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Fully non-linear simulations of galaxy intrinsic alignments for weak lensing with the MillenniumTNG lightcone

T0 review · 2 major / 6 minor · reviewed 2026-08-07 · deepseek-v4-flash

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Pith's one-line read Simulations show galaxy intrinsic alignments shift weak-lensing convergence statistics by up to 30 percent, a level Stage IV surveys must model.

desk verdict Substantial forward-model result quantifying IA contamination in WL statistics from a large hydro lightcone; the shape-estimator resolution caveat makes the headline amplitudes indicative rather than definitive. read the letter →

arxiv 2505.15882 v1 pith:RXAZ7DY6 submitted 2025-05-21 astro-ph.CO astro-ph.GA

Fulvio Ferlito , Volker Springel , Christopher T. Davies , Toshiki Kurita , Ana Maria Delgado , Sownak Bose , Lars Hernquist This is my paper
classification astro-ph.COastro-ph.GA
keywords intrinsicalignmentsweaklensingconvergencestatisticsMillenniumTNGforwardmodelingshearcorrelationfunctionhydrodynamicalsimulation
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 builds a complete weak-lensing galaxy catalogue from the 740 Mpc MillenniumTNG hydrodynamical simulation, computing both the intrinsic shapes of galaxies and the gravitational shear acting on them through full-sky ray tracing. It then compares convergence maps made with and without intrinsic alignments, isolating the IA contribution by randomizing galaxy orientations while preserving shape noise. The central result is that intrinsic alignments modify the convergence power spectrum by up to 20 percent at all angular scales, reshape the convergence PDF tails by 10–20 percent, and distort peak and minimum counts by up to 30 percent, with strong dependence on redshift and galaxy stellar mass. For the most massive galaxy samples, the intrinsic shear autocorrelation becomes comparable to the gravitational shear signal on small angular scales. The authors argue these effects are large enough that Stage IV surveys need fully non-linear forward modeling of intrinsic alignments rather than analytic corrections.

What carries the argument

The central object is a seamless lightcone from the MTNG740 hydrodynamical simulation, from which galaxies are identified with subhalo finders. The intrinsic shear of each galaxy is computed from the V-band luminosity-weighted inertia tensor of its stellar particles, converted to shear with responsivity $R=1$; the extrinsic (lensing) shear is obtained by full-sky ray tracing with the DORIAN code without invoking the Born approximation. Convergence maps are built through the Kaiser-Squires inversion of shear at the observed galaxy positions. The isolating step is the 'randomized orientations' comparison: keeping each galaxy's shape modulus but rotating its orientation by a random angle erases the alignment while preserving shape noise, so the difference between the 'WL + GSN + IA' and 'WL + GSN' maps is purely the IA signal.

What would settle it

Recompute the convergence statistics using the same lightcone but with intrinsic shears obtained from higher-resolution zoom-in simulations of a matched galaxy sample; if the ellipticity distribution becomes less round at low redshift and the IA fractions change by more than the statistical errors, the shape estimator is the limiting assumption. Alternatively, measure the IA-induced convergence power spectrum modulation in a Stage IV deep field and compare the low-redshift amplitude directly with the simulation's prediction.

Watch

Extended reading notes

Core claim

In the MTNG740 lightcone spanning one octant of the sky out to z=1.5, intrinsic alignments are a first-order contaminant of weak-lensing observables. The convergence power spectrum acquires a redshift- and scale-dependent modulation: roughly a 10 percent enhancement at high redshift, a scale-dependent increase peaking at 20 percent at small scales in the intermediate bin, and a transition from about 10 percent suppression at large scales to 20 percent enhancement at small scales in the lowest bin. This behavior follows from the interplay of the negative gravitational-intrinsic cross-correlation (GI), which dominates at low redshift, and the positive intrinsic-intrinsic autocorrelation (II), which dominates at high redshift. The convergence PDF, peak, and minimum counts respond accordingly, with tail changes up to 30 percent, and the signal grows strongly with stellar mass cuts: for $M_* > 5\times 10^{10}\,h^{-1}M_\odot$, the II autocorrelation reaches the same order as the gravitational shear autocorrelation, even dominating the minus component below about 7 arcminutes. The measured IA signal is only approximately captured by the Nonlinear Alignment model, which deviates from the simulated pipeline by up to about 50 percent.

Load-bearing premise

The simulated galaxy shapes, derived from the V-band luminosity-weighted inertia tensor of stellar particles with responsivity $R=1$, faithfully represent the true ellipticities and alignments of galaxies; the paper itself notes that low particle counts may artificially round galaxies at low redshift, which would bias the IA amplitude.

Editorial extensions

If this is right

  • Stage IV surveys like Euclid, Rubin, and Roman will need to include non-linear intrinsic alignment modeling in their convergence statistics pipelines, since analytic NLA corrections deviate from the simulated signal by up to about 50 percent.
  • Intrinsic alignments affect higher-order statistics (PDF, peaks, minima) at the 10–30 percent level, so constraints derived from those statistics must marginalize over or forward-model IA.
  • Applying stellar mass cuts that select massive galaxies strengthens the IA contamination, making shape-calibration and IA treatment especially important for samples biased toward high stellar mass.
  • The same lightcone forward-modeling framework can be extended to other observables, such as galaxy-galaxy lensing, without additional analytic approximations.

Reading between the lines

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

  • If the simulated IA fractions are correct, tomographic cosmological inference from Stage IV surveys could be biased unless IA is modeled non-linearly; a direct quantification would propagate these convergence shifts into posterior shifts for $S_8$ and $\Omega_m$.
  • The paper's own caveat about low particle counts artificially rounding galaxies at low redshift implies the low-redshift IA contamination may be underestimated; higher-resolution zoom simulations of matched galaxies could test this and would likely revise the quoted fractions.
  • The orientation-randomization technique provides a clean calibration strategy that could be applied to other hydro simulations or observational shape catalogues to separate IA from shape noise without relying on a particular analytic model.
  • Releasing the shear catalogue will let other groups test IA models directly against a non-linear forward model, potentially replacing NLA as the standard benchmark.
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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

2 major / 6 minor

Summary. This paper presents a forward-modeled weak lensing galaxy catalogue from the MillenniumTNG740 hydrodynamical lightcone. For each galaxy the authors compute an intrinsic shear from the V-band luminosity-weighted inertia tensor of stellar particles and a gravitational shear from full-sky ray tracing with DORIAN, then build convergence maps for four shear combinations: WL, GSN, WL+GSN, and WL+GSN+IA. They measure shear correlation functions, convergence power spectra, PDFs, and peak and minimum counts in three redshift bins and for three stellar-mass thresholds. The central quantitative claim is that IA modifies the convergence power spectrum by up to about 20%, alters PDF tails by 10-20%, changes peak and minimum counts by up to about 30%, and that for high stellar-mass cuts the intrinsic-intrinsic correlation approaches the gravitational shear correlation. They also fit an NLA amplitude to the simulated correlation functions as a validation step.

Significance. If the quantitative claims hold, this is a valuable demonstration that fully non-linear, simulation-based IA modeling is needed for Stage IV lensing analyses. The orientation-randomization control is a clean way to isolate IA while preserving shape noise, and the use of a single large-volume lightcone with both intrinsic and ray-traced lensing shears is a methodological step forward. The paper is transparent about pipeline ingredients and flags the main resolution limitation. However, the headline percentages are currently presented without sampling error bars and rest on a shape estimator whose resolution dependence is acknowledged but not quantified, so the strength of the conclusions is not yet matched by the presented evidence.

major comments (2)
  1. [Sec. 3.4 / Eq. (18)] The fidelity of the V-band luminosity-weighted inertia-tensor shapes (Eq. 18) is the load-bearing element of the analysis. The catalogue is built from subhalos with only 100 stellar particles (Sec. 3.3), and Sec. 3.4 itself states that low particle counts can lead to artificially short relaxation times and exaggerated roundness at low redshift. Because ξ_II scales as the square of the intrinsic shear amplitude and ξ_GI scales linearly, and because the PDF, peak, and minimum statistics inherit these amplitudes, the quoted 20%, 10-20%, and 30% impacts are directly sensitive to this resolution effect. The manuscript should quantify this sensitivity (e.g., through zoom-in simulations or a particle-threshold/shape-estimator comparison) or explicitly qualify the headline numbers as lower limits or resolution-dependent estimates. As written, the abstract and conclusions report these percentages without that qualification.
  2. [Sec. 4.2.2 / Figs. 5-6] All impact ratios are derived from a single octant of the sky, and no error bars are provided for the ratios shown in Figs. 5 and 6 or for the correlation-function ratios in Figs. 4 and 7. Without jackknife, bootstrap, or split-sample estimates, it is unclear which of the 5-20% features are significant relative to cosmic variance and shot noise. The construction of the 'WL+IA' power spectrum by subtracting the GSN spectrum from the WL+GSN+IA spectrum (Sec. 4.2.2) adds a further single-realization subtraction whose residual cross-terms are not estimated. Adding error estimates or at least explicitly labeling the results as single-realization estimates is necessary to support the quantitative central claim.
minor comments (6)
  1. [Sec. 4.1] The NLA fit is not an independent validation because the A1 amplitude is fitted to the same simulated correlation functions; the statement that the NLA model 'provides good overall agreement' should be reframed as a consistency check, and the best-fit A1 values should be quoted with uncertainties and with the fit range and weighting specified.
  2. [Sec. 3.4] The caveat about numerical resolution should be connected to the abstract's quantitative claims; as written, the caveat appears only in the methods section and is not carried into the conclusions.
  3. [Sec. 3.6 / 4.2.2] Please specify whether the randomized-orientation field used for the 'GSN' map is the same realization as that used in the 'WL+GSN' map, and describe how realization-specific cross-terms are treated in the subtraction used to obtain the 'WL+IA' spectrum.
  4. [Sec. 2.3] There is a typo: 'fileds' should be 'fields'; in the footnote, 'formθ' should be 'from θ'.
  5. [Sec. 4.3 / Fig. 7] The text states that ξ−,II dominates ξ−,GG below about 7 arcmin, while the caption says the IA signal is 'comparable' to the WL signal; please make the statement precise about which component and which angular scales are meant.
  6. [Data availability] The catalogue is the main product but is only promised for future release; providing an access mechanism or explicit release plan would improve reproducibility.

Circularity Check

1 steps flagged · score 2.0 of 10

Only minor circularity: the NLA 'theoretical prediction' in Sec. 4.1 has its amplitude fitted to the same measured ξ_II and ξ_GI curves it is then compared with; the headline IA-impact results are direct forward-model measurements and are not circular.

  1. fitted input called prediction [Section 4.1, Figure 3 caption and surrounding text (A1 best-fit description)]
    "Best-fit values of the alignment amplitude, obtained by minimizing the root mean square error between the NLA prediction and our data for θ≳2 arcmin, are approximately A1 ≈ [2.06,2.55,3.52] for the low-, intermediate-, and high-redshift bin respectively. Overall, we observe a qualitatively good agreement between our results and the theoretical predictions in the angular range we investigate."

    The NLA 'theory prediction' for ξ_II and ξ_GI is not an independent prediction: its only free parameter, A1, is obtained by fitting the NLA model to the same measured ξ_II/ξ_GI curves that are then displayed as the comparison. Minimizing the RMSE against those curves forces agreement in overall amplitude, so the quoted 'good overall agreement' is partly the residual of a fit rather than an external validation. The scale dependence of the correlation functions is not fixed by A1 and does provide non-trivial information, and the central IA-impact results (convergence power-spectrum ratios, PDF, peak and minimum counts) are measured directly from the forward model with a randomized-orientation control, so this fitted-input validation step is not load-bearing for the headline numbers.

full rationale

The paper's central claim is a direct simulation measurement: intrinsic shear is computed from the V-band luminosity-weighted inertia tensor of stellar particles (Eq. 18), gravitational shear from full-sky ray tracing with DORIAN, and the IA contribution is isolated by comparing actual galaxy orientations with a randomized-orientation control that preserves shape noise. This is a controlled forward-model experiment, not a fit renamed as a prediction, so the headline statistics (up to 20% power-spectrum modification, 10-20% PDF tail changes, up to 30% peak/minimum distortions, and ξ_II comparable to ξ_GG at high stellar mass) do not reduce to their inputs by construction. The only circular element is the validation step in Sec. 4.1: the NLA amplitude A1 is fitted to the same ξ_II/ξ_GI measurements against which the NLA model is then displayed and described as agreeing. Because the fit is openly stated and the comparison is not used to derive the main results, this is a minor, non-load-bearing circularity rather than a fundamental one. Self-citations to Delgado et al. (2023) for the shape-estimator convention and to Ferlito et al. (2024) for DORIAN are not load-bearing: D23 is a prior independent measurement on the same simulation, and DORIAN is a public code with external validation; neither is invoked as a uniqueness theorem to forbid alternatives. The admitted resolution limitation (low stellar-particle counts causing artificially round shapes at low redshift) and the absence of a public catalogue are correctness or reproducibility risks, not circularity. Overall, the derivation chain for the central IA-impact claim is self-contained, with only a minor validation-fit issue, so the circularity score is low.

Assumptions & free parameters 2 free parameters · 4 assumptions · 0 invented entities

The ledger captures the main parameter choices and assumptions. The only numerical fits are NLA amplitudes used for validation; the central IA impact is measured directly. No new physical entities are introduced.

free parameters (2)
  • NLA alignment amplitude A1 = redshift bins: [2.06, 2.55, 3.52]; mass bins: [3.31, 4.07, 7.93]
    Fitted to simulated xiII and xiGI by RMSE minimization in Secs 4.1 and 4.3; used as validation, not as the central claim.
  • Galaxy selection thresholds = 100 stellar particles; M_total >= 1e10 M_sun; effective M_star >= ~1e9 M_sun
    Chosen to approximate Stage IV survey samples (Sec 3.3); affects source density and mass dependence but not fitted to the target result.
assumptions (4)
  • domain assumption MTNG740 hydrodynamics and galaxy formation model produces realistic galaxy shapes and alignments.
    Central claim relies on simulation fidelity; no observational calibration of shapes is performed in this work.
  • domain assumption V-band luminosity-weighted inertia tensor with R=1 maps simulation stellar shapes to observed ellipticity and shear.
    Sec 3.4; if the shape estimator is biased, all IA statistics shift.
  • domain assumption Randomizing intrinsic orientations removes IA while preserving shape noise exactly.
    Sec 3.6; controls depend on orientations being uncorrelated with large-scale structure after randomization.
  • domain assumption Ray tracing and Kaiser-Squires inversion from shear at galaxy positions yield unbiased convergence maps.
    Sec 3.5 and 3.6; interpolation and KS inversion introduce approximations.

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Cite this review

Pith. "Pith review of Fully non-linear simulations of galaxy intrinsic alignments for weak lensing with the MillenniumTNG lightcone." pith.science (2026). https://pith.science/paper/RXAZ7DY6

@misc{pith2026250515882,
  author       = {Pith},
  title        = {Pith review of: Fully non-linear simulations of galaxy intrinsic alignments for weak lensing with the MillenniumTNG lightcone},
  year         = {2026},
  howpublished = {\url{https://pith.science/paper/RXAZ7DY6}},
  note         = {Machine review of arXiv:2505.15882}
}
abstract

We present a complete forward model of a realistic weak lensing galaxy catalogue based on the 740 Mpc hydrodynamical MillenniumTNG (MTNG) simulation. Starting with a complete particle and cell lightcone covering one octant of the sky with redshift range 0 < $z$ < 1.5, we apply a group and subhalo finder to generate the corresponding galaxy catalogue for a fiducial observer. For all galaxies, we compute both their intrinsic and lensing-induced shear. The intrinsic component is derived from the luminosity-weighted inertia tensor of stellar particles, while the extrinsic (gravitational) shear is obtained through full-sky ray-tracing on the same lightcone. This allows us to directly predict the impact of intrinsic alignment (IA) of galaxies on the shear correlation function and popular convergence statistics in a fully non-linear forward model. We find that IA modifies the convergence power spectrum at all angular scales by up to 20%, it significantly impacts the PDF, altering its tails by 10-20%, and distorts peak and minimum counts up to 30%, depending on redshift and scale. We also evaluate the impact of the IA signal on the shear correlation function finding that, along with a redshift dependence, the signal strongly increases for higher galaxy stellar mass cuts applied to the catalogue. Notably, with the highest stellar mass cut we apply, the intrinsic shear autocorrelation can become comparable to the gravitational shear component on small angular scales. Our results highlight the importance of accurately modeling IA for precision weak lensing cosmology with upcoming Stage IV surveys.

Figures

Figures reproduced from arXiv: 2505.15882 by the authors.

Figure 1
Figure 1. The left, center and right panels show the redshift distribution, the mass function and the absolute ellipticity distribution of galaxies in our catalogue, respectively. The shaded regions in the left panel refer to the three redshift bins used in this work and are consistent with the colours adopted in the two rightmost panels. The grey dashed lines in the central panel refer to the minimum stellar mass cuts of [5 … view at source ↗
Figure 2
Figure 2. From left to right: full “WL + GSN + IA” (Weak Lensing + Galaxy Shape Noise + Intrinsic Alignment) map displayed as an octant of the sky with a zoom into a 10 × 10 deg2 square patch, followed by zoomed patches of the same area, for the “WL”, “GSN + IA”, and “GSN” cases. The maps are computed considering source galaxies in our central redshift bin, 0.8 < z < 1.2. For illustrative purposes we have smoothed the maps us… view at source ↗
Figure 3
Figure 3. Comparison between the shear correlation function as computed on our results and its theoretical prediction, obtained by means of the CCL library (Chisari et al. 2019). Each column refers to a different redshift bin. The top panels show the shear correlation function, while the bottom panels give the ratio of the theoretical prediction over our results. In the case of ξII and ξGI we use the Nonlinear Alignment model… view at source ↗
Figures from the paper (4 more)
Figure 4
Figure 4. Figure 4: Shear auto-correlation of the pure weak lensing component ξGG (green lines), auto-correlation of the pure intrinsic alignment component ξII (red lines), and their cross-correlation ξGI with inverted sign (yellow lines). The solid and dashed lines indicate the ξ+ and ξ−…
Figure 5
Figure 5. Figure 5: Top: Angular power spectrum of convergence maps. Dashed green lines show the pure weak lensing (WL) signal; light blue dotted lines indicate galaxy shape noise (GSN); purple solid lines represent maps including both WL and IA, with GSN subtracted. Bottom sub-panels sho…
Figure 6
Figure 6. Figure 6: Top (bottom): Peak (minimum) counts distribution of convergence maps; the purple solid lines refer to maps containing the total signal comprehensive of WL, intrinsic galaxy shapes (GSN), and orientations (IA); the orange solid lines refer to a version of the previous c…
Figure 7
Figure 7. Figure 7: Left (right): the light blue, violet and pink curves refer to the auto-correlation of the pure intrinsic alignment component ξII (cross-correlation between intrinsic and gravitational shear ξGI) for increasingly higher minimum stellar mass thresholds. The green lines r…

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Forward citations

Cited by 3 Pith papers

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

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  3. The correlation between voids identified in 3D large-scale-structure and 2D weak-lensing maps

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Pith tools

Reviewed August 7, 2026 · model on record in the stance chip above.