Cosmic Velocity Flows: from Theory to Observations

Saee Dhawalikar

REVIEW 2 major objections 4 minor 192 references

Cosmic Velocity Flows: from Theory to Observations

T0 review · 2 major / 4 minor · reviewed 2026-08-05 · deepseek-v4-flash

Challenge this review Re-run · record.json Download PDF Read on arXiv ↗

Pith's one-line read The thesis claims that cosmic filaments are hierarchically nested structures whose phase space shows coherent infall, multistreaming, and caustic-like features, recoverable from discrete tracers by Skeletor, a Voronoi-based hierarchical fil

desk verdict Sahyadri and the mock-calibration framework are real contributions, but the phase-space 'discovery' rests on defining Rv as the infall minimum and then scaling by Rv, so the headline features are built in. read the letter →

arxiv 2608.03530 v1 pith:JMBJJDVG submitted 2026-08-04 astro-ph.CO

Saee Dhawalikar This is my paper

classification astro-ph.CO

keywords cosmicwebfilamentsN-bodysimulationsVoronoitessellationphase-spacestructurehierarchicalformationlarge-scalepeculiarvelocities

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 thesis tries to establish that cosmic filaments—the dense threads of the cosmic web—can be identified reliably from discrete galaxy-like tracers, and that once identified they show a rich, ordered phase-space structure that two-point clustering statistics miss. It builds three things: the Sahyadri simulation suite, which resolves halos roughly 25 times lighter than the previous best parameter-varying suite; a calibration framework (FilGen/FilAPT) showing that filament curvature and spine-reconstruction noise bias measured profiles and can be corrected with optimized Fourier smoothing; and Skeletor, a Voronoi-based hierarchical filament finder. Applied to simulations, Skeletor splits filaments into nested sub-filaments and stacks their density and velocity profiles, revealing coherent radial infall, multistreaming, and caustic-like features near the filament edge. If right, these results give a physically motivated, dynamics-based way to define filament boundaries and a new observational handle on nonlinear structure formation.

What carries the argument

Skeletor is the central object: a Voronoi-based hierarchical filament finder. It quantifies local anisotropy from the Voronoi tessellation of tracer positions, selects filament-like cells, connects them into spines, orders the resulting network by a mass hierarchy, and optionally refines spines with dark-matter density while estimating filament radius Rv from the minimum of the radial infall velocity. Supporting it are the FilGen/FilAPT calibration tools, which create controlled mock filaments with known spines, and the Sahyadri N-body suite, whose seed-matched parameter variations and high mass resolution supply the tracer populations and the beyond-two-point statistics (VVF, kNN) that the

What would settle it

Recompute the stacked phase-space profiles using a filament radius defined independently of the velocity profile—say, from the density-gradient or tangential-velocity transition—and without the Rv>0.6 cut; if the coherent-infall and caustic features at r/Rv≈1 disperse, they were built in by the radius definition rather than discovered.

Watch

Extended reading notes

Core claim

The central discovery is that the phase space of cosmic filaments is organized and hierarchical. Using Skeletor, the thesis reconstructs filament spines directly from discrete tracers with a Voronoi tessellation, uses dark-matter information to refine the spine and to define each filament's radius Rv as the location of maximum radial infall, and classifies nested sub-filaments within parent filaments. Stacked profiles then show coherent anisotropic inflow toward the spine, a velocity transition at the inferred boundary, multistreaming inside, and localized caustic-like features—signatures expected from anisotropic gravitational collapse. The thesis also shows that sub-filaments are statistic

Load-bearing premise

The central premise is that every filament has a single coherent radial infall whose deepest point is its physical edge; filaments whose fitted infall profile shows a different inner minimum are cut out rather than analysed.

Editorial extensions

If this is right

Filament boundaries can be defined dynamically by the radius of maximum coherent infall, tying geometry directly to ongoing gravitational collapse.
Filament hierarchy matters: sub-filaments embedded in parent filaments have distinct density and velocity profiles, so stacked filament statistics should separate hierarchy levels.
Phase-space diagnostics such as infall, multistreaming, and caustics provide observables beyond the power spectrum for the quasi-linear and nonlinear regimes.
Optimized Fourier spine smoothing substantially improves the recovery of density and velocity profiles, reducing methodology-induced bias in filament studies.
Sahyadri's resolution enables VVF and kNN statistics at high tracer density with clear Omega_m sensitivity, supporting cosmological constraints from beyond-two-point statistics.

Reading between the lines

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

A natural next step, not developed in the thesis, is to test whether the stacked phase-space profiles are universal across mass and redshift; the thesis frames universality as motivation, and the tools make it directly testable.
Because the Rv-scaled profiles may be partly built into the radius definition, the claimed features near r/Rv=1 should be checked against a radius defined independently of the velocity profile, for example from the density gradient.
The parent/sub-filament decomposition suggests that environment definitions for galaxy evolution studies may need to distinguish parent-filament from sub-filament membership, potentially affecting quenching and assembly-bias analyses.
Skeletor's inputs are only tracer positions and masses, so the same phase-space reconstruction could be attempted with spectroscopic galaxy surveys; the thesis's calibration framework could quantify how redshift-space distortions bias the inferred velocities.

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.

Desk Editor's Note

read the letter

Two things to know about this thesis. The Sahyadri simulation suite and the calibration framework in Chapter 3 are real additions: a 2048^3 box at 200 Mpc/h, resolving halos to 3.2e9 Msun, validated against Halofit and Tinker, with public pipeline code, and a controlled mock generator plus optimized Fourier smoothing that demonstrably reduces profile biases when the truth is known. Those parts deserve citation and referee time. The rest—Skeletor and the phase-space analysis—is where the trouble is.

The central problem is a definitional circularity. Chapter 4 defines the filament radius Rv as the location of maximum radial infall from a quadratic fit to vr(r). Chapter 6 then stacks profiles in units of r/Rv and presents the infall dip near r/Rv=1 as a physical boundary condition. That dip is built in by construction; it is not an independent measurement. The analysis then cuts at Rv=0.6 h^-1 Mpc to remove a secondary population whose fits give an 'unphysical inner minimum'—systems that do not have the assumed single-infall shape. So the reported 'coherent infall' is selected for, not discovered. Fig 6.8 compares other radius estimators in bins of Rv after the cut, which does not break the circularity. The multistreaming and caustic-like features at small radii are more independent, but their interpretation as evidence for universal filament boundaries inherits the same issue.

That said, I don't think this is fatal to the whole thesis. The calibration work in Chapter 3 stands on its own, and the Sahyadri validation is solid. The problem is localized to the overinterpretation of the phase-space results in Chapters 5 and 6. The fix is well-defined: use an independent radius definition for the profiles (e.g., density gradient or fixed physical scale), quantify the sensitivity to the Rv cut, and release Skeletor and the filament tools so others can check the robustness.

My take: this thesis deserves a serious referee. It is an honest, mostly well-written methods thesis with one load-bearing circularity in the dynamical claims. I'd recommend acceptance only after major revision that decouples the radius definition from the measurement and reports the analysis without the post-hoc cut, or at least shows the conclusions are robust to it. If the authors can do that, the phase-space chapter would be a useful contribution rather than a cautionary tale.

Referee Report

2 major / 4 minor

Summary. The thesis develops a set of numerical and methodological tools for studying the non-linear cosmic web, with emphasis on filamentary structure and velocity flows. It introduces the Sahyadri suite of high-resolution N-body simulations with systematic cosmological parameter variations; a calibration framework (FilGen/FilAPT) built on controlled filament realizations with known ground truth, including a Fourier-space smoothing technique; and Skeletor, a Voronoi-based hierarchical filament finder that reconstructs filament spines and sub-filaments from discrete tracers. These tools are then applied to study filament phase-space structure, reporting coherent radial infall, multistreaming, caustic-like features, and a hierarchy of sub-filaments. The central dynamical claims are that filaments have physically meaningful boundaries and that stacked phase-space profiles reveal a universal or quasi-universal structure.

Significance. The manuscript has several genuine strengths. The Sahyadri suite is carefully validated against Halofit and Tinker predictions (§2.4.2, Appendix A.3), and its improved mass resolution is quantified clearly. The FilGen/FilAPT calibration framework is a valuable contribution: it provides controlled realizations with known truth, and the optimized Fourier smoothing demonstrably reduces reconstruction biases (§3.3–3.4). Skeletor is a novel method that incorporates hierarchy in a principled way and does not require gridding of tracers. The public release of code and data products is also commendable. If the phase-space results were robust, the thesis would constitute a significant step toward a physical, dynamics-based description of filaments. However, as detailed below, the central phase-space claims currently rest on a radius definition that is partly circular, so the dynamical picture--coherent infall, filament boundaries, and the distinctiveness of sub-filaments--needs additional independent validation before those claims can be accepted.

major comments (2)

[§4.3.6, Figs. 5.2, 6.6, 6.8] The comparison of alternative radius definitions in Fig. 6.8 is performed in bins of Rv after the sample has already been selected and scaled by Rv, so it does not break the circularity. An independent radius estimator (e.g., from density gradient or velocity dispersion) should be computed per filament, and the correlation between Rv and that estimator should be assessed without conditioning on Rv. Unless the phase-space features are shown to persist with an independently defined radius, the central claim of coherent infall and filament boundaries is not yet supported.
[§6.3.4, Fig. 6.5] The same concern applies to the substructure analysis in Chapter 5, where parent and sub-filament profiles are compared using Rv-scaled radial distances (Fig. 5.2 and Fig. 4.10). The claim that sub-filaments are 'distinctly different' is based on the same velocity-defined radius and the same quality cuts. Please show whether the differences persist when profiles are compared in absolute radius or with a radius definition that does not rely on the infall minimum.

minor comments (4)

[Appendix C.2] Typo in figure caption: 'panles' should be 'panels'. There are also several similar typographical and formatting issues throughout (e.g., 'wheras' in the Appendix C.4 caption, inconsistent spacing in 'er f'). A careful proofreading pass is needed.
[§3.4.1] The description of the optimized Fourier smoothing is clear but the connection to the earlier FilAPT module could be made more explicit. In particular, the reader would benefit from a statement of how the optimization criterion behaves when the true profile is not known (as in real applications), and whether the method has been tested on mock filaments with a wide range of signal-to-noise.
[Chapter 6] The phase-space plots (Fig. 6.10) and the interpretation in terms of multistreaming are interesting, but the figure labels are small and the text does not state the number of filaments used to produce the stacked distribution. Adding the sample size and the uncertainty on the median velocity would strengthen the presentation.
[§2.4.1] The claim that 'Sahyadri resolves halos down to M_min = 3.2e9 h−1 M_sun' relies on a 40-particle threshold. The manuscript could state more explicitly how the results depend on this resolution threshold, particularly for the VVF and kNN statistics, since these are sensitive to the lowest-mass tracers.

Circularity Check

2 steps flagged · score 6.0 of 10

Phase-space 'boundary' and coherent-infall features are largely built into the Rv definition and the Rv cut; other results (multistreaming, density profiles) remain independent.

self definitional [Ch. 4 §4.3.6 / Fig. 4.5 caption; Ch. 5 Fig. 5.2 caption]
"The red curve shows the quadratic fit used to locate the velocity dip. The solid vertical line indicates the final filament radius Rv, defined by the location of largest radial infall. ... The radial distance is scaled by the radius of the filament, Rv."

Because Rv is defined as the location of the vr dip, stacking profiles in units of r/Rv places the dip at r/Rv=1 by construction. The thesis then presents this dip as a discovered 'filament boundary' and 'coherent infall' feature. The existence of negative vr at small radii is an independent measurement, but the specific claim that the boundary/infall feature sits at r/Rv≈1 is a restatement of the definition, not an empirical discovery.
fitted input called prediction [Ch. 6 Fig. 6.5 caption; Ch. 6 Figs. 6.6, 6.8]
"The main population shows the expected positive correlation between filament radius and node mass, while a secondary population at low Rv arises from systems where the fitting procedure identifies an unphysical inner minimum in the radial velocity profile. The vertical dashed line marks the cut at Rv = 0.6 h−1Mpc adopted for the remainder of the analysis."

The sample is cleaned by removing systems whose quadratic fit yields Rv < 0.6 h−1Mpc, described as an 'unphysical inner minimum'. These are precisely the objects that do not conform to the assumed single-infall profile used to define Rv. After this cut, the stacked profiles are presented as evidence of coherent infall and universal filament boundaries. The agreement with the assumed profile is therefore partly enforced by sample selection, so the 'prediction' of coherent infall is not independent of the fitted definition and cut.

full rationale

The central dynamical claim—that filament boundaries and coherent infall features appear at r/Rv≈1—is partially circular. Rv is defined as the location of maximum radial infall (the vr minimum) via a quadratic fit, and then all stacked phase-space profiles are scaled by Rv. This forces the infall dip to appear at r/Rv=1 by construction. The additional cut at Rv=0.6 h−1Mpc removes the secondary population whose fits show an 'unphysical inner minimum', i.e., the systems that most strongly violate the assumed single-infall profile; the cleaned sample is then used to report coherent inflow and boundary features, making the agreement with the assumed profile partly a selection effect. However, the thesis also contains genuinely independent content: the multistreaming and caustic-like phase-space features are not guaranteed by the radius definition, the density and dispersion profiles are measured without imposing the dip position, the substructure classification is geometric rather than velocity-based, and the Sahyadri suite is validated against external fitting functions (Halofit, Tinker). The optimized-smoothing claim is checked against known ground-truth profiles in the FilGen framework, so it is not circular despite its heuristic objective. No load-bearing self-citation chain or imported uniqueness theorem was found. Score 6 reflects partial circularity of the boundary/infall claim, not full circularity of the thesis.

Assumptions & free parameters 6 free parameters · 6 assumptions · 1 invented entities

The central claims rest on a moderate number of adjustable parameters, mostly in the mock generator, the filament finder's thresholds, and the radius definition. The most impactful free parameters are the Rv quality cut and the smoothing optimization target, because they shape the physical conclusions. The assumptions are standard CDM cosmology plus the paper-specific hierarchy and radius definitions, which are the main load-bearing premises.

free parameters (6)

FilGen velocity ansatz parameters (V0z, V0r, sigma0, a, b, c, u, g) = V0z=V0r=250 km/s, sigma0=300 km/s, a=0.125, b=2.5, c=15, u=8, g=0.5
Chosen by hand to 'approximately match' the radial velocity profiles of [157] (Section 3.3.2.1). These set the ground truth in the calibration mocks, so the demonstrated biases and the performance of the smoothing method depend on them.
Anisotropy threshold alpha_th = 95th percentile of random-catalogue alpha distribution (default)
Used in Skeletor to select filament-like Voronoi cells (Appendix C.3). Shifting this threshold changes the recovered filament population.
Connectivity parameter dcut = l_mean (mean inter-tracer spacing)
Controls how filament segments are linked into spines (Appendix C.4). The length distribution and hierarchy collapse are sensitive to this choice.
Hierarchy mass thresholds = Mass bins used in the mass-thresholded hierarchy (Appendix C.2)
Define parent and sub-filament levels. Sensitivity tests show little variation, but the classification is constructed from these thresholds.
Filament radius quality cut = Rv > 0.6 h^-1 Mpc
Removes a 'secondary population' of filaments whose fitted radial velocity minima are deemed unphysical (Chapter 6, Figure 6.5). The reported phase-space trends depend on this cut.
Smoothing parameters in optimized Fourier/neighbour smoothing = Chosen per filament by minimizing the width of the inferred density profile
The optimization objective assumes that the true density profile is narrow, which is part of the circularity concern; the selected smoothing scale affects all recovered profiles (Appendix B.5).

assumptions (6)

standard math FLRW background and Newtonian N-body dynamics for sub-horizon structure formation
Invoked in Chapter 2 (Eqs. 1.1-2.3). The simulations and all analysis assume this framework.
domain assumption Cold dark matter with collisionless particles and no massive neutrinos
Stated in Section 2.4.1: 'massive neutrinos are not included'. The Sahyadri simulations therefore probe a particular dark matter model.
ad hoc to paper The cosmic web has a hierarchical filament-in-filament structure that can be decomposed via mass thresholds
Core to Skeletor and the sub-filament analysis (Chapters 4 and 5). The paper does not prove this decomposition is unique or physically preferred.
ad hoc to paper The location of maximum radial infall defines the 'true' filament radius
Used to define Rv in Section 4.3.6 and throughout Chapter 6. This is a dynamical definition, not derived from first principles, and it creates the circularity with the stacked profiles.
domain assumption The analytic velocity ansatz in Eqs. 3.1-3.3 represents realistic cosmic filament kinematics
The mock filament ground truth in Chapter 3 is built from this ansatz, so the calibration results measure how well the tools recover this particular model, not necessarily real filaments.
domain assumption Voronoi cell anisotropy is a faithful proxy for filamentary environment
The motivating observation in Chapter 4 (Figure 4.1). If tracer bias makes Voronoi cells anisotropic for other reasons, the Skeletor selection would be contaminated.

invented entities (1)

Sub-filaments (filamentary substructures embedded within parent filaments)
purpose: To classify nested filamentary systems and study their separate statistical and geometric properties (Chapters 4 and 5).
Sub-filaments are defined by the mass-hierarchy classifier in Skeletor. No independent observable signature is provided that would distinguish a sub-filament from a parent filament in galaxy surveys.

how reviews work

0 comments

Cite this review

Pith. "Pith review of Cosmic Velocity Flows: from Theory to Observations." pith.science (2026). https://pith.science/paper/JMBJJDVG

@misc{pith2026260803530,
  author       = {Pith},
  title        = {Pith review of: Cosmic Velocity Flows: from Theory to Observations},
  year         = {2026},
  howpublished = {\url{https://pith.science/paper/JMBJJDVG}},
  note         = {Machine review of arXiv:2608.03530}
}

abstract

The Large-Scale Structure (LSS) of the Universe forms a complex network of nodes, filaments, sheets, and voids known as the Cosmic Web. As current and upcoming galaxy surveys increasingly probe the quasi-linear and non-linear regimes of structure formation, understanding its geometry and dynamics is essential for precision cosmology. In particular, cosmic filaments, which channel matter across the web, are central to these dynamical processes. This thesis develops numerical tools to study the non-linear cosmic web. First, the Sahyadri suite of high-resolution cosmological $N$-body simulations is introduced, providing a framework for precision studies of LSS and its cosmological dependence. A calibration framework for filament reconstruction is then developed using controlled filament realizations, enabling systematic investigation of reconstruction biases. The effects of filament curvature and reconstruction noise on inferred filament properties are quantified, and a novel Fourier-space smoothing approach is introduced to improve profile recovery. The thesis further presents Skeletor, a Voronoi-based filament finder that identifies filamentary structures directly from discrete tracers while explicitly incorporating the hierarchical nature of the cosmic web. A novel framework for classifying sub-filamentary structure is developed. Applying these tools to cosmological simulations reveals distinct properties of filament substructure and provides a detailed view of filament phase space, including coherent inflows, multistreaming, and caustic-like features. Together, these developments provide a framework for studying the geometry, hierarchy, and dynamics of the non-linear cosmic web. More broadly, they contribute to the ongoing effort to build a physically motivated understanding of the non-linear cosmic web beyond traditional measures of clustering.

Figures

Figures reproduced from arXiv: 2608.03530 by the authors.

**Figure 1.1.** Visualization of the large-scale galaxy and quasar distribution mapped by the DESI [PITH_FULL_IMAGE:figures/full_fig_p034_1_1.png] view at source ↗

**Figure 1.2.** Dark matter density fields illustrating the cosmic web at multiple scales, adapted [PITH_FULL_IMAGE:figures/full_fig_p037_1_2.png] view at source ↗

**Figure 2.1.** Stellar mass function using a stellar-to-halo mass relation and a conditional [PITH_FULL_IMAGE:figures/full_fig_p052_2_1.png] view at source ↗

Figures from the paper (47 more)

**Figure 2.2.** Figure 2.2: Comparison of the Sahyadri simulation suite with other large-scale structure simulation efforts. Grey lines indicate simulations with constant particle number assuming Planck 2018 cosmology. Coloured points highlight suites with cosmology variations. The red (black)…

**Figure 2.3.** Figure 2.3: Visualization of the evolution of the dark matter density field as a function of redshift [PITH_FULL_IMAGE:figures/full_fig_p057_2_3.png]

**Figure 2.4.** Figure 2.4: Comparison between AbacusSummit-like and [PITH_FULL_IMAGE:figures/full_fig_p058_2_4.png]

**Figure 2.5.** Figure 2.5: Same as Figure [PITH_FULL_IMAGE:figures/full_fig_p059_2_5.png]

**Figure 2.6.** Figure 2.6: Visualizations of single-cell slices of the tessellated density field at [PITH_FULL_IMAGE:figures/full_fig_p060_2_6.png]

**Figure 2.7.** Figure 2.7: Variation of the matter power spectrum as a function of [PITH_FULL_IMAGE:figures/full_fig_p061_2_7.png]

**Figure 2.8.** Figure 2.8: Comparison of the halo power spectrum (Phh) for different tracers, Ωmvalues, and redshifts. The top panels show Phh for two tracer populations with different number densities, thresholded on Vpeak(see text for details). Solid lines correspond to the fiducial cosmolog…

**Figure 2.9.** Figure 2.9: Variation of the mass function as a function of [PITH_FULL_IMAGE:figures/full_fig_p063_2_9.png]

**Figure 2.10.** Figure 2.10: Same as Figure [PITH_FULL_IMAGE:figures/full_fig_p063_2_10.png]

**Figure 2.11.** Figure 2.11: Same as Figure [PITH_FULL_IMAGE:figures/full_fig_p064_2_11.png]

**Figure 2.12.** Figure 2.12: Spearman rank correlations between halo environment and internal properties, as a [PITH_FULL_IMAGE:figures/full_fig_p066_2_12.png]

**Figure 2.13.** Figure 2.13: Redshift dependence of correlations for the fiducial cosmology. The panels are the [PITH_FULL_IMAGE:figures/full_fig_p066_2_13.png]

**Figure 3.1.** Figure 3.1: Plots showing number density projections of the fiducial filament along the three [PITH_FULL_IMAGE:figures/full_fig_p076_3_1.png]

**Figure 3.2.** Figure 3.2: Various profiles for the fiducial filament model. The left (right) panels show longitudi [PITH_FULL_IMAGE:figures/full_fig_p079_3_2.png]

**Figure 3.3.** Figure 3.3: Projected number density for the thick filament. The panels are the same as Figure [PITH_FULL_IMAGE:figures/full_fig_p080_3_3.png]

**Figure 3.4.** Figure 3.4: Radial and longitudinal density and velocity profiles for the thick filament. The [PITH_FULL_IMAGE:figures/full_fig_p081_3_4.png]

**Figure 3.5.** Figure 3.5: Effect of sampling of the spine on the density and velocity profiles. The panels are [PITH_FULL_IMAGE:figures/full_fig_p084_3_5.png]

**Figure 3.6.** Figure 3.6: Effect of error in spine extraction on the estimated density and velocity profiles. [PITH_FULL_IMAGE:figures/full_fig_p085_3_6.png]

**Figure 3.7.** Figure 3.7: Comparison of optimized and constant smoothing and curvature segregation on the [PITH_FULL_IMAGE:figures/full_fig_p086_3_7.png]

**Figure 3.8.** Figure 3.8: PDFs of lengths lfil of the DisPerSE inferred spines in units of the length lf of the actual spine. Pink colour represents the unsmoothed case, while green and purple colours represent the spines after applying a constant neighbour smoothing and optimized Fourier smo…

**Figure 3.9.** Figure 3.9: Distribution of the parameters of the filaments, [PITH_FULL_IMAGE:figures/full_fig_p089_3_9.png]

**Figure 3.10.** Figure 3.10: Illustration of need for optimized smoothing for a diverse filament set. The left panel [PITH_FULL_IMAGE:figures/full_fig_p089_3_10.png]

**Figure 3.11.** Figure 3.11: Effect of redshift space distortions on the density profiles of straight filaments with [PITH_FULL_IMAGE:figures/full_fig_p091_3_11.png]

**Figure 4.1.** Figure 4.1: Illustration of the geometric motivation behind [PITH_FULL_IMAGE:figures/full_fig_p101_4_1.png]

**Figure 4.2.** Figure 4.2: Schematic overview of the Skeletor algorithm. scales. At each hierarchy level, the most massive halos act as nodes, whereas the filamentary structures connecting them are traced by lower-mass halos arranged along the spine like beads on a string. Progressively loweri…

**Figure 4.3.** Figure 4.3: Distribution of the anisotropy parameter [PITH_FULL_IMAGE:figures/full_fig_p106_4_3.png]

**Figure 4.4.** Figure 4.4: Example of the dipole-minimization smoothing procedure. The radial density profile [PITH_FULL_IMAGE:figures/full_fig_p109_4_4.png]

**Figure 4.5.** Figure 4.5: Example illustrating the estimation of the filament radius. The plot shows the radial [PITH_FULL_IMAGE:figures/full_fig_p110_4_5.png]

**Figure 4.6.** Figure 4.6: Reconstruction of the prominent filament shown in Figure [PITH_FULL_IMAGE:figures/full_fig_p112_4_6.png]

**Figure 4.7.** Figure 4.7: Comparison of filament networks identified by [PITH_FULL_IMAGE:figures/full_fig_p113_4_7.png]

**Figure 4.8.** Figure 4.8: Length distribution of filaments identified by [PITH_FULL_IMAGE:figures/full_fig_p114_4_8.png]

**Figure 4.9.** Figure 4.9: Average radial density (left) and radial velocity (right) profiles of filaments identified [PITH_FULL_IMAGE:figures/full_fig_p115_4_9.png]

**Figure 4.10.** Figure 4.10: Comparison between the stacked radial profiles of parent (black) and sub-filaments [PITH_FULL_IMAGE:figures/full_fig_p116_4_10.png]

**Figure 5.1.** Figure 5.1: Left panel: Distribution of the total node mass, log(M1+M2). Right panel: Distribution of the corresponding node mass ratio, M1/M2. Parent filaments are shown in black and subfilaments in red. Node masses are reported in units of M⊙/h. we perform a second comparison…

**Figure 5.2.** Figure 5.2: Comparison of the radial density and velocity profiles of parent filaments (solid curves) [PITH_FULL_IMAGE:figures/full_fig_p123_5_2.png]

**Figure 6.1.** Figure 6.1: Stacked radial phase-space profiles in ten percentile bins of filament curvature, [PITH_FULL_IMAGE:figures/full_fig_p132_6_1.png]

**Figure 6.2.** Figure 6.2: Illustration of filament curvature. The figure shows the projection of a filament [PITH_FULL_IMAGE:figures/full_fig_p133_6_2.png]

**Figure 6.3.** Figure 6.3: Stacked density and radial velocity profiles in ten percentile bins of filament length. [PITH_FULL_IMAGE:figures/full_fig_p133_6_3.png]

**Figure 6.4.** Figure 6.4: Stacked phase-space profiles in ten percentile bins of the total node mass, [PITH_FULL_IMAGE:figures/full_fig_p135_6_4.png]

**Figure 6.5.** Figure 6.5: Two-dimensional distribution of the velocity-defined filament radius, [PITH_FULL_IMAGE:figures/full_fig_p135_6_5.png]

**Figure 6.6.** Figure 6.6: Stacked phase-space profiles in ten percentile bins of the velocity-defined filament [PITH_FULL_IMAGE:figures/full_fig_p136_6_6.png]

**Figure 6.7.** Figure 6.7: Two-dimensional distribution of the velocity-defined filament radius, [PITH_FULL_IMAGE:figures/full_fig_p137_6_7.png]

**Figure 6.8.** Figure 6.8: Comparison of different filament radius definitions relative to the velocity-defined [PITH_FULL_IMAGE:figures/full_fig_p138_6_8.png]

**Figure 6.9.** Figure 6.9: Individual filament profiles for two representative primary filaments (red and blue). [PITH_FULL_IMAGE:figures/full_fig_p139_6_9.png]

**Figure 6.10.** Figure 6.10: (left panel:) Schematic illustrating the construction of the filament phase-space distribution. The solid black line represents the filament spine made up of discrete segments, with cylinders of radius Rv centred on individual spine segments and oriented perpendicul…

**Figure 6.11.** Figure 6.11: Examples of (x,vx) phase-space diagrams for three individual parent filaments. In all cases, coherent infall towards the filament spine is followed by multistreaming, and eventually a sharp broadening of the velocity distribution in the central regions. Localized en…

**Figure 6.12.** Figure 6.12: Radial velocity distributions, P(vr), at three neighbouring cylindrical radii for a representative parent filament. The left, centre, and right panels correspond to regions dominated by coherent infall, multistreaming, and the central dynamically mixed region, respe…

Discussion (0). Sign in to comment.

Reference graph

Works this paper leans on

192 extracted references · 14 canonical work pages

[1]

Springel, Volker and White, Simon D. M. and Jenkins, Adrian and others , journal =. Simulations of the formation, evolution and clustering of galaxies and quasars , volume =. 2005 , doi =

2005
[2]

2008 , doi =

, month = jan, number =. 2008 , doi =

2008
[3]

2014 , doi =

, month = jan, number =. 2014 , doi =

2014
[4]

2010 , doi =

, month =. 2010 , doi =

2010
[5]

2002 , doi =

, month = dec, number =. 2002 , doi =

2002
[6]

2005 , doi =

, month = nov, number =. 2005 , doi =

2005
[7]

arXiv e-prints , title =
[8]

LSST: From Science Drivers to Reference Design and Anticipated Data Products , volume =

Ivezi. LSST: From Science Drivers to Reference Design and Anticipated Data Products , volume =. The Astrophysical Journal , number =. 2019 , doi =

2019

Show all 192 references

[9]

2018 , doi =

, month = sep, pages =. 2018 , doi =

2018
[10]

2015 , doi =

, month = nov, number =. 2015 , doi =

2015
[11]

2011 , doi =

Philosophical Transactions of the Royal Society of London Series A , month = dec, number =. 2011 , doi =

2011
[12]

2011 , doi =

, month =. 2011 , doi =

2011
[13]

2011 , doi =

, month = nov, number =. 2011 , doi =

2011
[14]

2005 , doi =

, month =. 2005 , doi =

2005
[15]

2021 , doi =

, month =. 2021 , doi =

2021
[16]

2010 , doi =

, month = jan, number =. 2010 , doi =

2010
[17]

2002 , doi =

, month = apr, pages =. 2002 , doi =

2002
[18]

Computational Astrophysics and Cosmology , keywords =

PKDGRAV3: beyond trillion particle cosmological simulations for the next era of galaxy surveys. Computational Astrophysics and Cosmology , keywords =. doi:10.1186/s40668-017-0021-1 , archivePrefix =. 1609.08621 , primaryClass =

arXiv
[19]

2021 , doi =

, month = nov, number =. 2021 , doi =

2021
[20]

2013 , doi =

, month = nov, number =. 2013 , doi =

2013
[21]

2016 , doi =

, month = jan, pages =. 2016 , doi =

2016
[22]

2024 , doi =

, month = may, number =. 2024 , doi =

2024
[23]

1985 , doi =

, month = may, pages =. 1985 , doi =

1985
[24]

2001 , doi =

, month = dec, number =. 2001 , doi =

2001
[25]

and Hearin, Andrew P

Behroozi, Peter and Wechsler, Risa H. and Hearin, Andrew P. and Conroy, Charlie , journal =. UniverseMachine: The correlation between galaxy growth and dark matter halo assembly from z = 0-10 , volume =. 2019 , doi =

2019
[26]

The IllustrisTNG simulations: public data release , volume =

Nelson, Dylan and Pillepich, Annalisa and Springel, Volker and others , journal =. The IllustrisTNG simulations: public data release , volume =. 2019 , doi =

2019
[27]

and Bower, Richard G

Schaye, Joop and Crain, Robert A. and Bower, Richard G. and others , journal =. The EAGLE project: simulating the evolution and assembly of galaxies and their environments , volume =. 2015 , doi =

2015
[28]

SIMBA: Cosmological simulations with black hole growth and feedback , volume =

Dav. SIMBA: Cosmological simulations with black hole growth and feedback , volume =. Monthly Notices of the Royal Astronomical Society , number =. 2019 , doi =

2019
[29]

2019 , doi =

The Open Journal of Astrophysics , month = jun, number =. 2019 , doi =

2019
[30]

de Jong, R. S. and Agertz, O. and Berbel, A. Agudo and others , journal =. 4MOST: Project overview and information for the First Call for Proposals , volume =. 2019 , doi =

2019
[31]

and Chiba, Masashi and others , journal =

Takada, Masahiro and Ellis, Richard S. and Chiba, Masashi and others , journal =. Extragalactic science, cosmology, and Galactic archaeology with the Subaru Prime Focus Spectrograph , volume =. 2014 , doi =

2014
[32]

and others , journal =

Ishiyama, Tomoaki and Prada, Francisco and Klypin, Anatoly A. and others , journal =. The Uchuu simulations: Data Release 1 and dark matter halo concentrations , volume =. 2021 , doi =

2021
[33]

Introducing the Illustris Project: simulating the coevolution of dark and visible matter in the Universe , volume =

Vogelsberger, Mark and Genel, Shy and Springel, Volker and others , journal =. Introducing the Illustris Project: simulating the coevolution of dark and visible matter in the Universe , volume =. 2014 , doi =

2014
[34]

First results from the IllustrisTNG simulations: the galaxy colour bimodality , volume =

Pillepich, Annalisa and Nelson, Dylan and Hernquist, Lars and others , journal =. First results from the IllustrisTNG simulations: the galaxy colour bimodality , volume =. 2018 , doi =

2018
[35]

Boylan-Kolchin, Michael and Springel, Volker and White, Simon D. M. and Jenkins, Adrian and Lemson, Gerard , journal =. Resolving cosmic structure formation with the Millennium-II Simulation , volume =. 2009 , doi =

2009
[36]

and Trujillo-Gomez, Sebastian and Primack, Joel , journal =

Klypin, Anatoly A. and Trujillo-Gomez, Sebastian and Primack, Joel , journal =. Dark Matter Halos in the Standard Cosmological Model: Results from the Bolshoi Simulation , volume =. 2011 , doi =

2011
[37]

MultiDark simulations: the story of dark matter halo concentrations and density profiles , volume =

Klypin, Anatoly and Yepes, Gustavo and Gottl. MultiDark simulations: the story of dark matter halo concentrations and density profiles , volume =. Monthly Notices of the Royal Astronomical Society , number =. 2016 , doi =

2016
[38]

The Quijote simulations , volume =

Villaescusa-Navarro, Francisco and Hahn, ChangHoon and Massara, Elena and others , journal =. The Quijote simulations , volume =. 2020 , doi =

2020
[39]

and Tinker, Jeremy L

DeRose, Joseph and Wechsler, Risa H. and Tinker, Jeremy L. and others , journal =. The Aemulus Project. II. Emulating the Halo Mass Function , volume =. 2019 , doi =

2019
[40]

McClintock, Thomas and Varga, T. N. and Gruen, D. and others , journal =. Dark Energy Survey Year 1 Results: Weak Lensing Mass Calibration of redMaPPer Galaxy Clusters , volume =. 2019 , doi =

2019
[41]

Dark Quest

Nishimichi, Takahiro and Shirata, Akihito and Taruya, Atsushi and others , journal =. Dark Quest. I. Fast and Accurate Emulation of Halo Clustering Statistics and Its Application to Galaxy Clustering , volume =. 2019 , doi =

2019
[42]

and Garrison, Lehman H

Maksimova, Nina A. and Garrison, Lehman H. and Hadzhiyska, Boryana and others , journal =. AbacusSummit: a massive set of high-accuracy, high-resolution N-body simulations , volume =. 2021 , doi =

2021
[43]

Using GAMA to probe the impact of small-scale galaxy physics on nonlinear redshift-space distortions , volume =

Alam, Shadab and Peacock, John A and Farrow, Daniel J and Loveday, J and Hopkins, A M , journal =. Using GAMA to probe the impact of small-scale galaxy physics on nonlinear redshift-space distortions , volume =. 2021 , doi =

2021
[44]

, keywords =

Towards unbiased recovery of cosmic filament properties: the role of spine curvature and optimized smoothing. , keywords =. doi:10.1088/1475-7516/2024/09/041 , archivePrefix =. 2402.18669 , primaryClass =

2024 arXiv
[45]

and Ruiz-Macias, Omar and others , journal =

Hahn, ChangHoon and Wilson, Michael J. and Ruiz-Macias, Omar and others , journal =. The DESI Bright Galaxy Survey: Final Target Selection, Design, and Validation , volume =. 2023 , doi =

2023
[46]

Towards testing the theory of gravity with DESI: summary statistics, model predictions and future simulation requirements , volume =

Yildiz, Eleonora and Biagetti, Matteo and Seljak, Uro. Towards testing the theory of gravity with DESI: summary statistics, model predictions and future simulation requirements , volume =. Monthly Notices of the Royal Astronomical Society , number =. 2020 , doi =

2020
[47]

and McIntosh, Daniel H

Bell, Eric F. and McIntosh, Daniel H. and Katz, Neal and Weinberg, Martin D. , journal =. The Optical and Near-Infrared Properties of Galaxies. I. Luminosity and Stellar Mass Functions , volume =. 2003 , doi =

2003
[48]

and Hill, David T

Driver, Simon P. and Hill, David T. and Kelvin, Lee S. and others , journal =. Galaxy and Mass Assembly (GAMA): survey diagnostics and core data release , volume =. 2011 , doi =

2011
[49]

Baldry, I. K. and Driver, S. P. and Loveday, J. and others , journal =. Galaxy And Mass Assembly (GAMA): the galaxy stellar mass function at z < 0.06 , volume =. 2012 , doi =

2012
[50]

and Tinker, Jeremy L

Wetzel, Andrew R. and Tinker, Jeremy L. and Conroy, Charlie and van den Bosch, Frank C. , journal =. Galaxy Evolution in Groups and Clusters: Satellite Star Formation Histories and Quenching Time-scales in a Hierarchical Universe , volume =. 2013 , doi =

2013
[51]

and Greene, Jenny E

Reines, Amy E. and Greene, Jenny E. and Geha, Marla , journal =. Dwarf Galaxies with Optical Signatures of Active Massive Black Holes , volume =. 2013 , doi =

2013
[52]

and Yuan, Wenlong and Macri, Lucas M

Riess, Adam G. and Yuan, Wenlong and Macri, Lucas M. and others , journal =. A Comprehensive Measurement of the Local Value of the Hubble Constant with 1 km s ^. 2022 , doi =

2022
[53]

Planck 2018 results. VI. Cosmological parameters , volume =. Astronomy & Astrophysics , pages =. 2020 , doi =

2018
[54]

2024 , doi =

arXiv e-prints , month =. 2024 , doi =

2024
[55]

and Aguilar, J

Abdul Karim, M. and Aguilar, J. and Ahlen, S. and Alam, S. and Allen, L. and Prieto, C. Allende and Alves, O. and Anand, A. and Andrade, U. and Armengaud, E. and Aviles, A. and Bailey, S. and Baltay, C. and Bansal, P. and Bault, A. and Behera, J. and BenZvi, S. and Bianchi, D....

2025
[56]

Galaxy power spectrum multipoles covariance in perturbation theory , volume =

Wadekar, Digvijay and Scoccimarro, Rom. Galaxy power spectrum multipoles covariance in perturbation theory , volume =. Physical Review D , number =. 2020 , doi =

2020
[57]

Galaxy clustering in the DESI Legacy Survey and its imprint on the CMB , volume =

Hang, Qianjun and Alam, Shadab and Peacock, John A and Cai, Yan-Chuan , journal =. Galaxy clustering in the DESI Legacy Survey and its imprint on the CMB , volume =. 2020 , doi =

2020
[58]

, journal =

Ishiyama, Tomoaki and Prada, Francisco and Klypin, Anatoly A. , journal =. Evolution of clustering in cosmological models with time-varying dark energy , volume =. 2025 , doi =

2025
[59]

2013 , doi =

, month =. 2013 , doi =

2013
[60]

2018 , doi =

, month =. 2018 , doi =

2018
[61]

2020 , doi =

, month =. 2020 , doi =

2020
[62]

2007 , doi =

, month =. 2007 , doi =

2007
[63]

2015 , doi =

, month =. 2015 , doi =

2015
[64]

2016 , doi =

, month =. 2016 , doi =

2016
[65]

2022 , doi =

, month =. 2022 , doi =

2022
[66]

2012 , doi =

, month =. 2012 , doi =

2012
[67]

2008 , doi =

, month =. 2008 , doi =

2008
[68]

Nouvelles applications des paramètres continus à la théorie des formes quadratiques

Voronoi, Georges , journal =. Nouvelles applications des paramètres continus à la théorie des formes quadratiques. Deuxième mémoire. Recherches sur les parallélloèdres primitifs. , volume =. 1908 , url =

1908
[69]

2020 , doi =

Banerjee, Arka and Abel, Tom , journal =. 2020 , doi =

2020
[70]

2021 , doi =

Banerjee, Arka and Abel, Tom , journal =. 2021 , doi =

2021
[71]

2023 , doi =

Banerjee, Arka and Abel, Tom , journal =. 2023 , doi =

2023
[72]

2025 , doi =

Gangopadhyay, Kwanit and Banerjee, Arka and Abel, Tom , journal =. 2025 , doi =

2025
[73]

2022 , doi =

Banerjee, Arka and Kokron, Nickolas and Abel, Tom , journal =. 2022 , doi =

2022
[74]

2019 , doi =

, month =. 2019 , doi =

2019
[75]

2025 , doi =

, month =. 2025 , doi =

2025
[76]

1998 , doi =

, month =. 1998 , doi =

1998
[77]

The Cosmic Linear Anisotropy Solving System (CLASS)

Blas, Diego and Lesgourgues, Julien and Tram, Thomas , journal =. The Cosmic Linear Anisotropy Solving System (CLASS). Part II: Approximation schemes , volume =. 2011 , doi =

2011
[78]

The Cosmic Linear Anisotropy Solving System (CLASS) I: Overview , year =

Lesgourgues, Julien , journal =. The Cosmic Linear Anisotropy Solving System (CLASS) I: Overview , year =
[79]

2023 , doi =

, month =. 2023 , doi =

2023
[80]

and Garrison, Lehman H

Maksimova, Nina A. and Garrison, Lehman H. and Hadzhiyska, Boryana and Bose, Sownak and Eisenstein, Daniel J. , journal =. AbacusSummit: a massive set of high-accuracy, high-resolution N-body simulations , volume =. 2021 , doi =

2021
[81]

arXiv , author =:1712.05768 , journal =

doi:10.3847/1538-4365/aabfd3 , eid =. arXiv , author =:1712.05768 , journal =

arXiv
[82]

, keywords =

Hydrodynamical Simulations of the Galaxy Population: Enduring Successes and Outstanding Challenges. , keywords =. doi:10.1146/annurev-astro-041923-043618 , archivePrefix =. 2309.17075 , primaryClass =

arXiv
[83]

Nature Reviews Physics , keywords =

Cosmological simulations of galaxy formation. Nature Reviews Physics , keywords =. doi:10.1038/s42254-019-0127-2 , archivePrefix =. 1909.07976 , primaryClass =

1909 arXiv
[84]

, keywords =

The clustering of galaxies in the completed SDSS-III Baryon Oscillation Spectroscopic Survey: cosmological analysis of the DR12 galaxy sample. , keywords =. doi:10.1093/mnras/stx721 , archivePrefix =. 1607.03155 , primaryClass =

arXiv
[85]

, keywords =

Assembly bias in the clustering of dark matter haloes. , keywords =. doi:10.1111/j.1745-3933.2007.00292.x , archivePrefix =. astro-ph/0611921 , primaryClass =

2007
[86]

, keywords =

The Sloan Digital Sky Survey: Technical Summary. , keywords =. doi:10.1086/301513 , archivePrefix =. astro-ph/0006396 , primaryClass =

arXiv
[87]

, keywords =

Detection of the Baryon Acoustic Peak in the Large-Scale Correlation Function of SDSS Luminous Red Galaxies. , keywords =. doi:10.1086/466512 , archivePrefix =. astro-ph/0501171 , primaryClass =

arXiv
[88]

IEEE Proceedings , year = 2009, month = aug, volume =

The Square Kilometre Array. IEEE Proceedings , year = 2009, month = aug, volume =. doi:10.1109/JPROC.2009.2021005 , adsurl =

2009
[89]

, keywords =

Observational probes of cosmic acceleration. , keywords =. doi:10.1016/j.physrep.2013.05.001 , archivePrefix =. 1201.2434 , primaryClass =

2013 arXiv
[90]

doi:10.1093/mnras/stx1976 , eprint =

, keywords =. doi:10.1093/mnras/stx1976 , eprint =

doi
[92]

doi:10.1086/192267 , journal =

doi
[93]

, keywords =

How filaments of galaxies are woven into the cosmic web. , keywords =. doi:10.1038/380603a0 , archivePrefix =. astro-ph/9512141 , primaryClass =

arXiv
[94]

doi:10.1093/mnras/sts416 , eprint =

, keywords =. doi:10.1093/mnras/sts416 , eprint =

doi
[95]

doi:10.1093/mnras/stu768 , eprint =

, keywords =. doi:10.1093/mnras/stu768 , eprint =

doi
[96]

doi:10.1086/304888 , eprint =

, keywords =. doi:10.1086/304888 , eprint =

doi
[97]

arXiv , author =:2003.09697 , journal =

doi:10.1051/0004-6361/202037986 , eid =. arXiv , author =:2003.09697 , journal =

2003 arXiv
[98]

arXiv , author =:2002.01486 , journal =

doi:10.1051/0004-6361/202037647 , eid =. arXiv , author =:2002.01486 , journal =

2002 arXiv
[99]

doi:10.1093/mnras/stz1106 , eprint =

, keywords =. doi:10.1093/mnras/stz1106 , eprint =

doi
[100]

doi:10.1111/j.1365-2966.2010.17263.x , eprint =

, keywords =. doi:10.1111/j.1365-2966.2010.17263.x , eprint =

2010
[101]

, keywords =

Galaxy morphology in rich clusters: implications for the formation and evolution of galaxies. , keywords =. doi:10.1086/157753 , adsurl =

doi
[102]

, keywords =

Physical Properties and Environments of Nearby Galaxies. , keywords =. doi:10.1146/annurev-astro-082708-101734 , archivePrefix =. 0908.3017 , primaryClass =

arXiv
[104]

, keywords =

Swirling around filaments: are large-scale structure vortices spinning up dark haloes?. , keywords =. doi:10.1093/mnras/stu2289 , archivePrefix =. 1310.3801 , primaryClass =

arXiv
[105]

doi:10.1093/mnras/227.1.1 , journal =

doi
[106]

, keywords =

Redshift-space distortions, pairwise velocities, and nonlinearities. , keywords =. doi:10.1103/PhysRevD.70.083007 , archivePrefix =. astro-ph/0407214 , primaryClass =

arXiv
[107]

The Evolving Universe , year = 1998, editor =

Linear Redshift Distortions: a Review. The Evolving Universe , year = 1998, editor =. doi:10.1007/978-94-011-4960-0_17 , archivePrefix =. astro-ph/9708102 , primaryClass =

1998 arXiv
[108]

, keywords =

A test of the nature of cosmic acceleration using galaxy redshift distortions. , keywords =. doi:10.1038/nature06555 , archivePrefix =. 0802.1944 , primaryClass =

1944 arXiv
[109]

doi:10.1016/S0370-1573(02)00135-7 , eprint =

, keywords =. doi:10.1016/S0370-1573(02)00135-7 , eprint =

doi
[110]

, keywords =

Critical look at cosmological perturbation theory techniques. , keywords =. doi:10.1103/PhysRevD.80.043531 , archivePrefix =. 0905.0479 , primaryClass =

arXiv
[111]

, keywords =

Cosmological non-linearities as an effective fluid. , keywords =. doi:10.1088/1475-7516/2012/07/051 , archivePrefix =. 1004.2488 , primaryClass =

2012 arXiv
[112]

Journal of High Energy Physics , keywords =

The effective field theory of cosmological large scale structures. Journal of High Energy Physics , keywords =. doi:10.1007/JHEP09(2012)082 , archivePrefix =. 1206.2926 , primaryClass =

2012 arXiv
[113]

doi:10.1086/184625 , journal =

doi
[115]

arXiv , author =:2308.16186 , journal =

doi:10.48550/arXiv.2308.16186 , eid =. arXiv , author =:2308.16186 , journal =

doi arXiv
[117]

doi:10.1111/j.1365-2966.2006.11318.x , eprint =

, keywords =. doi:10.1111/j.1365-2966.2006.11318.x , eprint =

2006
[118]

doi:10.1093/mnras/stx2638 , eprint =

, keywords =. doi:10.1093/mnras/stx2638 , eprint =

doi
[119]

doi:10.1093/mnras/stu1227 , eprint =

, keywords =. doi:10.1093/mnras/stu1227 , eprint =

doi
[120]

doi:10.1111/j.1365-2966.2009.15271.x , eprint =

, keywords =. doi:10.1111/j.1365-2966.2009.15271.x , eprint =

2009
[121]

doi:10.1093/mnras/sty191 , eprint =

, keywords =. doi:10.1093/mnras/sty191 , eprint =

doi
[122]

doi:10.1093/mnras/stx873 , eprint =

, keywords =. doi:10.1093/mnras/stx873 , eprint =

doi
[123]

doi:10.1111/j.1365-2966.2005.09451.x , eprint =

, keywords =. doi:10.1111/j.1365-2966.2005.09451.x , eprint =

2005
[124]

American Astronomical Society Meeting Abstracts , eid =
[125]

arXiv , author =:1301.6792 , journal =

doi:10.1088/0004-637X/766/2/115 , eid =. arXiv , author =:1301.6792 , journal =

arXiv
[126]

doi:10.1093/mnras/staa1779 , eprint =

, keywords =. doi:10.1093/mnras/staa1779 , eprint =

doi
[127]

arXiv , author =:1507.05926 , journal =

doi:10.1051/0004-6361/201525861 , eid =. arXiv , author =:1507.05926 , journal =

arXiv
[128]

arXiv , author =:2107.08663 , journal =

doi:10.3847/1538-4357/ac15f1 , eid =. arXiv , author =:2107.08663 , journal =

arXiv
[129]

arXiv , author =:2402.11678 , journal =

arXiv
[130]

Trudy Astrofizicheskogo Instituta Alma-Ata , month =
[131]

doi:10.1086/508988 , eprint =

, keywords =. doi:10.1086/508988 , eprint =

doi
[133]

doi:10.1093/mnras/stv513 , eprint =

, keywords =. doi:10.1093/mnras/stv513 , eprint =

doi
[134]

arXiv , author =:1403.5499 , journal =

doi:10.1103/PhysRevLett.112.251302 , eid =. arXiv , author =:1403.5499 , journal =

arXiv
[135]

doi:10.1093/mnras/stac2564 , eprint =

, keywords =. doi:10.1093/mnras/stac2564 , eprint =

doi
[136]

arXiv e-prints , keywords =

Universal Dark-matter Density Profiles of Cosmic Filaments. arXiv e-prints , keywords =. doi:10.48550/arXiv.2604.05033 , archivePrefix =. 2604.05033 , primaryClass =

doi arXiv
[139]

doi:10.1111/j.1365-2966.2011.18394.x , eprint =

, keywords =. doi:10.1111/j.1365-2966.2011.18394.x , eprint =

2011
[140]

, keywords =

Minimal spanning trees, filaments and galaxy clustering. , keywords =. doi:10.1093/mnras/216.1.17 , adsurl =

doi
[141]

, keywords =

Detection and analysis of cluster-cluster filaments. , keywords =. doi:10.1093/mnras/staa3112 , archivePrefix =. 1911.06768 , primaryClass =

1911 arXiv
[143]

, keywords =

Cosmic web, multistream flows, and tessellations. , keywords =. doi:10.1103/PhysRevD.85.083005 , archivePrefix =. 1111.2366 , primaryClass =

arXiv
[144]

arXiv e-prints , keywords =

Sahyadri: A simulation suite for the cosmology dependence of the Cosmic Web. arXiv e-prints , keywords =. doi:10.48550/arXiv.2601.07924 , archivePrefix =. 2601.07924 , primaryClass =

doi arXiv
[145]

doi:10.1093/mnras/stab015 , eprint =

, keywords =. doi:10.1093/mnras/stab015 , eprint =

doi
[146]

arXiv , author =:2209.05495 , journal =

doi:10.1051/0004-6361/202244935 , eid =. arXiv , author =:2209.05495 , journal =

arXiv
[147]

doi:10.1093/mnras/stad3208 , eprint =

, keywords =. doi:10.1093/mnras/stad3208 , eprint =

doi
[148]

arXiv , author =:2103.06619 , journal =

doi:10.1051/0004-6361/202039169 , eid =. arXiv , author =:2103.06619 , journal =

arXiv
[149]

arXiv , author =:2402.04837 , journal =

doi:10.48550/arXiv.2402.04837 , eid =. arXiv , author =:2402.04837 , journal =

doi arXiv
[150]

Resumming cosmological perturbations via the Lagrangian picture: One-loop results in real space and in redshift space , author =. Phys. Rev. D , volume =. 2008 , month =. doi:10.1103/PhysRevD.77.063530 , url =

2008 doi
[151]

, keywords =

Stabilizing simulation-based cosmological Fisher forecasts: a case study using the Voronoi volume function. , keywords =. doi:10.1088/1475-7516/2026/03/040 , archivePrefix =. 2506.16408 , primaryClass =

2026
[152]

arXiv , author =:2309.08659 , journal =

doi:10.48550/arXiv.2309.08659 , eid =. arXiv , author =:2309.08659 , journal =

doi arXiv
[153]

doi:10.1111/j.1365-2966.2012.21911.x , eprint =

, keywords =. doi:10.1111/j.1365-2966.2012.21911.x , eprint =

2012
[154]

doi:10.1046/j.1365-8711.2001.04222.x , eprint =

, keywords =. doi:10.1046/j.1365-8711.2001.04222.x , eprint =

2001
[155]

doi:10.1093/mnras/282.2.436 , eprint =

, keywords =. doi:10.1093/mnras/282.2.436 , eprint =

doi
[156]

doi:10.1111/j.1745-3933.2011.01081.x , eprint =

, keywords =. doi:10.1111/j.1745-3933.2011.01081.x , eprint =

2011
[157]

arXiv , author =:1101.4017 , journal =

doi:10.1088/1475-7516/2011/05/010 , eid =. arXiv , author =:1101.4017 , journal =

2011 arXiv
[158]

arXiv , author =:2307.13754 , journal =

doi:10.48550/arXiv.2307.13754 , eid =. arXiv , author =:2307.13754 , journal =

doi arXiv
[159]

doi:10.1086/432084 , eprint =

, keywords =. doi:10.1086/432084 , eprint =

doi
[160]

doi:10.1093/mnras/sts006 , eprint =

, keywords =. doi:10.1093/mnras/sts006 , eprint =

doi
[161]

, isbn =

Apostol, T.M. , isbn =. Calculus, Volume I, 2nd Ed One-variable Calculus, with an Introduction to Linear Algebra , url =
[162]

doi:10.1086/170520 , journal =

doi
[163]

arXiv , author =:2205.07906 , journal =

doi:10.48550/arXiv.2205.07906 , eid =. arXiv , author =:2205.07906 , journal =

doi arXiv
[165]

, keywords =

ZOBOV: a parameter-free void-finding algorithm. , keywords =. doi:10.1111/j.1365-2966.2008.13180.x , archivePrefix =. 0712.3049 , primaryClass =

2008
[167]

Astronomy and Computing , keywords =

VIDE: The Void IDentification and Examination toolkit. Astronomy and Computing , keywords =. doi:10.1016/j.ascom.2014.10.002 , archivePrefix =. 1406.1191 , primaryClass =

2014 arXiv
[168]

DTFE: The Delaunay tessellation field estimator
[169]

, keywords =

Continuous fields and discrete samples: reconstruction through Delaunay tessellations. , keywords =. doi:10.48550/arXiv.astro-ph/0011007 , archivePrefix =. astro-ph/0011007 , primaryClass =

doi arXiv
[171]

arXiv e-prints , keywords =

Geometry and Morphology of the Cosmic Web: Analyzing Spatial Patterns in the Universe. arXiv e-prints , keywords =. doi:10.48550/arXiv.0912.3448 , archivePrefix =. 0912.3448 , primaryClass =

doi arXiv
[172]

, keywords =

Relative distribution of dark matter, gas, and stars around cosmic filaments in the IllustrisTNG simulation. , keywords =. doi:10.1051/0004-6361/202141974 , archivePrefix =. 2109.06198 , primaryClass =

arXiv
[173]

, keywords =

The Zel'dovich approximation: key to understanding cosmic web complexity. , keywords =. doi:10.1093/mnras/stt2142 , archivePrefix =. 1311.7134 , primaryClass =

arXiv
[174]

, keywords =

The 3D skeleton: tracing the filamentary structure of the Universe. , keywords =. doi:10.1111/j.1365-2966.2007.12685.x , archivePrefix =. 0707.3123 , primaryClass =

2007
[175]

, keywords =

On the connectivity of the cosmic web: theory and implications for cosmology and galaxy formation. , keywords =. doi:10.1093/mnras/sty1643 , archivePrefix =. 1803.11477 , primaryClass =

arXiv
[176]

, keywords =

On the environmental dependence of halo formation. , keywords =. doi:10.1111/j.1365-2966.2004.07733.x , archivePrefix =. astro-ph/0402237 , primaryClass =

2004
[177]

, keywords =

Renormalized cosmological perturbation theory. , keywords =. doi:10.1103/PhysRevD.73.063519 , archivePrefix =. astro-ph/0509418 , primaryClass =

arXiv
[178]

, keywords =

Memory of initial conditions in gravitational clustering. , keywords =. doi:10.1103/PhysRevD.73.063520 , archivePrefix =. astro-ph/0509419 , primaryClass =

arXiv
[179]

, keywords =

Nonlinear evolution of baryon acoustic oscillations. , keywords =. doi:10.1103/PhysRevD.77.023533 , archivePrefix =. 0704.2783 , primaryClass =

arXiv
[180]

Annales de la Soci

Un Univers homog \`e ne de masse constante et de rayon croissant rendant compte de la vitesse radiale des n \'e buleuses extra-galactiques. Annales de la Soci
[181]

Proceedings of the National Academy of Science , year = 1929, month = mar, volume =

A Relation between Distance and Radial Velocity among Extra-Galactic Nebulae. Proceedings of the National Academy of Science , year = 1929, month = mar, volume =. doi:10.1073/pnas.15.3.168 , adsurl =

1929 doi
[182]

doi:10.1515/9780691206721 , adsurl =

Principles of Physical Cosmology. doi:10.1515/9780691206721 , adsurl =

doi
[183]

Cosmological Physics
[184]

, keywords =

The clustering of galaxies in the SDSS-III Baryon Oscillation Spectroscopic Survey: a large sample of mock galaxy catalogues. , keywords =. doi:10.1093/mnras/sts084 , archivePrefix =. 1203.6609 , primaryClass =

arXiv
[185]

, keywords =

Dark Energy Survey Year-1 results: galaxy mock catalogues for BAO. , keywords =. doi:10.1093/mnras/sty1389 , archivePrefix =. 1712.06232 , primaryClass =

arXiv
[186]

, keywords =

Comparing approximate methods for mock catalogues and covariance matrices II: power spectrum multipoles. , keywords =. doi:10.1093/mnras/stz507 , archivePrefix =. 1806.09497 , primaryClass =

arXiv
[187]

Proceedings of the National Academy of Science , keywords =

The frontier of simulation-based inference. Proceedings of the National Academy of Science , keywords =. doi:10.1073/pnas.1912789117 , archivePrefix =. 1911.01429 , primaryClass =

1911 arXiv
[188]

Living Reviews in Computational Astrophysics , keywords =

Large-scale dark matter simulations. Living Reviews in Computational Astrophysics , keywords =. doi:10.1007/s41115-021-00013-z , archivePrefix =. 2112.05165 , primaryClass =

arXiv
[189]

Testing the robustness of simulations for the DESI dark time survey

The DESI N-body simulation project - I. Testing the robustness of simulations for the DESI dark time survey. , keywords =. doi:10.1093/mnras/stac1947 , archivePrefix =. 2112.09138 , primaryClass =

arXiv
[190]

, keywords =

Generating mock galaxy catalogues for flux-limited samples like the DESI Bright Galaxy Survey. , keywords =. doi:10.1093/mnras/stae1503 , archivePrefix =. 2312.08792 , primaryClass =

arXiv
[191]

, keywords =

The Luminosity and Color Dependence of the Galaxy Correlation Function. , keywords =. doi:10.1086/431891 , archivePrefix =. astro-ph/0408569 , primaryClass =

arXiv
[192]

, keywords =

Galaxy Clustering in the Completed SDSS Redshift Survey: The Dependence on Color and Luminosity. , keywords =. doi:10.1088/0004-637X/736/1/59 , archivePrefix =. 1005.2413 , primaryClass =

arXiv
[193]

2LPTIC: 2nd-order Lagrangian Perturbation Theory Initial Conditions
[194]

MUSIC: MUlti-Scale Initial Conditions
[195]

arXiv e-prints , keywords =

Formation and Evolution of Galaxies: Les Houches Lectures. arXiv e-prints , keywords =. doi:10.48550/arXiv.astro-ph/9410043 , archivePrefix =. astro-ph/9410043 , primaryClass =

doi arXiv
[196]

, keywords =

A hierarchical O(N log N) force-calculation algorithm. , keywords =. doi:10.1038/324446a0 , adsurl =

doi
[197]

Journal of Astrophysics and Astronomy , keywords =

TreePM: A Code for Cosmological N-Body Simulations. Journal of Astrophysics and Astronomy , keywords =. doi:10.1007/BF02702282 , archivePrefix =. astro-ph/9911025 , primaryClass =

arXiv
[198]

, keywords =

General relativistic corrections to N -body simulations and the Zel'dovich approximation. , keywords =. doi:10.1103/PhysRevD.92.123517 , archivePrefix =. 1505.04756 , primaryClass =

arXiv
[199]

, keywords =

Linear power spectrum of observed source number counts. , keywords =. doi:10.1103/PhysRevD.84.043516 , archivePrefix =. 1105.5292 , primaryClass =

arXiv
[200]

Classical and Quantum Gravity , keywords =

Relativistic effect in galaxy clustering. Classical and Quantum Gravity , keywords =. doi:10.1088/0264-9381/31/23/234001 , archivePrefix =. 1409.3223 , primaryClass =

arXiv
[201]

, keywords =

Hierarchical reconstruction of the cosmic web, the H-Spine method. , keywords =. doi:10.1093/mnras/stae468 , archivePrefix =. 2308.16186 , primaryClass =

arXiv
[202]

, keywords =

Cosmic web dependence of galaxy clustering and quenching in SDSS. , keywords =. doi:10.1093/mnras/sty3477 , archivePrefix =. 1801.04878 , primaryClass =

arXiv
[203]

General properties

The large scale structure of the universe I. General properties. One-and two-dimensional models. Geophysical and Astrophysical Fluid Dynamics , keywords =. doi:10.1080/03091928208209001 , adsurl =

doi

Pith tools

Reviewed August 5, 2026 · model on record in the stance chip above.

[1] [1]

Springel, Volker and White, Simon D. M. and Jenkins, Adrian and others , journal =. Simulations of the formation, evolution and clustering of galaxies and quasars , volume =. 2005 , doi =

2005

[2] [2]

2008 , doi =

, month = jan, number =. 2008 , doi =

2008

[3] [3]

2014 , doi =

, month = jan, number =. 2014 , doi =

2014

[4] [4]

2010 , doi =

, month =. 2010 , doi =

2010

[5] [5]

2002 , doi =

, month = dec, number =. 2002 , doi =

2002

[6] [6]

2005 , doi =

, month = nov, number =. 2005 , doi =

2005

[7] [7]

arXiv e-prints , title =

[8] [8]

LSST: From Science Drivers to Reference Design and Anticipated Data Products , volume =

Ivezi. LSST: From Science Drivers to Reference Design and Anticipated Data Products , volume =. The Astrophysical Journal , number =. 2019 , doi =

2019