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arxiv: 2512.17865 · v2 · submitted 2025-12-19 · 🌌 astro-ph.CO

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Constraining primordial non-Gaussianity from DESI DR1 quasars and Planck PR4 CMB Lensing

Sofia Chiarenza , Alex Krolewski , Marco Bonici , Edmond Chaussidon , Roger de Belsunce , Will Percival , Jessica Nicole Aguilar , Steven Ahlen
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Anton Baleato Lizancos Davide Bianchi David Brooks Todd Claybaugh Andrei Cuceu Kyle Dawson Axel de la Macorra Peter Doel Simone Ferraro Andreu Font-Ribera Jaime E. Forero-Romero Enrique Gazta\~naga Satya Gontcho A Gontcho Gaston Gutierrez Hiram K. Herrera-Alcantar Klaus Honscheid Dragan Huterer Mustapha Ishak Dick Joyce David Kirkby Anthony Kremin Ofer Lahav Claire Lamman Martin Landriau Laurent Le Guillou Michael Levi Marc Manera Paul Martini Aaron Meisner Ramon Miquel Seshadri Nadathur Jeffrey A. Newman Gustavo Niz Nathalie Palanque-Delabrouille Claire Poppett Francisco Prada Ignasi P\'erez-R\`afols Graziano Rossi Eusebio Sanchez David Schlegel Michael Schubnell Hee-Jong Seo Joseph Harry Silber David Sprayberry Gregory Tarl\'e Benjamin Alan Weaver Christophe Y\`eche Rongpu Zhou Hu Zou
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Pith reviewed 2026-05-16 20:29 UTC · model grok-4.3

classification 🌌 astro-ph.CO
keywords primordial non-Gaussianityf_NLDESI quasarsCMB lensingcross-correlationinflationlarge-scale structure
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The pith

Cross-correlating DESI DR1 quasars with Planck PR4 CMB lensing constrains local primordial non-Gaussianity to f_NL near zero with 35 percent tighter bounds.

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

The paper measures local-type primordial non-Gaussianity by cross-correlating 1.2 million spectroscopically confirmed DESI DR1 quasars with Planck PR4 CMB lensing reconstructions in three tomographic redshift bins spanning 0.8 to 3.5. It fits the non-Gaussianity parameter f_NL simultaneously with linear bias amplitudes in each bin using a catalog-based pseudo-C_ℓ estimator and linear imaging weights, obtaining f_NL = 2^{+28}_{-34} for response parameter p=1.6 and f_NL = 6^{+20}_{-24} for p=1.0. A sympathetic reader cares because these limits test whether early-universe fluctuations were Gaussian, which distinguishes single-field inflation from multi-field scenarios. The spectroscopic sample purity and lower lensing noise deliver a 35 percent improvement over previous photometric quasar analyses from the Legacy Imaging Survey DR9. An optimal weighting scheme is also derived that further refines the constraint.

Core claim

The central claim is the first measurement of local-type primordial non-Gaussianity from the cross-correlation of 1.2 million DESI DR1 quasars and Planck PR4 CMB lensing maps. In three redshift bins covering about 20 percent of the sky, simultaneous fitting of f_NL and per-bin linear bias yields f_NL = 2^{+28}_{-34} when the response parameter p equals 1.6 and f_NL = 6^{+20}_{-24} when p equals 1.0. These results tighten prior constraints by roughly 35 percent, while an optimal weighting scheme produces f_NL = 19^{+25}_{-31} assuming p=1.6.

What carries the argument

The tomographic cross-power spectrum between quasar overdensities and CMB lensing convergence, measured with a catalog-based pseudo-C_ℓ estimator and linear imaging weights validated on noiseless mocks.

If this is right

  • The measured f_NL values remain consistent with zero, supporting Gaussian initial conditions.
  • The spectroscopic quasar sample and reduced Planck PR4 noise produce cleaner large-scale cross-spectra than photometric predecessors.
  • Optimal weighting increases the constraining power on f_NL beyond the baseline analysis.
  • The approach demonstrates that DESI quasars can probe inflationary physics at high redshift.

Where Pith is reading between the lines

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

  • The same cross-correlation method could be applied to future DESI releases or other spectroscopic surveys to reach sub-10 uncertainties on f_NL.
  • If f_NL stays near zero with tighter errors, it would further disfavor multi-field inflation models that predict detectable non-Gaussianity.
  • The choice of response parameter p shifts the central value, indicating that independent calibration of p would reduce the dominant systematic uncertainty.

Load-bearing premise

The linear imaging weights, validated only on noiseless mocks, fully capture all relevant systematics in the real cross-power spectra without biasing the f_NL measurement.

What would settle it

A statistically significant shift away from the reported f_NL central values in the same quasar-lensing cross-power spectra when the identical weights and simultaneous bias-plus-f_NL fit are applied to a larger independent dataset.

read the original abstract

We present the first measurement of local-type primordial non-Gaussianity from the cross-correlation between $1.2$ million spectroscopically confirmed quasars from the first data release (DR1) of the Dark Energy Spectroscopic Instrument (DESI) and the Planck PR4 CMB lensing reconstructions. The analysis is performed in three tomographic redshift bins covering $0.8 < z < 3.5$, covering a sky fraction of $\sim 20\%$. We adopt a catalog-based pseudo-$C_\ell$ estimator and apply linear imaging weights validated on noiseless mocks. Compared to previous analyses using photometric quasar samples, our results benefit from the high purity of the DESI spectroscopic sample, the reduced noise of PR4 lensing, and the absence of excess large-scale power in the spectroscopic quasar auto-correlation. Fitting simultaneously for the non-Gaussianity parameter $f_{\mathrm{NL}}$ and the linear bias amplitude in each redshift bin, we obtain $f_{\mathrm{NL}} = 2^{+28}_{-34}$ for a response parameter $p=1.6$, and $f_{\mathrm{NL}} = 6^{+20}_{-24}$ for $p=1.0$. These results improve the constraints on $f_{\mathrm{NL}}$ by $\sim 35\%$ compared to the previous analysis based on the Legacy Imaging Survey DR9. Additionally, we derive an optimal weighting scheme to maximize the constraining power. In this case, and assuming $p=1.6$, we obtain $f_\mathrm{NL}=19^{+25}_{-31}$. Our results demonstrate the statistical power of DESI quasars for probing inflationary physics, and highlight the promise of future DESI data releases.

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 / 1 minor

Summary. The paper reports the first measurement of local-type primordial non-Gaussianity (f_NL) via cross-correlation of 1.2 million DESI DR1 spectroscopic quasars (0.8 < z < 3.5, three tomographic bins, ~20% sky fraction) with Planck PR4 CMB lensing. Using a catalog-based pseudo-C_ℓ estimator with linear imaging weights validated on noiseless mocks, the authors simultaneously fit f_NL and per-bin linear bias amplitudes, obtaining f_NL = 2^{+28}_{-34} (p=1.6) and f_NL = 6^{+20}_{-24} (p=1.0). These constraints improve by ~35% over the prior Legacy Imaging Survey DR9 analysis. An optimal weighting scheme is also derived, yielding f_NL = 19^{+25}_{-31} for p=1.6.

Significance. If the mock-validated weights fully control systematics, the work demonstrates the statistical power of DESI's high-purity spectroscopic quasar sample for inflationary constraints, avoiding excess large-scale power seen in photometric samples and benefiting from lower-noise PR4 lensing. The ~35% tightening and consistency with f_NL=0 provide a useful benchmark for future DESI releases.

major comments (2)
  1. [Abstract and Methods] Abstract and Methods (catalog-based pseudo-C_ℓ estimator): linear imaging weights are validated exclusively on noiseless mocks, yet the central claim that the resulting cross-power spectra are unbiased for the joint f_NL + bias fit rests on the untested assumption that noise-induced selection, imaging artifacts, and redshift-dependent systematics are fully captured. Any residual bias at large scales would directly shift the reported f_NL = 2^{+28}_{-34} or 6^{+20}_{-24}.
  2. [Results] Results (f_NL fitting procedure): the response parameter p is fixed at discrete values (1.6 or 1.0) rather than marginalized; because the model for the scale-dependent bias depends on p, the quoted asymmetric errors on f_NL do not include this model uncertainty and the ~35% improvement claim relative to DR9 is therefore conditional on the chosen p.
minor comments (1)
  1. [Results] The optimal weighting scheme is mentioned but its explicit form, derivation, and impact on the covariance are not shown in sufficient detail for independent reproduction.

Simulated Author's Rebuttal

2 responses · 0 unresolved

We thank the referee for their detailed and insightful comments on our manuscript. We have carefully considered each point and provide point-by-point responses below. Where revisions are needed, we commit to incorporating them in the updated version.

read point-by-point responses

  1. Referee: [Abstract and Methods] Abstract and Methods (catalog-based pseudo-C_ℓ estimator): linear imaging weights are validated exclusively on noiseless mocks, yet the central claim that the resulting cross-power spectra are unbiased for the joint f_NL + bias fit rests on the untested assumption that noise-induced selection, imaging artifacts, and redshift-dependent systematics are fully captured. Any residual bias at large scales would directly shift the reported f_NL = 2^{+28}_{-34} or 6^{+20}_{-24}.

    Authors: We agree that validation on noiseless mocks alone leaves open the possibility of residual biases from noise and other effects. The linear imaging weights primarily address large-scale imaging systematics, and the estimator's covariance includes noise contributions. However, to fully address this, we will perform additional validation using mocks that include realistic noise and selection effects, and include these results in the revised manuscript to confirm the robustness of our f_NL measurements. revision: yes

  2. Referee: [Results] Results (f_NL fitting procedure): the response parameter p is fixed at discrete values (1.6 or 1.0) rather than marginalized; because the model for the scale-dependent bias depends on p, the quoted asymmetric errors on f_NL do not include this model uncertainty and the ~35% improvement claim relative to DR9 is therefore conditional on the chosen p.

    Authors: The choice of p=1.6 and p=1.0 follows common practice in the literature for modeling the scale-dependent bias in quasars, reflecting different theoretical expectations for the response. We report constraints for both values explicitly to highlight the dependence. The 35% improvement is calculated relative to the DR9 analysis using the same p values. We will revise the text to explicitly state that the results are conditional on the fixed p and discuss the impact of this model choice, though full marginalization is beyond the scope of this work as p is a discrete modeling parameter. revision: partial

Circularity Check

0 steps flagged

Fitting f_NL simultaneously with per-bin bias amplitudes yields no circularity; result does not reduce to input assumptions by construction

full rationale

The derivation obtains f_NL by fitting the observed quasar-lensing cross-power spectra while jointly fitting linear bias amplitudes in each tomographic bin. The response parameter p is fixed at discrete external values (1.6 or 1.0) rather than derived from the data, and the linear imaging weights are validated on separate noiseless mocks. No equation in the paper equates the fitted f_NL to a quantity defined solely by those inputs or by a self-citation chain. The ~35% improvement is a comparison to prior external work, not a self-referential reduction. This is a standard parameter fit with independent content, warranting only a minor score for the fixed-p choice.

Axiom & Free-Parameter Ledger

2 free parameters · 2 axioms · 0 invented entities

The measurement rests on fitting per-bin linear bias amplitudes and fixing the response parameter p at discrete values, plus standard assumptions about the purity of the spectroscopic sample and the accuracy of the lensing reconstruction.

free parameters (2)
  • linear bias amplitude
    Fitted simultaneously with f_NL in each of the three tomographic redshift bins
  • response parameter p = 1.6 or 1.0
    Fixed at either 1.6 or 1.0 in separate fits; also tested in an optimal weighting scheme
axioms (2)
  • domain assumption The DESI spectroscopic quasar sample has high purity and exhibits no excess large-scale power in its auto-correlation
    Cited as a key advantage over previous photometric analyses
  • domain assumption Linear imaging weights validated on noiseless mocks can be applied to real data without introducing bias in the f_NL measurement
    Used to process the observed cross-correlation

pith-pipeline@v0.9.0 · 5898 in / 1663 out tokens · 27339 ms · 2026-05-16T20:29:00.754082+00:00 · methodology

discussion (0)

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Forward citations

Cited by 2 Pith papers

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

  1. Measurement of the galaxy-velocity power spectrum of DESI tracers with the kinematic Sunyaev-Zeldovich effect using DESI DR2 and ACT DR6

    astro-ph.CO 2026-04 unverdicted novelty 7.0

    DESI DR2 and ACT DR6 data yield 17σ LRG-velocity, 8.3σ ELG-velocity, and 6.8σ QSO-velocity detections plus a 3.1σ velocity-velocity signal, producing f_NL^loc = 15.9_{-34.4}^{+34.6} from the velocity field.

  2. 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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