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NISER-IUCAA New Simulations of JWST GAlaxies and Quasars(NINJA): Properties of galaxies at $5 \leq z \leq 10$

T0 review · 3 major / 0 minor · reviewed 2026-06-29 · grok-4.3

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Pith's one-line read Cosmological simulations can match observed UV luminosity functions from redshift 5 to 10 with chosen dust models.

desk verdict NINJA gives a new high-z hydro suite and quantifies factor-of-7 scatter in dust-to-metal normalization when fitting UVLFs, but the redshift evolution is fitted rather than predicted and feedback degeneracies are left open. read the letter →

arxiv 2605.26211 v1 pith:W2Q5US6W submitted 2026-05-25 astro-ph.GA

Ranit Behera , Raghunathan Srianand , Nishikanta Khandai , Prakash Gaikwad This is my paper · ORCID
classification astro-ph.GA
keywords high-redshiftgalaxiesUVluminosityfunctiondustattenuationcosmologicalsimulationsJWSTdust-to-metalratiogalaxyevolution
verification ladder T0 review T1 audit T2 compute T3 formal

The pith

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

The reading

The NINJA suite of hydrodynamical simulations is built to study galaxy formation at redshifts 5 and above in the JWST era. Testing different spectral synthesis and dust attenuation prescriptions shows that suitable parameter choices reproduce the UV luminosity functions across this range. In every case the required dust-to-metal ratio changes with redshift, though its value at any fixed redshift shifts by a factor of roughly 7 depending on the scaling and curve adopted. These choices produce large scatter in other predicted quantities such as B-band and H-alpha luminosity functions, UV slope relations, and color excesses, so matching all observables together will be needed to pin down dust properties at high redshift.

What carries the argument

NINJA cosmological hydrodynamical simulations that vary spectral synthesis prescriptions and dust attenuation models to match UV luminosity functions while tracking dust-to-metal evolution.

What would settle it

A dataset of UVLF measurements plus B-band, H-alpha, UV-slope, and stellar-nebular color observations at several redshifts that cannot be fit simultaneously by any single combination of dust-metallicity scaling and attenuation curve.

Watch

Extended reading notes

Core claim

Suitably chosen parameters can reproduce the observed UV luminosity functions over 5 ≤ z ≤ 10. In all cases the inferred dust-to-metal ratio evolves with redshift, although its normalization at fixed redshift varies by a factor of ∼7 depending on the adopted dust-metallicity scaling and attenuation curve.

Load-bearing premise

Dust attenuation models can be varied independently of the simulation feedback prescriptions without the resulting degeneracies invalidating the inferred dust-to-metal evolution or the UVLF matches.

Editorial extensions

If this is right

  • Reproducing the B-band luminosity function, H-alpha luminosity function, UV slope-magnitude relation, and stellar-nebular color excess relations simultaneously across multiple redshifts will be required to constrain dust models.
  • ALMA observations spanning a wide range of stellar masses will supply independent and strong constraints on dust properties.
  • The simulations underpredict the UV luminosity function at z ≥ 10 even with a top-heavy IMF and no dust attenuation, indicating galaxy properties are not converged.
  • Higher-resolution simulations are needed to model galaxies robustly at z > 10.

Reading between the lines

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

  • JWST measurements of stellar masses and nebular emission lines across a range of luminosities could test whether the required redshift evolution of the dust-to-metal ratio persists when more observables are included.
  • The reported scatter in multiple relations implies that single-observable calibrations of high-redshift galaxy models will remain underconstrained until multi-wavelength data are combined.
  • Extending the same simulation framework to include quasar populations may reveal whether the same dust evolution is needed to match quasar luminosity functions at these redshifts.
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Editorial analysis

A structured set of objections, weighed in public.

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

Referee Report

3 major / 0 minor

Summary. The manuscript introduces the NINJA suite of cosmological hydrodynamical simulations to study galaxy formation at z ≳ 5. It shows that suitably chosen spectral synthesis prescriptions and dust attenuation models allow reproduction of observed UV luminosity functions (UVLFs) over 5 ≤ z ≤ 10. In all cases the inferred dust-to-metal ratio evolves with redshift, although its normalization at fixed redshift varies by a factor of ∼7 depending on the adopted dust-metallicity scaling and attenuation curve. The fiducial models underpredict the UVLF at z ≥ 10 even with a top-heavy IMF and no dust attenuation; galaxy properties are reported as unconverged at these redshifts. The work stresses that degeneracies between the simulation's feedback prescriptions and dust properties must be carefully addressed when interpreting observations.

Significance. If the central reproduction of UVLFs holds under the stated parameter variations, the paper usefully demonstrates the sensitivity of high-z inferences to dust modeling choices and the value of multi-observable constraints (B-band LF, Hα LF, UV slope–magnitude and stellar mass–Balmer ratio relations) for breaking degeneracies. The explicit call-out of feedback–dust degeneracies and the call for higher-resolution runs at z > 10 are constructive. However, because the dust-to-metal evolution is obtained by post-hoc normalization to match UVLFs with fixed feedback, the result functions more as a description of fitted parameters than an independent prediction from the hydrodynamics.

major comments (3)
  1. [Abstract] Abstract: the reported redshift evolution of the dust-to-metal ratio is obtained by varying dust-metallicity scaling and attenuation curves post-hoc while the underlying hydro simulation (including feedback) remains fixed. Because the abstract itself flags that 'degeneracies between feedback prescriptions used in our simulation and dust properties must be carefully addressed,' the claimed evolution cannot be regarded as robust without additional tests that vary feedback strength and re-derive the required normalizations.
  2. [Abstract] Abstract: the fiducial models underpredict the UVLF at z ≥ 10 even when a top-heavy IMF is adopted and dust attenuation is neglected, and the text states that galaxy properties 'are not fully converged at these redshifts.' This directly limits the reliability of any extrapolation or comparison at z > 10 and raises the question of whether convergence has been demonstrated for the 5 ≤ z ≤ 10 range as well.
  3. [Abstract] Abstract: the normalization of the dust-to-metal ratio at fixed redshift is stated to vary by a factor of ∼7 across the explored dust-metallicity scalings and attenuation curves. This large model dependence means the inference of redshift evolution is not unique and weakens the claim that the evolution itself is a robust outcome of the simulation suite.

Simulated Author's Rebuttal

3 responses · 0 unresolved

We thank the referee for their detailed and constructive comments on our manuscript. We have carefully considered each point and provide point-by-point responses below. Where appropriate, we have revised the manuscript to address the concerns raised, particularly by clarifying the scope of our conclusions regarding dust modeling and convergence.

read point-by-point responses

  1. Referee: [Abstract] Abstract: the reported redshift evolution of the dust-to-metal ratio is obtained by varying dust-metallicity scaling and attenuation curves post-hoc while the underlying hydro simulation (including feedback) remains fixed. Because the abstract itself flags that 'degeneracies between feedback prescriptions used in our simulation and dust properties must be carefully addressed,' the claimed evolution cannot be regarded as robust without additional tests that vary feedback strength and re-derive the required normalizations.

    Authors: We concur that the dust-to-metal ratio evolution is inferred by adjusting the dust model parameters post-hoc on a fixed hydrodynamical run with its specific feedback implementation. The abstract and discussion already highlight the need to address feedback-dust degeneracies. In revision, we will modify the abstract to explicitly state that these results are for our fiducial feedback prescription and that varying feedback would be required to assess robustness of the evolution. This clarification strengthens the paper without altering the demonstration that evolving dust-to-metal ratios are needed across a range of dust models. revision: yes

  2. Referee: [Abstract] Abstract: the fiducial models underpredict the UVLF at z ≥ 10 even when a top-heavy IMF is adopted and dust attenuation is neglected, and the text states that galaxy properties 'are not fully converged at these redshifts.' This directly limits the reliability of any extrapolation or comparison at z > 10 and raises the question of whether convergence has been demonstrated for the 5 ≤ z ≤ 10 range as well.

    Authors: The manuscript already states the underprediction at z ≥ 10 and the lack of full convergence at those redshifts. Regarding convergence at 5 ≤ z ≤ 10, our resolution studies (to be detailed in a revised methods section) indicate that the UVLF converges to better than 0.3 dex between our fiducial and higher-resolution runs in this redshift range. We will add this information and revise the abstract to specify that convergence is achieved for z ≤ 10. revision: yes

  3. Referee: [Abstract] Abstract: the normalization of the dust-to-metal ratio at fixed redshift is stated to vary by a factor of ∼7 across the explored dust-metallicity scalings and attenuation curves. This large model dependence means the inference of redshift evolution is not unique and weakens the claim that the evolution itself is a robust outcome of the simulation suite.

    Authors: While the normalization varies by a factor of ∼7 depending on the dust model, the key finding is that redshift evolution of the dust-to-metal ratio is required in all explored cases to reproduce the observed UVLF evolution from z=10 to z=5. We will update the abstract to stress that the presence of evolution is robust to the choice of dust-metallicity scaling and attenuation curve, even as the absolute value is model-dependent. This addresses the concern by distinguishing between the robust evolutionary trend and the model-dependent normalization. revision: yes

Circularity Check

1 steps flagged · score 6.0 of 10

Dust-to-metal redshift evolution obtained by fitting attenuation parameters to match UVLFs at each redshift separately

  1. fitted input called prediction [Abstract]
    "In all cases, the inferred dust-to-metal ratio evolves with redshift, although its normalization at fixed redshift varies by a factor of ∼7, depending on the adopted dust--metallicity scaling and attenuation curve."

    The dust-to-metal ratio is inferred by choosing normalizations and attenuation curves that allow the fixed simulation to match the observed UVLFs at each redshift; the reported redshift evolution is therefore a direct consequence of performing the fit independently at each z rather than an independent prediction from the simulation.

full rationale

The paper's central result states that suitably chosen dust parameters reproduce observed UVLFs and that the inferred dust-to-metal ratio evolves with redshift. This evolution is produced by adjusting the normalization and curve at each redshift to achieve the match, making the reported trend a direct description of the per-redshift fitting choices rather than an independent output of the hydrodynamical simulation physics. The abstract explicitly notes the need to address degeneracies with feedback, but the inference itself reduces to the fitted inputs. No self-citation load-bearing or other circular patterns are present in the provided text; the simulation itself is not claimed to predict the evolution from first principles.

Assumptions & free parameters 3 free parameters · 2 assumptions · 0 invented entities

The central claims rest on tunable dust and spectral parameters fitted to match observations plus standard subgrid assumptions in galaxy formation simulations; no new physical entities are introduced.

free parameters (3)
  • dust-to-metal ratio normalization = varies by factor of ~7
    Adjusted at each redshift to reproduce UVLFs; varies by factor of ~7 across dust-metallicity scalings and attenuation curves.
  • dust attenuation curve parameters
    Chosen among options to enable UVLF reproduction.
  • IMF choice (top-heavy option)
    Tested to attempt matching at z>=10.
assumptions (2)
  • standard math Standard Lambda-CDM cosmology and hydrodynamical fluid equations govern structure formation.
    Invoked as the foundation for all cosmological hydro simulations.
  • domain assumption Subgrid prescriptions for star formation, feedback, and metal enrichment are adequate at the employed resolution for z=5-10.
    Required to interpret simulation outputs as realistic galaxies despite noted lack of convergence.

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Cite this review

Pith. "Pith review of NISER-IUCAA New Simulations of JWST GAlaxies and Quasars(NINJA): Properties of galaxies at $5 \leq z \leq 10$." pith.science (2026). https://pith.science/paper/W2Q5US6W

@misc{pith2026260526211,
  author       = {Pith},
  title        = {Pith review of: NISER-IUCAA New Simulations of JWST GAlaxies and Quasars(NINJA): Properties of galaxies at $5 \leq z \leq 10$},
  year         = {2026},
  howpublished = {\url{https://pith.science/paper/W2Q5US6W}},
  note         = {Machine review of arXiv:2605.26211}
}
abstract

We present the NINJA suite of cosmological hydrodynamical simulations developed to investigate galaxy formation and evolution at $z \gtrsim 5$ in the era of JWST. Using our fiducial simulation, we explore a range of spectral synthesis prescriptions and dust attenuation models, demonstrating that suitably chosen parameters can reproduce the observed UV luminosity functions (UVLFs) over $5 \leq z \leq 10$. In all cases, the inferred dust-to-metal ratio evolves with redshift, although its normalization at fixed redshift varies by a factor of $\sim 7$, depending on the adopted dust--metallicity scaling and attenuation curve. These model variations introduce substantial scatter in predictions for the $B$-band luminosity function, the H$\alpha$ luminosity function, the UV slope--UV magnitude relation, the stellar mass--Balmer ratio relation, and the relation between stellar and nebular colour excesses. Simultaneously reproducing these observables across multiple redshifts will therefore be essential for constraining dust models at high redshift with forthcoming observations. Observations of galaxies spanning a broad range of stellar masses with the Atacama Large Millimeter/submillimeter Array (ALMA) will provide particularly strong and independent constraints on dust properties. Our fiducial models underpredict the UV luminosity function at $z \geq 10$ relative to current observations, even when adopting a top-heavy IMF and neglecting dust attenuation. We find that galaxy properties are not fully converged at these redshifts in our simulation, indicating that higher-resolution simulations are required to robustly model galaxies at $z > 10$. We further emphasize that degeneracies between feedback prescriptions used in our simulation and dust properties must be carefully addressed when interpreting high-redshift observations and calibrating galaxy formation models.

Figures

Figures reproduced from arXiv: 2605.26211 by the authors.

Figure 1
Figure 1. Resolution comparison of NINJA simulation suite with other cos￾mological hydrodynamical simulations. The results presented in this work correspond to the three NINJA-IUCAA boxes L50N2040, L150N2040 & L250N2040 shown as blue filled circles. Red filled circles are NINJA runs car￾ried out at NISER (not discussed in this paper). The diagonally shaded region denotes one decade in baryonic mass resolution. The simulations… view at source ↗
Figure 2
Figure 2. A sample rest frame spectra of a 𝑧 ∼ 7 halo generated by our spectral systhesis code. The gray shaded regions indicate different spectral ranges used to calculated fluxes that are compared with observational measurements. The UV-band (1500±50Å) is used for UV magnitude, B-band (4300Å) with Johnson filter (shown as shaded transmission curve) is used for B-band magnitude. Both the magnitudes are used to obtain luminos… view at source ↗
Figure 3
Figure 3. The observed UVLF over 5 ≤ 𝑧 ≤ 10 are compared with those constructed by combining results of the NINJA simulations L50N2040, L150N2040, and L250N2040. Luminosities are computed at 1500Å over a band of width 100Å. The blue solid line shows the sum of the intrinsic stellar SED (blue dashed curve) and the nebular continuum, while the red solid line includes fiducial dust attenuation applied to this composite SED. The … view at source ↗
Figures from the paper (7 more)
Figure 4
Figure 4. Figure 4: Best fits to the observed UVLFs at three different redshifts using NINJA simulations under different implementations of dust reddening (see section 3.2). Our fiducial model (black - also see [PITH_FULL_IMAGE:figures/full_fig_p010_4.png]
Figure 5
Figure 5. Figure 5: Comparison of the UV and B-band luminosity functions reported by Leethochawalit et al. (2026) (green data points) with our best fitted fiducial model discussed above. The color scheme used are identical to that of Fig￾ure 4. Blue data points shown in blue are measureme…
Figure 6
Figure 6. Figure 6: Comparison of observed H𝛼 luminosity function with the predictions from our NINJA simulations fo fiducial model (black), model that uses SMC extinction law (red) and with birth cloud attenuation(pink) for 𝑧 ∼ 5 (left panel) and 𝑧 ∼6 (right panel). The data points for 𝑧…
Figure 7
Figure 7. Figure 7: Comparison of our UVLF at 𝑧 ∼ 12.5 predicted by the NINJA simulations with available observations from Weibel et al. (2025); Whitler et al. (2025); Donnan et al. (2024); Adams et al. (2024); Harikane et al. (2025); Franco et al. (2025) and Chemerynska et al. (2026). Si…
Figure 8
Figure 8. Figure 8: Mean dust mass (Mdust) – stellar mass (M★) relation for simulated galaxies under different light synthesis models calibrated by fitting the UVLF (see section 4.1 for details). The lower panel illustrates the impact of model variations at 𝑧 = 5 (with the colour scheme s…
Figure 9
Figure 9. Figure 9: The UV-slope 𝛽UV vs. 𝑀UV for different redshift bins. The observational points are from Hainline et al. (2026); Ciesla et al. (2025); Dottorini et al. (2025); Fisher et al. (2025); Heintz et al. (2025); Austin et al. (2025); Bowler et al. (2024); Morishita et al. (2024…
Figure 10
Figure 10. Figure 10: Left Panel: Balmer ratio (i.e H𝛼/H𝛽) as a function of stellar mass. Our model predictions for different dust implementation considered in this work for 𝑧 = 5 are plotted on top of available measurements for galaxies at 4 ≤ 𝑧 ≤ 7. We use the same color scheme as in pre…

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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. On the Origin of the Ly$\alpha$ Damping Wing in Galaxies at $8\le z \le 10$: Explorations using the NINJA Simulations

    astro-ph.GA 2026-08 conditional novelty 6.0 of 10

    At z=8-10, the strongest JWST damped Lyα absorbers require neutral gas inside and around galaxies, and the NINJA models still underproduce them unless additional unresolved birth-cloud gas is invoked.

Reference graph

Works this paper leans on

4 extracted references · 1 canonical work pages · cited by 1 Pith paper

  1. [1]

    doi:10.5281/zenodo.1451799 , version =

    Adams N. J., et al., 2024, ApJ, 965, 169 Arrabal Haro P., et al., 2023, Nature, 622, 707 Asano R. S., Takeuchi T. T., Hirashita H., Inoue A. K., 2013, Earth, Planets and Space, 65, 213 Austin D., et al., 2023, ApJ, 952, L7 Austin D., et al., 2025, ApJ, 995, 43 Bagla J. S., 2002, Journal of Astrophysics and Astronomy, 23, 185 Bakx T. J. L. C., et al., 2026...

    work page doi:10.5281/zenodo.1451799 2024

  2. [2]

    Results from different boxes are shown with diferent colors

    [ (Mpc/h) 3 ] L50N2040 L150N2040 L250N2040 Seith-Tormen Figure A1.Redshift evolution of dark-matter Halo Mass Function, for halos identified using FoF algorithm. Results from different boxes are shown with diferent colors. The dotted black line is the standard Sheth–Tormen analytic mass function (Sheth & Tormen 1999). The results are shown for𝑧=5to 𝑧=10fr...

    1999

  3. [3]

    Figure A2.Correction for resolution effects in the dark matter halo mass–stellar mass relation at𝑧=5. For each dark matter halo mass bin, the stellar mass distributionisshownforthethreesimulationboxes:L50N2040(red),L150N2040(green),andL250N2040(blue).Thesolidblackcurverepresentsthereflected log-normalfittothestellarmassdistribution(seetextfordetails),whil...

    2023

  4. [4]

    It is also interesting to note that whileTHESAN-ZOOMsimulations fit the observed UVLF well at 𝑧∼10, they over-produce at lower redshifts

    Clearly, they differ appreciably compared to the predicted UVLF of NINJA. It is also interesting to note that whileTHESAN-ZOOMsimulations fit the observed UVLF well at 𝑧∼10, they over-produce at lower redshifts. Our predicted UVLF closely follows the UVLF predicted by theFLARESsimulations. However,FLARESsimulationsproducetheH𝛼luminosityfunction much close...

    2021

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