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The MAGPI Survey: radial trends in star formation across different cosmological simulations in comparison with observations at $z \sim$ 0.3

T0 review · 3 major / 4 minor · reviewed 2026-08-12 · deepseek-v4-flash

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Pith's one-line read At $z\sim0.3$, spaxel-resolved star-formation profiles in MAGPI disagree with all three cosmological simulations even though global main-sequence slopes agree, and the central suppression difference tracks active-galactic-nucleus feedback…

desk verdict A careful mock-observation comparison of MAGPI radial star formation with three simulations whose qualitative results are worth engaging, but the headline resolved-SFMS slope mismatch rests on two unmatched estimators and needs a validation test before it is cited as quantitative evidence. read the letter →

arxiv 2411.17882 v1 pith:36KRAEIP submitted 2024-11-26 astro-ph.GA

Marcie Mun , Emily Wisnioski , Katherine E. Harborne , Claudia D. P. Lagos , Lucas M. Valenzuela , Rhea-Silvia Remus , J. Trevor Mendel , Andrew J. Battisti
show 15 more authors
Sara L. Ellison Caroline Foster Matias Bravo Sarah Brough Scott M. Croom Tianmu Gao Kathryn Grasha Anshu Gupta Yifan Mai Anilkumar Mailvaganam Eric G. M. Muller Gauri Sharma Sarah M. Sweet Edward N. Taylor Tayyaba Zafar
This is my paper · ORCID
classification astro-ph.GA
keywords galaxyevolutionstarformationintegralfieldspectroscopycosmologicalsimulationsstar-formingmainsequenceAGNfeedbackenvironmentradialprofiles
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 show that how star formation is arranged inside a galaxy—not just how much star formation it has in total—is a sharper test of cosmological simulations. Using MAGPI integral-field observations at $z\sim 0.3$ and mock observations of EAGLE, Magneticum, and IllustrisTNG built with SimSpin, the authors find that the slope of the resolved (per-spaxel) star-forming main sequence disagrees between MAGPI and all three simulations at the $1$–$2\sigma$ level, while the global star-forming main sequence agrees. The paper argues that the spatial pattern of disagreement, particularly central star-formation suppression within $\sim1.5\,R_e$, tracks how each simulation implements active galactic nucleus feedback. If true, radial star-formation profiles become a discriminating probe of subgrid physics that global scaling relations cannot provide.

What carries the argument

The load-bearing object is the resolved star-forming main sequence and the radial offset from it, $\Delta\Sigma_{\rm SFR}=\log_{10}(\Sigma_{\rm SFR,spax})-\log_{10}(\Sigma_{\rm SFR,MS})$, measured in elliptical annuli of width $0.5\,R_e$ out to $5\,R_e$. The resolved SFMS is the per-spaxel relation between star-formation-rate surface density and stellar-mass surface density; MAGPI's version is built from dust-corrected H$\alpha$ star-forming spaxels, while each simulation's version is built from the peak of the $\Sigma_{\rm SFR}$ probability density in bins of $\Sigma_*$. SimSpin mock data cubes impose MAGPI's PSF, line-spread function, pixel scale, and SFR/stellar-mass surface-density detection limits on the simulations, so the comparison is meant to be an instrument-matched one.

What would settle it

Re-fit the resolved star-forming main sequence for MAGPI and every simulation using one common method—for instance, applying the simulation PDF-peak fit to MAGPI spaxels or applying the MAGPI linear fit to simulation spaxels. If the slopes then agree within 1$\sigma$, the reported resolved-SFMS disagreement is a fitting artifact; if they still disagree, the claim of a physical discrepancy survives.

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Extended reading notes

Core claim

The central claim is that spaxel-resolved star-formation profiles at $z\sim0.3$ separate the MAGPI observations from all three simulations in a way that global measurements hide. The resolved star-forming main sequence fitted to MAGPI's H$\alpha$-detected star-forming spaxels has a steeper slope ($0.92\pm0.01$) than the slopes obtained from the peak of the $\Sigma_{\rm SFR}$ probability distribution in each simulation ($0.73$–$0.81$), a disagreement outside $1$–$2\sigma$. In radial $\Delta\Sigma_{\rm SFR}$ profiles, the simulations only match the observed inside-out quenching signature for galaxies far below the main sequence; for galaxies on or just below it, the simulations show differing central suppression within $\sim1.5\,R_e$, which the paper attributes to different AGN feedback prescriptions (single-mode thermal feedback in EAGLE versus dual-mode thermal/kinetic feedback in Magneticum and IllustrisTNG). The paper further claims that centrals and satellites follow different radial quenching paths, with centrals showing halo-mass-dependent central suppression and satellites showing increasing outskirts suppression, and that these environmental trends only appear when both central/satellite status and halo mass are controlled.

Load-bearing premise

The comparison assumes that the resolved star-forming main sequence measured from MAGPI's dust-corrected H$\alpha$ star-forming spaxels and the one measured from each simulation's peak of the $\Sigma_{\rm SFR}$ probability density over all non-zero SFR spaxels are the same quantity; the paper never applies a single fitting method to both datasets.

Editorial extensions

If this is right

  • Resolved star-formation scaling relations are a model discriminator even when the global star-forming main sequence is reproduced within $1$–$2\sigma$.
  • Galaxies far below the star-forming main sequence show inside-out quenching in both MAGPI and all three simulations, so this quenching mode is robust across feedback implementations.
  • Differences in central suppression within $\sim1.5\,R_e$ can be used to distinguish AGN feedback prescriptions, with the strongest suppression appearing in simulations that inject kinetic or dual-mode AGN feedback.
  • Environmental quenching is visible in radial profiles only when galaxies are split by central/satellite status and halo mass; population-averaged profiles wash it out.
  • Mock observations that match PSF, pixel scale, and detection limits are necessary for any such comparison, because resolution and selection effects change the measured radial trends.

Reading between the lines

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

  • Inference: The resolved-SFMS slope gap might partly reflect the different SFR tracers, since H$\alpha$ traces roughly 10 Myr of star formation while simulations report instantaneous SFRs; averaging simulated SFRs over about 10 Myr before fitting would test whether the slope disagreement is physical.
  • Inference: Applying the same fitting algorithm, either the PDF-peak method or the direct linear fit, to both MAGPI and simulation spaxels would isolate whether the reported resolved-SFMS disagreement is a method artifact, a test the paper does not perform.
  • Inference: If the central-suppression attribution to AGN feedback is correct, simulations that toggle between kinetic and thermal AGN modes at fixed resolution should reproduce the Magneticum/IllustrisTNG versus EAGLE ordering in central slopes, offering a clean falsification test.
  • Inference: The environmental result implies that group-scale integral-field surveys need sample sizes large enough to bin by both central/satellite status and halo mass, which may push future wide-field spectrographs to prioritize depth over field of view.
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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

3 major / 4 minor

Summary. The paper compares spatially resolved star formation at z~0.3 between MAGPI observations and mock MUSE observations of galaxies drawn from the EAGLE, Magneticum, and IllustrisTNG cosmological simulations, using SimSpin to match PSF, pixel scale, and spaxel-by-spaxel SFR and stellar-mass detection limits. It reports that the global star-forming main sequence (SFMS) slopes agree within 1-2 sigma, while the resolved SFMS slopes are shallower in all three simulations than in MAGPI (Table 2). It then constructs DeltaSigma_SFR radial profiles for galaxies in different DeltaSFR bins, finding that simulations and MAGPI agree only for galaxies far below the SFMS, that central suppression within R~1.5 Re differs among simulations, and that central versus satellite galaxies show distinct environmental trends.

Significance. If the resolved-SFMS discrepancy and the radial-profile differences are astrophysical rather than methodological, the paper would demonstrate that spatially resolved star formation provides a discriminating test of subgrid feedback models beyond global scaling relations. The study is timely and the observational matching effort is substantial: the authors use mock observations, match detection limits and parameter ranges, and analyze three independent simulation codes. The central result, however, hinges on the comparability of two different resolved-SFMS estimators, and the current manuscript does not validate that comparability, so the quantitative conclusions are not yet secure.

major comments (3)
  1. [Section 4.4, Table 2, Fig. 3] The load-bearing claim that the resolved SFMS slope does not agree within 1-2 sigma between MAGPI and the simulations rests on comparing two different estimators. MAGPI's resolved SFMS is derived from a direct fit to H-alpha-detected, BPT-classified star-forming spaxels, whereas the simulations use the peak of the Sigma_SFR probability density over all non-zero SFR spaxels, fitted with ODR. These differ in spaxel selection, SFR tracer, and fitting statistic. The simulation PDF peak may be systematically dragged down at high Sigma_star by low-sSFR spaxels that MAGPI would exclude, which could explain the shallower slopes (MAGPI 0.92+-0.01 versus EAGLE 0.80+-0.02, Magneticum 0.73+-0.07, IllustrisTNG 0.81+-0.02). Because DeltaSigma_SFR in Eq. (2) is measured relative to each sample's own resolved SFMS, the radial-profile comparison in Fig. 4 and the claim of agreement only far below the SFMS are also affected. The authors acknowledge the different approaches in Section 4.4 but never validate them against one another; applying the same resolved-SFMS estimator to both datasets, or otherwise demonstrating that the slope difference survives, is required.
  2. [Section 5, Table 3, Fig. 4] The quoted inner and outer profile slopes and their errors are bootstrap standard errors on medians. With thousands of simulated galaxies and many spaxels per bin, these errors are extremely small (often <0.01 dex/Re), while the galaxy-to-galaxy scatter is roughly 0.4 dex, as the authors note in Section 4.5 and illustrate in Appendix B. The abstract's 'does not agree within 1-2 sigma' statement and the interpretation of slope differences in Section 5.2 therefore rely on error bars that understate the true population scatter. The authors should report the scatter, use a mixed-effects or hierarchical model, or otherwise present a significance measure that reflects the galaxy-to-galaxy variance. Additionally, the choice of 1.5 Re as the inner/outer division is an ad hoc assumption (Section 5.1); a sensitivity test using other cutoffs would strengthen the slope comparisons in Table 3.
  3. [Abstract and Section 6.1] The abstract attributes the differences in central suppression within R~1.5 Re to different AGN feedback prescriptions. The three simulations differ simultaneously in hydrodynamic scheme, resolution, stellar feedback implementation, BH seeding, and calibration targets, so the comparison is not a controlled experiment. The interpretation is plausible and consistent with previous literature, but as stated it overreaches. The authors should either temper the causal attribution or support it with an analysis that controls for at least some of the other differences, such as comparing feedback variants within the same simulation code or explicitly discussing how resolution and seeding affect the central profiles.
minor comments (4)
  1. [Section 4.4, Eq. (1)] The definitions of log10(SFR_MS) and log10(Sigma_SFR,MS) in Eqs. (1) and (2) are not written explicitly as functions of stellar mass; making the functional dependence clear would help readers reproduce the DeltaSFR and DeltaSigma_SFR calculations.
  2. [Fig. 3 caption] The caption refers to 'turquoise data points' for the simulation SFMS fits, but the figure appears to use a different color scheme; the caption should be aligned with the actual plot.
  3. [Throughout] There are several grammatical and word-choice issues, such as 'the latter for which may not be reflected in use of SFR indicators' in Section 1 and the use of 'i.e.' where 'e.g.' is meant in Sections 4.2 and 5.1. A careful language edit would improve clarity.
  4. [Section 4.5] The statement that bootstrap errors 'may not represent the overall scatter' is important but could be emphasized more strongly; the main text frequently discusses 'discrepancies' without recalling this caveat.

Circularity Check

0 steps flagged · score 0.0 of 10

No derivation-level circularity: the simulation predictions are independent of MAGPI inputs, and the resolved-SFMS comparison is a fitted comparison, not a fitted input called a prediction.

full rationale

The paper's central comparison is between MAGPI observations (Paper I) and mock observations built from EAGLE, Magneticum, and IllustrisTNG. The simulation radial profiles use instantaneous SFRs from the simulations themselves, processed through SimSpin, and each simulation's resolved SFMS is fitted independently from its own mock spaxel distribution rather than being tuned to reproduce MAGPI's resolved SFMS. Moreover, the simulations were calibrated to z~0 global observables such as the stellar mass function and galaxy sizes, not to the z~0.3 resolved SFMS slopes or radial DeltaSigmaSFR profiles that are the paper's headline results, so the comparison is an out-of-sample prediction. The main caveat is methodological rather than circular: MAGPI's resolved SFMS is fit to H-alpha-detected, BPT-classified star-forming spaxels, while the simulation resolved SFMS uses the peak of the SigmaSFR PDF over all spaxels above a detection floor, so the reported slope difference (Table 2) may partly reflect estimator mismatch instead of astrophysics. This is a comparability/robustness concern and should be weighed as correctness risk, but it does not reduce any equation to its own inputs, and the paper explicitly acknowledges the different approaches in Section 4.4. Self-citations (Mun et al. 2024, Harborne et al. 2020, 2023) point to independent, published data products or public codes rather than to an unverified uniqueness claim. No circular step can be exhibited, so the circularity score is 0.

Assumptions & free parameters 4 free parameters · 5 assumptions · 0 invented entities

No new entities are introduced. The central claims rest on inherited simulation subgrid parameters (listed as free parameters), on comparability assumptions for SFR indicators and fitting methods, and on the fidelity of SimSpin mock observations. No parameter is fitted to the MAGPI data in this paper.

free parameters (4)
  • EAGLE subgrid feedback parameters (e.g., AGN stochastic heating energy/temperature) = Not specified in this paper; calibrated in prior simulation papers.
    EAGLE free parameters were fine-tuned to match z=0 stellar mass function, galaxy sizes, and stellar-to-BH mass (Section 3.1); the radial profiles in this paper inherit these choices.
  • Magneticum AGN radio-mode feedback efficiency = 4x larger feedback efficiency (Section 3.2)
    Magneticum is calibrated to reproduce intracluster medium hot gas, not the z=0 galaxy stellar mass function (Section 3.2); this affects central suppression in the profiles.
  • IllustrisTNG AGN kinetic feedback parameters and BH mass threshold = BH mass threshold 10^8.2 Msun for kinetic mode (Section 3.3)
    TNG is calibrated to match z=0 stellar mass function, stellar-to-halo mass, BH-to-halo mass, halo gas fraction, and stellar sizes (Section 3.3); the kinetic mode threshold shapes central quenching.
  • Spaxel-by-spaxel SFR and Sigma_star detection limits = log10(SFR/Msun/yr) ~ -4.35; log10(Sigma_star/Msun/kpc2) ~ 7.1
    These limits are chosen from MAGPI observations and Magneticum resolution (Section 4.2) and applied to all simulations. They are not fitted to the target radial trends, but they set the sample selection.
assumptions (5)
  • domain assumption The subgrid physics of EAGLE, Magneticum, and IllustrisTNG are sufficiently realistic to represent galaxy star formation and quenching at z~0.3.
    Invoked throughout (Sections 3, 5, 6); the radial profiles are interpreted as predictions of the simulations' feedback models.
  • domain assumption H-alpha-based and D4000-based SFR indicators from MAGPI trace the same star formation as the instantaneous SFRs in simulations, after applying detection limits.
    The comparison of radial profiles (Section 5.2) relies on this; the paper discusses differences in timescale and contamination but does not correct for them.
  • domain assumption The resolved SFMS fitting methods are comparable between MAGPI (H-alpha-detected spaxels) and simulations (PDF peak of all SFR spaxels).
    The resolved SFMS slope discrepancy (Table 2) is the basis for a central claim; this comparability is assumed, not tested.
  • domain assumption SimSpin mock cubes adequately reproduce MUSE observational conditions despite lacking noise and dust emission.
    Section 4.1 states no observational noise is added and dust is neglected; these omissions are assumed not to bias the comparison.
  • ad hoc to paper The 1.5 Re cutoff for inner/outer slope fitting is appropriate for separating internal and external quenching processes.
    Section 4.5/5.1 says the cutoff is motivated by central depressions being encapsulated within 1-1.5 Re; this choice is used to interpret environmental vs AGN effects.

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Cite this review

Pith. "Pith review of The MAGPI Survey: radial trends in star formation across different cosmological simulations in comparison with observations at $z \sim$ 0.3." pith.science (2026). https://pith.science/paper/36KRAEIP

@misc{pith2026241117882,
  author       = {Pith},
  title        = {Pith review of: The MAGPI Survey: radial trends in star formation across different cosmological simulations in comparison with observations at $z \sim$ 0.3},
  year         = {2026},
  howpublished = {\url{https://pith.science/paper/36KRAEIP}},
  note         = {Machine review of arXiv:2411.17882}
}
abstract

We investigate the internal and external mechanisms that regulate and quench star formation (SF) in galaxies at $z \sim 0.3$ using MAGPI observations and the EAGLE, Magneticum, and IllustrisTNG cosmological simulations. Using SimSpin to generate mock observations of simulated galaxies, we match detection/resolution limits in star formation rates and stellar mass, along with MAGPI observational details including the average point spread function and pixel scale. While we find a good agreement in the slope of the global star-forming main sequence (SFMS) between MAGPI observations and all three simulations, the slope of the resolved SFMS does not agree within 1 $-$ 2$\sigma$. Furthermore, in radial SF trends, good agreement between observations and simulations exists only for galaxies far below the SFMS, where we capture evidence for inside-out quenching. The simulations overall agree with each other between $\sim1.5-4 \ R_{\rm e}$ but show varying central suppression within $R \sim 1.5 \ R_{\rm e}$ for galaxies on and below the SFMS, attributable to different AGN feedback prescriptions. All three simulations show similar dependencies of SF radial trends with environment. Central galaxies are subject to both internal and external mechanisms, showing increased SF suppression in the centre with increasing halo mass, indicating AGN feedback. Satellite galaxies display increasing suppression in the outskirts as halo mass increases, indicative of environmental processes. These results demonstrate the power of spatially resolved studies of galaxies; while global properties align, radial profiles reveal discrepancies between observations and simulations and their underlying physics.

Figures

Figures reproduced from arXiv: 2411.17882 by the authors.

Figure 1
Figure 1. Histograms of the measured 𝑀★ for the MAGPI sample and each simulation. The MAGPI sample probes down to much lower masses, whereas the simulations can only probe down to 108 M⊙, mostly due to numerical resolution limits. The red dash-dotted lines indicate the range of 𝑀★ we measure radial trends for, where the lower and upper cut offs are set by Magneticum and MAGPI, respectively. Mock data cubes consist of two spat… view at source ↗
Figure 2
Figure 2. Histograms of the measured 𝑀crit,200 for central galaxies with 9.7 ≤ log10(𝑀★/M⊙) ≤ 11.4 (i.e., stellar masses in the range indicated by the red dash-dotted lines in [PITH_FULL_IMAGE:figures/full_fig_p005_2.png] view at source ↗
Figure 3
Figure 3. Top to bottom: resolved (left column) and global (middle column) SFMS fits and ΔSFR histograms (right column) for MAGPI, EAGLE, Magneticum, and IllustrisTNG. Both the resolved and global SFMS fits for MAGPI are measured based on Hα-detected SF spaxels/galaxies. The best fit global and resolved SFMS for MAGPI with the root mean square (RMS) error are overlaid as blue solid and dashed lines, respectively, for each sim… view at source ↗
Figures from the paper (4 more)
Figure 4
Figure 4. Figure 4: Median ΔΣSFR profiles as observed in the respective 𝑧 ∼ 0.3 snapshots for EAGLE (dash-dotted), Magneticum (dotted), and IllustrisTNG (dashed), plotted along with the MAGPI (solid) sample. The profiles are measured with respect to the corresponding resolved SFMS for eac…
Figure 5
Figure 5. Figure 5: ΔΣSFR profiles for SFMS galaxies (i.e., -0.5 < ΔSFR < 0.5) shown separately for centrals (left column) and satellites (right column), for MAGPI (dotted) and all simulations (solid). The black lines in each panel show the median profiles for all centrals and satellites,…
Figure 6
Figure 6. Figure 6: Median ΔΣSFR profiles for central galaxies in the -0.5 < ΔSFR < 0.5 bin for EAGLE (pink; dash-dotted), Magneticum (green; dotted), and IllustrisTNG (orange; dashed) split across 6 different bins of 𝑀crit,200 and 𝑀★. The same 𝑀crit,200 bins are used as done in Section 5…
Figure 7
Figure 7. Figure 7: Analogous to [PITH_FULL_IMAGE:figures/full_fig_p014_7.png]

Discussion (0). Continue with ORCID to comment.

Forward citations

Cited by 1 Pith paper

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

  1. What's Missing in AGN Feedback? Lessons learnt from Magneticum, IllustrisTNG and Simba

    astro-ph.GA 2026-07 conditional novelty 6.0 of 10

    No current simulation simultaneously reproduces observed halo hot-gas fractions and local galaxy star-formation/quenching demographics; strong AGN feedback overquenches, weak feedback retains too much gas.

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Pith tools

Reviewed August 12, 2026 · model on record in the stance chip above.