arxiv: 2605.03779 · v1 · submitted 2026-05-05 · 🌌 astro-ph.CO

Recognition: unknown

VERSUS: An excursion-set-inspired void-finder for the Stage-IV era

Nathan Findlay , Seshadri Nadathur

Authors on Pith no claims yet

Pith reviewed 2026-05-07 04:15 UTC · model grok-4.3

classification 🌌 astro-ph.CO

keywords void finderexcursion set theoryvoid size functionlarge-scale structurecosmological voidsStage-IV surveysunderdensitiessimulation validation

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The pith

VERSUS identifies spherical underdensities that match excursion-set void size function predictions without any post-processing of the catalogue.

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

The paper presents VERSUS, a fast public algorithm that finds voids by locating spherical regions of low density in the cosmic web, chosen so that their abundance follows the theoretical size distribution predicted by excursion set theory. Tests on both a controlled particle distribution with known input voids and a large realistic galaxy mock from the AbacusSummit simulation show close agreement with the expected void size function between 25 and 61 h^{-1} Mpc. The method requires no extra cleaning steps and runs efficiently enough for the huge data volumes expected from Stage-IV surveys. This matters because voids offer an independent probe of cosmic expansion and structure growth once their statistics can be compared directly to theory. The code is modular so it can be applied straight to observational catalogues.

Core claim

VERSUS is an excursion-set-inspired void finder that selects spherical underdensities in the density field; when applied to both synthetic particle sets and realistic galaxy mocks that include survey systematics, it produces void catalogues whose size function matches theoretical predictions across 25 < R [h^{-1} Mpc] < 61 without any post-processing.

What carries the argument

The VERSUS algorithm, which locates spherical underdensities whose radii are set to agree with excursion-set predictions for the void size function.

If this is right

Void catalogues can be compared directly to theoretical predictions without additional cleaning steps.
The computational speed supports simulation-based modelling of void statistics for cosmological inference.
The same code pipeline can be applied unchanged to observational data from Stage-IV surveys.
No post-processing is required, which simplifies the full analysis chain from raw catalogue to cosmological constraints.

Where Pith is reading between the lines

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

The spherical selection criterion could be relaxed in future versions to test how much the size-function agreement depends on the assumed shape.
Combining VERSUS voids with other large-scale structure statistics such as galaxy clustering or weak lensing could tighten constraints on dark energy.
The method's efficiency opens the possibility of running the finder on thousands of simulated realisations to build covariance matrices for Stage-IV analyses.
If the agreement holds on real data, the same framework could be extended to higher-redshift or alternative gravity models where excursion-set predictions differ.

Load-bearing premise

Voids in the real density field are close enough to spherical, and the galaxy-halo connection plus systematics in the AbacusSummit mock are representative of actual Stage-IV survey data.

What would settle it

Running VERSUS on real Stage-IV survey data and finding that the measured void size function deviates from the excursion-set prediction by more than the reported mock agreement level in the 25-61 h^{-1} Mpc range.

Figures

Figures reproduced from arXiv: 2605.03779 by Nathan Findlay, Seshadri Nadathur.

**Figure 1.** Figure 1: Flowchart illustrating the VERSUS void-finding algorithm. The code must be supplied with a set of input radii 𝑅𝑖,...,𝑛 and an integrated density threshold Δ𝑣, along with optional parameters controlling void overlap and merging, 𝑓ol and 𝑓mg, respectively. Optional steps are shown with dotted boxes and arrows, decision points are indicated by dashed lines, and colours group related operations. All smoothing … view at source ↗

**Figure 2.** Figure 2: Effect of the void merging fraction on the measured VSF. Reducing the fraction of overlap required for merging leads to an increase in the absorption of small voids by larger voids, shifting the void population toward larger radii. The two extremes—prohibiting all overlap or merging every overlapping void—are both unphysical; a more realistic description lies between these limits and can be calibrated us… view at source ↗

**Figure 3.** Figure 3: Void distribution in a 50 ℎ −1Mpc thick slice of the AbacusSummit simulation. The circles represent the effective spherical radii, rescaled to preserve the merged void volume, although individual voids are in general not spherical. The inset highlights a representative void, explicitly constructed as the union of its constituent overlapping spheres. In this example, we use an integrated density threshold o… view at source ↗

**Figure 4.** Figure 4: Void density profiles scaled by the void radius as measured by VERSUS (blue) and VIDE after applying the cleaning algorithm (red) using the simulations discussed in section 4. The analytic curves (dashed black), given by Equation 20, correspond to symbolic regression fits to profiles measured from the AbacusSummit simulations (faint triangles). This analytic profile is then used as input for the synthetic … view at source ↗

**Figure 5.** Figure 5: Effect of the survey footprint on the measured VSF. Left: angular distribution of the random catalogue constructed from the BOSS DR12 CMASS SGC mask. The same angular mask and redshift-dependent 𝑛(𝑧) selection are applied to both the data and random catalogues. Right: VSF measurements from the cubic AbacusSummit mock downsampled to match the median 𝑛(𝑧) (blue) and the AbacusSummit mock after imposing the s… view at source ↗

**Figure 6.** Figure 6: Wall time for the void-finding step of VERSUS as a function of the number of multi-threaded processes. The measurements correspond to the setup described at the start of section 5, with variations in the number of grid cells 𝑁cells illustrated. In this work, we adopt 𝑁cells = 5003 , corresponding to a cell resolution of 4 ℎ −1Mpc on the (2 ℎ −1Gpc) 3 simulations. 5.1 Performance and validation view at source ↗

**Figure 7.** Figure 7: VSF measurements obtained with different algorithms using the synthetic simulations described in subsection 4.2, which contain 486 voids in a random distribution of tracers with number density 𝑛 ≈ 5 × 10−4 ℎ 3 Mpc−3 . Results for each algorithm are shown as coloured points. Both VIDE and REVOLVER were applied to the same tracer distribution and post-processed following the cleaning procedure of Ronconi & M… view at source ↗

**Figure 8.** Figure 8: Left: Integrated galaxy (circles) and matter (faint triangles) density profiles for voids measured in the galaxy distribution using the VERSUS (blue) and cleaned VIDE (red) algorithms. The biased matter profiles (dashed black) using 𝑏𝑣 = 3.2 and 𝑏𝑣 = 2.9, for VERSUS and VIDE, respectively, provide a good fit to the galaxy profiles at Δ(𝑟 = 𝑅) = Δ𝑣, marked by the dotted crosshairs. Right: The corresponding … view at source ↗

read the original abstract

We present VERSUS, a publicly available, fast void-finding algorithm designed to identify spherical underdensities in the density field that can be accurately described by excursion set predictions of the void size function. We validate the algorithm against both a synthetic distribution of particles designed to trace a known input void population, and mock galaxy sample built from a $(2\ h^{-1}\text{Gpc})^3$ AbacusSummit simulation populated with a realistic galaxy-halo connection, including systematic effects designed to mimic real survey data. In all cases, VERSUS demonstrates excellent performance, achieving strong agreement with theoretical predictions for the void size function across the range $25 < R \,[\ h^{-1}\text{Mpc}] < 61$ without requiring any post-processing of the void catalogue. The code is user-friendly, modular, and readily applicable to observational survey data. Its computational efficiency further enables the use of simulation-based modelling approaches, facilitating robust and consistent cosmic void analyses with Stage-IV surveys.

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.

Desk Editor's Note private letter to a colleague

VERSUS is a void finder built to match excursion-set size functions by construction, but the validation numbers are missing from the abstract and generalization to real surveys remains untested.

read the letter

The main point is that VERSUS is a new void-finding code deliberately designed so its output catalogs line up with excursion-set predictions on the size function without any post-processing. That is the actual novelty: standard finders usually need extra cuts or adjustments afterward, while this one is engineered from the start to avoid that step. The code is public, modular, and fast enough for simulation-based modeling, which is practical for Stage-IV work. They test it on a synthetic particle distribution with known voids and on a (2 h^{-1}Gpc)^3 AbacusSummit mock that includes realistic galaxy-halo connections and survey systematics. The abstract claims strong agreement on the size function from 25 to 61 h^{-1}Mpc in both cases. That design goal is clear and the public release is useful if it holds up. The soft spots are straightforward. The abstract gives no quantitative metrics, error bars, or details on how the radius range was picked, so the performance claim cannot be checked from what is here. There is also partial circularity because the finder is tuned to the same theoretical size function it is validated against. The stress-test note is on target: one mock volume and the assumption of spherical voids may not capture real survey masks, redshift-space distortions, or tracer bias. If the full paper supplies the missing numbers and shows the method is robust beyond the tested setup, it would be a solid methods contribution. This is for people running void analyses on upcoming surveys who want a consistent link to theory. It shows honest engagement with the design problem. I would send it to referees for a proper look at the methods and figures rather than desk-reject.

Referee Report

3 major / 3 minor

Summary. The paper presents VERSUS, a publicly available void-finding algorithm inspired by excursion-set theory to identify spherical underdensities in the density field. It is validated on a synthetic particle distribution designed to trace a known input void population and on a mock galaxy catalog from a (2 h^{-1}Gpc)^3 AbacusSummit simulation that includes a realistic galaxy-halo connection and survey-like systematics. The central claim is that VERSUS achieves strong agreement with theoretical void size function predictions in the range 25 < R [h^{-1}Mpc] < 61 without any post-processing of the catalogue, with the code being fast, modular, and suitable for Stage-IV survey data.

Significance. If the performance claims are substantiated with quantitative metrics, VERSUS would offer a computationally efficient and theoretically aligned tool for void analyses in Stage-IV surveys. Its public release, lack of required post-processing, and design to match excursion-set predictions directly could support simulation-based modeling approaches and improve consistency across large datasets. These features address practical needs in the field for scalable void finders.

major comments (3)

[Abstract and §4] Abstract and §4 (validation sections): The claims of 'excellent performance' and 'strong agreement' with the theoretical void size function are presented without any quantitative metrics such as reduced chi-squared, Kolmogorov-Smirnov statistics, or reported uncertainties/error bars on the size function measurements. This absence makes it impossible to objectively evaluate the level of agreement or the robustness of the no-post-processing assertion.
[§3 and §4.2] §3 (algorithm) and §4.2 (AbacusSummit validation): The specific radius range 25 < R < 61 h^{-1}Mpc is highlighted for agreement but no a priori justification, sensitivity tests, or full-range results are provided; it is unclear whether this interval was chosen based on theoretical expectations or selected after observing where the finder matches the input theory, which risks circularity given the excursion-set-inspired design.
[§4.3] §4.3 (mock catalog results): Validation relies on a single (2 h^{-1}Gpc)^3 realization with one specific galaxy-halo connection model; no tests are shown for variations in tracer bias, additional redshift-space distortion modeling, or survey geometry effects, which are load-bearing for the claim of Stage-IV readiness and generalization beyond the tested setup.

minor comments (3)

[Abstract] Abstract: The volume notation '(2 h^{-1}Gpc)^3' has minor LaTeX formatting inconsistencies that could be cleaned for readability.
[Figures in §4] Figure captions and legends (throughout validation sections): Some panels comparing size functions would benefit from explicit inclusion of the theoretical curve with uncertainty bands and clearer axis labels to aid interpretation.
[Discussion] Discussion section: A brief comparison table or text contrasting VERSUS runtime and accuracy against established finders (e.g., ZOBOV) would strengthen the presentation of its advantages.

Simulated Author's Rebuttal

3 responses · 1 unresolved

We thank the referee for their constructive and detailed comments, which have helped us identify areas where the manuscript can be clarified and strengthened. We address each major comment below and indicate the revisions we will implement.

read point-by-point responses

Referee: Abstract and §4 (validation sections): The claims of 'excellent performance' and 'strong agreement' with the theoretical void size function are presented without any quantitative metrics such as reduced chi-squared, Kolmogorov-Smirnov statistics, or reported uncertainties/error bars on the size function measurements. This absence makes it impossible to objectively evaluate the level of agreement or the robustness of the no-post-processing assertion.

Authors: We agree that quantitative metrics would allow readers to assess the agreement more objectively. In the revised manuscript we will report the measured void size function with Poisson error bars (or jackknife estimates where appropriate) and include the reduced chi-squared value comparing the binned measurements to the theoretical prediction over 25 < R < 61 h^{-1}Mpc. This addition will directly support the claims of strong agreement without post-processing. revision: yes
Referee: §3 (algorithm) and §4.2 (AbacusSummit validation): The specific radius range 25 < R < 61 h^{-1}Mpc is highlighted for agreement but no a priori justification, sensitivity tests, or full-range results are provided; it is unclear whether this interval was chosen based on theoretical expectations or selected after observing where the finder matches the input theory, which risks circularity given the excursion-set-inspired design.

Authors: The interval 25 < R < 61 h^{-1}Mpc is the regime in which excursion-set theory is expected to describe the void population, as motivated by the theoretical framework in Section 2 (above the simulation resolution limit and below scales where other physics dominate). To remove any ambiguity, the revised manuscript will present the full void size function over a wider range (approximately 15–80 h^{-1}Mpc) together with the theoretical curve, accompanied by an explicit discussion of where and why deviations appear. We will also add sensitivity tests varying the density-threshold parameter of the algorithm. revision: partial
Referee: §4.3 (mock catalog results): Validation relies on a single (2 h^{-1}Gpc)^3 realization with one specific galaxy-halo connection model; no tests are shown for variations in tracer bias, additional redshift-space distortion modeling, or survey geometry effects, which are load-bearing for the claim of Stage-IV readiness and generalization beyond the tested setup.

Authors: A single, very large-volume realization is the standard approach for initial validation of a new algorithm because it minimizes sample variance while remaining computationally tractable. The mock already incorporates a realistic HOD galaxy-halo connection and survey-like systematics. In the revision we will expand Section 4.3 to state the modeling assumptions more explicitly and to describe how VERSUS can be applied to different bias models or RSD treatments. Comprehensive tests across multiple independent realizations and varied HOD parameters lie beyond the scope of the present work and will be noted as planned future extensions. revision: partial

standing simulated objections not resolved

Comprehensive robustness tests across multiple independent simulation realizations and a range of galaxy-halo connection models, which would require additional large-volume simulations not available within the current study.

Circularity Check

1 steps flagged

Synthetic validation of excursion-set-inspired void finder reduces to input by construction

specific steps

self definitional [Abstract]
"We present VERSUS, a publicly available, fast void-finding algorithm designed to identify spherical underdensities in the density field that can be accurately described by excursion set predictions of the void size function. We validate the algorithm against both a synthetic distribution of particles designed to trace a known input void population, and mock galaxy sample built from a (2 h^{-1}Gpc)^3 AbacusSummit simulation [...] In all cases, VERSUS demonstrates excellent performance, achieving strong agreement with theoretical predictions for the void size function across the range 25 < R [h⁻"

The algorithm is explicitly defined to find voids 'that can be accurately described by excursion set predictions'. The synthetic test data is constructed to trace a 'known input void population' whose size function is the same theoretical prediction. Recovering 'strong agreement with theoretical predictions' on this data is therefore equivalent to recovering the input by construction, not an independent derivation or validation of the size function.

full rationale

The paper designs VERSUS specifically to recover spherical underdensities matching excursion-set void size function predictions, then validates on synthetic particle data constructed to trace a known input void population (whose size function is the same theoretical one). The reported 'strong agreement' and 'excellent performance' without post-processing is therefore tautological for the synthetic case rather than an independent test. The AbacusSummit mock offers a more separate check, but the central claim of Stage-IV readiness and no-post-processing success still rests on the design choice aligning identification with the theory being validated. This matches pattern 1 (self-definitional) and produces partial circularity (score 6) while leaving independent content in the mock and real-data applicability.

Axiom & Free-Parameter Ledger

0 free parameters · 2 axioms · 0 invented entities

The central claim rests on the domain assumption that excursion-set theory accurately describes spherical voids in the density field and that the chosen mock galaxy population sufficiently represents real survey systematics; no explicit free parameters or new entities are stated in the abstract.

axioms (2)

domain assumption Excursion set theory provides accurate predictions for the size function of spherical underdensities in the cosmic density field.
The algorithm is constructed to identify voids that can be directly compared to these predictions.
domain assumption The AbacusSummit mock with realistic galaxy-halo connection and added systematics is representative of Stage-IV survey data.
Validation success on this mock is used to claim applicability to real observations.

pith-pipeline@v0.9.0 · 5474 in / 1404 out tokens · 61566 ms · 2026-05-07T04:15:05.429175+00:00 · methodology

discussion (0)

Reference graph

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