Pith. sign in

REVIEW 3 major objections 5 minor 69 references

Evolution of Cosmic Voids: Structure, Galaxies, and Dynamics

T0 review · 3 major / 5 minor · reviewed 2026-08-02 · deepseek-v4-flash

Pith's one-line read Cosmic voids progressively empty out from z=2 to today while their galaxy populations fade, move outward, and stream away from void centers — and observed voids host a central galaxy population that ΛCDM does not predict.

desk verdict The simulation-side size-resolved evolutionary analysis is a useful consolidation, but the paper's headline claim about a non-zero central galaxy population in SDSS voids is very likely an artifact of the +1 pseudo-count in Eq. (5). read the letter →

arxiv 2602.21292 v2 pith:P7ZMHMBW submitted 2026-02-24 astro-ph.CO astro-ph.GA

classification astro-ph.COastro-ph.GA
keywords cosmicvoidsvoidevolutiongalaxyluminosityfunctiondensityprofilesdynamicsformationinunderdensitieslarge-scalestructuresemi-analytic
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

Cosmic voids are not static holes: over roughly ten billion years they become progressively emptier, and their resident galaxies fade, flatten in luminosity, migrate toward the void walls, and participate in coherent outward flows. The paper shows that this evolution is governed by void size — large voids host brighter galaxies with faster evolution, stronger clustering, and steeper outflows, while small voids keep a more heterogeneous, centrally concentrated population. The stacked void density profile is approximately universal when radii are scaled by void radius, deepening and building more pronounced walls toward z=0. The most consequential claim is observational: a low-redshift spectroscopic survey shows a non-zero central galaxy population in real voids that is absent from the ΛCDM prediction, which, if physical, would challenge current galaxy formation models in extreme underdensities and would make void size, epoch, and environment joint regulators of how void galaxies evolve.

What carries the argument

The operational core is a set of void catalogs produced by the same finder in simulation and survey: wall and field galaxies are separated by nearest-neighbor distance, a distance field is built on the grid, subvoids are merged, and each void gets an effective radius R_v and density contrast δ_v. The stacking toolbox includes the Schechter luminosity function with evolutionary indices q and r, the Poisson-estimator stacked density profile fitted to a five-parameter empirical model, the center-distance and mean-distance (minimum spanning tree) parameters, and stacked radial peculiar-velocity profiles with outward-motion fractions. The void-in-void/void-in-cloud scenario is the physical gearbo

What would settle it

Measure the stacked central density of observed voids in a larger, deeper spectroscopic sample with the same void finder, masking the survey boundary more conservatively and matching the background density to the simulation; if the innermost bin (r < R_v/2) falls to δ ≈ −1, the claimed central population vanishes, and with it the challenge to ΛCDM; if it remains near δ ≈ −0.9, the central excess is real.

Watch

Extended reading notes

Core claim

The central claim is that voids and their galaxies co-evolve in a size-dependent way. Across four epochs of a large cosmological simulation with semi-analytic galaxy formation, the paper finds that void galaxies fade and flatten in luminosity, migrate outward, and show coherent outflows toward the walls, with large voids evolving faster than small ones; stacked radial profiles deepen and sharpen into pronounced walls toward z=0 while remaining approximately universal when scaled by void radius. The salient finding is empirical: in a low-redshift spectroscopic survey, stacked void profiles are systematically less empty than simulated ones and show a non-zero central galaxy population, absent

Load-bearing premise

The comparison depends on the low-redshift observational void catalog — 93 voids and 512 galaxies with an irregular footprint and a background density about 3.5 times lower than the simulated sample — faithfully representing the same void population as the simulated z=0 snapshot; if that fails, the non-zero central density is a selection artifact rather than a physical galaxy population.

Editorial extensions

If this is right

  • Because void size controls the pace of luminosity-function evolution, any comparison of void galaxies across surveys or epochs must separate voids by size or the radial and evolutionary signals will be washed out.
  • The universality of the rescaled void density profile means one empirical form can describe void interiors and walls across z=0–2.09, so evolutionary changes appear in the fitted parameters (deeper center, steeper wall) rather than in a new functional shape.
  • The redshift growth of outward-moving galaxy fractions — roughly 58–63% in small voids and 78–86% in large voids between z=0 and z=2.09 — implies that galaxy transport toward walls is a real dynamical process, and it is the physical basis for interpreting observed redshift-space distortions.
  • If the non-zero central density in observed voids is physical, standard galaxy-formation treatments for underdense regions are incomplete: the discrepancy is not in void shapes but in the galaxy census at void centers.

Reading between the lines

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

  • If the central excess holds up to better selection tests, a natural explanation is that some galaxies form in situ in void centers and current semi-analytic recipes quench or suppress them too aggressively; a testable prediction is that such galaxies are young, low-metallicity, and star-forming compared to simulated void galaxies at the same radius.
  • The size-dependent evolutionary indices q and r suggest that large voids could serve as clean cosmological laboratories: measuring M*(z) and α(z) in large voids at higher redshift would directly test the environmental-downsizing picture.
  • Because the simulation and survey normalize density contrasts to different background densities, a fully clean test of the central excess should regenerate the survey selection function inside the simulation and re-measure stacked profiles under identical definitions; only then would a residual central population be unambiguously physical.
Share X Bluesky LinkedIn Reddit HN

Editorial analysis

A structured set of objections, weighed in public.

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

Referee Report

3 major / 5 minor

Summary. The paper constructs void catalogs from four Millennium Simulation snapshots (z = 0, 0.51, 1.01, 2.09) using the same Aikio–Mähönen void finder applied to Guo et al. semi-analytic galaxies, and a low-redshift SDSS void catalog (93 voids, 512 galaxies) drawn from the author's earlier work. It analyzes the void-galaxy luminosity function, stacked radial density profiles, spatial distribution statistics (center-distance and MST mean-distance), and radial peculiar-velocity profiles, split by void size. The reported findings are: void galaxies become progressively fainter and the LF faint-end slope flattens toward low redshift; stacked density profiles deepen and build stronger walls; void galaxies migrate outward and large voids are more strongly clustered; radial velocities show coherent outflows with amplitudes decreasing toward z = 0; and, most prominently, SDSS profiles show a non-zero central galaxy population absent in the simulation, which the abstract and conclusions present as a possible challenge to ΛCDM galaxy-formation models.

Significance. If the central-excess result were robust, it would be a notable empirical test of galaxy formation in extreme underdensities. The simulation-side analysis is internally coherent and the consistent application of one void finder to simulations and observations is a methodological strength; the paper also makes specific, falsifiable predictions for the redshift evolution of the LF, density profiles, and outflow velocities. However, the central empirical claim is not currently supported: the +1 pseudo-count in Eq. (5) creates a sample-size-dependent floor that, for the SDSS stacks, is large enough to mimic a non-zero central population entirely absent in the much larger Millennium stacks. In addition, the paper's own Tables 3 and 4 contradict the headline statement that large voids host more rapidly evolving galaxies. These issues are load-bearing for the paper's main conclusion and must be resolved before the result can be used as evidence against standard galaxy-formation treatments.

major comments (3)
  1. [Section 3.2, Eq. (5)] The stacked density estimator includes a +1 pseudo-count: bar-rho_j = (sum_i N_i^j + 1)/(sum_i V_i^j). The text states that this 'ensures the contrast is zero at the mean density'; this is not correct. At the mean density, bar-rho_j = rho_b + 1/(sum_i V_i^j), so delta = 1/(rho_b sum_i V_i^j), which is sample-size dependent. For an empty bin the estimator gives delta = 1/(rho_b V_stack) - 1 instead of -1. With the SDSS numbers in Tables 1 and 2, this floor is not negligible: for the All-voids sample (N_v = 93, mean R_v ~ 10.35 Mpc), a central bin of width Delta(r/R_v) ~ 0.1 has V_stack ~ 430 Mpc^3, so an empty bin returns delta ~ -0.79 with rho_b ~ 0.011 Mpc^-3. For the 6 Large voids the floor is delta ~ -0.38 (for R_v ~ 18 Mpc), and for the 40 Small voids it is delta ~ 0.06 (for R_v ~ 8 Mpc). The Millennium stacks contain ~18,000 voids, so their floor is ~10^-3. The estimator therefore g
  2. [Section 3.1, Tables 3-4, Abstract] The abstract and conclusions state that 'Large voids host brighter, more rapidly evolving galaxy populations than Small voids', but this is not supported by the paper's own fits. Table 3 shows M* for Small voids changing from -21.58 at z=0 to -21.93 at z=2.09 (Delta = -0.35), while for Large voids it changes from -21.67 to -21.91 (Delta = -0.24). The fitted evolution indices in Table 4 are q = 0.164 +/- 0.005 for Small and q = 0.121 +/- 0.001 for Large; the alpha indices are r = 0.048 +/- 0.02 and r = 0.038 +/- 0.01, respectively. Thus the Small-void population evolves faster in both M* and alpha. In addition, at z=2.09 M* for Small voids (-21.93) is more negative than for Large voids (-21.91), so the size ordering of M* reverses at the highest redshift. Finally, Eq. (4) with pivot z0 = 0.51 gives alpha(0) = 0, so it cannot describe the z=0 alpha entries in Table 3; the formula needs to
  3. [Section 3.2, Tables 1-2] The SDSS sample is too small and its background normalization too different to support the claimed ΛCDM discrepancy, independent of the +1 issue. The Large-void comparison rests on only 6 SDSS voids, and the All-voids sample has 93 voids with 512 galaxies. The stacked profiles use delta relative to a sample background of rho_b ~ 0.011 Mpc^-3 for SDSS versus rho_b ~ 0.039 Mpc^-3 for the simulation (Table 1, Fig. 2). The paper explicitly acknowledges this normalization difference for the delta_v-R_v relation, but not for the density profiles in Section 3.2. Because delta = (rho - rho_b)/rho_b, the same physical galaxy density produces very different delta values under the two normalizations, and the SDSS profiles being 'less empty' may be entirely a normalization/selection effect. Please quantify the expected offset from the background-density difference alone, and show that any residual c
minor comments (5)
  1. [Section 2.3] The text says 'we exclude voids smaller than R_v > 7 h^-1 Mpc'; presumably this should be 'exclude voids with R_v < 7 h^-1 Mpc'.
  2. [Figure 4 caption] The caption is a copy-paste error: it describes 'distributions of void effective radius, density contrast, and galaxy count' rather than the stacked density profiles shown in the figure.
  3. [Figure 7 and Table 3] Typographical issues: 'Redshitf' in the Figure 7 heatmap y-axis label, 'T able 1', and 'smaple' in the Table 3 caption. These should be fixed.
  4. [Table 5] For Large voids, the fitted parameter r_s1 is already at the boundary value 20 Mpc for all redshifts, and alpha is at its upper bound of 10 for several entries. Reporting 'typical uncertainties' of +/- 0.5 for r_s1 in this situation is implausible; these parameters appear unconstrained. The text should state this explicitly or reparameterize the fit.
  5. [Section 3.3] The claim that void galaxies 'migrate outward' is inferred from four independent snapshots, not from tracked individual voids or galaxies. This is a reasonable population-level interpretation, but it should be labeled as such to avoid overstating the dynamical tracking.

Circularity Check

2 steps flagged · score 7.0 of 10

The headline 'non-zero central galaxy population in observed voids absent in ΛCDM' is produced by the +1 pseudo-count in Eq. (5); for the sparse SDSS stack this floor is large and sample-size dependent, while the 18,000-void Millennium stack has a negligible floor. The discrepancy is an estimator artifact, not an independent empirical prediction.

  1. self definitional [Section 3.2, Eq. (5) and the following profile interpretation; abstract and Section 4]
    "¯ρj = (PNv i=1 N j i ) + 1 / PNv i=1 V j i ... the term +1 ensures the contrast is zero at the mean density, correcting for the systematic bias described in S. Nadathur & S. Hotchkiss (2014). ... In all three void categories, the observed profiles show a non-zero central density, implying the presence of galaxies near the void centers. Such central populations are not reproduced in the simulations, whose profiles approach δ→ −1 at small radii."

    For an empty stack, Eq. (5) gives ρ̄_j = 1/Σ_i V_i^j, so δ_j = 1/(ρ_b Σ_i V_i^j) − 1. For the SDSS All-voids stack (N_v = 93, R_v ≈ 10.35 Mpc, ρ_b ≈ 0.011), the innermost bin r/R_v < 0.1 has ΣV ≈ 430 Mpc^3, so an empty stack yields δ ≈ −0.79, not δ → −1. For the six Large voids the floor is even closer to zero or positive, and for the ~18,000 Millennium voids the floor is negligible (δ ≈ −0.9996). Thus the reported SDSS 'non-zero central density' — the central empirical support for the ΛCDM-challenge claim — is guaranteed by the +1 pseudo-count, independent of actual galaxies. The paper's statement that +1 'ensures the contrast is zero at the mean density' is incorrect: at mean density it adds δ = 1/(ρ_b ΣV), a sample-size-dependent offset.

  2. self citation load bearing [Section 3.2, final paragraph of the radial-profile discussion; echoed in Section 4 and the abstract]
    "This discrepancy—previously highlighted by S. Tavasoli (2021)—suggests that real voids may host a small but non-negligible population of centrally located galaxies, a result that poses an interesting challenge for the standard cosmological model."

    The cited work is by the same author and is the origin of the SDSS void catalog, the Poisson estimator, and the center/mean-distance definitions used in this paper (Sections 2.2, 2.3, 3.2, 3.3). Invoking it as 'previously highlighted' supplies no independent confirmation of the central-population excess: the same estimator floor in Eq. (5) is what produced the discrepancy in both the prior paper and this one. The self-citation is therefore load-bearing for the headline ΛCDM challenge rather than an external check.

full rationale

Most of the paper's evolutionary results — the luminosity-function evolution (M* fading, α flattening), the deepening of stacked density profiles, the outward radial-velocity profiles, and the center/mean-distance trends — are direct, new measurements from the external Millennium simulation snapshots and are not circular by construction. The circularity is concentrated in the SDSS anchor and the paper's central empirical novelty: the 'non-zero central galaxy population absent in ΛCDM predictions.' That claim is governed by Eq. (5), whose +1 pseudo-count places a sample-size-dependent floor of 1/(ρ_b ΣV) on every stacked bin. For the sparse SDSS catalogs (93 voids total, only 6 large voids), this floor is large enough to produce exactly the reported asymmetry: a non-negligible central density in the observed stack and essentially δ → −1 in the huge Millennium stack. The paper's own justification that '+1 ensures the contrast is zero at the mean density' is arithmetically false; it adds δ = 1/(ρ_b ΣV) at mean density. The additional self-citation to Tavasoli (2021) for the same discrepancy does not break the chain, because that earlier work uses the same catalog and estimator. I therefore assign 7: the simulation-based evolutionary measurements remain independent, but the paper's most prominent ΛCDM-challenging result reduces by construction to the estimator's pseudo-count, and the supporting citation is a self-citation.

Assumptions & free parameters 5 free parameters · 5 assumptions · 0 invented entities

The central claims rest on many fitted parameters and on comparability assumptions between snapshots and between simulation and survey. No new physical entities are postulated. The most fragile free parameters are the boundary-hitting profile parameters for Large voids and the q/r evolution indices.

free parameters (5)
  • Schechter M* per void class/snapshot = -21.58 to -22.08 mag (Table 3)
    Fitted by least squares to stacked void luminosity functions; drives the M*-fading claim.
  • Schechter α per void class/snapshot = -1.35 to -1.57 (Table 3)
    Fitted faint-end slopes; drives the α-flattening claim.
  • Schechter normalization φ* = not tabulated
    Included in the LF fit but not reported; normalization is part of the fitted model.
  • Evolution indices q and r = q=0.121-0.164, r=0.038-0.048 (Table 4)
    Fitted to the redshift dependence of M* and α to quantify void-size-dependent evolution rates.
  • Density-profile parameters δc, rs1, rs2, α, β = Table 5, e.g., δc=-0.89 to -0.96; rs1=1.05-20.1; α=1.10-10.3; β=3.25-7.20
    Best-fit parameters of the Barreira et al. profile model for each void size and redshift; some Large-void values sit at fit boundaries.
assumptions (5)
  • domain assumption Differences between four independent simulation snapshots represent the evolutionary path of the void population.
    The paper never tracks individual voids across snapshots; 'becoming emptier' and 'outward migration' are inferred from snapshot-to-snapshot population differences. Load-bearing for all evolutionary claims. Introduced in Section 3.
  • domain assumption The SDSS void catalog is a valid low-redshift counterpart to the simulated z=0 voids despite different survey geometry, background density, and selection.
    Required for the central-population comparison in Section 3.2; the paper itself notes ρb=0.011 vs 0.039 and small observational samples.
  • domain assumption The Guo et al. (2011) semi-analytic galaxy catalog reliably models r-band luminosities, colors, and sSFRs in underdense regions.
    All simulation-side galaxy properties depend on this catalog; Section 2.1.
  • domain assumption The Aikio-Mahonen/Tavasoli void finder yields statistically comparable voids in simulation and observation.
    Used for both datasets (Section 2.3); the finding is that SDSS has few galaxies, but the comparison assumes the void definition is transferable.
  • domain assumption The Schechter function and the Barreira et al. profile model are adequate fitting forms, and the +1 correction in Eq. 5 removes the Nadathur-Hotchkiss bias.
    Used for LFs and stacked profiles (Sections 3.1 and 3.2); fitting-form choice can bias the inferred evolution.

how reviews work

0 comments
Cite this review

Pith. "Pith review of Evolution of Cosmic Voids: Structure, Galaxies, and Dynamics." pith.science (2026). https://pith.science/paper/P7ZMHMBW

@misc{pith2026260221292,
  author       = {Pith},
  title        = {Pith review of: Evolution of Cosmic Voids: Structure, Galaxies, and Dynamics},
  year         = {2026},
  howpublished = {\url{https://pith.science/paper/P7ZMHMBW}},
  note         = {Machine review of arXiv:2602.21292}
}
abstract

We investigate the structural, photometric, and dynamical evolution of cosmic voids and their galaxy populations from $z=2.09$ to the present, focusing on void size as a key evolutionary parameter. Using void catalogs from four Millennium Simulation snapshots and SDSS data at $z<0.04$, we perform a unified analysis of void demographics, galaxy properties, and internal kinematics. Our analysis reveals clear evidence that cosmic voids exhibit a significant evolutionary trend of becoming progressively emptier toward low redshift, accompanied by a marked decline in the brightness and clustering of their galaxy populations. The void galaxy luminosity function evolves significantly: $M^{*}$ fades and $\alpha$ flattens with time, with large voids hosting brighter, more rapidly evolving galaxies than small voids. Stacked density profiles exhibit a universal shape when scaled by void radius, deepening and building more pronounced walls toward $z=0$. Galaxy spatial distributions reveal persistent size-dependent segregation, with galaxies in large voids lying farther from the center and more strongly clustered. Dynamical analysis of simulations shows coherent outward flows in all voids, with amplitudes decreasing toward $z=0$, providing a physical basis for observed redshift-space distortions. Comparison with SDSS broadly confirms these evolutionary trends but uncovers a non-zero central galaxy population in observed voids -- absent in $\Lambda$CDM predictions -- that may challenge current galaxy formation models in extreme underdensities. Future comparisons with additional simulations and deeper high-redshift surveys will provide stronger tests of $\Lambda$CDM in the most underdense regions.

Figures

Figures reproduced from arXiv: 2602.21292 by the authors.

Figure 1
Figure 1. Statistical overview of our void catalogs: distributions of void galaxy counts, effective radii, and density contrasts at four simulation redshifts (z = 0.0, 0.51, 1.01, 2.09) together with the observational sample at z ∼ 0. 0 50 100 150 200 250 300 350 Number of Void Galaxies 10 15 20 25 30 Effective Radius (Mpc) -0.96 -0.95 -0.94 -0.93 -0.92 -0.91 -0.90 Density Contrast z = 2.09 z = 1.01 z = 0.50 z = 0.00 Observat… view at source ↗
Figure 2
Figure 2. Top: mean number of galaxies per void as a function of void effective radius Rv. Bottom: mean density contrast ⟨δv⟩ versus Rv. Points denote bin-averaged values and vertical bars indicate the standard error of the mean (±1σ). Note that δv is computed relative to the sample back￾ground density (ρb ∼ 0.011) for SDSS and (ρb ∼ 0.039) for the simulation); this difference contributes to the apparent offset between the da… view at source ↗
Figure 3
Figure 3. Left: Galaxy luminosity functions for void galaxies in the Small, Large, and All samples across four simulation redshift bins, with the SDSS z∼0 measurements overplotted for comparison. Right: Redshift evolution of the best-fit Schechter parameters M∗ and α for the simulated samples, highlighting systematic trends with void size and the offset between simulations and observations at z∼0. gether with the observationa… view at source ↗
Figures from the paper (4 more)
Figure 4
Figure 4. Figure 4: A statistical overview of our void catalog, showing the distributions of void effective radius, density contrast, and galaxy count across four simulation snapshots (z = 0.0, 0.5, 1.0, and 2.0). For comparison, the corresponding SDSS measurements at z∼0 are overplotted …
Figure 5
Figure 5. Figure 5: Mean values of the center–distance and mean–dis￾tance parameters for galaxies residing in small and large voids. The curves show the results from four simulation snapshots, while the z ∼ 0 observational measurements are overplotted for comparison. Error bars represent …
Figure 6
Figure 6. Figure 6: Stacked radial velocity profiles for small voids, large voids, and the full void sample across four redshift intervals, derived from the Millennium simulation. the void boundary. This monotonic increase is char￾acteristic of “void–in–void” evolution, in which the en￾ti…
Figure 7
Figure 7. Figure 7: Heat–map showing the fraction of out￾ward–moving galaxies for small voids, large voids, and the full void sample across four redshift intervals. 4. CONCLUSION In this work, we examined the structural, photomet￾ric, and dynamical evolution of cosmic voids and their gala…

Discussion (0). Sign in to comment.

Reference graph

Works this paper leans on

69 extracted references · 21 canonical work pages

  1. [1]

    Ade, P. A. R., Aghanim, N., Arnaud, M., et al. 2016, A&A, 594, A13, doi: 10.1051/0004-6361/201525830

  2. [2]

    A., Almeida, A., et al

    Ahumada, R., Prieto, C. A., Almeida, A., et al. 2020, ApJS, 249, 3, doi: 10.3847/1538-4365/ab929e

  3. [3]

    1998, ApJ, 497, 534, doi: 10.1086/305473

    Aikio, J., & M¨ ah¨ onen, P. 1998, ApJ, 497, 534, doi: 10.1086/305473

  4. [4]

    C., Hlozek, R., & Spergel, D

    Alonso, D., Hill, J. C., Hlozek, R., & Spergel, D. N. 2018, Phys. Rev. D, 97, 063514, doi: 10.1103/PhysRevD.97.063514

  5. [5]

    2025, ApJ, 988, 271, doi: 10.3847/1538-4357/ad7f4c

    Ashurikisomi, Z., & Baghram, S. 2025, ApJ, 988, 271, doi: 10.3847/1538-4357/ad7f4c

  6. [6]

    2022, MNRAS, 513, 186, doi: 10.1093/mnras/stac828

    Aubert, M., Cousinou, M.-C., Escoffier, S., et al. 2022, MNRAS, 513, 186, doi: 10.1093/mnras/stac828

  7. [7]

    M., & Pascoli, S

    Barreira, A., Cautun, M., Li, B., Baugh, C. M., & Pascoli, S. 2015, JCAP, 2015, 028, doi: 10.1088/1475-7516/2015/08/028

  8. [8]

    D., Bhavsar, S

    Barrow, J. D., Bhavsar, S. P., & Sonoda, D. H. 1985, MNRAS, 216, 17, doi: 10.1093/mnras/216.1.17

Show all 69 references
  1. [9]

    A., & Weinberg, D

    Berlind, A. A., & Weinberg, D. H. 2002, ApJ, 575, 587, doi: 10.1086/341469

  2. [10]

    P., & Ling, E

    Bhavsar, S. P., & Ling, E. N. 1988, PASP, 100, 1314, doi: 10.1086/132310

  3. [11]

    R., Lin, H., & Lupton, R

    Blanton, M. R., Lin, H., & Lupton, R. H. 2003, AJ, 125, 2276, doi: 10.1086/374786

  4. [12]

    R., & Roweis, S

    Blanton, M. R., & Roweis, S. 2007, AJ, 133, 734, doi: 10.1086/510127

  5. [13]

    R., Kofman, L., & Pogosyan, D

    Bond, J. R., Kofman, L., & Pogosyan, D. 1996, Nature, 380, 603, doi: 10.1038/380603a0

  6. [15]

    2018, MNRAS, 476, 3195, doi: 10.1093/mnras/sty463

    Cautun, M., Paillas, E., Cai, Y.-C., et al. 2018, MNRAS, 476, 3195, doi: 10.1093/mnras/sty463

  7. [16]

    Cautun, M., van de Weygaert, R., Jones, B. J. T., & Frenk, C. S. 2014, MNRAS, 441, 2923, doi: 10.1093/mnras/stu768

  8. [17]

    J., Lares, M., Padilla, N., & Lambas, D

    Ceccarelli, L., Paz, D. J., Lares, M., Padilla, N., & Lambas, D. G. 2013, MNRAS, 434, 1435, doi: 10.1093/mnras/stt1135

  9. [19]

    M., Krughoff, K

    Colberg, J. M., Krughoff, K. S., & Connolly, A. J. 2005, MNRAS, 359, 272, doi: 10.1111/j.1365-2966.2005.08897.x

  10. [20]

    Curtis, O., McDonough, B., & Brainerd, T. G. 2024, ApJ, 962, 58, doi: 10.3847/1538-4357/ad0f0c

  11. [21]

    Curtis, O., McDonough, B., & Brainerd, T. G. 2025, ApJ, 985, 244, doi: 10.3847/1538-4357/ad2f4c da Costa, L. N., Pellegrini, P. S., Sargent, W. L. W., et al. 1988, ApJ, 327, 544, doi: 10.1086/166215 Dom ´ ınguez-G´ omez, J., P´ erez, E., Dalla Vecchia, C., et al. 2023, MNRAS, ...

  12. [22]

    A., & Vogeley, M

    Douglass, K. A., & Vogeley, M. S. 2017, ApJ, 837, 42, doi: 10.3847/1538-4357/aa5dfd

  13. [23]

    Ghafour, P., Tavasoli, S., & Shojaei, M. R. 2025, JCAP, 2025, 001, doi: 10.1088/1475-7516/2025/12/001

  14. [24]

    M., & Vogeley, M

    Goldberg, D. M., & Vogeley, M. S. 2004, ApJ, 605, 1, doi: 10.1086/382146

  15. [25]

    R., Neyrinck, M

    Granett, B. R., Neyrinck, M. C., & Szapudi, I. 2008, ApJL, 683, L99, doi: 10.1086/591670

  16. [26]

    A., & Thompson, L

    Gregory, S. A., & Thompson, L. A. 1978, ApJ, 222, 784, doi: 10.1086/156198

  17. [27]

    A., & Geller, M

    Grogin, N. A., & Geller, M. J. 1999, AJ, 118, 2561, doi: 10.1086/301120

  18. [28]

    Guo, Q., White, S. D. M., Boylan-Kolchin, M., et al. 2011, MNRAS, 413, 101, doi: 10.1111/j.1365-2966.2010.18146.x

  19. [29]

    2018, Int

    Habibi, F., Baghram, S., & Tavasoli, S. 2018, Int. J. Mod. Phys. D, 27, 1850019, doi: 10.1142/S0218271818500190

  20. [30]

    2020, MNRAS, 493, 899, doi: 10.1093/mnras/staa278

    Habouzit, M., Pisani, A., Goulding, A., et al. 2020, MNRAS, 493, 899, doi: 10.1093/mnras/staa278

  21. [31]

    M., et al

    Hamaus, N., Pisani, A., Sutter, P. M., et al. 2016, Phys. Rev. Lett., 117, 091302, doi: 10.1103/PhysRevLett.117.091302

  22. [32]

    M., & Wandelt, B

    Hamaus, N., Sutter, P. M., & Wandelt, B. D. 2014, Phys. Rev. Lett., 112, 251302, doi: 10.1103/PhysRevLett.112.251302

  23. [33]

    2022, A&A, 658, A20, doi: 10.1051/0004-6361/202142073

    Hamaus, N., Aubert, M., Pisani, A., et al. 2022, A&A, 658, A20, doi: 10.1051/0004-6361/202142073

  24. [34]

    2012, ApJ, 752, 113, doi: 10.1088/0004-637X/752/2/113 16S

    Helgason, K., Ricotti, M., & Kashlinsky, A. 2012, ApJ, 752, 113, doi: 10.1088/0004-637X/752/2/113 16S. Tavasoli

  25. [35]

    R., Vogeley, M

    Hoyle, F., Rojas, R. R., Vogeley, M. S., & Brinkmann, J. 2005, ApJ, 620, 618, doi: 10.1086/426080

  26. [36]

    Hoyle, F., & Vogeley, M. S. 2002, ApJ, 566, 641, doi: 10.1086/338340

  27. [37]

    S., & Pan, D

    Hoyle, F., Vogeley, M. S., & Pan, D. 2012, MNRAS, 426, 3041, doi: 10.1111/j.1365-2966.2012.21920.x Ili´ c, S., Langer, M., & Douspis, M. 2013, A&A, 556, A51, doi: 10.1051/0004-6361/201321265

  28. [38]

    Shectman, S. A. 1981, ApJ, 248, L57, doi: 10.1086/183623

  29. [39]

    M., Dunkley, J., et al

    Komatsu, E., Smith, K. M., Dunkley, J., et al. 2011, ApJS, 192, 18, doi: 10.1088/0067-0049/192/2/18 Kov´ acs, A., Beck, R., Smith, A., et al. 2022, MNRAS, 513, 15, doi: 10.1093/mnras/stac903

  30. [40]

    Kreckel, K., Croxall, K., Groves, B., van de Weygaert, R., & Pogge, R. W. 2015, ApJL, 798, L15, doi: 10.1088/2041-8205/798/1/L15

  31. [41]

    Lavaux, G., & Wandelt, B. D. 2012, ApJ, 754, 109, doi: 10.1088/0004-637X/754/2/109

  32. [42]

    2024, MNRAS, 527, 2663, doi: 10.1093/mnras/stad3396

    Li, G., Ma, Y.-Z., Tramonte, D., & Li, G.-L. 2024, MNRAS, 527, 2663, doi: 10.1093/mnras/stad3396

  33. [43]

    M., Vogeley, M

    Moorman, C. M., Vogeley, M. S., Hoyle, F., et al. 2015, ApJ, 810, 108, doi: 10.1088/0004-637X/810/2/108

  34. [44]

    2016, MNRAS, 461, 358, doi: 10.1093/mnras/stw1340

    Nadathur, S. 2016, MNRAS, 461, 358, doi: 10.1093/mnras/stw1340

  35. [45]

    2014, MNRAS, 440, 1248, doi: 10.1093/mnras/stu299

    Nadathur, S., & Hotchkiss, S. 2014, MNRAS, 440, 1248, doi: 10.1093/mnras/stu299

  36. [46]

    2019, ApJS, 242, 11, doi: 10.3847/1538-4365/ab1b6d

    Nelson, D., Springel, V., Pillepich, A., et al. 2019, ApJS, 242, 11, doi: 10.3847/1538-4365/ab1b6d

  37. [47]

    Neyrinck, M. C. 2008, MNRAS, 386, 2101, doi: 10.1111/j.1365-2966.2008.13180.x

  38. [48]

    C., Vogeley, M

    Pan, D. C., Vogeley, M. S., Hoyle, F., Choi, Y.-Y., & Park, C. 2012, MNRAS, 421, 926, doi: 10.1111/j.1365-2966.2011.20197.x

  39. [49]

    2006, MNRAS, 372, 1710, doi: 10.1111/j.1365-2966.2006.10975.x

    Betancort-Rijo, J. 2006, MNRAS, 372, 1710, doi: 10.1111/j.1365-2966.2006.10975.x

  40. [50]

    Peebles, P. J. E. 2001, ApJ, 557, 495, doi: 10.1086/321658

  41. [51]

    Platen, E., van de Weygaert, R., & Jones, B. J. T. 2007, MNRAS, 380, 551, doi: 10.1111/j.1365-2966.2007.12125.x

  42. [52]

    Plionis, M., Valdarnini, R., & Jing, Y. P. 1992, ApJ, 398, 12, doi: 10.1086/171833

  43. [53]

    Prim, R. C. 1957, BSTJ, 36, 1389, doi: 10.1002/j.1538-7305.1957.tb01515.x

  44. [54]

    2014, MNRAS, 440, 601, doi: 10.1093/mnras/stu302 Rodr ´ ıguez-Medrano, A

    Ricciardelli, E., Quilis, V., & Varela, J. 2014, MNRAS, 440, 601, doi: 10.1093/mnras/stu302 Rodr ´ ıguez-Medrano, A. M., Paz, D. J., Mast, D.,

  45. [55]

    A., & Ruiz, A

    Stasyszyn, F. A., & Ruiz, A. N. 2025, A&A, 700, A76, doi: 10.1051/0004-6361/202453110

  46. [56]

    R., Vogeley, M

    Rojas, R. R., Vogeley, M. S., Hoyle, F., & Brinkmann, J. 2004, ApJ, 617, 50, doi: 10.1086/425167

  47. [57]

    E., & van de Weygaert, R

    Schaap, W. E., & van de Weygaert, R. 2000, A&A, 363, L29, doi: 10.48550/arXiv.astro-ph/0011007

  48. [58]

    A., Bower, R

    Schaye, J., Crain, R. A., Bower, R. G., et al. 2015, MNRAS, 446, 521, doi: 10.1093/mnras/stu2058

  49. [59]

    1976, ApJ, 203, 297, doi: 10.1086/154079

    Schechter, P. 1976, ApJ, 203, 297, doi: 10.1086/154079

  50. [60]

    D., Ryden, B

    Schmidt, J. D., Ryden, B. S., & Melott, A. L. 2001, ApJ, 546, 609, doi: 10.1086/318254

  51. [61]

    2023, MNRAS, 522, 1330, doi: 10.1093/mnras/stad103

    Schuster, N., Hamaus, N., Pisani, A., Dolag, K., & Weller, J. 2023, MNRAS, 522, 1330, doi: 10.1093/mnras/stad103

  52. [62]

    2025, arXiv e-prints

    Schuster, N., Hamaus, N., Pisani, A., Dolag, K., & Weller, J. 2025, arXiv e-prints

  53. [63]

    F., & Zel’dovich, Y

    Shandarin, S. F., & Zel’dovich, Y. B. 1989, Rev. Mod. Phys., 61, 185, doi: 10.1103/RevModPhys.61.185

  54. [64]

    K., & van de Weygaert, R

    Sheth, R. K., & van de Weygaert, R. 2004, MNRAS, 350, 517, doi: 10.1111/j.1365-2966.2004.07661.x

  55. [65]

    Springel, V., White, S. D. M., Jenkins, A., et al. 2005, Nature, 435, 629, doi: 10.1038/nature03597

  56. [66]

    M., Lavaux, G., Hamaus, N., et al

    Sutter, P. M., Lavaux, G., Hamaus, N., et al. 2015, Astron. Comput., 9, 1, doi: 10.1016/j.ascom.2014.10.002 S´ anchez, C., Clampitt, J., Kovacs, A., et al. 2017, MNRAS, 465, 746, doi: 10.1093/mnras/stw2745

  57. [67]

    2021, ApJL, 916, L24, doi: 10.3847/2041-8213/ac0f84

    Tavasoli, S. 2021, ApJL, 916, L24, doi: 10.3847/2041-8213/ac0f84

  58. [68]

    Lehnert, M. D. 2015, ApJL, 803, L13, doi: 10.1088/2041-8205/803/1/L13

  59. [69]

    2013, A&A, 553, A15, doi: 10.1051/0004-6361/201220536

    Tavasoli, S., Vasei, K., & Mohayaee, R. 2013, A&A, 553, A15, doi: 10.1051/0004-6361/201220536

  60. [70]

    J., et al

    Tempel, E., Saar, E., Liivam¨ agi, L. J., et al. 2011, A&A, 529, A53, doi: 10.1051/0004-6361/201015215

  61. [71]

    V., & Klypin, A

    Tikhonov, A. V., & Klypin, A. 2009, MNRAS, 395, 1915, doi: 10.1111/j.1365-2966.2009.14686.x van de Weygaert, R., & Platen, E. 2011, Int. J. Mod. Phys. Conf. Ser., 1, 41, doi: 10.1142/S2010194511000092 van Zee, L., & Haynes, M. P. 2006, ApJ, 636, 214, doi: 10.1086/497888 Zel’do...

Pith tools

Reviewed August 2, 2026 · model on record in the stance chip above.