pith. sign in

arxiv: 2605.28644 · v1 · pith:VZAYQLNKnew · submitted 2026-05-27 · 🌌 astro-ph.CO

Exploring non-Poisson satellite occupation in HOD models and its impact on 2- and 3-point galaxy clustering

Antoine Rocher This is my paper

Pith reviewed 2026-06-29 10:39 UTC · model grok-4.3

classification 🌌 astro-ph.CO
keywords halo occupation distributionsatellite occupationgalaxy clusteringConway-Maxwell-Poissoncounts-in-cylindersgalaxy bispectrumnon-Poisson statistics
0
0 comments X

The pith

Non-Poisson satellite numbers in halos change small-scale galaxy clustering by up to 10 percent.

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

Standard HOD models assume satellite galaxies follow a Poisson distribution at fixed halo mass. This paper replaces that assumption with the Conway-Maxwell-Poisson distribution controlled by a single extra parameter that allows the variance to be sub- or super-Poisson. The resulting changes produce clear shifts in projected two-point clustering and in counts-in-cylinders statistics on small scales, while the tree-level galaxy bispectrum on larger scales remains almost unchanged. A reader should care because small-scale clustering measurements are increasingly used to extract cosmological information, so an incorrect variance assumption could bias those inferences.

Core claim

Replacing the Poisson satellite occupation with the CMP distribution at fixed halo mass alters the variance and thereby shifts the projected correlation function by up to 10 percent, the monopole and quadrupole by up to 5 percent, and counts-in-cylinders by up to 30 percent, while the tree-level bispectrum in the Sugiyama basis changes by less than 2 percent for k_max less than or equal to 0.3.

What carries the argument

The Conway-Maxwell-Poisson distribution, which adds a single dispersion parameter ν to the Poisson model and thereby sets the variance of the satellite count at fixed halo mass.

If this is right

  • Small-scale two-point clustering analyses must allow for non-Poisson satellite variance to avoid systematic errors of several percent.
  • Counts-in-cylinders measurements become a direct probe of the satellite variance parameter.
  • Tree-level bispectrum constraints on scales k less than 0.3 remain robust against this modeling choice.
  • Mock catalogs built with the HODDIES package can incorporate the CMP extension once the numerical scheme for λ is inserted.

Where Pith is reading between the lines

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

  • Group catalogs from spectroscopic surveys could measure the actual variance of satellite numbers and thereby constrain ν directly.
  • Surveys that combine small-scale clustering with higher-order statistics may need to marginalize over ν to keep cosmological parameter errors unbiased.
  • The limited effect on the bispectrum suggests that any non-Poisson signal is largely absorbed into the two-point function on the scales currently used for cosmology.

Load-bearing premise

The numerical scheme that links the small- and large-λ regimes for the CMP expectation parameter achieves roughly 5 percent accuracy across the relevant range of ν.

What would settle it

A direct count of satellite galaxies per halo at fixed mass that yields a variance outside the range spanned by 0.5 less than ν less than 2, or measured counts-in-cylinders that deviate from the predicted 30 percent shift when ν is varied.

read the original abstract

Understanding the connection between galaxies and dark matter halos is a central challenge in modern cosmology. The Halo Occupation Distribution (HOD) framework provides a widely used statistical description of how galaxies populate dark matter halos, enabling precise modelling of galaxy clustering. A common assumption in standard HOD models is that the number of satellite galaxies follows a Poisson distribution at fixed halo mass. In this work, we revisit this assumption and introduce the Conway-Maxwell-Poisson (CMP) distribution as a minimal extension of of the Poisson model, which add a single parameter, $\nu$, to explore sub- and super-Poisson behaviour. We derive analytical approximations for the CMP expectation parameter $\lambda$ and develop a numerical scheme that smoothly connects small- and large-$\lambda$ regimes, achieving $\sim5\%$ accuracy for $0.5 < \nu < 2$. Using the \texttt{HODDIES} package, we study the impact of non-Poisson satellite occupations on mock galaxy catalogues and clustering statistics. Variations in the variance of the satellite occupation significantly affect small-scale clustering, producing deviations of up to $10\%$ in projected clustering and $5\%$ in the monopole and quadrupole. We further investigate higher-order statistics using counts-in-cylinders (CiC) and the tree-level galaxy bispectrum. CiC statistics are highly sensitive to changes in the variance, with variations up to $\sim30\%$, while the tree-level galaxy bispectrum (in the Sugiyama basis) is only weakly affected ($<2\%$ up to $k_\mathrm{max} = 0.3$). These results suggest that non-Poisson satellite statistics are important for small-scale analyses, but should have a limited impact on cosmological constraints from power spectrum and bispectrum measurements using large scales $k_\mathrm{max} < 0.3$.

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.

Referee Report

1 major / 1 minor

Summary. The manuscript introduces the Conway-Maxwell-Poisson (CMP) distribution as a one-parameter extension to the standard Poisson satellite occupation in HOD models, controlled by ν. It derives analytical approximations for the CMP mean parameter λ and presents a numerical scheme connecting small- and large-λ regimes that achieves ~5% accuracy for 0.5<ν<2. The scheme is implemented in the HODDIES package to generate mocks, which are then used to quantify the impact of non-Poisson variance on the projected correlation function (deviations up to 10%), monopole and quadrupole (up to 5%), counts-in-cylinders (up to ~30%), and tree-level galaxy bispectrum (<2% up to k_max=0.3).

Significance. If the numerical scheme is shown to be accurate and the reported percentage shifts are robust to its errors, the results would establish that satellite occupation variance is an important modeling choice for small-scale clustering analyses (particularly CiC) while having only limited impact on large-scale power-spectrum and bispectrum cosmology. The work supplies a concrete, minimal extension and quantitative benchmarks that could be adopted or tested by other HOD implementations.

major comments (1)
  1. [Numerical scheme for CMP λ (methods section describing the approximation and its insertion into HODDIES)] The central results rest on inserting the numerical approximation for CMP λ(ν) into HODDIES. The manuscript states that the scheme achieves ~5% accuracy across 0.5<ν<2, but provides no direct comparison to exact CMP root-finding, no error budget on the resulting <N_sat> or variance at the halo masses that dominate small-scale pairs, and no propagation test showing that a 5% λ error produces <1% bias in the quoted 10% wp or 30% CiC shifts. This validation step is load-bearing for attributing the deviations to the physical non-Poisson effect rather than to the approximation.
minor comments (1)
  1. [Abstract] Abstract contains a typographical repetition: 'minimal extension of of the Poisson model'.

Simulated Author's Rebuttal

1 responses · 0 unresolved

We thank the referee for their careful reading of the manuscript and for highlighting the need for stronger validation of the numerical scheme. We address the single major comment below.

read point-by-point responses

  1. Referee: [Numerical scheme for CMP λ (methods section describing the approximation and its insertion into HODDIES)] The central results rest on inserting the numerical approximation for CMP λ(ν) into HODDIES. The manuscript states that the scheme achieves ~5% accuracy across 0.5<ν<2, but provides no direct comparison to exact CMP root-finding, no error budget on the resulting <N_sat> or variance at the halo masses that dominate small-scale pairs, and no propagation test showing that a 5% λ error produces <1% bias in the quoted 10% wp or 30% CiC shifts. This validation step is load-bearing for attributing the deviations to the physical non-Poisson effect rather than to the approximation.

    Authors: We agree that the current presentation lacks sufficient validation of the numerical scheme. In the revised manuscript we will add (i) a direct comparison of the approximate λ(ν) against exact numerical root-finding over the full range 0.5<ν<2, (ii) an error budget on the resulting mean and variance of N_sat evaluated at the halo masses that dominate the small-scale pair counts, and (iii) a propagation test that injects the maximum 5% λ error into the mock generation and quantifies the induced bias in wp, the multipoles, and CiC. These additions will be placed in the methods section and will demonstrate that the reported percentage shifts remain attributable to the non-Poisson variance rather than to the approximation error. revision: yes

Circularity Check

0 steps flagged

No significant circularity; clustering shifts are direct numerical outputs from HOD mocks

full rationale

The paper's central claims consist of measured percentage deviations in wp, monopole/quadrupole, CiC, and bispectrum obtained by inserting the CMP distribution (with parameter ν) into the HODDIES package and running mock catalogs. These shifts are simulation outputs, not quantities defined in terms of ν or λ by construction. The stated ~5% accuracy of the λ(ν) numerical scheme is an independent approximation claim whose validation is not shown to rely on the clustering results themselves. No self-definitional, fitted-input-as-prediction, or load-bearing self-citation steps are present in the provided text; the derivation chain remains self-contained against external benchmarks.

Axiom & Free-Parameter Ledger

1 free parameters · 1 axioms · 0 invented entities

The paper rests on the standard HOD framework plus one new dispersion parameter. No new particles or forces are postulated.

free parameters (1)
  • ν
    Dispersion parameter in the Conway-Maxwell-Poisson distribution that controls deviation from Poisson variance; its value is explored rather than fitted to data in the reported experiments.
axioms (1)
  • domain assumption The Conway-Maxwell-Poisson distribution is a minimal and sufficient extension of the Poisson model for satellite occupation at fixed halo mass.
    Invoked when the authors state that CMP 'add[s] a single parameter, ν, to explore sub- and super-Poisson behaviour'.

pith-pipeline@v0.9.1-grok · 5876 in / 1601 out tokens · 41315 ms · 2026-06-29T10:39:21.432110+00:00 · methodology

discussion (0)

Sign in with ORCID, Apple, or X to comment. Anyone can read and Pith papers without signing in.

Reference graph

Works this paper leans on

60 extracted references · 11 canonical work pages · 2 internal anchors

  1. [1]

    Abareshi, J

    B. Abareshi, J. Aguilar, S. Ahlen, S. Alam, D.M. Alexander, R. Alfarsy et al.,Overview of the Instrumentation for the Dark Energy Spectroscopic Instrument,The Astronomical Journal164 (2022) 207

    2022

  2. [2]

    de Jong, O

    R.S. de Jong, O. Agertz, A.A. Berbel, J. Aird, D.A. Alexander, A. Amarsi et al.,4MOST: Project overview and information for the First Call for Proposals,The Messenger175(2019) 3

    2019

  3. [3]

    Euclid Definition Study Report

    R. Laureijs, J. Amiaux, S. Arduini, J.-L. Auguères, J. Brinchmann, R. Cole et al.,Euclid Definition Study Report, (2011), 10.48550/arXiv.1110.3193. – 17 –

    work page internal anchor Pith review Pith/arXiv arXiv doi:10.48550/arxiv.1110.3193 2011

  4. [4]

    Ivezic, S.M

    Z. Ivezic, S.M. Kahn, J.A. Tyson, B. Abel, E. Acosta, R. Allsman et al.,LSST: from Science Drivers to Reference Design and Anticipated Data Products,The Astrophysical Journal873 (2019) 111

    2019

  5. [5]

    Collaboration, A.G

    D. Collaboration, A.G. Adame, J. Aguilar, S. Ahlen, S. Alam, D.M. Alexander et al.,DESI 2024 II: Sample Definitions, Characteristics, and Two-point Clustering Statistics,Journal of Cosmology and Astroparticle Physics2025(2025) 017

    2024

  6. [6]

    Collaboration, A.G

    D. Collaboration, A.G. Adame, J. Aguilar, S. Ahlen, S. Alam, D.M. Alexander et al.,DESI 2024 III: Baryon Acoustic Oscillations from Galaxies and Quasars,Journal of Cosmology and Astroparticle Physics2025(2025) 012

    2024

  7. [7]

    Collaboration, M

    D. Collaboration, M. Abdul-Karim, J. Aguilar, S. Ahlen, S. Alam, L. Allen et al.,DESI DR2 Results II: Measurements of Baryon Acoustic Oscillations and Cosmological Constraints, Physical Review D112(2025) 083515

    2025

  8. [8]

    Adame, J

    A.G. Adame, J. Aguilar, S. Ahlen, S. Alam, D.M. Alexander, M. Alvarez et al.,DESI 2024 V: Full-Shape Galaxy Clustering from Galaxies and Quasars,Journal of Cosmology and Astroparticle Physics2025(2025) 008

    2024

  9. [9]

    Snowmass white paper: Effective field theories in cosmology,

    G. Cabass, M.M. Ivanov, M. Lewandowski, M. Mirbabayi and M. Simonović,Snowmass White Paper: Effective Field Theories in Cosmology, (2022), 10.48550/arXiv.2203.08232

    work page doi:10.48550/arxiv.2203.08232 2022

  10. [10]

    Senatore,Bias in the Effective Field Theory of Large Scale Structures,Journal of Cosmology and Astroparticle Physics2015(2015) 007

    L. Senatore,Bias in the Effective Field Theory of Large Scale Structures,Journal of Cosmology and Astroparticle Physics2015(2015) 007

    2015

  11. [11]

    White and M.J

    S.D.M. White and M.J. Rees,Core condensation in heavy halos: a two-stage theory for galaxy formation and clustering.,Monthly Notices of the Royal Astronomical Society183(1978) 341

    1978

  12. [12]

    Findlay, S

    N. Findlay, S. Nadathur, W.J. Percival, A.d. Mattia, P. Zarrouk, H. Gil-Marín et al.,Exploring HOD-dependent systematics for the DESI 2024 Full-Shape galaxy clustering analysis,Journal of Cosmology and Astroparticle Physics2025(2025) 007

    2024

  13. [13]

    Garcia-Quintero, J

    C. Garcia-Quintero, J. Mena-Fernández, A. Rocher, S. Yuan, B. Hadzhiyska, O. Alves et al., HOD-Dependent Systematics in Emission Line Galaxies for the DESI 2024 BAO analysis, Journal of Cosmology and Astroparticle Physics2025(2025) 132

    2024

  14. [14]

    Wechsler and J.L

    R.H. Wechsler and J.L. Tinker,The Connection between Galaxies and their Dark Matter Halos, Annual Review of Astronomy and Astrophysics56(2018) 435

    2018

  15. [15]

    Cole, C.G

    S. Cole, C.G. Lacey, C.M. Baugh and C.S. Frenk,Hierarchical galaxy formation,Monthly Notices of the Royal Astronomical Society319(2000) 168

    2000

  16. [16]

    Baugh,A primer on hierarchical galaxy formation: the semi-analytical approach,Reports on Progress in Physics69(2006) 3101

    C.M. Baugh,A primer on hierarchical galaxy formation: the semi-analytical approach,Reports on Progress in Physics69(2006) 3101

    2006

  17. [17]

    Moster, T

    B.P. Moster, T. Naab and S.D.M. White,Galactic star formation and accretion histories from matching galaxies to dark matter haloes,Monthly Notices of the Royal Astronomical Society 428(2013) 3121

    2013

  18. [18]

    Behroozi, R

    P. Behroozi, R. Wechsler, A. Hearin and C. Conroy,UniverseMachine: The Correlation between Galaxy Growth and Dark Matter Halo Assembly from z=0-10,Monthly Notices of the Royal Astronomical Society488(2019) 3143

    2019

  19. [19]

    Kravtsov, A.A

    A.V. Kravtsov, A.A. Berlind, R.H. Wechsler, A.A. Klypin, S. Gottlöber, B. Allgood et al.,The Dark Side of the Halo Occupation Distribution,The Astrophysical Journal609(2004) 35

    2004

  20. [20]

    Tasitsiomi, A.V

    A. Tasitsiomi, A.V. Kravtsov, R.H. Wechsler and J.R. Primack,Modeling Galaxy-Mass Correlations in Dissipationless Simulations,The Astrophysical Journal614(2004) 533

    2004

  21. [21]

    Vale and J.P

    A. Vale and J.P. Ostriker,The non-parametric model for linking galaxy luminosity with halo/subhalo mass,Monthly Notices of the Royal Astronomical Society371(2006) 1173. – 18 –

    2006

  22. [22]

    Conroy, R.H

    C. Conroy, R.H. Wechsler and A.V. Kravtsov,Modeling Luminosity-dependent Galaxy Clustering through Cosmic Time,The Astrophysical Journal647(2006) 201

    2006

  23. [23]

    Favole, J

    G. Favole, J. Comparat, F. Prada, G. Yepes, E. Jullo, A. Niemiec et al.,Clustering properties of g-selected galaxies at z 0.8,Monthly Notices of the Royal Astronomical Society461(2016) 3421

    2016

  24. [24]

    S. Yuan, H. Zhang, A.J. Ross, J. Donald-McCann, B. Hadzhiyska, R.H. Wechsler et al.,The DESI One-Percent Survey: Exploring the Halo Occupation Distribution of Luminous Red Galaxies and Quasi-Stellar Objects with AbacusSummit, (2023), 10.48550/arXiv.2306.06314

    work page doi:10.48550/arxiv.2306.06314 2023

  25. [25]

    Berlind and D.H

    A.A. Berlind and D.H. Weinberg,The Halo Occupation Distribution: Towards an Empirical Determination of the Relation Between Galaxies and Mass,The Astrophysical Journal575 (2002) 587

    2002

  26. [26]

    Zheng, A.A

    Z. Zheng, A.A. Berlind, D.H. Weinberg, A.J. Benson, C.M. Baugh, S. Cole et al.,Theoretical Models of the Halo Occupation Distribution: Separating Central and Satellite Galaxies,The Astrophysical Journal633(2005) 791

    2005

  27. [27]

    Zheng, A.L

    Z. Zheng, A.L. Coil and I. Zehavi,Galaxy Evolution from Halo Occupation Distribution Modeling of DEEP2 and SDSS Galaxy Clustering,The Astrophysical Journal667(2007) 760

    2007

  28. [28]

    Zehavi, Z

    I. Zehavi, Z. Zheng, D.H. Weinberg, M.R. Blanton, N.A. Bahcall, A.A. Berlind et al.,Galaxy Clustering in the Completed SDSS Redshift Survey: The Dependence on Color and Luminosity, The Astrophysical Journal736(2011) 59

    2011

  29. [29]

    Hadzhiyska, D

    B. Hadzhiyska, D. Eisenstein, L. Hernquist, R. Pakmor, S. Bose, A.M. Delgado et al.,The MillenniumTNG Project: an improved two-halo model for the galaxy–halo connection of red and blue galaxies,Monthly Notices of the Royal Astronomical Society524(2023) 2507

    2023

  30. [30]

    Geach, D

    J.E. Geach, D. Sobral, R.C. Hickox, D.A. Wake, I. Smail, P.N. Best et al.,The clustering of hα emitters atz= 2.23from HiZELS: Clustering of HAEs atz= 2.23,Monthly Notices of the Royal Astronomical Society426(2012) 679

    2012

  31. [31]

    Gonzalez-Perez, J

    V. Gonzalez-Perez, J. Comparat, P. Norberg, C.M. Baugh, S. Contreras, C. Lacey et al.,The host dark matter haloes of [O II] emitters at 0.5 < z < 1.5,Monthly Notices of the Royal Astronomical Society474(2018) 4024

    2018

  32. [32]

    Rocher, V

    A. Rocher, V. Ruhlmann-Kleider, E. Burtin, S. Yuan, A. de Mattia, A.J. Ross et al.,The DESI One-Percent survey: exploring the Halo Occupation Distribution of Emission Line Galaxies with AbacusSummit simulations,Journal of Cosmology and Astroparticle Physics2023(2023) 016

    2023

  33. [33]

    Avila, V

    S. Avila, V. Gonzalez-Perez, F.G. Mohammad, A.d. Mattia, C. Zhao, A. Raichoor et al.,The Completed SDSS-IV extended Baryon Oscillation Spectroscopic Survey: exploring the Halo Occupation Distribution model for Emission Line Galaxies,Monthly Notices of the Royal Astronomical Society499(2020) 5486

    2020

  34. [34]

    Navarro, C.S

    J.F. Navarro, C.S. Frenk and S.D.M. White,A Universal Density Profile from Hierarchical Clustering,The Astrophysical Journal490(1997) 493

    1997

  35. [35]

    Boylan-Kolchin, V

    M. Boylan-Kolchin, V. Springel, S.D.M. White, A. Jenkins and G. Lemson,Resolving cosmic structure formation with the Millennium-II Simulation,Monthly Notices of the Royal Astronomical Society398(2009) 1150

    2009

  36. [36]

    Jiang and F.C

    F. Jiang and F.C. Van Den Bosch,Statistics of dark matter substructure – III. Halo-to-halo variance,Monthly Notices of the Royal Astronomical Society472(2017) 657

    2017

  37. [37]

    2021, The IllustrisTNG Simulations: Public Data Release

    D. Nelson, V. Springel, A. Pillepich, V. Rodriguez-Gomez, P. Torrey, S. Genel et al.,The IllustrisTNG Simulations: Public Data Release, (2021), 10.48550/arXiv.1812.05609

    work page doi:10.48550/arxiv.1812.05609 2021

  38. [38]

    Chaves-Montero, R.E

    J. Chaves-Montero, R.E. Angulo and S. Contreras,The galaxy formation origin of the lensing is low problem,Monthly Notices of the Royal Astronomical Society521(2023) 937. – 19 –

    2023

  39. [39]

    Reanalyzing DESI DR1: 2. Constraints on Dark Energy, Spatial Curvature, and Neutrino Masses

    A. Chudaykin, M.M. Ivanov and O.H.E. Philcox,Reanalyzing DESI DR1: 2. Constraints on Dark Energy, Spatial Curvature, and Neutrino Masses, (2025), 10.48550/arXiv.2511.20757

    work page internal anchor Pith review Pith/arXiv arXiv doi:10.48550/arxiv.2511.20757 2025

  40. [40]

    D’Amico, Y

    G. D’Amico, Y. Donath, M. Lewandowski, L. Senatore and P. Zhang,The BOSS bispectrum analysis at one loop from the Effective Field Theory of Large-Scale Structure,Journal of Cosmology and Astroparticle Physics2024(2024) 059

    2024

  41. [41]

    Z. Lu, T. Simon and P. Zhang,Preference for evolving dark energy in light of the galaxy bispectrum, (2025), 10.48550/arXiv.2503.04602

    work page doi:10.48550/arxiv.2503.04602 2025

  42. [42]

    Jiménez, S

    E. Jiménez, S. Contreras, N. Padilla, I. Zehavi, C.M. Baugh and V. Gonzalez-Perez,Extensions to the halo occupation distribution model for more accurate clustering predictions,Monthly Notices of the Royal Astronomical Society490(2019) 3532

    2019

  43. [43]

    A Queuing Model with State Dependent Service Rates,

    B. Vos-Ginés, S. Avila, V. Gonzalez-Perez and G. Yepes,Improving and extending non-Poissonian distributions for satellite galaxies sampling in HOD: applications to eBOSS ELGs, (2023), 10.48550/arXiv.2310.18189. [44]R. W. Conway and W. L. Maxwell, “A Queuing Model with State Dependent Service Rates,” Journal of Industrial Engineering, Vol. 12, 1962, pp. 13...

    work page doi:10.48550/arxiv.2310.18189 2023

  44. [44]

    Sugiyama, S

    N.S. Sugiyama, S. Saito, F. Beutler and H.-J. Seo,A complete FFT-based decomposition formalism for the redshift-space bispectrum,Monthly Notices of the Royal Astronomical Society 484(2019) 364

    2019

  45. [45]

    Reid and D.N

    B.A. Reid and D.N. Spergel,Constraining the LRG Halo Occupation Distribution using Counts-in-Cylinders,The Astrophysical Journal698(2009) 143

    2009

  46. [46]

    Gaunt, S

    R.E. Gaunt, S. Iyengar, A.B. Olde Daalhuis and B. Simsek,An asymptotic expansion for the normalizing constant of the Conway–Maxwell–Poisson distribution,Annals of the Institute of Statistical Mathematics71(2019) 163

    2019

  47. [47]

    Rocher,HODDIES: Dressing up halos with galaxies – a efficient hod code for stage-iv cosmological surveys,Journal of Cosmology and Astroparticle Physics(in prep.)

    A. Rocher,HODDIES: Dressing up halos with galaxies – a efficient hod code for stage-iv cosmological surveys,Journal of Cosmology and Astroparticle Physics(in prep.)

  48. [48]

    Maksimova, L.H

    N.A. Maksimova, L.H. Garrison, D.J. Eisenstein, B. Hadzhiyska, S. Bose and T.P. Satterthwaite,AbacusSummit: A Massive Set of High-Accuracy, High-Resolution $N$-Body Simulations,Monthly Notices of the Royal Astronomical Society508(2021) 4017

    2021

  49. [49]

    Collaboration, N

    P. Collaboration, N. Aghanim, Y. Akrami, M. Ashdown, J. Aumont, C. Baccigalupi et al., Planck 2018 results. VI. Cosmological parameters,Astronomy & Astrophysics641(2020) A6

    2018

  50. [50]

    Contreras, C

    S. Contreras, C. Baugh, P. Norberg and N. Padilla,How robust are predictions of galaxy clustering?,Monthly Notices of the Royal Astronomical Society432(2013) 2717

    2013

  51. [51]

    Smith, E

    A. Smith, E. Burtin, J. Hou, R. Neveux, A.J. Ross, S. Alam et al.,The completed SDSS-IV extended Baryon Oscillation Spectroscopic Survey: N-body mock challenge for the quasar sample,Monthly Notices of the Royal Astronomical Society499(2020) 269

    2020

  52. [52]

    Sinha and L.H

    M. Sinha and L.H. Garrison,Corrfunc — A Suite of Blazing Fast Correlation Functions on the CPU,Monthly Notices of the Royal Astronomical Society491(2020) 3022. [54]Peebles Hauser 1974 - Recherche Google,

    2020

  53. [53]

    The Open Journal of Astrophysics , keywords =

    M. Asgari, A.J. Mead and C. Heymans,The halo model for cosmology: a pedagogical review, The Open Journal of Astrophysics6(2023) 10.21105/astro.2303.08752

    work page doi:10.21105/astro.2303.08752 2023

  54. [54]

    Seljak,Analytic model for galaxy and dark matter clustering,Monthly Notices of the Royal Astronomical Society318(2000) 203

    U. Seljak,Analytic model for galaxy and dark matter clustering,Monthly Notices of the Royal Astronomical Society318(2000) 203

    2000

  55. [55]

    URL https://www.worldscientific.com/ doi/abs/10.1142/0270

    D.A. Varshalovich, A.N. Moskalev and V.K. Khersonskii,Quantum Theory of Angular Momentum(Jan., 1988), 10.1142/0270. – 20 –

    work page doi:10.1142/0270 1988

  56. [56]

    Kaiser,Clustering in real space and in redshift space,Monthly Notices of the Royal Astronomical Society227(1987) 1

    N. Kaiser,Clustering in real space and in redshift space,Monthly Notices of the Royal Astronomical Society227(1987) 1

    1987

  57. [57]

    Alcock and B

    C. Alcock and B. Paczynski,An evolution free test for non-zero cosmological constant,Nature 281(1979) 358

    1979

  58. [58]

    Wang, Y.-Y

    K. Wang, Y.-Y. Mao, A.R. Zentner, H. Guo, J.U. Lange, F.C. van den Bosch et al.,Evidence of galaxy assembly bias in SDSS DR7 galaxy samples from count statistics,Monthly Notices of the Royal Astronomical Society516(2022) 4003

    2022

  59. [59]

    Pearl, A.R

    A.N. Pearl, A.R. Zentner, J.A. Newman, R. Bezanson, K. Wang, J. Moustakas et al.,The DESI One-Percent Survey: Evidence for Assembly Bias from Low-Redshift Counts-in-Cylinders Measurements, (2023), 10.48550/arXiv.2309.08675

    work page doi:10.48550/arxiv.2309.08675 2023

  60. [60]

    Wang, D.J

    H. Wang, D.J. Eisenstein, J.N. Aguilar, S. Ahlen, D. Bianchi, D. Brooks et al., Galaxy-Multiplet Clustering from DESI DR2, (2025), 10.48550/arXiv.2511.15354. – 21 –

    work page doi:10.48550/arxiv.2511.15354 2025