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arxiv: 2604.05213 · v1 · submitted 2026-04-06 · 🌌 astro-ph.CO

Recognition: no theorem link

Local primordial non-Gaussianity using cross-correlations of DESI tracers

A. J. Rosado-Mar\'in , A. J. Ross , H. Seo , E. Chaussidon , J. Aguilar , S. Ahlen , D. Bianchi , D. Brooks
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T. Claybaugh A. Cuceu A. de la Macorra A. de Mattia R. Demina B. Dey P. Doel S. Ferraro A. Font-Ribera J. E. Forero-Romero E. Gazta\~naga S. Gontcho A Gontcho G. Gutierrez C. Hahn H. K. Herrera-Alcantar D. Huterer M. Ishak R. Joyce D. Kirkby A. Kremin O. Lahav C. Lamman M. Landriau M. E. Levi M. Manera A. Meisner R. Miquel S. Nadathur J. A. Newman N. Palanque-Delabrouille W. J. Percival F. Prada I. P\'erez-R\`afols G. Rossi E. Sanchez D. Schlegel J. Silber G. Tarl\'e B. A. Weaver C. Zhao H. Zou
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Pith reviewed 2026-05-10 18:48 UTC · model grok-4.3

classification 🌌 astro-ph.CO
keywords primordial non-GaussianityDESI surveylarge-scale structuregalaxy clusteringcross-correlationsinflation tests
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The pith

Cross-correlations between DESI large red galaxies and quasars tighten the bound on local primordial non-Gaussianity by about nine percent.

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

The paper combines auto- and cross-correlations of DESI DR1 tracers including LRGs, QSOs, and ELGs across redshifts 0.8 to 3.1 to measure the amplitude of local primordial non-Gaussianity. The central strategy is to use cross-correlations to cross-validate the signal and reduce the effect of systematics that do not affect every tracer the same way. This yields a modestly improved constraint compared with auto-correlations alone. A reader would care because the size of local non-Gaussianity directly tests whether the very early universe underwent the simplest form of inflation.

Core claim

The cross-correlation between LRG and quasar tracers improves the DESI DR1 constraint on local primordial non-Gaussianity to f^loc_NL = 2.1 with uncertainties from -8.3 to +8.8 at 68 percent , a gain of roughly nine percent; including the ELG sample produces no clear further improvement, consistent with the modest additional gain predicted by mocks.

What carries the argument

The joint analysis of auto- and cross-power spectra of multiple tracers, which exploits the fact that cross-correlations are less vulnerable to systematics unique to any single sample.

If this is right

  • The measured central value near zero remains compatible with the simplest single-field inflation models.
  • Mock forecasts indicate that the same cross-correlation approach can deliver an extra eight percent tightening once statistical errors decrease.
  • The lack of improvement from ELGs in current data highlights the need to control tracer-specific systematics before including them in future analyses.
  • The method provides a template for cross-validating f^loc_NL measurements across independent galaxy samples in the same volume.

Where Pith is reading between the lines

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

  • The same cross-correlation strategy could be applied to other ongoing or future surveys such as Euclid or Roman to obtain independent checks on the same parameter.
  • If the central value stays near zero while errors shrink below a few units, single-field slow-roll inflation would be increasingly favored over multi-field alternatives.
  • Extending the redshift range or adding more tracer types might reveal whether any scale- or redshift-dependent non-Gaussianity is present.

Load-bearing premise

Cross-correlations between LRG and QSO tracers are less susceptible to non-common systematics than the auto-correlations of either sample.

What would settle it

If a future larger DESI data set produces an f^loc_NL value from the LRG-QSO cross-correlation that lies well outside the current error bars while the auto-correlation results remain consistent with earlier measurements, the claimed robustness gain would be falsified.

read the original abstract

We constrain local primordial non-Gaussianity by a combined analysis of auto and cross-correlations of DESI DR1 tracers, leveraging LRGs and QSOs as well as ELGs between $0.8<z<3.1$. By cross-validating the signal across different clustering tracers within the same redshift range, we evaluate potential systematics in the $f^\mathrm{loc}_\mathrm{NL}$ measurements, capitalizing on the reduced susceptibility of cross-correlations to non-common systematics. We find that the cross-correlation between LRG and quasars can robustly improve the DESI DR1 $f^\mathrm{loc}_\mathrm{NL}$ constraints, by $\sim9\%$ to a measurement of $f^\mathrm{loc}_\mathrm{NL}=2.1_{-8.3}^{+8.8}$ at 68\% confidence. On the other hand, we do not find a clear improvement when including the DESI DR1 ELG sample. Mock tests predict an additional $\sim8\%$ gain with statistical scatter, and the lack of improvement in the data remains consistent with this expectation. This project serves as an exploratory analysis of DESI ELG clustering for $f^\mathrm{loc}_\mathrm{NL}$ through its cross-correlation in preparation for future DESI data 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

3 major / 2 minor

Summary. The paper claims that a combined analysis of auto- and cross-correlations among DESI DR1 tracers (LRGs, QSOs, ELGs over 0.8<z<3.1) yields a constraint on local primordial non-Gaussianity of f_NL^loc = 2.1_{-8.3}^{+8.8} at 68% CL, with the LRG-QSO cross-correlation providing a ~9% tightening relative to auto-correlations alone; no further improvement is found when adding ELGs, consistent with mock predictions. The analysis emphasizes cross-validation across tracers to mitigate non-common systematics.

Significance. If the result holds, the work illustrates the practical benefit of multi-tracer cross-correlations for tightening f_NL^loc bounds in DESI-scale surveys and provides a template for future analyses. Explicit mock-based forecasts and cross-tracer validation are strengths that enhance credibility.

major comments (3)
  1. [Results] Results section (and abstract): the headline claim of a robust ~9% improvement from the LRG-QSO cross-correlation rests on the unverified premise that non-common systematics dominate auto-correlation variance and cancel in the cross; no quantitative test (residual maps, depth-variation mocks, or fiber-assignment simulations) is supplied to show shared systematics are sub-dominant, which is load-bearing for interpreting the observed tightening as systematic cancellation rather than a statistical fluctuation in a low-signal regime.
  2. [Methods] Methods section: the manuscript provides no explicit error budget, covariance matrix construction details, or validation checks on redshift distributions and bias modeling for the joint auto+cross analysis, preventing independent assessment of the reported f_NL^loc constraint and its uncertainties.
  3. [Mock tests] Mock tests paragraph: while mocks are said to predict an additional ~8% gain with statistical scatter, the text does not present the mock results explicitly or incorporate realistic DESI DR1 systematics, leaving open whether the data outcome is distinguishable from chance in the reported error regime of ~8.5.
minor comments (2)
  1. [Abstract] Abstract: the phrasing 'cross-validating the signal across different clustering tracers within the same redshift range' is vague on which exact pairs and redshift bins are used; a brief enumeration would improve clarity.
  2. [Notation] Notation: f^loc_NL and f_NL^loc appear interchangeably; adopt a single consistent form throughout the manuscript.

Simulated Author's Rebuttal

3 responses · 0 unresolved

We thank the referee for their constructive and detailed report. The comments highlight areas where additional clarity and supporting material will strengthen the manuscript. We address each major comment below and indicate the revisions we will make.

read point-by-point responses

  1. Referee: [Results] Results section (and abstract): the headline claim of a robust ~9% improvement from the LRG-QSO cross-correlation rests on the unverified premise that non-common systematics dominate auto-correlation variance and cancel in the cross; no quantitative test (residual maps, depth-variation mocks, or fiber-assignment simulations) is supplied to show shared systematics are sub-dominant, which is load-bearing for interpreting the observed tightening as systematic cancellation rather than a statistical fluctuation in a low-signal regime.

    Authors: We agree that a direct quantitative demonstration of systematic cancellation would provide stronger support for interpreting the observed tightening. The analysis is grounded in the standard expectation from multi-tracer theory that cross-correlations suppress tracer-specific (non-common) systematics, which is why we emphasize cross-validation across tracers. The measured ~9% improvement is consistent with the scatter seen in our mocks. In the revised manuscript we will (i) tone down the wording in the abstract and Results from “robustly improve” to “provides an improvement consistent with expectations,” (ii) add a short paragraph discussing the assumption and its limitations, and (iii) include a simple depth-variation test using the existing data to show that the cross-correlation signal is stable under changes in survey depth. Full fiber-assignment end-to-end simulations remain outside the scope of this exploratory DR1 analysis. revision: partial

  2. Referee: [Methods] Methods section: the manuscript provides no explicit error budget, covariance matrix construction details, or validation checks on redshift distributions and bias modeling for the joint auto+cross analysis, preventing independent assessment of the reported f_NL^loc constraint and its uncertainties.

    Authors: We acknowledge that the Methods section is insufficiently detailed for independent reproduction. The covariance matrix is built from the analytic Gaussian expression for the auto- and cross-power spectra (including the full cross-covariance blocks) and has been validated against the same set of mocks used for the forecasts. Redshift distributions are taken directly from the DESI DR1 catalog releases with the standard photometric-redshift weighting; linear bias parameters are marginalized with a scale-dependent PNG correction. In the revised version we will add (i) an explicit error-budget table listing the dominant contributions, (ii) the precise covariance formula and its implementation, and (iii) supplementary figures showing the n(z) validation and bias-model checks for the joint analysis. revision: yes

  3. Referee: [Mock tests] Mock tests paragraph: while mocks are said to predict an additional ~8% gain with statistical scatter, the text does not present the mock results explicitly or incorporate realistic DESI DR1 systematics, leaving open whether the data outcome is distinguishable from chance in the reported error regime of ~8.5.

    Authors: The mock results are currently summarized rather than shown in detail. We will move the relevant mock distributions (including the histogram of recovered f_NL improvements) into the main text as a new figure, together with the quoted ~8% mean gain and its scatter. The mocks used are halo catalogs populated with DESI-like number densities and linear bias but do not yet include the full suite of observational systematics (fiber assignment, imaging depth variations, etc.). We will add an explicit statement noting this limitation and confirming that the observed lack of improvement when adding ELGs lies well within the statistical scatter of the current mocks. A more complete systematics-inclusive mock suite is planned for future DESI data releases. revision: yes

Circularity Check

0 steps flagged

No significant circularity detected in the f_NL derivation chain

full rationale

The central result (f^loc_NL = 2.1_{-8.3}^{+8.8} with ~9% tightening from LRG×QSO cross-correlation) is obtained by fitting measured auto- and cross-correlation functions of DESI DR1 tracers directly to a theoretical model, with validation against external mock catalogs. No equation or step reduces the reported constraint, the improvement percentage, or the multi-tracer rationale to a fitted parameter, self-citation, or input by construction. The assumption that cross-correlations reduce non-common systematics is presented as a standard methodological premise rather than a derived claim that loops back onto the data or prior author work.

Axiom & Free-Parameter Ledger

2 free parameters · 2 axioms · 0 invented entities

Abstract-only review; modeling details unavailable. Free parameters and assumptions inferred from standard LSS analysis of f_NL.

free parameters (2)
  • galaxy bias and redshift distribution parameters
    Nuisance parameters required to model the amplitude and shape of the observed clustering signal.
  • f_NL^loc
    Target parameter fitted to the combined auto- and cross-correlation data.
axioms (2)
  • domain assumption Standard flat Lambda-CDM background cosmology
    Used to predict the expected clustering shape in the absence of non-Gaussianity.
  • ad hoc to paper Cross-correlations suppress non-common systematics
    Central justification for combining LRG and QSO samples.

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discussion (0)

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Forward citations

Cited by 1 Pith paper

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score.

  1. New constraints on primordial non-Gaussianity from large-scale cross-correlations of CMB lensing and the cosmic infrared background

    astro-ph.CO 2026-05 unverdicted novelty 4.0

    Dust-cleaned CIB and CMB lensing cross-correlations yield f_NL^local = 43 ± 23, tightening constraints on local primordial non-Gaussianity.

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