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arxiv: 2204.05305 · v4 · pith:ZFENB7GNnew · submitted 2022-04-11 · 🌌 astro-ph.CO

Galaxy and halo angular clustering in LCDM and Modified Gravity cosmologies

Pawe{\l} Drozda , Wojciech A. Hellwing , Maciej Bilicki This is my paper

Pith reviewed 2026-05-24 12:44 UTC · model grok-4.3

classification 🌌 astro-ph.CO
keywords modified gravityangular clusteringcounts-in-cellshigher-order statisticsgalaxy mocksN-body simulationsf(R) gravitynDGP model
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0 comments X

The pith

Third-order angular statistics distinguish modified gravity from Lambda-CDM at 2-4 sigma for galaxies and halos.

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

The paper compares angular clustering of galaxies, halos, and dark matter in standard Lambda-CDM versus modified gravity models using N-body simulations and observer-frame lightcone mocks. It measures area-averaged correlation functions W_J and reduced cumulants S_J up to ninth order with counts-in-cells, finding up to 20 percent relative deviations from general relativity. The redshift slice 0.15 to 0.3 maximizes the signal, and third-order measures prove most sensitive for halos and galaxies. This opens a route to gravity tests in photometric surveys at modest number densities.

Core claim

Using counts-in-cells on mock catalogs from N-body simulations of f(R) and nDGP models, the study finds that third-order angular statistics W_3 and S_3 provide the most sensitive probe, reaching 2 to 4 sigma significance at scales of about 0.13 degrees for halos and galaxies, while the dark matter field shows even larger deviations at smaller scales.

What carries the argument

Area-averaged angular correlation functions W_J and reduced cumulants S_J measured via counts-in-cells in observer-frame lightcones from N-body simulations.

If this is right

  • Third-order statistics are the most sensitive probe for halos and galaxies among the orders tested.
  • Relative MG deviations reach up to 20 percent compared with GR.
  • Dark matter shows stronger deviations exceeding 5 sigma but at smaller angular scales around 0.08 degrees.
  • Detectable signals appear even in mocks with low surface densities, implying stronger constraints from denser future surveys.

Where Pith is reading between the lines

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

  • The identified optimal redshift range could guide target selection for gravity tests in ongoing or planned photometric surveys.
  • Baryonic effects likely limit the use of the dark-matter signal at the smallest scales where deviations are largest.
  • The same counts-in-cells approach could be applied to additional modified-gravity models or to cross-correlations with other tracers.

Load-bearing premise

The N-body simulations and resulting mock catalogs accurately capture the modified-gravity effects on halo and galaxy clustering without needing to model baryonic physics or survey selection at the quoted scales and number densities.

What would settle it

Measuring the scale dependence of reduced skewness S_3 in a real photometric survey at 0.15 < z < 0.3 and checking whether the value at theta approximately 0.13 degrees matches GR or MG simulation predictions at the reported significance.

Figures

Figures reproduced from arXiv: 2204.05305 by Maciej Bilicki, Pawe{\l} Drozda, Wojciech A. Hellwing.

Figure 1
Figure 1. Figure 1: FIG. 1. Probability density functions of the counts-in-cells [PITH_FULL_IMAGE:figures/full_fig_p006_1.png] view at source ↗
Figure 3
Figure 3. Figure 3: FIG. 3. Two-point area-averaged angular correlation func [PITH_FULL_IMAGE:figures/full_fig_p007_3.png] view at source ↗
Figure 4
Figure 4. Figure 4: FIG. 4. Similar to Fig [PITH_FULL_IMAGE:figures/full_fig_p008_4.png] view at source ↗
Figure 5
Figure 5. Figure 5: FIG. 5. Three-point averaged angular correlation function (columns to the left) and reduced skewness (columns to the right) [PITH_FULL_IMAGE:figures/full_fig_p009_5.png] view at source ↗
Figure 6
Figure 6. Figure 6: FIG. 6. Clustering of all orders considered in this work. From top to bottom, we present the results for dark matter, halos, [PITH_FULL_IMAGE:figures/full_fig_p010_6.png] view at source ↗
Figure 7
Figure 7. Figure 7: FIG. 7. Illustration of our method to calculate the effective [PITH_FULL_IMAGE:figures/full_fig_p013_7.png] view at source ↗
read the original abstract

Using a suite of $N$-body simulations we study the angular clustering of galaxies, halos, and dark matter in $\mathrm{\Lambda \text{CDM}}$ and Modified Gravity (MG) scenarios. We consider two general categories of such MG models, one is the $f(R)$ gravity, and the other is the normal branch of the Dvali-Gabadadze-Porrati brane world (nDGP). To measure angular clustering we construct a set of observer-frame lightcones and resulting mock sky catalogs. We focus on the area-averaged angular correlation functions, $W_J$, and the associated reduced cumulants, $S_J\equiv W_J/W_2^{(J-1)}$, and robustly measure them up to the 9th order using counts-in-cells (CIC). We find that $0.15 < z < 0.3$ is the optimal redshift range to maximize the MG signal in our lightcones. Analyzing various scales for the two types of statistics, we identify up to 20\% relative departures in MG measurements from general relativity (GR), with varying signal significance. For the case of halos and galaxies, we find that $3$rd order statistics offer the most sensitive probe of the different structure formation scenarios, with both $W_3$ and the reduced skewness, $S_3$, reaching from $2\sigma$ to $4\sigma$ significance at angular scales $\theta \sim 0.13 ^\circ$. The MG clustering of the smooth dark matter field is characterized by even stronger deviations ($\stackrel{>}{{}_\sim} 5\sigma$) from GR, albeit at a bit smaller scales of $\theta\sim0.08^\circ$, where baryonic physics is already important. Finally, we stress out that our mock halo and galaxy catalogs are characterized by rather low surface number densities when compared to existing and forthcoming state-of-the-art photometric surveys. This opens up exciting potential for testing GR and MG using angular clustering in future applications, with even higher precision and significance than reported here.

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.

Circularity Check

0 steps flagged

No significant circularity; measurements are direct simulation outputs.

full rationale

The paper reports direct counts-in-cells measurements of W_J and S_J from N-body light-cone mocks in LCDM and MG models. No parameters are fitted to a subset of data and then presented as predictions of related quantities, no self-definitional relations appear in the described chain, and no load-bearing uniqueness theorems or ansatzes are imported via self-citation. The central results (differences at 2-4σ for halos/galaxies) are outputs of the simulation pipeline rather than reductions to the inputs by construction, making the derivation self-contained.

Axiom & Free-Parameter Ledger

0 free parameters · 2 axioms · 0 invented entities

The central claim rests on the assumption that the chosen N-body codes and halo finders correctly implement the MG force laws and that the light-cone construction introduces no significant projection artifacts; no free parameters are explicitly fitted in the abstract, and no new entities are postulated.

axioms (2)
  • domain assumption Standard LCDM background cosmology and initial conditions are used as the GR baseline.
    The paper compares MG runs against LCDM runs that share the same initial conditions and background expansion.
  • domain assumption Baryonic physics can be neglected at the angular scales and redshifts where the MG signal is reported for halos and galaxies.
    The abstract notes that baryonic effects become important at smaller scales for the dark-matter field but does not quantify their impact on the halo/galaxy measurements.

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Reference graph

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