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Intrinsic alignment of disks and ellipticals across hydrodynamical simulations

T0 review · 5 major / 5 minor · reviewed 2026-08-04 · deepseek-v4-flash

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Pith's one-line read Disk galaxies align radially around ellipticals in three major simulations, with one negative exception tied to shape definition and redshift.

desk verdict A genuinely consistent cross-simulation IA comparison that localizes the negative disk signal to one specific recipe in Horizon-AGN; worth refereeing, but the fixed 10% elliptical split leaves the 'resolution' claim conditional. read the letter →

arxiv 2510.11118 v3 pith:CGM7JQQ5 submitted 2025-10-13 astro-ph.GA astro-ph.CO

M. L. van Heukelum , N. E. Chisari This is my paper
classification astro-ph.GAastro-ph.CO
keywords intrinsicalignmentsdiskgalaxiesellipticalhydrodynamicalsimulationsweaklensinggalaxyshapesmorphologyselectionquadrupolecorrelation
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 paper tries to settle conflicting measurements of disk galaxy intrinsic alignments by measuring the same statistics consistently across three hydrodynamical simulations. It finds that disk and elliptical alignments around galaxies are positive and robust in TNG300 and EAGLE, and positive or null in Horizon-AGN. The sole negative signal—disks around ellipticals—appears only for reduced shapes at z=1 when disks are identified by a rotational-velocity threshold. Re-weighting samples by stellar mass shows that mass alone does not set the alignment amplitude at small scales, pointing to sub-grid physics. If correct, the work reconciles earlier contradictory disk alignment results as artifacts of measurement choices.

What carries the argument

The central tool is the projected quadrupole statistic ξ̃_{g+,2}, estimated with a modified Landy–Szalay estimator, applied to galaxy shapes computed from both the simple and reduced inertia tensors. The morphological split into disks and ellipticals is made consistently across simulations using abundance matching on four variables: |v/σ|, κ_rot, r−i colour, and bulge-to-total ratio. This uniform re-measurement of shapes and selection variables is what allows a direct cross-simulation comparison.

What would settle it

Measure the disk-around-elliptical correlation in a larger simulation box (e.g., MillenniumTNG or COLIBRE) using reduced shapes and |v/σ| at z=1; if the negative signal does not reappear outside Horizon-AGN, the claim that this is a Horizon-AGN-specific effect is falsified. Alternatively, repeat the analysis using theoretically motivated thresholds (κ_rot > 0.5, |v/σ| > 1) instead of abundance matching; if the positive signals turn negative, the abundance-matching choice is the decisive factor.

Watch

Extended reading notes

Core claim

Using a uniform measurement pipeline for projected galaxy shapes and a fixed abundance-matching split into 10% ellipticals and 90% disks, the authors measure quadrupole alignments in TNG300, EAGLE, and Horizon-AGN at z=0 and z=1. They find that all galaxy position–shape correlations are positive or consistent with zero in the three simulations, except for one case: disks around ellipticals, defined by |v/σ|, with reduced shapes at z=1 in Horizon-AGN, which is negative. This negative signal matches the specific choices that produced the earlier negative detection in Horizon-AGN, implying that the longstanding tension in disk alignment measurements arises from differing methodologies and sampl

Load-bearing premise

The assumption that a fixed 10% elliptical / 90% disk abundance-matching split yields comparable morphological samples across all three simulations and both redshifts is load-bearing; if the true elliptical fraction differs by simulation or evolves with redshift, the cross-simulation sign and amplitude comparisons could be biased.

Editorial extensions

If this is right

  • Earlier positive, null, and negative disk alignment measurements in simulations can be reconciled: most of the spread is due to shape definition, sample selection, and redshift, not to intrinsic differences between simulations.
  • The negative disk-around-elliptical signal is not a generic simulation outcome; it is specific to reduced shapes at z=1 with a |v/σ| selection in Horizon-AGN.
  • The stellar mass distribution of a selected morphological sample explains much of the alignment amplitude at large scales, but not at small scales (r ≲ 3 Mpc/h), where other physics must be involved.
  • The consistent positive or null disk alignments measured here imply that blue/disk galaxies do show non-negligible intrinsic alignments in simulations, cautioning against weak-lensing mitigation strategies that assume no blue alignment.
  • The abundance-matching split, while not matching theoretical thresholds, provides a stable comparison baseline; the resulting signals are robust to shape choice and redshift in TNG300 and EAGLE.

Reading between the lines

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

  • If the same negative signal appears in other simulations when reduced shapes and |v/σ| are used at z=1, it would suggest a generic small-scale physical mechanism (e.g., tidal torquing of inner disk regions) rather than a Horizon-AGN artifact—testable with larger boxes like MillenniumTNG.
  • The re-weighting result implies that IA amplitude as a function of morphology may be set by an interplay of stellar mass and environment; a direct test would be measuring alignments in samples matched in both mass and large-scale density.
  • Observationally, the predicted difference between colour-selected and kinematics-selected disks is hard to test now, but upcoming integral-field surveys could provide the kinematic classifications needed to check whether the simulated distinction is physical.
  • The fixed 10% elliptical fraction, if relaxed to an evolving fraction, might change the sign or amplitude of the z=1 signals; this is a clean parameter to vary in a follow-up study.
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Editorial analysis

A structured set of objections, weighed in public.

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

Referee Report

5 major / 5 minor

Summary. The paper presents a systematic comparison of projected intrinsic-alignment quadrupoles in TNG300, EAGLE, and Horizon-AGN at z=0 and z=1, for simple and reduced inertia-tensor shapes and multiple morphological selections (|v/σ|, κ_rot, r−i, BTR, and stellar mass). Samples are split into disks and ellipticals by abundance matching with a fixed 10% elliptical fraction. The central claim is that all measured signals are positive or null except for one negative correlation: disks around ellipticals in Horizon-AGN at z=1, for reduced shapes and galaxies selected by |v/σ|. A re-weighting analysis in TNG300 is used to argue that sub-grid physics, not stellar mass alone, drives small-scale amplitude differences. The paper aims to resolve the conflicting disk-IA detections in the literature by showing that the negative signal is specific to a particular shape definition, redshift, and morphological proxy.

Significance. If the conclusions hold, this is a valuable reference comparison for the disk-IA field: it provides a consistent remeasurement of shapes, kinematics, and correlation statistics across three widely used simulations. The paper's strengths include the public code MEASUREIA validated against HALOTOOLS and TREECORR, jackknife covariances with N_jk=64, and resolution/box-size checks in Appendix A. The central negative-signal claim, however, is not quantified with a detection significance, and the fixed 10% abundance-matching split is acknowledged to be ad hoc; the reported robustness is therefore stronger than the evidence currently supports.

major comments (5)
  1. [§3.4, Fig. 10] The negative disks-around-ellipticals signal in Horizon-AGN is the paper's central new claim, but no detection significance or χ²/dof relative to zero is provided. The jackknife error bars in Fig. 10 appear large compared to the signal in several radial bins. Please quantify the detection (e.g., χ² against zero using the full covariance, or the number of bins exceeding 1σ/2σ).
  2. [§3.1.2, §4, Figs. 3–4] The fixed 10% elliptical fraction is an acknowledged ad hoc choice: it does not match the colour bimodality or the theoretically motivated thresholds κ_rot=0.5 and |v/σ|=1, and the |v/σ| distributions evolve in opposite directions in EAGLE and Horizon-AGN. Thus the 'ellipticals' selected as the lowest 10% of |v/σ| in Horizon-AGN at z=1 may be a different galaxy population than the corresponding 10% in TNG300/EAGLE, making the negative signal a potential selection artifact. Please test sensitivity to the elliptical fraction (e.g., 5%, 15%, 20%) and/or show persistence with physically motivated thresholds or mass-matched samples.
  3. [Abstract vs §3.5 and Conclusion 8] The submission's abstract states that the re-weighting 'suggests that stellar mass is the driving factor determining the amplitude of the correlations.' This directly contradicts §3.5 and Conclusion 8, which conclude that stellar mass can be ruled out as the main driver at non-linear scales and that sub-grid physics is responsible. The body text is internally consistent, but the abstract as written inverts the central result; this must be reconciled.
  4. [§3.2, Appendix C, Conclusions] The claim that disk and elliptical signals are 'positive and robust in EAGLE' is not supported by the paper's own error bars. §3.2 states that 'no robust conclusions can be drawn' in EAGLE, and Appendix C notes that the disk/elliptical selections overlap within errors. Please either soften the abstract/conclusion claim for EAGLE or provide quantitative evidence (e.g., stacked signals with errors) that the positive sign is robust.
  5. [§3.5, Fig. 11] The re-weighted correlation functions are shown without propagated uncertainties, and the conclusion that the offset increases at r≲3 Mpc/h is based on visual inspection. Please provide jackknife errors on the re-weighted curves or quote a significance for the offset (e.g., amplitude ratio at a fixed scale). Also state explicitly that this test is restricted to TNG300 and to the three morphological selections considered.
minor comments (5)
  1. [Eq. (16)] Equation (16) appears empty; either fill it with the intended expression or remove it.
  2. [§4] The references to 'COLIBRE ()' and 'MilleniumTNG ()' are missing citations; please add proper references.
  3. [Throughout] Typos and formatting issues: 'baded' should be 'based'; 'Dark Energy Survy' should be 'Survey'; 'V ogelsberger' has stray spacing; 'co¨ordinate' should be 'coordinate'.
  4. [§3.1.2] The term 'abundance matching' is used for a fixed 10% percentile split; this is not a match to an observed abundance. Consider using 'fixed percentile split' or clarify the terminology.
  5. [Fig. 10 caption] The caption should specify that the negative claim refers only to the |v/σ| reduced-shape z=1 panel, and should include a significance statement.

Circularity Check

0 steps flagged · score 0.0 of 10

No circular derivation: the reported alignment signals are direct measurements from simulation particle data, validated against external estimators; self-citations are consistency checks, not load-bearing inputs.

full rationale

This is an empirical measurement paper, not a derivation. The intrinsic-alignment quadrupoles are computed directly from galaxy particle data using the Landy-Szalay estimator (Eq. 4), the inertia tensors (Eqs. 1-2), and explicitly defined morphological variables (Section 2.4); no parameter is fitted to the correlation functions and then presented as a prediction. The only sample-adjustment choice, the fixed 10% elliptical fraction (§3.1.2), is made before the measurements and is explicitly acknowledged in §4 as not matching the colour bimodality or the theoretically motivated thresholds and as not accounting for redshift evolution; this is a validity limitation, not a circular step. The claimed exception - negative disks-around-ellipticals correlation in Horizon-AGN for reduced shapes, |v/σ|, z=1 - is a direct measurement. Its agreement with Chisari et al. (2015, 2016) is a consistency check, and those prior results are not inputs that force the sign. The measurement code is validated against external packages (HALOTOOLS, TREECORR), providing independent benchmark support. Self-citations occur, e.g. assuming S+R=0 'following Chisari et al. (2015)', but this random-point correction is standard and not load-bearing for the central conclusion. No equation or fitted quantity is equivalent by construction to the reported signals. Score 0.

Assumptions & free parameters 3 free parameters · 4 assumptions · 0 invented entities

No new physical entities are introduced. The paper's inputs are existing simulation outputs, public estimators, and hand-chosen selection criteria. The central claims rest on these measurement choices rather than on a fitted model, so the free-parameter count reflects selection choices rather than model fitting.

free parameters (3)
  • Elliptical fraction (abundance matching) = 10%
    Fixed split of the shape sample into 10% ellipticals and 90% disks applied at all redshifts and in all simulations (§3.1.2). Chosen by hand; the authors acknowledge it does not match colour bimodality or theoretical κ_rot/|v/σ| thresholds (§4).
  • Shape sample stellar mass cut = M_* > 10^9.15 M_sun/h
    Chosen to correspond to 300 stellar particles in TNG300 for converged shapes (§2.4). Resolution-motivated, not fitted to the IA signal.
  • Position sample stellar mass cut = M_* > 10^8.35 M_sun/h
    Chosen to correspond to 50 stellar particles in the lowest-resolution simulation (§2.4); resolution-motivated.
assumptions (4)
  • standard math Landy-Szalay estimator provides an unbiased estimate of galaxy-position-shape correlations
    Used for all correlation functions (§2.3); a standard statistical estimator.
  • domain assumption The quadrupole estimator ξ̃_{g+,2} from Singh et al. (2024) has higher signal-to-noise than w_g+ and correctly reconstructs alignment statistics
    The paper relies on this estimator for all main results (§2.3.2); no independent verification within this work beyond validating the code against existing tools.
  • domain assumption Jackknife covariance with N_jk=64 sub-volumes adequately captures the covariance of the correlation functions
    Used for all error bars (§2.3.3); relies on the Hirata et al. (2004) criterion, but jackknife from a single simulation volume underestimates cosmic variance.
  • domain assumption The three simulations (TNG300, EAGLE, Horizon-AGN) produce galaxy populations whose morphologies can be meaningfully compared
    Central to the cross-simulation comparison; differences in sub-grid physics are the intended subject but also act as a confound.

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Cite this review

Pith. "Pith review of Intrinsic alignment of disks and ellipticals across hydrodynamical simulations." pith.science (2026). https://pith.science/paper/CGM7JQQ5

@misc{pith2026251011118,
  author       = {Pith},
  title        = {Pith review of: Intrinsic alignment of disks and ellipticals across hydrodynamical simulations},
  year         = {2026},
  howpublished = {\url{https://pith.science/paper/CGM7JQQ5}},
  note         = {Machine review of arXiv:2510.11118}
}
abstract

The correlations between the positions and shapes of galaxies, i.e. intrinsic alignments, have been measured in many observational studies and hydrodynamical simulations. The position-shape correlation measurements of disk galaxies with varying methodologies, samples and hydrodynamical simulations are inconsistent in amplitude and sign. This work compares the correlations of disk and elliptical shapes around all galaxy positions and disk shapes around the positions of ellipticals at $z=0$ and $z=1$ for two different shape definitions in TNG300, Horizon-AGN and EAGLE for multiple morphological definitions in a consistent way. All types of signals are positive and robust in TNG300 and EAGLE and positive or null in Horizon-AGN. A re-weighting of the ellipticals around all galaxies correlations in TNG300, according to the underlying stellar mass distributions of the samples, suggests that stellar mass is the driving factor determining the amplitude of the correlations. The exception to this is the negative correlation of disks around ellipticals in Horizon-AGN. This arises for reduced shapes, which down-weight the outskirts of galaxies, at $z=1$, when disks are identified via a threshold in $|v/\sigma|$, the rotational velocity over the velocity dispersion.

Figures

Figures reproduced from arXiv: 2510.11118 by the authors.

Figure 6
Figure 6. For each simulation and selection made, the signals [PITH_FULL_IMAGE:figures/full_fig_p009_6.png] view at source ↗
Figure 7
Figure 7. The IA correlations of the elliptical shape samples [PITH_FULL_IMAGE:figures/full_fig_p013_7.png] view at source ↗

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Cited by 1 Pith paper

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Reference graph

Works this paper leans on

72 extracted references · 9 canonical work pages · cited by 1 Pith paper

  1. [1]

    Abbott T. M. C., et al., 2018, @doi [ ] 10.3847/1538-4365/aae9f0 , https://ui.adsabs.harvard.edu/abs/2018ApJS..239...18A 239, 18

    doi:10.3847/1538-4365/aae9f0 2018

  2. [2]

    Aihara H., et al., 2018, @doi [ ] 10.1093/pasj/psx066 , https://ui.adsabs.harvard.edu/abs/2018PASJ...70S...4A 70, S4

    doi:10.1093/pasj/psx066 2018

  3. [4]

    E., Codis S., Martin G., Dubois Y., Devriendt J., Pichon C., Slyz A., 2019, @doi [Monthly Notices of the Royal Astronomical Society] 10.1093/mnras/stz3166

    Bate J., Chisari N. E., Codis S., Martin G., Dubois Y., Devriendt J., Pichon C., Slyz A., 2019, @doi [Monthly Notices of the Royal Astronomical Society] 10.1093/mnras/stz3166

    doi:10.1093/mnras/stz3166 2019

  4. [5]

    K., Chen Y., Tenneti A., Di Matteo T., Mandelbaum R., 2019, @doi [Monthly Notices of the Royal Astronomical Society] 10.1093/mnras/stz3240 , 491, 4116–4130

    Bhowmick A. K., Chen Y., Tenneti A., Di Matteo T., Mandelbaum R., 2019, @doi [Monthly Notices of the Royal Astronomical Society] 10.1093/mnras/stz3240 , 491, 4116–4130

    doi:10.1093/mnras/stz3240 2019

  5. [6]

    R., et al., 2003, @doi [The Astrophysical Journal] 10.1086/375528 , 594, 186

    Blanton M. R., et al., 2003, @doi [The Astrophysical Journal] 10.1086/375528 , 594, 186

    doi:10.1086/375528 2003

  6. [7]

    E., Dvorkin C., 2013, @doi [Journal of Cosmology and Astroparticle Physics] 10.1088/1475-7516/2013/12/029 , 2013, 029–029

    Chisari N. E., Dvorkin C., 2013, @doi [Journal of Cosmology and Astroparticle Physics] 10.1088/1475-7516/2013/12/029 , 2013, 029–029

    doi:10.1088/1475-7516/2013/12/029 2013

  7. [8]

    Chisari N., et al., 2015, @doi [Monthly Notices of the Royal Astronomical Society] 10.1093/mnras/stv2154 , 454, 2736–2753

    doi:10.1093/mnras/stv2154 2015

  8. [9]

    Chisari N., et al., 2016, @doi [Monthly Notices of the Royal Astronomical Society] 10.1093/mnras/stw1409 , 461, 2702–2721

    doi:10.1093/mnras/stw1409 2016

Show all 72 references
  1. [10]

    E., et al., 2018, @doi [Monthly Notices of the Royal Astronomical Society] 10.1093/mnras/sty2093 , 480, 3962–3977

    Chisari N. E., et al., 2018, @doi [Monthly Notices of the Royal Astronomical Society] 10.1093/mnras/sty2093 , 480, 3962–3977

    2018 doi

  2. [11]

    A., et al., 2015, @doi [ ] 10.1093/mnras/stv725 , https://ui.adsabs.harvard.edu/abs/2015MNRAS.450.1937C 450, 1937

    Crain R. A., et al., 2015, @doi [ ] 10.1093/mnras/stv725 , https://ui.adsabs.harvard.edu/abs/2015MNRAS.450.1937C 450, 1937

    2015 doi

  3. [12]

    H., Appleby S., 2019, @doi [Monthly Notices of the Royal Astronomical Society] 10.1093/mnras/stz937 , 486, 2827–2849

    Davé R., Anglés-Alcázar D., Narayanan D., Li Q., Rafieferantsoa M. H., Appleby S., 2019, @doi [Monthly Notices of the Royal Astronomical Society] 10.1093/mnras/stz937 , 486, 2827–2849

    2019 doi

  4. [13]

    M., et al., 2023, @doi [Monthly Notices of the Royal Astronomical Society] 10.1093/mnras/stad1781 , 523, 5899–5914

    Delgado A. M., et al., 2023, @doi [Monthly Notices of the Royal Astronomical Society] 10.1093/mnras/stad1781 , 523, 5899–5914

    2023 doi

  5. [14]

    Dubois Y., et al., 2014, @doi [Monthly Notices of the Royal Astronomical Society] 10.1093/mnras/stu1227 , 444, 1453–1468

    2014 doi

  6. [15]

    Dubois Y., Peirani S., Pichon C., Devriendt J., Gavazzi R., Welker C., Volonteri M., 2016, @doi [Monthly Notices of the Royal Astronomical Society] 10.1093/mnras/stw2265 , 463, 3948–3964

    2016 doi

  7. [16]

    Genel S., et al., 2014, @doi [Monthly Notices of the Royal Astronomical Society] 10.1093/mnras/stu1654 , 445, 175

    2014 doi

  8. [17]

    M., Hernquist L., Vogelsberger M., Snyder G

    Genel S., Fall S. M., Hernquist L., Vogelsberger M., Snyder G. F., Rodriguez-Gomez V., Sijacki D., Springel V., 2015, @doi [ ] 10.1088/2041-8205/804/2/L40 , https://ui.adsabs.harvard.edu/abs/2015ApJ...804L..40G 804, L40

    2015 doi

  9. [18]

    E., Bilicki M., Barbera F

    Georgiou C., Chisari N. E., Bilicki M., Barbera F. L., Napolitano N. R., Roy N., Tortora C., 2025, Intrinsic galaxy alignments in the KiDS-1000 bright sample: dependence on colour, luminosity, morphology, and galaxy scale ( @eprint arXiv 2502.09452 ), https://arxiv.org/abs/2502.09452

    2025 arXiv

  10. [19]

    Haslbauer M., Banik I., Kroupa P., Wittenburg N., Javanmardi B., 2022, @doi [The Astrophysical Journal] 10.3847/1538-4357/ac46ac , 925, 183

    2022 doi

  11. [20]

    P., et al., 2017, @doi [The Astronomical Journal] 10.3847/1538-3881/aa859f , https://ui.adsabs.harvard.edu/abs/2017AJ....154..190H 154, 190

    Hearin A. P., et al., 2017, @doi [The Astronomical Journal] 10.3847/1538-3881/aa859f , https://ui.adsabs.harvard.edu/abs/2017AJ....154..190H 154, 190

    2017 doi

  12. [21]

    Hilbert S., Xu D., Schneider P., Springel V., Vogelsberger M., Hernquist L., 2017, @doi [Monthly Notices of the Royal Astronomical Society] 10.1093/mnras/stx482 , 468, 790–823

    2017 doi

  13. [23]

    Ivezi \'c Z ., et al., 2019, @doi [ ] 10.3847/1538-4357/ab042c , https://ui.adsabs.harvard.edu/abs/2019ApJ...873..111I 873, 111

    2019 doi

  14. [24]

    M., Fischer P., Smith D., Jain B., Tyson J

    Jarvis M., Bernstein G. M., Fischer P., Smith D., Jain B., Tyson J. A., Wittman D., 2003, @doi [The Astronomical Journal] 10.1086/367799 , 125, 1014–1032

    2003 doi

  15. [25]

    Jarvis M., Bernstein G., Jain B., 2004, @doi [Monthly Notices of the Royal Astronomical Society] 10.1111/j.1365-2966.2004.07926.x , 352, 338

    2004

  16. [26]

    Johnston, Harry et al., 2019, @doi [A&A] 10.1051/0004-6361/201834714 , 624, A30

    2019 doi

  17. [27]

    Kaviraj S., et al., 2017, @doi [Monthly Notices of the Royal Astronomical Society] 10.1093/mnras/stx126 , p. stx126

    2017 doi

  18. [28]

    Khandai N., Di Matteo T., Croft R., Wilkins S., Feng Y., Tucker E., DeGraf C., Liu M.-S., 2015, @doi [Monthly Notices of the Royal Astronomical Society] 10.1093/mnras/stv627 , 450, 1349

    2015 doi

  19. [29]

    Kiessling A., et al., 2015, @doi [Space Science Reviews] 10.1007/s11214-015-0203-6 , 193, 67–136

    2015 doi

  20. [30]

    Kogai K., Akitsu K., Schmidt F., Urakawa Y., 2021, @doi [Journal of Cosmology and Astroparticle Physics] 10.1088/1475-7516/2021/03/060 , 2021, 060

    2021 doi

  21. [31]

    Komatsu E., et al., 2011, @doi [The Astrophysical Journal Supplement Series] 10.1088/0067-0049/192/2/18 , 192, 18

    2011 doi

  22. [32]

    Kraljic K., Davé R., Pichon C., 2020, @doi [Monthly Notices of the Royal Astronomical Society] 10.1093/mnras/staa250 , 493, 362–381

    2020 doi

  23. [33]

    D., Szalay A

    Landy S. D., Szalay A. S., 1993, @doi [ ] 10.1086/172900 , https://ui.adsabs.harvard.edu/abs/1993ApJ...412...64L 412, 64

    1993 doi

  24. [34]

    arXiv:1110.3193

    Laureijs R., et al., 2011, @doi [arXiv e-prints] 10.48550/arXiv.1110.3193 , https://ui.adsabs.harvard.edu/abs/2011arXiv1110.3193L p. arXiv:1110.3193

    2011 doi arXiv

  25. [35]

    Lee J., Moon J.-S., 2022, @doi [The Astrophysical Journal] 10.3847/1538-4357/ac879d , 936, 119

    2022 doi

  26. [36]

    Lee J., et al., 2021, @doi [The Astrophysical Journal] 10.3847/1538-4357/abd08b , 908, 11

    2021 doi

  27. [37]

    Li S.-S., Kuijken K., Hoekstra H., Hildebrandt H., Joachimi B., Kannawadi A., 2021, @doi [ ] 10.1051/0004-6361/202039254 , https://ui.adsabs.harvard.edu/abs/2021A&A...646A.175L 646, A175

    2021 doi

  28. [38]

    M., Ishak M., Seljak U., Brinkmann J., 2006, @doi [Monthly Notices of the Royal Astronomical Society] 10.1111/j.1365-2966.2005.09946.x , 367, 611–626

    Mandelbaum R., Hirata C. M., Ishak M., Seljak U., Brinkmann J., 2006, @doi [Monthly Notices of the Royal Astronomical Society] 10.1111/j.1365-2966.2005.09946.x , 367, 611–626

    2006

  29. [39]

    Mandelbaum R., et al., 2011, @doi [Monthly Notices of the Royal Astronomical Society] 10.1111/j.1365-2966.2010.17485.x , 410, 844

    2011

  30. [40]

    A., Nichol R

    Maraston C., Strömbäck G., Thomas D., Wake D. A., Nichol R. C., 2009, @doi [Monthly Notices of the Royal Astronomical Society: Letters] 10.1111/j.1745-3933.2009.00621.x , 394, L107

    2009

  31. [41]

    McCullough J., et al., 2024, Dark Energy Survey Year 3: Blue Shear ( @eprint arXiv 2410.22272 ), https://arxiv.org/abs/2410.22272

    2024 arXiv

  32. [42]

    Moon J.-S., Lee J., 2024, @doi [The Astrophysical Journal] 10.3847/1538-4357/ad3825 , 966, 100

    2024 doi

  33. [43]

    Mortlock A., et al., 2013, @doi [Monthly Notices of the Royal Astronomical Society] 10.1093/mnras/stt793 , 433, 1185–1201

    2013 doi

  34. [44]

    Nelson D., et al., 2017, @doi [Monthly Notices of the Royal Astronomical Society] 10.1093/mnras/stx3040 , 475, 624–647

    2017 doi

  35. [45]

    Nelson D., et al., 2021, The IllustrisTNG Simulations: Public Data Release ( @eprint arXiv 1812.05609 ), https://arxiv.org/abs/1812.05609

    2021 arXiv

  36. [46]

    Pillepich A., et al., 2017, @doi [Monthly Notices of the Royal Astronomical Society] 10.1093/mnras/stx2656 , 473, 4077–4106

    2017 doi

  37. [47]

    Planck Collaboration et al., 2014, @doi [A&A] 10.1051/0004-6361/201321591 , 571, A16

    2014 doi

  38. [48]

    Planck Collaboration et al., 2016, @doi [A&A] 10.1051/0004-6361/201525830 , 594, A13

    2016 doi

  39. [49]

    Pulsoni C., Gerhard O., Arnaboldi M., Pillepich A., Nelson D., Hernquist L., Springel V., 2020, @doi [Astronomy & Astrophysics] 10.1051/0004-6361/202038253 , 641, A60

    2020 doi

  40. [50]

    M., 2009, @doi [International Journal of Modern Physics D] 10.1142/S0218271809014388 , 18, 173

    SCH\" A FER B. M., 2009, @doi [International Journal of Modern Physics D] 10.1142/S0218271809014388 , 18, 173

    2009 doi

  41. [51]

    Saga S., Shiraishi M., Akitsu K., Okumura T., 2024, @doi [Physical Review D] 10.1103/physrevd.109.043520 , 109

    2024 doi

  42. [52]

    Samuroff S., Mandelbaum R., Blazek J., 2021, @doi [Monthly Notices of the Royal Astronomical Society] 10.1093/mnras/stab2520 , 508, 637–664

    2021 doi

  43. [53]

    Schaye J., et al., 2015, @doi [ ] 10.1093/mnras/stu2058 , https://ui.adsabs.harvard.edu/abs/2015MNRAS.446..521S 446, 521

    2015 doi

  44. [54]

    S., Gao L., Crain R

    Shao S., Cautun M., Frenk C. S., Gao L., Crain R. A., Schaller M., Schaye J., Theuns T., 2016, @doi [Monthly Notices of the Royal Astronomical Society] 10.1093/mnras/stw1247 , 460, 3772–3783

    2016 doi

  45. [55]

    Shi J., Osato K., Kurita T., Takada M., 2021, @doi [The Astrophysical Journal] 10.3847/1538-4357/ac0cfa , 917, 109

    2021 doi

  46. [56]

    Singh S., Shakir A., Jagvaral Y., Mandelbaum R., 2024, Increasing the power of weak lensing survey data with multipole-based intrinsic alignment estimators ( @eprint arXiv 2307.02545 ), https://arxiv.org/abs/2307.02545

    2024 arXiv

  47. [57]

    Springel V., 2005, , 364, 1105

    2005

  48. [58]

    Springel V., 2010, @doi [Proceedings of the International Astronomical Union] 10.1017/S1743921311000378 , 6, 203–206

    2010 doi

  49. [59]

    Springel V., White S. D. M., Tormen G., Kauffmann G., 2001, @doi [ ] 10.1046/j.1365-8711.2001.04912.x , https://ui.adsabs.harvard.edu/abs/2001MNRAS.328..726S 328, 726

    2001

  50. [60]

    N., et al., 2014, @doi [Monthly Notices of the Royal Astronomical Society] 10.1093/mnras/stu1900 , 446, 2144

    Taylor E. N., et al., 2014, @doi [Monthly Notices of the Royal Astronomical Society] 10.1093/mnras/stu1900 , 446, 2144

    2014 doi

  51. [61]

    Tenneti A., Mandelbaum R., Di Matteo T., Feng Y., Khandai N., 2014, @doi [Monthly Notices of the Royal Astronomical Society] 10.1093/mnras/stu586 , 441, 470–485

    2014 doi

  52. [62]

    Tenneti A., Mandelbaum R., Di Matteo T., 2016, @doi [Monthly Notices of the Royal Astronomical Society] 10.1093/mnras/stw1823 , 462, 2668–2680

    2016 doi

  53. [63]

    Y., Feng Y., 2017, @doi [The Astrophysical Journal] 10.3847/1538-4357/834/2/169 , 834, 169

    Tenneti A., Gnedin N. Y., Feng Y., 2017, @doi [The Astrophysical Journal] 10.3847/1538-4357/834/2/169 , 834, 169

    2017 doi

  54. [64]

    Teyssier R., 2002, Astronomy & Astrophysics, 385, 337

    2002

  55. [65]

    W., et al., 2015, @doi [Monthly Notices of the Royal Astronomical Society] 10.1093/mnras/stv1461 , 452, 2879–2896

    Trayford J. W., et al., 2015, @doi [Monthly Notices of the Royal Astronomical Society] 10.1093/mnras/stv1461 , 452, 2879–2896

    2015 doi

  56. [66]

    Velliscig M., et al., 2015, @doi [Monthly Notices of the Royal Astronomical Society] 10.1093/mnras/stv2198 , 454, 3328–3340

    2015 doi

  57. [67]

    E., Schmidt F., 2021, @doi [Journal of Cosmology and Astroparticle Physics] 10.1088/1475-7516/2021/05/061 , 2021, 061

    Vlah Z., Chisari N. E., Schmidt F., 2021, @doi [Journal of Cosmology and Astroparticle Physics] 10.1088/1475-7516/2021/05/061 , 2021, 061

    2021 doi

  58. [68]

    Vogelsberger M., et al., 2014, @doi [Monthly Notices of the Royal Astronomical Society] 10.1093/mnras/stu1536 , 444, 1518

    2014 doi

  59. [69]

    Weinberger R., et al., 2016, @doi [Monthly Notices of the Royal Astronomical Society] 10.1093/mnras/stw2944 , 465, 3291–3308

    2016 doi

  60. [70]

    Welker C., Power C., Pichon C., Dubois Y., Devriendt J., Codis S., 2017, Caught in the rhythm II: Competitive alignments of satellites with their inner halo and central galaxy ( @eprint arXiv 1712.07818 ), https://arxiv.org/abs/1712.07818

    2017 arXiv

  61. [71]

    Zhang B., Lee K.-G., Krolewski A., Shi J., Horowitz B., Kooistra R., 2023, Alignments Between Galaxies and the Cosmic Web at z 1-2 in the IllustrisTNG Simulations ( @eprint arXiv 2211.09331 ), https://arxiv.org/abs/2211.09331

    2023 arXiv

  62. [72]

    de Jong J. T. A., Verdoes Kleijn G. A., Kuijken K. H., Valentijn E. A., 2013, @doi [Experimental Astronomy] 10.1007/s10686-012-9306-1 , https://ui.adsabs.harvard.edu/abs/2013ExA....35...25D 35, 25

    2013 doi

  63. [73]

    , " * write output.state after.block = add.period write newline

    ENTRY address author booktitle chapter edition editor howpublished institution journal key month note number organization pages publisher school series title type volume year label extra.label sort.label short.list INTEGERS output.state before.all mid.sentence after.sentence a...

  64. [74]

    write newline

    " write newline "" before.all 'output.state := FUNCTION n.dashify 't := "" t empty not t #1 #1 substring "-" = t #1 #2 substring "--" = not "--" * t #2 global.max substring 't := t #1 #1 substring "-" = "-" * t #2 global.max substring 't := while if t #1 #1 substring * t #2 gl...

Pith tools

Reviewed August 4, 2026 · model on record in the stance chip above.