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REVIEW 2 major objections 4 minor 43 references

The correlation between voids identified in 3D large-scale-structure and 2D weak-lensing maps

T0 review · 2 major / 4 minor · reviewed 2026-08-01 · deepseek-v4-flash

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Pith's one-line read Weak-lensing voids align with genuine 3D matter underdensities: low-redshift halo voids cluster around WL void centers at S/N ~ 25–29.

desk verdict Solid, useful simulation result on WL-void/3D-void correspondence; the qualitative signal is convincing, but the headline S/N is quoted at one tuned smoothing scale on noiseless maps and needs robustness tests before it should be cited as a number. read the letter →

arxiv 2607.20637 v1 pith:EREGZXB2 submitted 2026-07-22 astro-ph.CO

Y.Fang , C. T. Davies , N. Hamaus , J. J. Mohr This is my paper
classification astro-ph.CO
keywords cosmicvoidsweaklensingconvergencemapslarge-scalestructurevoidcross-correlationstackedprofilesmorphologycosmologicalsimulations
verification ladder T0 review T1 audit T2 compute T3 formal

The pith

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

The reading

This paper tries to establish that voids found in two-dimensional weak-lensing convergence maps are not artifacts of projection or noise, but correspond to real underdensities in the three-dimensional matter distribution. Using 108 full-sky ray-traced lensing simulations populated with a survey-like source redshift distribution, the authors stack the number density of 3D halo voids around 2D weak-lensing void centers and measure a positive excess at small angular separations. The detection is statistically significant for low-redshift halo voids (S/N around 25–29) and weakens for higher-redshift halo voids and for stricter peak-amplitude thresholds. The correlation also depends on halo void morphology, with rounder, less line-of-sight-aligned voids showing stronger associations. If right, this validates weak-lensing voids as physical tracers of matter underdensities and clarifies what observational void catalogs actually select.

What carries the argument

The load-bearing measurement is the stacked angular cross-correlation profile of 3D halo void centers around WL void centers, computed across 108 simulation realizations with a sample covariance and Hartlap-corrected inverse. WL voids are identified by a 2D tunnel-finder: a Delaunay triangulation of local convergence peaks (maxima in the smoothed convergence map) yields empty circumcircles, which are hierarchically cleaned to produce non-overlapping void candidates. Three peak-selection schemes (no threshold, positive peaks only, κ > 0.01) are compared. The characteristic sizes are matched to 3D halo voids by tuning the Gaussian smoothing scale to σ_smooth = 20 arcmin, which makes the WL voi

What would settle it

Recompute the stacked halo-void excess profile around WL voids using σ_smooth = 10 and 30 arcmin and check whether the low-redshift halo-void bin still yields S/N ≳ 25. If the signal drops below S/N ≈ 3 at either scale, or if it disappears when a different 2D void finder that does not require size-function matching is used, the claimed physical alignment would be shown to be scale-dependent rather than robust.

Watch

Extended reading notes

Core claim

The paper's central claim is that weak-lensing voids, defined as large empty circles in smoothed convergence maps, are preferentially located on top of genuine low-redshift voids in the 3D halo distribution. The evidence is a stacked angular excess number density profile, δwhv(θ) = nhv(θ)/n̄hv − 1, which rises to a positive peak inside the WL void radius and turns negative near the boundary, indicating a deficit of halo voids at the overdense walls. The amplitude depends strongly on the WL peak-selection scheme: retaining all peaks or only positive peaks yields S/N of 24.6 and 26.6 respectively, while a stringent κ > 0.01 threshold reduces the sample to about 140 voids per realization and dr

Load-bearing premise

The headline detection is quoted at a single, tuned smoothing scale (σ_smooth = 20 arcmin) chosen to make WL void sizes match halo void sizes; if the positive correlation does not persist at other smoothing scales, the S/N is a property of the chosen pipeline rather than of the underlying physical correspondence.

Editorial extensions

If this is right

  • Weak-lensing void catalogs can be interpreted as physical tracers of genuine matter underdensities, at least for low-redshift halo voids and when no aggressive peak threshold is applied.
  • Imposing high peak-amplitude thresholds to improve WL peak purity degrades the connection to true 3D underdensities, creating a trade-off between tracer purity and physical fidelity.
  • The correlation's strong redshift dependence means WL void signals are dominated by low-redshift structure, so measurements must account for the lensing kernel when comparing to 3D void statistics.
  • Rounder, less line-of-sight-aligned halo voids correlate more strongly with WL voids, implying that WL voids select a morphologically biased subset of the void population.
  • Future survey analyses using WL voids for cosmology will need to model this selection function and the effects of source redshift distribution and smoothing scale.

Reading between the lines

Editorial extensions of the paper, not claims the author makes directly.

  • A direct test of whether the S/N ≈ 25–29 signal is robust would be to rerun the entire stacking with σ_smooth = 10 and 30 arcmin; if the significance collapses, the quantitative claim is a property of the tuned pipeline rather than the physical correspondence.
  • Because the correlation is strongest for low-redshift, round halo voids, stacked WL void profiles might be used as a photometric-redshift sanity check: mismatches between predicted and measured correlation amplitudes across source bins could flag redshift distribution errors.
  • The compensation-wall feature (deficit of large halo voids, excess of small ones) suggests WL void walls are populated by subvoid-scale structures, offering a way to test hierarchical void formation in projected data.
  • If the selection bias toward round, low-redshift voids is confirmed in observations, it may make WL voids cleaner, more standardizable probes of modified gravity and dark energy than previously thought, at the cost of requiring careful calibration of the void shape distribution.
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Editorial analysis

A structured set of objections, weighed in public.

Desk editor's note, referee report, and a circularity audit.

Referee Report

2 major / 4 minor

Summary. The paper uses 108 realizations of the Takahashi et al. (2017) full-sky lensing simulations, populated with DES Y3-like source redshift distributions, to compare voids identified in 3D halo catalogs (VIDE) with voids identified in 2D WL convergence maps (tunnel algorithm on WL peaks). The central measurement is the stacked angular excess number density of 3D halo-void centers around WL-void centers. For low-redshift halo voids (0<z_hv<0.5) and WL voids from the full source sample, the authors report a positive small-scale correlation with S/N≈24.6–26.6 (no threshold and κ>0 selections) at a smoothing scale of σ_smooth=20 arcmin, which was chosen to match the WL and halo-void size functions. The signal weakens with halo-void redshift and with a stringent κ>0.01 peak selection, and shows modest morphology dependence. The paper concludes that WL voids trace genuine 3D underdensities, with the correspondence depending on WL selection and projection effects.

Significance. If the central result is robust, this is a useful direct simulation-based calibration of the physical meaning of WL voids, relevant for interpreting DES, Rubin, and Euclid void analyses. The paper has methodological strengths: 108 independent realizations, Hartlap-corrected covariance, a standard stacked-profile estimator, and public, well-established void finders. The observed redshift trends are physically plausible and consistent with the lensing kernel. The main quantitative claim, however, rests on a single smoothing scale selected by matching size functions, and the paper does not demonstrate that the S/N is stable across reasonable smoothing choices. The absence of shape noise is explicitly acknowledged but should be more prominently caveated in the abstract. These issues are local and addressable, not fatal to the overall approach.

major comments (2)
  1. [§3.2, Fig. 4; §4.2, Fig. 5] The headline S/N values (24.6 and 26.6 for the low-z, full-source case) are computed only at σ_smooth=20 arcmin, a scale chosen in §3.2 because the WL void size function 'most closely matches' the 3D halo-void size function. The paper does not recompute δwhv or the S/N at the other smoothing scales shown in Fig. 4 (15, 25, 30 arcmin), nor does it test whether the 20-arcmin choice is what produces the large S/N. Because matching the size functions also aligns the characteristic R_wlv over which the stacked profile is plotted (in units of R/R_wlv), the reported amplitude and S/N may be partly an artifact of the tuning rather than a robust statement about the physical correspondence. Please provide a smoothing-scale robustness test for at least the full-source, low-z halo-void configuration, and explicitly state how S/N and profile amplitude vary with σ_smooth.
  2. [§2, last paragraph; Abstract; §5] The paper states in §2 that shape noise, shear calibration bias, and instrumental systematics were not included, and it repeats this limitation in §5. This is good practice. However, the Abstract and §4.2 report 'statistically significant (S/N≳25)' with no qualifier that this significance is sample-variance-only in noiseless simulated convergence maps. Because the abstract will be read by observers, the S/N should be explicitly labeled as a simulation-only significance (e.g., 'in noiseless simulations and excluding shape noise'), so it is not mistaken for an observational detection significance.
minor comments (4)
  1. [§4.1, Eqs. (5)–(7)] The Hartlap correction is described in the text but not included in Eq. (6). As written, χ² should be multiplied by α (or the text should state that α has been absorbed into the reported values). This matters for exact reproducibility, since the S/N values are central to the paper.
  2. [Table 1] The κ>0.01 selection has N_wlv = 141 ± 130, i.e., a realization-to-realization dispersion comparable to the mean. It would be useful to report how many realizations contain zero WL voids under this selection, because the low-S/N results for this sample may be dominated by a few realizations.
  3. [§3.2] The threshold that removes Delaunay triangles with minimum internal angle below 20 degrees is introduced without justification or sensitivity test. A one-sentence explanation or a reference would help the reader assess whether the choice affects the WL-void catalog.
  4. [General] Minor editorial issues: 'V oids' in the Introduction should be 'Voids'; 'The elements in the covariance matrix was estimated via' should be 'were estimated'; Figure 5 is very dense and would benefit from a simplified layout or a separate table of S/N values for the key configurations.

Circularity Check

0 steps flagged · score 0.0 of 10

No significant circularity: the halo-void/WL-void correlation is a direct measurement; the smoothing-scale choice is a selection, not a fit to the signal.

full rationale

The paper's central claim is a stacked two-point measurement: the excess surface density of 3D halo void centers around WL void centers, Eqs. (2)-(3), with significance computed from a Hartlap-corrected covariance over 108 T17 realizations, Eqs. (4)-(7). Nothing in this chain fits a parameter to the cross-correlation amplitude; the null hypothesis is no correlation and the quoted S/N is a chi-square of the measured profile. The main tuning—smoothing scale σ_smooth=20 arcmin—is justified by matching the WL and halo-void size functions (Fig. 4), not by optimizing the alignment signal, so the measurement does not reduce by construction to that choice. The absence of a robustness scan across smoothing scales is a selection/robustness concern, not definitional circularity. The VIDE and tunnel tools are public codes used as external dependencies; author-overlapping citations (e.g., Sutter et al. 2015, Cautun et al. 2018) are not invoked to prove the result. Supporting physical-interpretation citations (Shimasue et al. 2024, Schuster et al. 2023) are not load-bearing. No self-definitional, fitted-input-called-prediction, or imported-uniqueness step is present.

Assumptions & free parameters 3 free parameters · 4 assumptions · 0 invented entities

The measurement uses established simulations and public void finders; no new physical entities are introduced. The only hand-tuned inputs are the smoothing scale, peak thresholds, and morphology cuts. The key assumption chain is that halos and the simulated convergence maps faithfully represent matter underdensities; these are domain assumptions, not fitted model parameters.

free parameters (3)
  • Gaussian smoothing scale σ_smooth = 20 arcmin
    Chosen in Sec. 3.2/Fig. 4 so the WL void size function matches the 3D halo void size function; the cross-correlation S/N is quoted only at this scale.
  • WL peak threshold κ>0.01 = 0.01
    Ad hoc high-threshold selection scheme in Sec. 3.2; strongly reduces WL void sample (N=141±130) and changes correlation amplitude.
  • Halo-void ellipticity split e_hv=0.15, LOS-alignment split |cosΘ|≤0.3/≥0.7 = 0.15, 0.3, 0.7
    Hand-chosen cuts in Sec. 4.3 to define morphology subsamples; secondary results depend on them.
assumptions (4)
  • domain assumption T17 N-body ray-tracing simulations reproduce the cosmological matter field and lensing convergence adequately at the scales probed by voids.
    Used throughout Sec. 2; all results are only as valid as the simulations.
  • domain assumption Dark-matter halos with M_vir>10^13 h^-1 Mpc trace the underdense regions of the matter field well enough for VIDE to find physical voids.
    Sec. 2/3.1; the 3D void catalog is built from halos, not the full matter field.
  • domain assumption DES Y3 DNF photo-z redshift distributions applied as LOS weights produce convergence maps representative of the real DES Y3 lensing signal.
    Sec. 2, Eq. 1; the source weighting is taken from Gatti et al. (2021) without propagating photo-z uncertainties.
  • domain assumption The tunnel algorithm's empty-circumcircle definition of WL voids captures meaningful projected underdensities.
    Sec. 3.2; the central claim is about voids defined this way.

how reviews work

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Cite this review

Pith. "Pith review of The correlation between voids identified in 3D large-scale-structure and 2D weak-lensing maps." pith.science (2026). https://pith.science/paper/EREGZXB2

@misc{pith2026260720637,
  author       = {Pith},
  title        = {Pith review of: The correlation between voids identified in 3D large-scale-structure and 2D weak-lensing maps},
  year         = {2026},
  howpublished = {\url{https://pith.science/paper/EREGZXB2}},
  note         = {Machine review of arXiv:2607.20637}
}
read the original abstract

We investigate the correspondence between voids identified in the 3D halo distribution and those detected in WL convergence maps. We used 108 realizations of the full-sky lensing simulations, populated with a source galaxy redshift distribution consistent with the Dark Energy Survey Year 3 sample. Catalogs of 3D halo voids and WL voids were constructed using the VIDE and tunnel algorithms, respectively. The spatial association between the two populations was quantified by measuring the angular excess number density of halo voids around WL void centers. We detected a statistically significant (S/N >= 25) positive correlation between WL voids and low-redshift halo voids (0 < z_hv < 0.5) at small angular separations, indicating that WL voids trace genuine underdensities in the large-scale matter distribution. The correlation amplitude closely depends on the WL void selection scheme and decreases when stringent peak-amplitude thresholds are applied, thereby reducing the number of detected WL voids and broadening their effective sizes. The signal also displays a strong redshift dependence: halo voids at higher redshift exhibit weaker correlations because of the declining efficiency of the WL kernel, while WL voids identified from higher-redshift source bins produce stronger correlations due to the increased contribution from line-of-sight structures. We additionally examined the impact of halo-void morphology and found that rounder voids with a weaker alignment along the line of sight display marginally stronger associations with WL voids. Our results provide new insights into the contribution of 3D structure to WL-selected underdensities and offer guidance for future observational analyses seeking to interpret WL voids as tracers of the matter field.

Figures

Figures reproduced from arXiv: 2607.20637 by the authors.

Figure 1
Figure 1. DNF-estimated photometric redshift distributions for [PITH_FULL_IMAGE:figures/full_fig_p002_1.png] view at source ↗
Figure 2
Figure 2. Mean 3D halo void counts as a function of e [PITH_FULL_IMAGE:figures/full_fig_p003_2.png] view at source ↗
Figure 3
Figure 3. Using 108 mock realizations, we compute the mean void [PITH_FULL_IMAGE:figures/full_fig_p004_3.png] view at source ↗
Figures from the paper (6 more)
Figure 4
Figure 4. Figure 4: Impact of convergence map smoothing on WL void sizes. [PITH_FULL_IMAGE:figures/full_fig_p005_4.png]
Figure 5
Figure 5. Figure 5: Mean excess projected number density profiles, [PITH_FULL_IMAGE:figures/full_fig_p007_5.png]
Figure 7
Figure 7. Figure 7: Hexagonal-binned density map showing the cosine of the [PITH_FULL_IMAGE:figures/full_fig_p008_7.png]
Figure 6
Figure 6. Figure 6: Hexagonal-binned density map of halo void ellipticity as [PITH_FULL_IMAGE:figures/full_fig_p008_6.png]
Figure 9
Figure 9. Figure 9: Radial profiles of average excess projected number [PITH_FULL_IMAGE:figures/full_fig_p009_9.png]
Figure 8
Figure 8. Figure 8: Radial profiles of average excess projected number den [PITH_FULL_IMAGE:figures/full_fig_p009_8.png]

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