Pith. sign in

REVIEW 2 major objections 2 minor 2 cited by

Fast and accurate Gaia-unWISE quasar mock catalogs from LPT and Eulerian bias

T0 review · 2 major / 2 minor · reviewed 2026-05-18 · grok-4.3

Challenge this review Download PDF Read on arXiv ↗ Review JSON

Pith's one-line read Quasar mock catalogs generated with Lagrangian perturbation theory and hierarchical bias accurately reproduce the Gaia-unWISE Quaia catalog's summary statistics.

desk verdict This delivers practical quasar mocks via LPT and Hicobian bias but the calibration transfer from N-body deserves closer inspection. read the letter →

arxiv 2509.15890 v2 submitted 2025-09-19 astro-ph.CO

Francesco Sinigaglia , Francisco-Shu Kitaura , Mahlet Shiferaw , Ginevra Favole , Kate Storey-Fisher , Nestor Arsenov This is my paper · ORCID
classification astro-ph.CO
keywords quasarmockcatalogsLagrangianperturbationtheorynonlinearbiasGaia-unWISEQuaialarge-scalestructurecosmologicalsimulationsredshiftspaceobservationaleffects
topics Dark Matter
open problems Dark Matter
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

The paper presents a method to produce fast and accurate full-sky quasar mock catalogs for the Gaia-unWISE Quaia catalog. It uses dark matter fields from augmented Lagrangian perturbation theory on the lightcone and applies a hierarchical nonlocal nonlinear bias scheme calibrated on Abacus simulation mocks matched to DESI observations. Observational effects such as redshift uncertainties, angular selection, and number counts are added to the mocks. The catalogs are validated against the real data using full-sky maps, redshift distributions, angular power spectra with covariances, and two-point correlation functions, showing excellent agreement. The mocks are made publicly available for cosmological studies.

What carries the argument

Hierarchical nonlocal nonlinear bias scheme (Hicobian) applied to Augmented Lagrangian Perturbation Theory lightcone fields from the WebON code.

What would settle it

Finding a statistically significant mismatch in the angular power spectra or two-point correlation functions between the mock catalogs and the Quaia catalog at multiple redshifts would falsify the accuracy claim.

Watch

Extended reading notes

Core claim

We present 100 full-sky quasar spectrophotometric mock catalogs with smooth redshift evolution from z=0 to z~4, tailored to analyze the Gaia-unWISE Quasar Catalog (Quaia). In particular, we apply a novel hierarchical nonlocal nonlinear bias scheme (Hicobian) to dark matter fields generated through Augmented Lagrangian Perturbation Theory on the lightcone (WebON code), calibrating the free parameters of the bias model on Abacus quasar HOD mock catalogs tuned to reproduce DESI Early Data Release observations in real and redshift space. After having obtained such accurate spectroscopic catalogs, we inject in the mocks the observational effects characterizing the Quaia catalog: (i) spectrophot o

Load-bearing premise

The hierarchical nonlocal nonlinear bias scheme calibrated on Abacus HOD mocks tuned to DESI Early Data Release observations can be transferred to WebON Augmented Lagrangian Perturbation Theory lightcone fields to produce quasar distributions that match Quaia after injecting observational effects.

Editorial extensions

If this is right

  • The mock catalogs accurately reproduce the Quaia catalog's full-sky maps and redshift distributions.
  • Angular power spectra and their covariances from the mocks match those of the real data.
  • Two-point correlation functions in the mocks align with observations after including selection effects.
  • The method enables efficient production of multiple mock realizations for statistical analysis.
  • Public release of the catalogs supports community-wide use in quasar cosmology studies.

Reading between the lines

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

  • The success of transferring the bias model suggests similar approaches could work for other large-scale structure tracers in future surveys.
  • This combination of fast LPT simulations with calibrated bias could scale to higher resolution or larger volumes for next-generation experiments.
  • Validation on power spectra implies the mocks capture the clustering properties needed for testing cosmological models.
  • Further development might incorporate additional effects like magnification bias for more complete mock realism.
Share X Bluesky LinkedIn Reddit HN

Signed reviews

No signed human review yet.

Editorial analysis

A structured set of objections, weighed in public.

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

Referee Report

2 major / 2 minor

Summary. The paper presents 100 full-sky quasar spectrophotometric mock catalogs spanning z=0 to z~4, generated by applying a hierarchical nonlocal nonlinear bias scheme (Hicobian) to dark matter fields from Augmented Lagrangian Perturbation Theory on the lightcone (WebON code). Bias parameters are calibrated on Abacus quasar HOD mocks tuned to DESI Early Data Release observations. Observational effects including spectrophotometric redshift uncertainties, angular selection function, and redshift number counts are injected to match the Gaia-unWISE Quasar Catalog (Quaia). Accuracy is assessed via full-sky maps, redshift uncertainty distributions, n(z), angular power spectra with normalized covariances, and angular two-point correlation functions, with claims of excellent agreement; the catalogs are publicly released.

Significance. If the accuracy holds, the work supplies a practical, publicly available set of mocks tailored for Quaia analyses, combining efficient LPT generation with a detailed Eulerian bias model to incorporate both structure formation and systematics. The public release of the 100 catalogs is a clear strength that supports reproducibility and community use in large-scale structure studies.

major comments (2)
  1. [bias calibration and application section] The transfer of Hicobian bias parameters (calibrated on Abacus N-body HOD mocks tuned to DESI EDR) to WebON LPT lightcone fields is central to the accuracy claim but lacks an isolated test. LPT is known to underpredict small-scale power and higher-order correlations relative to full N-body; if the hierarchical nonlocal terms compensate for Abacus-specific nonlinearities, they may be mis-calibrated on WebON. The validation on C_ℓ and w(θ) occurs only after injecting angular selection, n(z), and redshift errors, which can mask residual mismatches (see abstract and the bias application section).
  2. [validation section] The abstract states 'excellent agreement' on angular power spectra and covariances, but without quantitative error metrics or pre-injection comparisons to an N-body reference at fixed cosmology, it is difficult to assess whether the summary statistics fully support the central claim of faithful large-scale structure reproduction.
minor comments (2)
  1. Clarify the exact number and range of free parameters in the Hicobian model and how they are optimized (e.g., which summary statistics are used in the fit to Abacus mocks).
  2. Ensure all figures showing C_ℓ and w(θ) include error bars or shaded regions from the mock ensemble to allow direct visual assessment of agreement with Quaia.

Simulated Author's Rebuttal

2 responses · 0 unresolved

We thank the referee for their thorough review and constructive feedback on our manuscript. We address the major comments point by point below, providing clarifications on our methodology while indicating revisions to strengthen the presentation of the bias calibration and validation results.

read point-by-point responses

  1. Referee: [bias calibration and application section] The transfer of Hicobian bias parameters (calibrated on Abacus N-body HOD mocks tuned to DESI EDR) to WebON LPT lightcone fields is central to the accuracy claim but lacks an isolated test. LPT is known to underpredict small-scale power and higher-order correlations relative to full N-body; if the hierarchical nonlocal terms compensate for Abacus-specific nonlinearities, they may be mis-calibrated on WebON. The validation on C_ℓ and w(θ) occurs only after injecting angular selection, n(z), and redshift errors, which can mask residual mismatches (see abstract and the bias application section).

    Authors: We agree that an explicit isolated test of the bias model transfer would provide additional reassurance. The Hicobian hierarchical nonlocal nonlinear bias is formulated as an Eulerian prescription that incorporates higher-order and nonlocal terms precisely to capture clustering beyond the linear regime when applied to approximate density fields such as those from ALPT. The parameters were determined by matching the Abacus HOD mocks, which were themselves calibrated to DESI EDR clustering in real and redshift space. Because the subsequent validation demonstrates that the full pipeline (including observational effects) reproduces the Quaia summary statistics, we view the end-to-end agreement as the primary validation for the intended use of the mocks. Nevertheless, to address the concern directly, we will expand the bias application section with a new figure and accompanying text showing the angular power spectrum of the biased LPT fields prior to injection of selection and redshift errors, compared against the corresponding Abacus-based fields at the same cosmology. This will quantify any residual differences attributable to the underlying gravity solver. revision: partial

  2. Referee: [validation section] The abstract states 'excellent agreement' on angular power spectra and covariances, but without quantitative error metrics or pre-injection comparisons to an N-body reference at fixed cosmology, it is difficult to assess whether the summary statistics fully support the central claim of faithful large-scale structure reproduction.

    Authors: We accept that the phrase 'excellent agreement' would benefit from quantitative support. In the revised manuscript we will replace the qualitative statement in the abstract with explicit metrics, including the reduced chi-squared per degree of freedom for the angular power spectra (both auto- and cross-spectra) and the two-point correlation functions when comparing the mocks to Quaia. We will also report the fractional residuals and their rms values across the relevant multipole and angular-scale ranges. With respect to pre-injection comparisons against full N-body at fixed cosmology, our primary objective is to generate mocks that faithfully reproduce the observed Quaia catalog after all selection and error effects are applied; the LPT-based approach was chosen for computational efficiency to produce 100 full-sky realizations. A dedicated fixed-cosmology N-body benchmark is not part of the present study, but the added pre-injection power-spectrum comparison noted above will provide a direct check on the bias-model performance on the LPT fields themselves. revision: yes

Circularity Check

0 steps flagged · score 0.0 of 10

No significant circularity; validation uses independent external dataset

full rationale

The derivation chain generates DM fields via WebON LPT, applies Hicobian bias whose free parameters are calibrated on Abacus HOD mocks tuned to DESI EDR (an external survey), injects Quaia-specific observational effects, and validates summary statistics directly against the Quaia catalog. Since calibration data (DESI) and validation data (Quaia) are distinct and the LPT lightcone is generated independently, the reported agreement is a transfer test rather than a quantity forced by construction or self-definition. No self-citation load-bearing step, fitted-input-renamed-as-prediction, or ansatz-smuggled reduction appears in the abstract or described pipeline; the central claim retains independent content against external benchmarks.

Assumptions & free parameters 1 free parameters · 2 assumptions · 0 invented entities

The central claim rests on the transferability of a bias model calibrated on one set of mocks to another simulation framework, plus standard assumptions in perturbation theory and observational modeling.

free parameters (1)
  • free parameters of the Hicobian bias model
    Calibrated on Abacus quasar HOD mock catalogs tuned to DESI Early Data Release observations in real and redshift space.
assumptions (2)
  • domain assumption Augmented Lagrangian Perturbation Theory on the lightcone accurately captures the dark matter field evolution relevant for quasar bias modeling up to z~4.
    Invoked when generating the underlying dark matter fields with the WebON code.
  • domain assumption The hierarchical nonlocal nonlinear bias scheme (Hicobian) provides a sufficient description of quasar clustering from dark matter.
    Central modeling choice for mapping dark matter to quasars.

how reviews work

0 comments
Cite this review

Pith. "Pith review of Fast and accurate Gaia-unWISE quasar mock catalogs from LPT and Eulerian bias." pith.science (2026). https://pith.science/paper/2509.15890

@misc{pith2026250915890,
  author       = {Pith},
  title        = {Pith review of: Fast and accurate Gaia-unWISE quasar mock catalogs from LPT and Eulerian bias},
  year         = {2026},
  howpublished = {\url{https://pith.science/paper/2509.15890}},
  note         = {Machine review of arXiv:2509.15890}
}
abstract

We present $100$ full-sky quasar spectrophotometric mock catalogs with smooth redshift evolution from $z=0$ to $z\sim 4$, tailored to analyze the Gaia-unWISE Quasar Catalog (Quaia). In particular, we apply a novel hierarchical nonlocal nonlinear bias scheme (Hicobian) to dark matter fields generated through Augmented Lagrangian Perturbation Theory on the lightcone (WebON code), calibrating the free parameters of the bias model on Abacus quasar HOD mock catalogs tuned to reproduce DESI Early Data Release observations in real and redshift space. After having obtained such accurate spectroscopic catalogs, we inject in the mocks the observational effects characterizing the Quaia catalog: (i) spectrophotometric redshift uncertainties, (ii) the angular selection function, and (iii) the redshift number counts distribution. We assess the accuracy of our catalogs by validating a number of summary statistics: the full-sky QSO maps, the redshift uncertainty distributions as a function of redshift, the redshift $n(z)$ distribution, the angular power spectra and their normalized covariance matrices, and the angular two-point correlation functions. We find excellent agreement between these metrics from the mocks and from the Quaia catalog. We publicly release the mock catalogs to the community.

Discussion (0). Continue with ORCID to comment.

Forward citations

Cited by 2 Pith papers

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

  1. A local Universe catalogue of structures and voids dynamically identified using Cosmic-Flows4++ZOA peculiar velocities

    astro-ph.CO 2026-06 unverdicted novelty 4.0 of 10

    A catalogue of 37 voids (radii 13-38 h^{-1} Mpc) and 42 knots (volumes 10^4 to 3.3x10^5 h^{-3} Mpc^3) is presented using V-web on CF4++ZOA peculiar velocities within z=0.1.

  2. Tracing the high-z cosmic web with Quaia: catalogues of voids and clusters in the quasar distribution

    astro-ph.CO 2025-09 unverdicted novelty 4.0 of 10

    Using 708,483 quasars at 0.8<z<2.2 from Quaia, the authors identify 12,842 voids and 41,111 clusters whose radii, densities and profiles agree with 50 mock catalogues to within 5-10%, with no ultra-large structures ex...

Reference graph

Works this paper leans on

76 extracted references · 76 canonical work pages · cited by 2 Pith papers

  1. [1]

    M. Levi, C. Bebek, T. Beers, R. Blum, R. Cahn, D. Eisenstein et al.,The DESI Experiment, a whitepaper for Snowmass 2013,arXiv e-prints(2013) arXiv:1308.0847 [1308.0847]

    work page Pith review arXiv 2013

  2. [2]

    Amendola, S

    L. Amendola, S. Appleby, A. Avgoustidis, D. Bacon, T. Baker, M. Baldi et al.,Cosmology and fundamental physics with the Euclid satellite,Living Reviews in Relativity21(2018) 2 [1606.00180]

    work page arXiv 2018

  3. [3]

    J-PAS: The Javalambre-Physics of the Accelerated Universe Astrophysical Survey

    N. Benitez, R. Dupke, M. Moles, L. Sodre, J. Cenarro, A. Marin-Franch et al.,J-PAS: The Javalambre-Physics of the Accelerated Universe Astrophysical Survey,arXiv e-prints(2014) arXiv:1403.5237 [1403.5237]

    work page Pith review arXiv 2014

  4. [4]

    4MOST Consortium Survey 8: Cosmology Redshift Survey (CRS)

    J. Richard, J.P. Kneib, C. Blake, A. Raichoor, J. Comparat, T. Shanks et al.,4MOST Consortium Survey 8: Cosmology Redshift Survey (CRS),The Messenger175(2019) 50 [1903.02474]

    work page Pith review arXiv 2019

  5. [5]

    Y. Wang, Z. Zhai, A. Alavi, E. Massara, A. Pisani, A. Benson et al.,The High Latitude Spectroscopic Survey on the Nancy Grace Roman Space Telescope, ApJ928(2022) 1 [2110.01829]

    work page arXiv 2022

  6. [6]

    LSST: from Science Drivers to Reference Design and Anticipated Data Products

    Ž. Ivezić, 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, ApJ873(2019) 111 [0805.2366]

    work page Pith review arXiv 2019

  7. [7]

    The Dark Energy Survey Collaboration,The Dark Energy Survey,arXiv e-prints(2005) astro [astro-ph/0510346]

    work page Pith review arXiv 2005

  8. [8]

    The clustering of intermediate redshift quasars as measured by the Baryon Oscillation Spectroscopic Survey

    M. White, A.D. Myers, N.P. Ross, D.J. Schlegel, J.F. Hennawi, Y. Shen et al.,The clustering of intermediate-redshift quasars as measured by the Baryon Oscillation Spectroscopic Survey, MNRAS424(2012) 933 [1203.5306]. – 16 –

    work page Pith review arXiv 2012

Show all 76 references
  1. [9]

    H. Song, C. Park, H. Lietzen and M. Einasto,Quasars as a Tracer of Large-scale Structures in the Distant Universe, ApJ827(2016) 104 [1606.06307]

    2016 arXiv

  2. [10]

    Adame, J

    DESI Collaboration, A.G. Adame, J. Aguilar, S. Ahlen, S. Alam, D.M. Alexander et al.,DESI 2024 V: Full-Shape Galaxy Clustering from Galaxies and Quasars,arXiv e-prints(2024) arXiv:2411.12021 [2411.12021]

    2024 arXiv

  3. [11]

    Richarte, F

    M.G. Richarte, F. Toscano, D.G. Lambas, H.E. Luparello, L. Filipe Guimarães and J.C. Fabris, Quasar Pairs as Large–Scale Structure tracers,arXiv e-prints(2025) arXiv:2504.01251 [2504.01251]

    2025

  4. [12]

    Neyman and E.L

    J. Neyman and E.L. Scott,A Theory of the Spatial Distribution of Galaxies., ApJ116(1952) 144

    1952

  5. [13]

    Peebles,The Nature of the Distribution of Galaxies, A&A32(1974) 197

    P.J.E. Peebles,The Nature of the Distribution of Galaxies, A&A32(1974) 197

    1974

  6. [14]

    Benson, S

    A.J. Benson, S. Cole, C.S. Frenk, C.M. Baugh and C.G. Lacey,The nature of galaxy bias and clustering, MNRAS311(2000) 793 [astro-ph/9903343]

    2000 arXiv

  7. [15]

    Berlind and D.H

    A.A. Berlind and D.H. Weinberg,The Halo Occupation Distribution: Toward an Empirical Determination of the Relation between Galaxies and Mass, ApJ575(2002) 587 [astro-ph/0109001]

    2002 arXiv

  8. [16]

    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, ApJ 633(2005) 791 [astro-ph/0408564]

    2005 arXiv

  9. [17]

    Zheng, A.L

    Z. Zheng, A.L. Coil and I. Zehavi,Galaxy Evolution from Halo Occupation Distribution Modeling of DEEP2 and SDSS Galaxy Clustering, ApJ667(2007) 760 [astro-ph/0703457]

    2007 arXiv

  10. [18]

    Zentner, A.P

    A.R. Zentner, A.P. Hearin and F.C. van den Bosch,Galaxy assembly bias: a significant source of systematic error in the galaxy-halo relationship, MNRAS443(2014) 3044 [1311.1818]

    2014 arXiv

  11. [19]

    Hearin, A.R

    A.P. Hearin, A.R. Zentner, F.C. van den Bosch, D. Campbell and E. Tollerud,Introducing decorated HODs: modelling assembly bias in the galaxy-halo connection, MNRAS460(2016) 2552 [1512.03050]

    2016 arXiv

  12. [20]

    Rocher, V

    A. Rocher, V. Ruhlmann-Kleider, E. Burtin and A. de Mattia,Halo occupation distribution of Emission Line Galaxies: fitting method with Gaussian processes, J. Cosmology Astropart. Phys.2023(2023) 033 [2302.07056]

    2023

  13. [21]

    Vale and J.P

    A. Vale and J.P. Ostriker,Linking halo mass to galaxy luminosity, MNRAS353(2004) 189 [astro-ph/0402500]

    2004 arXiv

  14. [22]

    Conroy, R.H

    C. Conroy, R.H. Wechsler and A.V. Kravtsov,Modeling Luminosity-dependent Galaxy Clustering through Cosmic Time, ApJ647(2006) 201 [astro-ph/0512234]

    2006 arXiv

  15. [23]

    Behroozi, C

    P.S. Behroozi, C. Conroy and R.H. Wechsler,A Comprehensive Analysis of Uncertainties Affecting the Stellar Mass-Halo Mass Relation for 0 < z < 4, ApJ717(2010) 379 [1001.0015]

    2010 arXiv

  16. [24]

    Trujillo-Gomez, A

    S. Trujillo-Gomez, A. Klypin, J. Primack and A.J. Romanowsky,Galaxies inΛCDM with Halo Abundance Matching: Luminosity-Velocity Relation, Baryonic Mass-Velocity Relation, Velocity Function, and Clustering, ApJ742(2011) 16 [1005.1289]

    2011 arXiv

  17. [25]

    Reddick, R.H

    R.M. Reddick, R.H. Wechsler, J.L. Tinker and P.S. Behroozi,The Connection between Galaxies and Dark Matter Structures in the Local Universe, ApJ771(2013) 30 [1207.2160]

    2013 arXiv

  18. [26]

    Contreras, R.E

    S. Contreras, R.E. Angulo and M. Zennaro,A flexible subhalo abundance matching model for galaxy clustering in redshift space, MNRAS508(2021) 175 [2012.06596]

    2021

  19. [27]

    Favole, A.D

    G. Favole, A.D. Montero-Dorta, M.C. Artale, S. Contreras, I. Zehavi and X. Xu,Subhalo abundance matching through the lens of a hydrodynamical simulation, MNRAS509(2022) 1614 [2101.10733]. – 17 –

    2022

  20. [28]

    DeRose, M.R

    J. DeRose, M.R. Becker and R.H. Wechsler,Modeling Redshift-space Clustering with Abundance Matching, ApJ940(2022) 13 [2105.12104]

    2022

  21. [29]

    Monaco, T

    P. Monaco, T. Theuns and G. Taffoni,The pinocchio algorithm: pinpointing orbit-crossing collapsed hierarchical objects in a linear density field, MNRAS331(2002) 587 [astro-ph/0109323]

    2002 arXiv

  22. [30]

    Kitaura, G

    F.S. Kitaura, G. Yepes and F. Prada,Modelling baryon acoustic oscillations with perturbation theory and stochastic halo biasing., MNRAS439(2014) L21 [1307.3285]

    2014 arXiv

  23. [31]

    Avila, S.G

    S. Avila, S.G. Murray, A. Knebe, C. Power, A.S.G. Robotham and J. Garcia-Bellido, HALOGEN: a tool for fast generation of mock halo catalogues, MNRAS450(2015) 1856 [1412.5228]

    2015 arXiv

  24. [32]

    Kitaura, S

    F.-S. Kitaura, S. Rodríguez-Torres, C.-H. Chuang, C. Zhao, F. Prada, H. Gil-Marín et al.,The clustering of galaxies in the SDSS-III Baryon Oscillation Spectroscopic Survey: mock galaxy catalogues for the BOSS Final Data Release, MNRAS456(2016) 4156 [1509.06400]

    2016 arXiv

  25. [33]

    Chuang, F.-S

    C.-H. Chuang, F.-S. Kitaura, F. Prada, C. Zhao and G. Yepes,EZmocks: extending the Zel’dovich approximation to generate mock galaxy catalogues with accurate clustering statistics, MNRAS446(2015) 2621 [1409.1124]

    2015 arXiv

  26. [34]

    Balaguera-Antolínez, F.-S

    A. Balaguera-Antolínez, F.-S. Kitaura, M. Pellejero-Ibáñez, C. Zhao and T. Abel,BAM: bias assignment method to generate mock catalogues, MNRAS483(2019) L58 [1806.05870]

    2019 arXiv

  27. [35]

    Balaguera-Antolínez, F.-S

    A. Balaguera-Antolínez, F.-S. Kitaura, M. Pellejero-Ibáñez, M. Lippich, C. Zhao, A.G. Sánchez et al.,One simulation to have them all: performance of the Bias Assignment Method against N-body simulations, MNRAS491(2020) 2565 [1906.06109]

    2020

  28. [36]

    Zhao, C.-H

    C. Zhao, C.-H. Chuang, J. Bautista, A. de Mattia, A. Raichoor, A.J. Ross et al.,The completed SDSS-IV extended Baryon Oscillation Spectroscopic Survey: 1000 multi-tracer mock catalogues with redshift evolution and systematics for galaxies and quasars of the final data release,...

    2021

  29. [37]

    Coloma-Nadal, F.S

    J.M. Coloma-Nadal, F.S. Kitaura, J.E. García-Farieta, F. Sinigaglia, G. Favole and D. Forero Sánchez,The Hierarchical Cosmic Web and Assembly Bias,arXiv e-prints(2024) arXiv:2403.19337 [2403.19337]

    2024

  30. [38]

    Storey-Fisher, D.W

    K. Storey-Fisher, D.W. Hogg, H.-W. Rix, A.-C. Eilers, G. Fabbian, M.R. Blanton et al.,Quaia, the Gaia-unWISE Quasar Catalog: An All-sky Spectroscopic Quasar Sample, ApJ964(2024) 69 [2306.17749]

    2024

  31. [39]

    Delchambre, C.A.L

    L. Delchambre, C.A.L. Bailer-Jones, I. Bellas-Velidis, R. Drimmel, D. Garabato, R. Carballo et al.,Gaia Data Release 3. Apsis. III. Non-stellar content and source classification, A&A674 (2023) A31 [2206.06710]

    2023

  32. [40]

    Bailer-Jones, D

    Gaia Collaboration, C.A.L. Bailer-Jones, D. Teyssier, L. Delchambre, C. Ducourant, D. Garabato et al.,Gaia Data Release 3. The extragalactic content, A&A674(2023) A41 [2206.05681]

    2023

  33. [41]

    Vallenari, A.G.A

    Gaia Collaboration, A. Vallenari, A.G.A. Brown, T. Prusti, J.H.J. de Bruijne, F. Arenou et al., Gaia Data Release 3. Summary of the content and survey properties, A&A674(2023) A1 [2208.00211]

    2023

  34. [42]

    Wright, P.R.M

    E.L. Wright, P.R.M. Eisenhardt, A.K. Mainzer, M.E. Ressler, R.M. Cutri, T. Jarrett et al., The Wide-field Infrared Survey Explorer (WISE): Mission Description and Initial On-orbit Performance, AJ140(2010) 1868 [1008.0031]

    2010 arXiv

  35. [43]

    Lang,unWISE: Unblurred Coadds of the WISE Imaging, AJ147(2014) 108 [1405.0308]

    D. Lang,unWISE: Unblurred Coadds of the WISE Imaging, AJ147(2014) 108 [1405.0308]

    2014 arXiv

  36. [44]

    Hockney and J.W

    R.W. Hockney and J.W. Eastwood,Computer Simulation Using Particles(1981). – 18 –

    1981

  37. [45]

    T. Abel, O. Hahn and R. Kaehler,Tracing the dark matter sheet in phase space, MNRAS427 (2012) 61 [1111.3944]

    2012 arXiv

  38. [46]

    Kitaura and S

    F.S. Kitaura and S. Hess,Cosmological structure formation with augmented lagrangian perturbation theory., MNRAS435(2013) L78 [1212.3514]

    2013 arXiv

  39. [47]

    Kitaura, F

    F.S. Kitaura, F. Sinigaglia, A. Balaguera-Antolínez and G. Favole,The Cosmic Web from Perturbation Theory,arXiv e-prints(2023) arXiv:2301.03648 [2301.03648]

    2023

  40. [48]

    Bernardeau,The Nonlinear Evolution of Rare Events, ApJ427(1994) 51 [astro-ph/9311066]

    F. Bernardeau,The Nonlinear Evolution of Rare Events, ApJ427(1994) 51 [astro-ph/9311066]

    1994 arXiv

  41. [49]

    Mohayaee, H

    R. Mohayaee, H. Mathis, S. Colombi and J. Silk,Reconstruction of primordial density fields, MNRAS365(2006) 939 [astro-ph/0501217]

    2006 arXiv

  42. [50]

    Angulo and S.D.M

    R.E. Angulo and S.D.M. White,One simulation to fit them all - changing the background parameters of a cosmological N-body simulation, MNRAS405(2010) 143 [0912.4277]

    2010 arXiv

  43. [51]

    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, MNRAS508(2021) 4017 [2110.11398]

    2021

  44. [52]

    Garrison, D.J

    L.H. Garrison, D.J. Eisenstein and P.A. Pinto,A high-fidelity realization of the Euclid code comparison N-body simulation with ABACUS, MNRAS485(2019) 3370 [1810.02916]

    2019 arXiv

  45. [53]

    Garrison, D.J

    L.H. Garrison, D.J. Eisenstein, D. Ferrer, N.A. Maksimova and P.A. Pinto,The ABACUS cosmological N-body code, MNRAS508(2021) 575 [2110.11392]

    2021

  46. [54]

    Aghanim, Y

    Planck Collaboration, N. Aghanim, Y. Akrami, M. Ashdown, J. Aumont, C. Baccigalupi et al., Planck 2018 results. VI. Cosmological parameters, A&A641(2020) A6 [1807.06209]

    2018 arXiv

  47. [55]

    S. Yuan, H. Zhang, A.J. Ross, J. Donald-McCann, B. Hadzhiyska, R.H. Wechsler et al.,The DESI one-per cent survey: exploring the halo occupation distribution of luminous red galaxies and quasi-stellar objects with ABACUSSUMMIT, MNRAS530(2024) 947 [2306.06314]

    2024

  48. [56]

    Yuan, L.H

    S. Yuan, L.H. Garrison, B. Hadzhiyska, S. Bose and D.J. Eisenstein,ABACUSHOD: a highly efficient extended multitracer HOD framework and its application to BOSS and eBOSS data, MNRAS510(2022) 3301 [2110.11412]

    2022

  49. [57]

    O. Hahn, C. Porciani, C.M. Carollo and A. Dekel,Properties of dark matter haloes in clusters, filaments, sheets and voids,Monthly Notices of the Royal Astronomical Society375(2007) 489

    2007

  50. [58]

    Heavens and J

    A. Heavens and J. Peacock,Tidal torques and local density maxima,Monthly Notices of the Royal Astronomical Society232(1988) 339 [https://academic.oup.com/mnras/article-pdf/232/2/339/3316537/mnras232-0339.pdf]

    1988

  51. [59]

    McDonald and A

    P. McDonald and A. Roy,Clustering of dark matter tracers: generalizing bias for the coming era of precision LSS,Journal of Cosmology and Astroparticle Physics2009(2009) 020

    2009

  52. [60]

    Sinigaglia, F.-S

    F. Sinigaglia, F.-S. Kitaura, A. Balaguera-Antolínez, K. Nagamine, M. Ata, I. Shimizu et al., The bias from hydrodynamic simulations: Mapping baryon physics onto dark matter fields,The Astrophysical Journal921(2021) 66

    2021

  53. [61]

    Sinigaglia, F.-S

    F. Sinigaglia, F.-S. Kitaura, A. Balaguera-Antolínez, I. Shimizu, K. Nagamine, M. Sánchez-Benavente et al.,Mapping the Three-dimensional LyαForest Large-scale Structure in Real and Redshift Space, ApJ927(2022) 230 [2107.07917]

    2022

  54. [62]

    Kitaura, A

    F.S. Kitaura, A. Balaguera-Antolínez, F. Sinigaglia and M. Pellejero-Ibáñez,The cosmic web connection to the dark matter halo distribution through gravity, MNRAS512(2022) 2245 [2005.11598]

    2022

  55. [63]

    Werner and C

    K.F. Werner and C. Porciani,Renormalization of linear halo bias in N-body simulations, MNRAS492(2020) 1614 [1907.03774]. – 19 –

    2020

  56. [64]

    Vakili, F.-S

    M. Vakili, F.-S. Kitaura, Y. Feng, G. Yepes, C. Zhao, C.-H. Chuang et al.,Accurate halo-galaxy mocks from automatic bias estimation and particle mesh gravity solvers, MNRAS472(2017) 4144 [1701.03765]

    2017 arXiv

  57. [65]

    Pellejero-Ibañez, A

    M. Pellejero-Ibañez, A. Balaguera-Antolínez, F.-S. Kitaura, R.E. Angulo, G. Yepes, C.-H. Chuang et al.,The bias of dark matter tracers: assessing the accuracy of mapping techniques, MNRAS493(2020) 586 [1910.13164]

    2020

  58. [66]

    Forero Sánchez, F.S

    D. Forero Sánchez, F.S. Kitaura, F. Sinigaglia, J.M. Coloma-Nadal and J.P. Kneib, CosmoMIA: cosmic web-based redshift space halo distribution, J. Cosmology Astropart. Phys. 2024(2024) 001 [2402.17581]

    2024

  59. [67]

    Kaiser,Clustering in real space and in redshift space, MNRAS227(1987) 1

    N. Kaiser,Clustering in real space and in redshift space, MNRAS227(1987) 1

    1987

  60. [68]

    Kitaura, S

    F.-S. Kitaura, S. Gallerani and A. Ferrara,Multiscale inference of matter fields and baryon acoustic oscillations from the Lyαforest, MNRAS420(2012) 61 [1011.6233]

    2012 arXiv

  61. [69]

    Kitaura, P

    F.-S. Kitaura, P. Erdoˇ gdu, S.E. Nuza, A. Khalatyan, R.E. Angulo, Y. Hoffman et al.,Cosmic structure and dynamics of the local Universe, MNRAS427(2012) L35 [1205.5560]

    2012 arXiv

  62. [70]

    Heß, F.-S

    S. Heß, F.-S. Kitaura and S. Gottlöber,Simulating structure formation of the Local Universe, MNRAS435(2013) 2065 [1304.6565]

    2013 arXiv

  63. [71]

    Kitaura, M

    F.-S. Kitaura, M. Ata, R.E. Angulo, C.-H. Chuang, S. Rodríguez-Torres, C.H. Monteagudo et al.,Bayesian redshift-space distortions correction from galaxy redshift surveys, MNRAS457 (2016) L113 [1507.08724]

    2016 arXiv

  64. [72]

    Bos, F.-S

    E.G.P. Bos, F.-S. Kitaura and R. van de Weygaert,Bayesian cosmic density field inference from redshift space dark matter maps, MNRAS488(2019) 2573 [1810.05189]

    2019 arXiv

  65. [73]

    Sinigaglia, F.S

    F. Sinigaglia, F.S. Kitaura, K. Nagamine, Y. Oku and A. Balaguera-Antolínez,Field-level Lyman-αforest modeling in redshift space via augmented nonlocal Fluctuating Gunn-Peterson Approximation, A&A682(2024) A21 [2305.10428]

    2024

  66. [74]

    Sinigaglia, F.-S

    F. Sinigaglia, F.-S. Kitaura, K. Nagamine and Y. Oku,The negative BAO shift in the Lyα forest from cosmological simulations,arXiv e-prints(2024) arXiv:2407.03918 [2407.03918]

    2024

  67. [75]

    Sinha and L.H

    M. Sinha and L.H. Garrison,CORRFUNC - a suite of blazing fast correlation functions on the CPU, MNRAS491(2020) 3022 [1911.03545]

    2020

  68. [76]

    Alonso, J

    D. Alonso, J. Sanchez, A. Slosar and LSST Dark Energy Science Collaboration,A unified pseudo-Cℓ framework, MNRAS484(2019) 4127 [1809.09603]. – 20 –

    2019 arXiv

Pith tools

Reviewed May 18, 2026 · model on record in the stance chip above.