD mocks tuned to DESI EDR) to WebON LPT lightcone fields is central to the accuracy claim but lacks an isolated test. LPT is known to underpredict small-scale power and higher-order correlations relative to full N-body; if the hierarchical nonlocal terms compensate for Abacus-specific nonlinearities, they may be mis-calibrated on WebON. The validation on C_ℓ and w(θ) occurs only after injecting angular selection, n(z), and redshift errors, which can mask residual mismatches (see abstract and the bias application section).

Authors: We agree that an explicit isolated test of the bias model transfer would provide additional reassurance. The Hicobian hierarchical nonlocal nonlinear bias is formulated as an Eulerian prescription that incorporates higher-order and nonlocal terms precisely to capture clustering beyond the linear regime when applied to approximate density fields such as those from ALPT. The parameters were determined by matching the Abacus HOD mocks, which were themselves calibrated to DESI EDR clustering in real and redshift space. Because the subsequent validation demonstrates that the full pipeline (including observational effects) reproduces the Quaia summary statistics, we view the end-to-end agreement as the primary validation for the intended use of the mocks. Nevertheless, to address the concern directly, we will expand the bias application section with a new figure and accompanying text showing the angular power spectrum of the biased LPT fields prior to injection of selection and redshift errors, compared against the corresponding Abacus-based fields at the same cosmology. This will quantify any residual differences attributable to the underlying gravity solver. revision: partial
Referee: [validation section] The abstract states 'excellent agreement' on angular power spectra and covariances, but without quantitative error metrics or pre-injection comparisons to an N-body reference at fixed cosmology, it is difficult to assess whether the summary statistics fully support the central claim of faithful large-scale structure reproduction.

Authors: We accept that the phrase 'excellent agreement' would benefit from quantitative support. In the revised manuscript we will replace the qualitative statement in the abstract with explicit metrics, including the reduced chi-squared per degree of freedom for the angular power spectra (both auto- and cross-spectra) and the two-point correlation functions when comparing the mocks to Quaia. We will also report the fractional residuals and their rms values across the relevant multipole and angular-scale ranges. With respect to pre-injection comparisons against full N-body at fixed cosmology, our primary objective is to generate mocks that faithfully reproduce the observed Quaia catalog after all selection and error effects are applied; the LPT-based approach was chosen for computational efficiency to produce 100 full-sky realizations. A dedicated fixed-cosmology N-body benchmark is not part of the present study, but the added pre-injection power-spectrum comparison noted above will provide a direct check on the bias-model performance on the LPT fields themselves. revision: yes

Circularity Check

0 steps flagged

No significant circularity; validation uses independent external dataset

full rationale

The derivation chain generates DM fields via WebON LPT, applies Hicobian bias whose free parameters are calibrated on Abacus HOD mocks tuned to DESI EDR (an external survey), injects Quaia-specific observational effects, and validates summary statistics directly against the Quaia catalog. Since calibration data (DESI) and validation data (Quaia) are distinct and the LPT lightcone is generated independently, the reported agreement is a transfer test rather than a quantity forced by construction or self-definition. No self-citation load-bearing step, fitted-input-renamed-as-prediction, or ansatz-smuggled reduction appears in the abstract or described pipeline; the central claim retains independent content against external benchmarks.

Axiom & Free-Parameter Ledger

1 free parameters · 2 axioms · 0 invented entities

The central claim rests on the transferability of a bias model calibrated on one set of mocks to another simulation framework, plus standard assumptions in perturbation theory and observational modeling.

free parameters (1)

free parameters of the Hicobian bias model
Calibrated on Abacus quasar HOD mock catalogs tuned to DESI Early Data Release observations in real and redshift space.

axioms (2)

domain assumption Augmented Lagrangian Perturbation Theory on the lightcone accurately captures the dark matter field evolution relevant for quasar bias modeling up to z~4.
Invoked when generating the underlying dark matter fields with the WebON code.
domain assumption The hierarchical nonlocal nonlinear bias scheme (Hicobian) provides a sufficient description of quasar clustering from dark matter.
Central modeling choice for mapping dark matter to quasars.

pith-pipeline@v0.9.0 · 5778 in / 1552 out tokens · 45426 ms · 2026-05-18T15:50:59.404634+00:00 · methodology

discussion (0)

Forward citations

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