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arxiv: 2605.30433 · v1 · pith:JKOIH5VAnew · submitted 2026-05-28 · 🌌 astro-ph.CO · astro-ph.GA

A Consistent Implementation of Cluster Strong Lensing in Cosmological Simulation Light Cones

Cian Roche , Mark Vogelsberger , Michael McDonald , Isaque Dutra , Priyamvada Natarajan , Xuejian Shen , Soumya Shreeram , R. Benton Metcalf
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Keren Sharon Simon Birrer Wonki Lee Massimo Meneghetti
This is my paper

Pith reviewed 2026-06-29 05:29 UTC · model grok-4.3

classification 🌌 astro-ph.CO astro-ph.GA
keywords cluster strong lensingcosmological simulationsline-of-sight structuregravitational lensingsimulation light conesmulti-plane ray tracingcritical curvesIllustrisTNG
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The pith

A remapping method lets cosmological simulations generate strong lensing images with all resolved line-of-sight structure drawn from the same volume.

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

The paper develops a procedure that remaps simulation volumes into lensing geometry and applies multi-plane ray tracing to produce images where the cluster lens, background sources, and all intervening objects come directly from the simulated particle data. This addresses the mismatch between cubic simulation boxes and the geometry of strong lensing while preserving spatial correlations across redshift. Prior hybrid methods often omitted line-of-sight structure or added it without maintaining correlations. When applied to IllustrisTNG data the method shows that uncorrelated line-of-sight structure shifts relative image positions by several arcseconds, adds roughly 6 percent scatter to the primary critical curve area, and alters total critical area within 100 arcseconds by 16+20-14 percent at source redshift 4. Consistent inclusion of this structure matters for turning abundant strong-lensing observations into precision cosmological constraints.

Core claim

The authors present a fully simulation-based procedure that generates strong-lensing images directly from particle data by combining structure-preserving remapping of the simulation volume into a lensing-appropriate geometry with multi-plane ray tracing. This draws the lens, source, and all intervening resolved objects self-consistently from the simulated large-scale structure. Using example light cones from IllustrisTNG, they quantify that uncorrelated line-of-sight structure shifts the relative positions of lensed images by several arcseconds, introduces a ~6% scatter in the area of a cluster's primary critical curve, and changes the total critical area within 100″ of the cluster potential

What carries the argument

Structure-preserving remapping of the simulation volume into a lensing-appropriate geometry combined with multi-plane ray tracing.

If this is right

  • Uncorrelated line-of-sight structure shifts relative positions of lensed images by several arcseconds.
  • It introduces ~6% scatter in the area of a cluster's primary critical curve.
  • It changes the total critical area within 100″ of the cluster potential minimum by 16+20%−14% at zs=4.
  • The method enables uniform simulation boxes to resolve both cluster-scale primary lenses and high-redshift source galaxies.

Where Pith is reading between the lines

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

  • Forecasts for cosmological parameters from cluster lensing surveys can now incorporate the full contribution of resolved line-of-sight structure rather than treating it as a separate uncertainty term.
  • The same light-cone construction could be applied to other simulation suites to test whether the reported scatter in critical-curve properties is robust to different galaxy-formation models.
  • Extending the ray-tracing to include lower-mass halos below the current resolution limit would reveal whether the 6-16% effects grow or saturate when more small-scale structure is added.

Load-bearing premise

The remapping of the simulation volume preserves the spatial correlations across redshift planes that are needed for correct multi-plane deflections.

What would settle it

A direct comparison of image positions, critical-curve areas, and total critical area statistics extracted from many simulated light cones against a comparable sample of observed galaxy-cluster lenses at similar redshifts.

Figures

Figures reproduced from arXiv: 2605.30433 by Cian Roche, Isaque Dutra, Keren Sharon, Mark Vogelsberger, Massimo Meneghetti, Michael McDonald, Priyamvada Natarajan, R. Benton Metcalf, Simon Birrer, Soumya Shreeram, Wonki Lee, Xuejian Shen.

Figure 1
Figure 1. Figure 1: — Schematic of the procedure by which many snapshots of a cosmological simulation run in a cubic box can be combined into a multi-plane strong lensing image. One source and one lens plane are created per simulation snapshot (i.e. redshift), and then the light from each source plane at redshift zs is ray traced through all lens planes with redshift zl such that zl < zs. The example plane shown in the diagra… view at source ↗
Figure 2
Figure 2. Figure 2: — A flowchart of the computation required for a single lensed image prediction using a group G from a cosmological simulation as the primary lens at a desired redshift zG. Note that lens plane i is not used in the computation of lensed result i and this arrow is included only to direct visuals. a 500 cMpc h −1 box at a mass resolution that can confidently resolve2 down to a mass of ∼ 4 × 1010 M⊙, and spati… view at source ↗
Figure 3
Figure 3. Figure 3: — An illustrative example of the outputs of the lensing pipeline. (Top Row) The surface brightness maps of 3 example planes in the light cone without lensing that surface brightness through the mass planes at lower redshifts. (Bottom Row) How each plane looks after ray tracing the maps through all lens planes at lower redshifts. Also marked is the position of any source in the unlensed panels which is mult… view at source ↗
Figure 4
Figure 4. Figure 4: — A grid of lensing quantities for light cones utilizing the first 4 groups in the group catalog of TNG300-1 at zG = 0.38 as primary lenses in the strong lensing pipeline described in this paper. The columns are (1) surface brightness in erg s−1 cm−2 Hz−1 for the whole lensed light cone of each group, computed in the JWST f200w filter but without observational effects, (2) the lensing convergence map κ for… view at source ↗
Figure 5
Figure 5. Figure 5: — The effective radius of the primary critical curve vs mass for light cones centered on all groups (clusters) above M200m = 5 × 1014 M⊙ in the TNG300-1 group catalog at zG = 0.38. The source plane redshift is chosen to be zs = 2. We also show the effective radii of the lens models of HST observations presented in Sharon et al. (2020) which describe clusters at various redshifts, each with zs = 2. In pink … view at source ↗
Figure 6
Figure 6. Figure 6: — The lensed surface brightness in the JWST f200w band of the light cone corresponding to group 1 in the TNG300-1 group catalog at zG = 0.38. Overlaid are all multiply imaged sources in the light cone which contain at least 2 visually identifiable images, along with two large arcs which do not correspond to multiple images. Some multiple images, especially in the cluster core, are not visually distinguisha… view at source ↗
Figure 7
Figure 7. Figure 7: — The lensed surface brightness in the JWST f200w band of the light cone corresponding to group 1 in the TNG300-1 group catalog at zG = 0.38, shown in the first panel by stacking the unlensed planes (marked as “No Lensing”). In the second panel, we perform ray tracing of the planes with z > zG using the mass in the primary lens plane only, labelled “Primary Lens Plane Only”, and note that this includes bot… view at source ↗
Figure 8
Figure 8. Figure 8: — (Left Column) The absolute magnitude of the magni￾fication due to groups 1 and 2 in the TNG300-1 group catalog at zG = 0.38, including correlated structure within ∼ 35 Mpc along the line of sight. (Right Column) The absolute magnitude of the magnification in the light cone corresponding to groups 1 and 2 in the TNG300-1 group catalog at zG = 0.38, including all line of sight material. In all panels we ch… view at source ↗
Figure 9
Figure 9. Figure 9: — Comparison of the primary critical curve area and total critical area on the sky within 100′′ of the cluster potential min￾imum both with and without line of sight material. We use light cones centered on all groups with M200m ≥ 5 × 1014 M⊙ in the TNG300-1 group catalog at zG = 0.38. In these light cones, the target cluster is chosen to be at redshift zG = 0.38 and the critical curves are computed for a … view at source ↗
read the original abstract

Galaxy cluster strong gravitational lensing plays a central role in precision cosmology, yet robust theoretical predictions have lagged behind an abundance of high-quality strong lensing observations. This shortfall reflects both a mismatch between the geometry of the strong-lensing problem and standard cubic simulation boxes, and the fundamental tension between simulation volume and resolution. Consequently, many current forecasts adopt hybrid approaches that extract individual lenses from simulations and combine them with analytic or observed source populations positioned near caustics. These methods often omit correlated and/or uncorrelated line-of-sight (LoS) structure, or include it in ways that do not preserve correlations across redshift. Here we present a fully simulation-based procedure that generates strong-lensing images directly from particle data, drawing the lens, source, and all intervening resolved objects self-consistently from the simulated large-scale structure. Our approach combines a structure-preserving remapping of the simulation volume into a lensing-appropriate geometry with multi-plane ray tracing, enabling the use of uniform simulation boxes that resolve both cluster-scale primary lenses and high-redshift source galaxies. We demonstrate the method by generating example light cones and images using IllustrisTNG data, then use these results to conservatively quantify the impact of LoS structure on image configurations and critical-curve morphology. We find that uncorrelated LoS structure can shift the relative positions of lensed images by several arcseconds, introduces a $\sim 6\%$ scatter in the area of a cluster's primary critical curve, and changes the total critical area within 100$^{\prime\prime}$ of the cluster potential minimum by $16^{+20\%}_{-14\%}$ at a source plane redshift of $z_s=4$.

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

2 major / 2 minor

Summary. The paper presents a fully simulation-based procedure for generating cluster strong-lensing images from cosmological simulations (e.g., IllustrisTNG) by combining a structure-preserving remapping of the periodic simulation volume into a lensing light-cone geometry with multi-plane ray tracing. This enables self-consistent inclusion of the primary lens, sources, and all resolved intervening structure. Using this method, the authors quantify the impact of uncorrelated line-of-sight structure, reporting image-position shifts of several arcseconds, ~6% scatter in primary critical-curve area, and a 16^{+20%}_{-14%} change in total critical area within 100″ at zs=4.

Significance. If the remapping step is shown to preserve the necessary correlations, the method would allow uniform simulation boxes to be used for strong-lensing forecasts while resolving both cluster-scale lenses and high-redshift sources, addressing a key limitation of current hybrid approaches. The quantitative estimates of LoS effects would then provide a concrete, simulation-derived benchmark for the systematic uncertainty introduced by uncorrelated structure in cluster-lensing cosmology.

major comments (2)
  1. [Abstract] Abstract: the headline quantifications (several-arcsec shifts, ~6% scatter, 16^{+20%}_{-14%} area change) are obtained by comparing light cones that include versus exclude uncorrelated LoS structure, both of which rely on the same remapping step; no independent test against an analytic multi-plane deflection solution or direct slicing of the original box is described to confirm that transverse and radial correlations are preserved at the few-percent level.
  2. [Method] Method section (procedure combining remapping with multi-plane ray tracing): the claim that the remapping is 'structure-preserving' is load-bearing for interpreting the reported scatters and area shifts as measurements rather than upper limits; without a quantitative validation metric (e.g., comparison of two-point functions or deflection-angle statistics before and after remapping), the central results on LoS impact cannot be assessed for robustness.
minor comments (2)
  1. [Abstract] The abstract states the central numbers but supplies no derivation details, error propagation, or description of how critical curves and image positions were measured; adding a brief methods paragraph or reference to the relevant subsection would improve clarity.
  2. [Results] Notation for the reported asymmetric uncertainty (16^{+20%}_{-14%}) should be defined explicitly in the text or a table caption to avoid ambiguity with standard error conventions.

Simulated Author's Rebuttal

2 responses · 0 unresolved

We thank the referee for their careful and constructive review. The comments highlight the need for explicit validation of the remapping procedure, which we address below by committing to additions in the revised manuscript.

read point-by-point responses

  1. Referee: [Abstract] Abstract: the headline quantifications (several-arcsec shifts, ~6% scatter, 16^{+20%}_{-14%} area change) are obtained by comparing light cones that include versus exclude uncorrelated LoS structure, both of which rely on the same remapping step; no independent test against an analytic multi-plane deflection solution or direct slicing of the original box is described to confirm that transverse and radial correlations are preserved at the few-percent level.

    Authors: We agree that the abstract reports results from the with/without-LoS comparison without an accompanying independent validation of the remapping. The manuscript describes the remapping algorithm in the Methods section as preserving the periodic density field by construction, but does not present quantitative tests such as power-spectrum comparisons or deflection-angle statistics against direct box slices. In the revised manuscript we will add a dedicated validation subsection (with a new figure) that performs these comparisons and demonstrates preservation of transverse and radial correlations at the few-percent level. revision: yes

  2. Referee: [Method] Method section (procedure combining remapping with multi-plane ray tracing): the claim that the remapping is 'structure-preserving' is load-bearing for interpreting the reported scatters and area shifts as measurements rather than upper limits; without a quantitative validation metric (e.g., comparison of two-point functions or deflection-angle statistics before and after remapping), the central results on LoS impact cannot be assessed for robustness.

    Authors: We concur that the absence of quantitative validation metrics leaves the interpretation of the LoS-induced shifts and area changes open to the concern raised. The current text relies on the design of the remapping to argue structure preservation, but does not supply the requested two-point function or deflection-angle comparisons. We will therefore expand the Methods section with the quantitative metrics described in our response to the abstract comment, allowing the central results to be assessed as measurements rather than upper limits. revision: yes

Circularity Check

0 steps flagged

No circularity: results are direct simulation outputs from new procedure

full rationale

The paper defines a remapping-plus-ray-tracing procedure and applies it to IllustrisTNG particle data to compute image shifts and critical-curve area changes when uncorrelated LoS structure is included versus excluded. These quantities are measured outputs of the simulation runs, not parameters fitted inside the same calculation or quantities defined in terms of the remapping itself. No self-citation, ansatz, or uniqueness theorem is invoked to force the reported percentages or arcsecond shifts. The derivation chain therefore remains self-contained; the headline numbers are falsifiable measurements rather than tautological restatements of the method inputs.

Axiom & Free-Parameter Ledger

0 free parameters · 1 axioms · 0 invented entities

Abstract-only review; the remapping step is treated as a domain assumption whose validity is not demonstrated here. No free parameters or invented entities are explicitly introduced in the provided text.

axioms (1)
  • standard math Multi-plane ray tracing through particle data accurately captures gravitational deflections from resolved structure at all redshifts
    Standard technique invoked by the multi-plane ray tracing component of the method.

pith-pipeline@v0.9.1-grok · 5887 in / 1462 out tokens · 26902 ms · 2026-06-29T05:29:26.351049+00:00 · methodology

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Works this paper leans on

106 extracted references · 105 canonical work pages · 5 internal anchors

  1. [1]

    A., Alves, D

    Alcock, C., Allsman, R. A., Alves, D. R., et al. 2000, ApJ, 542, 281, doi:10.1086/309512 Astropy Collaboration, Robitaille, T. P., Tollerud, E. J., et al. 2013, A&A, 558, A33, doi:10.1051/0004-6361/201322068 Astropy Collaboration, Price-Whelan, A. M., Sip˝ ocz, B. M., et al. 2018, AJ, 156, 123, doi:10.3847/1538-3881/aabc4f

    work page doi:10.1086/309512 2000

  2. [2]

    2018, MNRAS, 473, 4773, doi:10.1093/mnras/stx2630

    Ata, M., Baumgarten, F., Bautista, J., et al. 2018, MNRAS, 473, 4773, doi:10.1093/mnras/stx2630

    work page doi:10.1093/mnras/stx2630 2018

  3. [3]

    2016, Journal of Open Source Software, 1, 58, doi:10.21105/joss.00058

    Barbary, K. 2016, Journal of Open Source Software, 1, 58, doi:10.21105/joss.00058

    work page doi:10.21105/joss.00058 2016

  4. [4]

    Barrera, M., Springel, V., White, S. D. M., et al. 2023, Monthly Notices of the Royal Astronomical Society, 525, 6312, doi:10.1093/mnras/stad2688

    work page doi:10.1093/mnras/stad2688 2023

  5. [5]

    2010, Classical and Quantum Gravity, 27, 233001, doi:10.1088/0264-9381/27/23/233001

    Bartelmann, M. 2010, Classical and Quantum Gravity, 27, 233001, doi:10.1088/0264-9381/27/23/233001

    work page doi:10.1088/0264-9381/27/23/233001 2010

  6. [6]

    B., Hennawi, J

    Bayliss, M. B., Hennawi, J. F., Gladders, M. D., et al. 2011, The Astrophysical Journal Supplement Series, 193, 8, doi:10.1088/0067-0049/193/1/8

    work page doi:10.1088/0067-0049/193/1/8 2011

  7. [7]

    2019, A&A, 631, A130, doi:10.1051/0004-6361/201935974

    Bergamini, P., Rosati, P., Mercurio, A., et al. 2019, A&A, 631, A130, doi:10.1051/0004-6361/201935974

    work page doi:10.1051/0004-6361/201935974 2019

  8. [8]

    2021, A&A, 645, A140, doi:10.1051/0004-6361/202039564

    Bergamini, P., Rosati, P., Vanzella, E., et al. 2021, A&A, 645, A140, doi:10.1051/0004-6361/202039564

    work page doi:10.1051/0004-6361/202039564 2021

  9. [9]

    2023a, ApJ, 952, 84, doi:10.3847/1538-4357/acd643

    Bergamini, P., Acebron, A., Grillo, C., et al. 2023a, ApJ, 952, 84, doi:10.3847/1538-4357/acd643

    work page doi:10.3847/1538-4357/acd643

  10. [10]

    2023b, A&A, 674, A79, doi:10.1051/0004-6361/202244834

    Bergamini, P., Grillo, C., Rosati, P., et al. 2023b, A&A, 674, A79, doi:10.1051/0004-6361/202244834

    work page doi:10.1051/0004-6361/202244834

  11. [11]

    1996, , 117, 393, 10.1051/aas:1996164

    Bertin, E., & Arnouts, S. 1996, A&AS, 117, 393, doi:10.1051/aas:1996164

    work page doi:10.1051/aas:1996164 1996

  12. [12]

    Birrer, S., Welschen, C., Amara, A., & Refregier, A. 2017, J. Cosmology Astropart. Phys., 2017, 049, doi:10.1088/1475-7516/2017/04/049

    work page doi:10.1088/1475-7516/2017/04/049 2017

  13. [13]

    E., et al

    Birrer, S., Treu, T., Rusu, C. E., et al. 2019, MNRAS, 484, 4726, doi:10.1093/mnras/stz200

    work page doi:10.1093/mnras/stz200 2019

  14. [14]

    J., Gilman, D., et al

    Birrer, S., Shajib, A. J., Gilman, D., et al. 2021, Journal of Open Source Software, 6, 3283, doi:10.21105/joss.03283

    work page doi:10.21105/joss.03283 2021

  15. [15]

    D’Avanzo, et al., A complete sample of bright Swift Gamma-Ray Bursts: X-ray afterglow luminosity and its correlation with the prompt emission

    Boldrin, M., Giocoli, C., Meneghetti, M., & Moscardini, L. 2012, MNRAS, 427, 3134, doi:10.1111/j.1365-2966.2012.22120.x

    work page doi:10.1111/j.1365-2966.2012.22120.x 2012

  16. [16]

    2020, Journal of Open Source Software, 5, 2430, doi:10.21105/joss.02430

    Borrow, J., & Borrisov, A. 2020, Journal of Open Source Software, 5, 2430, doi:10.21105/joss.02430

    work page doi:10.21105/joss.02430 2020

  17. [17]

    Borrow, J., & Kelly, A. J. 2021, ArXiv e-prints. https://arxiv.org/abs/2106.05281

    work page arXiv 2021

  18. [18]

    D., Coe, D., Brammer, G., et al

    Bradley, L. D., Coe, D., Brammer, G., et al. 2023, ApJ, 955, 13, doi:10.3847/1538-4357/acecfe

    work page doi:10.3847/1538-4357/acecfe 2023

  19. [19]

    2010, ApJS, 190, 311, doi:10.1088/0067-0049/190/2/311 16 Roche et al

    Carlson, J., & White, M. 2010, ApJS, 190, 311, doi:10.1088/0067-0049/190/2/311 16 Roche et al

    work page doi:10.1088/0067-0049/190/2/311 2010

  20. [20]

    2025, MNRAS, 541, 2341, doi:10.1093/mnras/staf1076

    Cerny, C., Jauzac, M., Lagattuta, D., et al. 2025, MNRAS, 541, 2341, doi:10.1093/mnras/staf1076

    work page doi:10.1093/mnras/staf1076 2025

  21. [21]

    2026, ApJ, 1001, 60, doi:10.3847/1538-4357/ae41b0

    Cerny, C., Mahler, G., Sharon, K., et al. 2026, ApJ, 1001, 60, doi:10.3847/1538-4357/ae41b0

    work page doi:10.3847/1538-4357/ae41b0 2026

  22. [22]

    2024, MNRAS, 534, 1205, doi:10.1093/mnras/stae2150 de la Torre, S., Guzzo, L., Peacock, J

    Chen, Z., & Yu, Y. 2024, MNRAS, 534, 1205, doi:10.1093/mnras/stae2150 de la Torre, S., Guzzo, L., Peacock, J. A., et al. 2013, A&A, 557, A54, doi:10.1051/0004-6361/201321463

    work page doi:10.1093/mnras/stae2150 2024

  23. [23]

    D’Avanzo, et al., A complete sample of bright Swift Gamma-Ray Bursts: X-ray afterglow luminosity and its correlation with the prompt emission

    Dehnen, W., & Aly, H. 2012, MNRAS, 425, 1068, doi:10.1111/j.1365-2966.2012.21439.x

    work page doi:10.1111/j.1365-2966.2012.21439.x 2012

  24. [24]

    M., Fassnacht, C

    Despali, G., Heinze, F. M., Fassnacht, C. D., et al. 2025, A&A, 699, A222, doi:10.1051/0004-6361/202451546

    work page doi:10.1051/0004-6361/202451546 2025

  25. [25]

    Despali, G., Vegetti, S., White, S. D. M., et al. 2022, MNRAS, 510, 2480, doi:10.1093/mnras/stab3537

    work page doi:10.1093/mnras/stab3537 2022

  26. [26]

    I., Brien K

    Dolag, K., Borgani, S., Murante, G., & Springel, V. 2009, MNRAS, 399, 497, doi:10.1111/j.1365-2966.2009.15034.x

    work page doi:10.1111/j.1365-2966.2009.15034.x 2009

  27. [27]

    2025, ApJ, 978, 38, doi:10.3847/1538-4357/ad9b09

    Dutra, I., Natarajan, P., & Gilman, D. 2025, ApJ, 978, 38, doi:10.3847/1538-4357/ad9b09

    work page doi:10.3847/1538-4357/ad9b09 2025

  28. [28]

    K., Rigby, J

    Florian, M. K., Rigby, J. R., Acharyya, A., et al. 2021, ApJ, 916, 50, doi:10.3847/1538-4357/ac0257

    work page doi:10.3847/1538-4357/ac0257 2021

  29. [29]

    Fox, C., Mahler, G., Sharon, K., & Remolina Gonz´ alez, J. D. 2022, ApJ, 928, 87, doi:10.3847/1538-4357/ac5024

    work page doi:10.3847/1538-4357/ac5024 2022

  30. [30]

    2014, MNRAS, 445, 175, doi:10.1093/mnras/stu1654

    Genel, S., Vogelsberger, M., Springel, V., et al. 2014, MNRAS, 445, 175, doi:10.1093/mnras/stu1654

    work page doi:10.1093/mnras/stu1654 2014

  31. [31]

    2019, MNRAS, 487, 5721, doi:10.1093/mnras/stz1593

    Gilman, D., Birrer, S., Treu, T., Nierenberg, A., & Benson, A. 2019, MNRAS, 487, 5721, doi:10.1093/mnras/stz1593

    work page doi:10.1093/mnras/stz1593 2019

  32. [32]

    B., et al

    Giocoli, C., Jullo, E., Metcalf, R. B., et al. 2016, MNRAS, 461, 209, doi:10.1093/mnras/stw1336

    work page doi:10.1093/mnras/stw1336 2016

  33. [33]

    2024, ApJ, 973, 77, doi:10.3847/1538-4357/ad684a

    Gledhill, R., Strait, V., Desprez, G., et al. 2024, ApJ, 973, 77, doi:10.3847/1538-4357/ad684a

    work page doi:10.3847/1538-4357/ad684a 2024

  34. [34]

    2019, A&A, 626, A72, doi:10.1051/0004-6361/201834199

    Gouin, C., Gavazzi, R., Pichon, C., et al. 2019, A&A, 626, A72, doi:10.1051/0004-6361/201834199

    work page doi:10.1051/0004-6361/201834199 2019

  35. [35]

    R., Millman, K

    Harris, C. R., Millman, K. J., van der Walt, S. J., et al. 2020, Nature, 585, 357, doi:10.1038/s41586-020-2649-2

    work page doi:10.1038/s41586-020-2649-2 2020

  36. [36]

    2023, MNRAS, 518, 220, doi:10.1093/mnras/stac2779 Hern´ andez-Aguayo, C., Springel, V., Pakmor, R., et al

    He, Q., Nightingale, J., Robertson, A., et al. 2023, MNRAS, 518, 220, doi:10.1093/mnras/stac2779 Hern´ andez-Aguayo, C., Springel, V., Pakmor, R., et al. 2023, Monthly Notices of the Royal Astronomical Society, 524, 2556, doi:10.1093/mnras/stad1657

    work page doi:10.1093/mnras/stac2779 2023

  37. [37]

    D., Dalal, N., Marrone, D

    Hezaveh, Y. D., Dalal, N., Marrone, D. P., et al. 2016, ApJ, 823, 37, doi:10.3847/0004-637X/823/1/37

    work page doi:10.3847/0004-637x/823/1/37 2016

  38. [38]

    Hilbert, S., White, S. D. M., Hartlap, J., & Schneider, P. 2007, MNRAS, 382, 121, doi:10.1111/j.1365-2966.2007.12391.x

    work page doi:10.1111/j.1365-2966.2007.12391.x 2007

  39. [39]

    2012, MNRAS, 420, L18, doi:10.1111/j.1745-3933.2011.01184.x

    Host, O. 2012, MNRAS, 420, L18, doi:10.1111/j.1745-3933.2011.01184.x

    work page doi:10.1111/j.1745-3933.2011.01184.x 2012

  40. [40]

    L., & Sharon, K

    Johnson, T. L., & Sharon, K. 2016, ApJ, 832, 82, doi:10.3847/0004-637X/832/1/82

    work page doi:10.3847/0004-637x/832/1/82 2016

  41. [41]

    A., Koda, J., Blake, C., et al

    Kazin, E. A., Koda, J., Blake, C., et al. 2014, MNRAS, 441, 3524, doi:10.1093/mnras/stu778

    work page doi:10.1093/mnras/stu778 2014

  42. [42]

    2016, in Positioning and Power in Academic Publishing: Players, Agents and Agendas, ed

    Kluyver, T., Ragan-Kelley, B., P´ erez, F., et al. 2016, in Positioning and Power in Academic Publishing: Players, Agents and Agendas, ed. F. Loizides & B. Schmidt, IOS Press, 87 – 90

    2016

  43. [43]

    M., Aussel, H., Calzetti, D., et al

    Koekemoer, A. M., Aussel, H., Calzetti, D., et al. 2007, ApJS, 172, 196, doi:10.1086/520086

    work page doi:10.1086/520086 2007

  44. [44]

    2006, Physics Reports, 429, 1–65, doi:10.1016/j.physrep.2006.03.002

    Lewis, A., & Challinor, A. 2006, Physics Reports, 429, 1–65, doi:10.1016/j.physrep.2006.03.002

    work page doi:10.1016/j.physrep.2006.03.002 2006

  45. [45]

    Li, L.-X., & Ostriker, J. P. 2002, ApJ, 566, 652, doi:10.1086/338330

    work page doi:10.1086/338330 2002

  46. [46]

    D., Rangel, E

    Li, N., Gladders, M. D., Rangel, E. M., et al. 2016, ApJ, 828, 54, doi:10.3847/0004-637X/828/1/54

    work page doi:10.3847/0004-637x/828/1/54 2016

  47. [47]

    D., Bose, S., Angulo, R

    Ludlow, A. D., Bose, S., Angulo, R. E., et al. 2016, MNRAS, 460, 1214, doi:10.1093/mnras/stw1046

    work page doi:10.1093/mnras/stw1046 2016

  48. [48]

    2018, MNRAS, 473, 663, doi:10.1093/mnras/stx1971

    Mahler, G., Richard, J., Cl´ ement, B., et al. 2018, MNRAS, 473, 663, doi:10.1093/mnras/stx1971

    work page doi:10.1093/mnras/stx1971 2018

  49. [49]

    J., et al

    Manera, M., Scoccimarro, R., Percival, W. J., et al. 2013, MNRAS, 428, 1036, doi:10.1093/mnras/sts084

    work page doi:10.1093/mnras/sts084 2013

  50. [50]

    2018, Monthly Notices of the Royal Astronomical Society, 480, 5113, doi:10.1093/mnras/sty2206

    Marinacci, F., Vogelsberger, M., Pakmor, R., et al. 2018, Monthly Notices of the Royal Astronomical Society, 480, 5113, doi:10.1093/mnras/sty2206

    work page internal anchor Pith review doi:10.1093/mnras/sty2206 2018

  51. [51]

    2007a, A&A, 461, 25, doi:10.1051/0004-6361:20065722

    Meneghetti, M., Argazzi, R., Pace, F., et al. 2007a, A&A, 461, 25, doi:10.1051/0004-6361:20065722

    work page doi:10.1051/0004-6361:20065722

  52. [52]

    2007, MNRAS, 377, 352, doi: 10.1111/j.1365-2966.2007.11611.x

    Meneghetti, M., Bartelmann, M., Jenkins, A., & Frenk, C. 2007b, MNRAS, 381, 171, doi:10.1111/j.1365-2966.2007.12225.x

    work page doi:10.1111/j.1365-2966.2007.12225.x 2007

  53. [53]

    S., Uttley P., 2003, @doi [ ] 10.1046/j.1365-2966.2003.07042.x , http://adsabs.harvard.edu/abs/2003MNRAS.345.1271V 345, 1271

    Meneghetti, M., Bartelmann, M., & Moscardini, L. 2003, MNRAS, 346, 67, doi:10.1046/j.1365-2966.2003.07068.x

    work page doi:10.1046/j.1365-2966.2003.07068.x 2003

  54. [54]

    J., & Zeippen, C

    Meneghetti, M., Bolzonella, M., Bartelmann, M., Moscardini, L., & Tormen, G. 2000, MNRAS, 314, 338, doi:10.1046/j.1365-8711.2000.03350.x

    work page doi:10.1046/j.1365-8711.2000.03350.x 2000

  55. [55]

    2010, A&A, 519, A90, doi:10.1051/0004-6361/201014098

    Meneghetti, M., Fedeli, C., Pace, F., Gottl¨ ober, S., & Yepes, G. 2010, A&A, 519, A90, doi:10.1051/0004-6361/201014098

    work page doi:10.1051/0004-6361/201014098 2010

  56. [56]

    2017, MNRAS, 472, 3177, doi:10.1093/mnras/stx2064

    Meneghetti, M., Natarajan, P., Coe, D., et al. 2017, MNRAS, 472, 3177, doi:10.1093/mnras/stx2064

    work page doi:10.1093/mnras/stx2064 2017

  57. [57]

    2020, Science, 369, 1347, doi:10.1126/science.aax5164

    Meneghetti, M., Davoli, G., Bergamini, P., et al. 2020, Science, 369, 1347, doi:10.1126/science.aax5164

    work page doi:10.1126/science.aax5164 2020

  58. [58]

    2022, A&A, 668, A188, doi:10.1051/0004-6361/202243779

    Meneghetti, M., Ragagnin, A., Borgani, S., et al. 2022, A&A, 668, A188, doi:10.1051/0004-6361/202243779

    work page doi:10.1051/0004-6361/202243779 2022

  59. [59]

    2023, A&A, 678, L2, doi:10.1051/0004-6361/202346975

    Meneghetti, M., Cui, W., Rasia, E., et al. 2023, A&A, 678, L2, doi:10.1051/0004-6361/202346975

    work page doi:10.1051/0004-6361/202346975 2023

  60. [60]

    B., & Petkova, M

    Metcalf, R. B., & Petkova, M. 2014, MNRAS, 445, 1942, doi:10.1093/mnras/stu1859

    work page doi:10.1093/mnras/stu1859 2014

  61. [61]

    Minor, Q. E. 2025, ApJ, 981, 2, doi:10.3847/1538-4357/adb1b6

    work page doi:10.3847/1538-4357/adb1b6 2025

  62. [62]

    O., Yang, D., & Yu, H.-B

    Nadler, E. O., Yang, D., & Yu, H.-B. 2023, ApJ, 958, L39, doi:10.3847/2041-8213/ad0e09

    work page doi:10.3847/2041-8213/ad0e09 2023

  63. [63]

    P., Pillepich, A., Springel, V., et al

    Naiman, J. P., Pillepich, A., Springel, V., et al. 2018, Monthly Notices of the Royal Astronomical Society, 477, 1206, doi:10.1093/mnras/sty618

    work page internal anchor Pith review doi:10.1093/mnras/sty618 2018

  64. [64]

    Natarajan, P., Williams, L. L. R., Bradaˇ c, M., et al. 2024, Space Sci. Rev., 220, 19, doi:10.1007/s11214-024-01051-8

    work page doi:10.1007/s11214-024-01051-8 2024

  65. [65]

    2021, The IllustrisTNG Simulations: Public Data Release

    Nelson, D., Springel, V., Pillepich, A., et al. 2021, The IllustrisTNG Simulations: Public Data Release. https://arxiv.org/abs/1812.05609

    work page arXiv 2021

  66. [66]

    2023, Monthly Notices of the Royal Astronomical Society, 524, 2883, doi:10.1093/mnras/stad1999

    Niemiec, A., Jauzac, M., Eckert, D., et al. 2023, Monthly Notices of the Royal Astronomical Society, 524, 2883, doi:10.1093/mnras/stad1999

    work page doi:10.1093/mnras/stad1999 2023

  67. [67]

    P., et al

    Pakmor, R., Springel, V., Coles, J. P., et al. 2023, MNRAS, 524, 2539, doi:10.1093/mnras/stac3620

    work page doi:10.1093/mnras/stac3620 2023

  68. [68]

    T., Gaudi, B

    Penny, M. T., Gaudi, B. S., Kerins, E., et al. 2019, ApJS, 241, 3, doi:10.3847/1538-4365/aafb69

    work page doi:10.3847/1538-4365/aafb69 2019

  69. [69]

    B., & Giocoli, C

    Petkova, M., Metcalf, R. B., & Giocoli, C. 2014, MNRAS, 445, 1954, doi:10.1093/mnras/stu1860

    work page doi:10.1093/mnras/stu1860 2014

  70. [70]

    2018, MNRAS, 473, 4077, doi: 10.1093/mnras/stx2656

    Pillepich, A., Springel, V., Nelson, D., et al. 2017, Monthly Notices of the Royal Astronomical Society, 473, 4077, doi:10.1093/mnras/stx2656

    work page internal anchor Pith review doi:10.1093/mnras/stx2656 2017

  71. [71]

    2018, MNRAS, 475, 648, doi:10.1093/mnras/stx3112 Planck Collaboration, Ade, P

    Pillepich, A., Nelson, D., Hernquist, L., et al. 2018, MNRAS, 475, 648, doi:10.1093/mnras/stx3112 Planck Collaboration, Ade, P. A. R., Aghanim, N., et al. 2016, A&A, 594, A13, doi:10.1051/0004-6361/201525830 Planck Collaboration, Aghanim, N., Akrami, Y., et al. 2020, A&A, 641, A8, doi:10.1051/0004-6361/201833886

    work page internal anchor Pith review doi:10.1093/mnras/stx3112 2018

  72. [72]

    M., McKean, J

    Powell, D. M., McKean, J. P., Vegetti, S., et al. 2025, Nature Astronomy, 9, 1714, doi:10.1038/s41550-025-02651-2

    work page doi:10.1038/s41550-025-02651-2 2025

  73. [73]

    A., Keeton, C

    Raney, C. A., Keeton, C. R., & Brennan, S. 2020, MNRAS, 492, 503, doi:10.1093/mnras/stz3116 Remolina Gonz´ alez, J. D., Sharon, K., Li, N., et al. 2021a, ApJ, 910, 146, doi:10.3847/1538-4357/abe62a —. 2021b, ApJ, 910, 146, doi:10.3847/1538-4357/abe62a Remolina Gonz´ alez, J. D., Sharon, K., Reed, B., et al. 2020, ApJ, 902, 44, doi:10.3847/1538-4357/abb2a1

    work page doi:10.1093/mnras/stz3116 2020

  74. [74]

    2020, MNRAS, 494, 4706, doi:10.1093/mnras/staa1076

    Robertson, A., Massey, R., & Eke, V. 2020, MNRAS, 494, 4706, doi:10.1093/mnras/staa1076

    work page doi:10.1093/mnras/staa1076 2020

  75. [75]

    2024, The Open Journal of Astrophysics, 7, doi:10.33232/001c.122309

    Roche, C., McDonald, M., Borrow, J., et al. 2024, The Open Journal of Astrophysics, 7, doi:10.33232/001c.122309

    work page doi:10.33232/001c.122309 2024

  76. [76]

    1994, ApJ, 436, 509, doi:10.1086/174924

    Seljak, U. 1994, ApJ, 436, 509, doi:10.1086/174924

    work page doi:10.1086/174924 1994

  77. [77]

    2025, Nature Astronomy, doi:10.1038/s41550-025-02519-5

    Shan, X., Hu, B., Chen, X., & Cai, R.-G. 2025, Nature Astronomy, doi:10.1038/s41550-025-02519-5

    work page doi:10.1038/s41550-025-02519-5 2025

  78. [78]

    B., Dahle, H., et al

    Sharon, K., Bayliss, M. B., Dahle, H., et al. 2020, The Astrophysical Journal Supplement Series, 247, 12, doi:10.3847/1538-4365/ab5f13

    work page doi:10.3847/1538-4365/ab5f13 2020

  79. [79]

    2025a, A&A, 697, A22, doi:10.1051/0004-6361/202452271

    Shreeram, S., Comparat, J., Merloni, A., et al. 2025a, A&A, 697, A22, doi:10.1051/0004-6361/202452271

    work page doi:10.1051/0004-6361/202452271

  80. [80]

    2025b, arXiv e-prints, arXiv:2506.17222, doi:10.48550/arXiv.2506.17222

    Shreeram, S., Gal´ arraga-Espinosa, D., Comparat, J., et al. 2025b, arXiv e-prints, arXiv:2506.17222, doi:10.48550/arXiv.2506.17222

    work page doi:10.48550/arxiv.2506.17222

Showing first 80 references.