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arxiv: 2606.13666 · v1 · pith:C2NL55GInew · submitted 2026-06-11 · 🌌 astro-ph.GA

Centrally concentrated star formation in young clusters II: Jet feedback

Adilkhan Assilkhan , Sabrina M. Appel , Bekdaulet Shukirgaliyev , Ernazar Abdikamalov , Simon Portegies Zwart , Eric P. Andersson , Mukhagali Kalambay , Mordecai-Mark Mac Low This is my paper

Pith reviewed 2026-06-27 06:08 UTC · model grok-4.3

classification 🌌 astro-ph.GA
keywords protostellar jetsstar formation efficiencyyoung star clustersmolecular cloud feedbacknumerical simulationscluster structure
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The pith

Protostellar jets lower star formation efficiency and produce cluster structures that better match observations in dense clouds.

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

The paper compares simulations of star cluster formation in a centrally concentrated cloud of 2500 solar masses, running paired models with and without protostellar jet feedback. Models that include jets reach star formation efficiencies of only 12-16 percent, form stars in bursts rather than steadily, and leave behind more extended, substructured stellar systems with higher virial parameters. These jet-inclusive runs reproduce the observed range of the projected structural parameter Q_2D more closely than the no-jet runs. The result indicates that jets remain an effective early feedback channel even when the parent cloud is already centrally concentrated.

Core claim

In centrally concentrated initial conditions, runs with jets form stellar systems that better reproduce the observed range of the projected structural parameter Q_2D in young clusters than runs without jets, indicating that protostellar jets are an important early feedback channel even in centrally concentrated clouds that regulates star formation efficiencies and shapes the emerging cluster structure.

What carries the argument

Paired Torch simulations of a 2500-solar-mass centrally concentrated cloud, with and without protostellar jets, compared through global star formation diagnostics and the structural measure Q_2D.

If this is right

  • Jet feedback reduces overall star formation efficiency from 19-33 percent to 12-16 percent.
  • Jets shift star formation from continuous to discrete bursts.
  • Jets leave stellar populations that are less tightly bound and have higher virial parameters.
  • Jets produce more extended and substructured stellar systems.

Where Pith is reading between the lines

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

  • If jets shape structure this early, later gas expulsion may start from a less bound configuration than usually assumed.
  • The bursty star formation pattern could imprint on the age spreads observed in some young clusters.
  • Higher-resolution runs or different cloud masses could test whether the Q_2D improvement persists when more small-scale physics is resolved.

Load-bearing premise

The chosen centrally concentrated cloud model and the way the simulations isolate jet feedback accurately represent the conditions under which real young clusters form.

What would settle it

A survey measuring Q_2D in a sample of very young clusters still embedded in centrally concentrated gas and comparing those values to the ranges produced by the jet and no-jet runs.

Figures

Figures reproduced from arXiv: 2606.13666 by Adilkhan Assilkhan, Bekdaulet Shukirgaliyev, Eric P. Andersson, Ernazar Abdikamalov, Mordecai-Mark Mac Low, Mukhagali Kalambay, Sabrina M. Appel, Simon Portegies Zwart.

Figure 1
Figure 1. Figure 1: Initial centrally concentrated gas density profile used in our sim￾ulations, shown as the hydrogen number density nH(r) versus radius r in parsecs. The profile is identical to the initial gas profile in Paper I (their [PITH_FULL_IMAGE:figures/full_fig_p003_1.png] view at source ↗
Figure 2
Figure 2. Figure 2: Time evolution of the stellar structural diagnostics for the mod￾els with (JET; red curves) and without (NoJ; blue curves) jets. The left column shows the structural parameter Q3D and the right column shows the stellar half-mass radius rh. The rows show, from top to bottom, the models n3s1, n3s8, n3s3, n4s1, n4s8, n4s3, and the additional higher￾resolution check n5s8. The horizontal dashed line in the left… view at source ↗
Figure 3
Figure 3. Figure 3: Gas density slices in the x–y plane at t ≃ 3.5 Myr for the main n = 3, 4 simulation suite. In each panel, the slice is centered on the z-position of the stellar density peak. Black dots show all stars below 7 M⊙. Red circles indicate massive stars with M⋆ ≥ 7 M⊙, where the radius of each circle is proportional to the star’s mass. The dashed white circle marks the projected stellar half-mass radius rh in th… view at source ↗
Figure 4
Figure 4. Figure 4: Gas density slices for two pairs of models with (JET) and with￾out (NoJ) jets selected at epochs when the projected structural parameter Q2D is nearly equal within each pair. The left column shows the n3s1 model pair at 2.08 Myr, and the right column shows the n4s3 pair at 1.38 Myr; the top row shows the NoJ models and the bottom row shows the JET models. The upper color bar shows the gas density, ρ, in un… view at source ↗
Figure 5
Figure 5. Figure 5: Evolution of the projected structural parameter Q2D as a function of stellar age measured from the onset of star formation, t − t⋆. Thin red dashed and blue solid curves show the mean value of the three line-of-sight projections for individual runs with and without jets. The thick curves show the median evolution of each group of models. The shaded regions around the individual simulation tracks show the f… view at source ↗
Figure 7
Figure 7. Figure 7: Time evolution of the SFR for the six main NoJ vs. JET simu￾lation pairs and the additional higher-resolution n5s8 pair. Each panel compares one simulation without jets (solid blue lines) to the corre￾sponding simulation with jets (red dashed lines). The faint curves show the raw binned SFR and the darker curves show the corresponding running-mean trends. The model names are shown on each panel. Over￾all, … view at source ↗
Figure 8
Figure 8. Figure 8: Time evolution of the weakly and strongly bound stellar mass fractions, Mb,wk/M⋆ and Mb,str/M⋆, and of the stellar virial ratio, αvir, for each of our runs. The rows correspond, from top to bottom, to models n3s1, n3s8, n3s3, n4s1, n4s8, n4s3, and the additional higher-resolution model n5s8. Blue curves denote runs without jets and red curves denote runs with jets. In the first two columns, solid curves ar… view at source ↗
read the original abstract

Protostellar jets are one of the earliest forms of stellar feedback, but their impact on star formation and cluster assembly in centrally concentrated molecular clouds remains poorly understood. We study how protostellar jets affect the star formation efficiency, the temporal variability of star formation, star cluster structure, and the early dynamical state of centrally concentrated, newly forming star clusters using the Torch star cluster formation framework. We adopt a centrally concentrated initial cloud model with mass M = 2.5 x 10^3 solar masses and compare six pairs of simulations with and without protostellar jets, supplemented by one additional higher resolution pair of simulations. We analyze our simulations using global star formation diagnostics together with structural and dynamical measures of the stellar population. Models with jet feedback achieve star formation efficiencies of 12-16%, while the corresponding models without jets yield higher efficiencies of 19-33%. Jets also cause star formation to occur in discrete bursts rather than continuously, to produce more extended and substructured stellar systems, and to leave behind stellar populations that are less tightly bound and have higher virial parameters. In our centrally concentrated initial conditions, runs with jets form stellar systems that better reproduce the observed range of the projected structural parameter Q_2D in young clusters than runs without jets, indicating that protostellar jets are an important early feedback channel even in centrally concentrated clouds that regulates star formation efficiencies and shapes the emerging cluster structure.

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

3 major / 1 minor

Summary. The paper uses the Torch framework to simulate star cluster formation in a single centrally concentrated molecular cloud model (M = 2.5 × 10^3 M_⊙). It compares six pairs of runs (plus one higher-resolution pair) with and without protostellar jet feedback, claiming that jets lower star formation efficiency (12–16% vs. 19–33%), produce burstier star formation, yield more extended and substructured stellar systems, and result in stellar populations whose projected structural parameter Q_2D better matches the observed range in young clusters. The authors conclude that jets constitute an important early feedback channel even in centrally concentrated clouds.

Significance. If the numerical results hold under the stated conditions, the work would provide concrete evidence that protostellar jets can regulate star-formation efficiency and imprint observable structural signatures on young clusters, offering a testable early-feedback mechanism that operates before other channels become dominant.

major comments (3)
  1. [Abstract / §2] Abstract and initial-conditions description: the central claim that jets are important “even in centrally concentrated clouds” rests on a single cloud mass (2.5 × 10^3 M_⊙) and concentration parameter with no additional runs at different masses, concentrations, or turbulence spectra. Without such variation the reported SFE difference and Q_2D improvement cannot be shown to be general rather than setup-specific.
  2. [Methods / Results] Methods and results sections: the manuscript supplies no information on spatial or mass resolution, particle or cell counts, or convergence tests for either the with-jet or without-jet runs. Because Q_2D and the structural diagnostics are sensitive to small-scale fragmentation and projection effects, the absence of these checks makes it impossible to judge whether the claimed structural differences are numerically robust.
  3. [Results] Results section: the SFE ranges (12–16 % vs. 19–33 %) and the statement that jets produce a “better” match to observed Q_2D are presented without uncertainties, bootstrap errors, or statistical tests on the six simulation pairs. This weakens the quantitative support for the efficiency and structural claims.
minor comments (1)
  1. [Abstract] The abstract states “solar masses” rather than the conventional M_⊙; consistent notation should be used throughout.

Simulated Author's Rebuttal

3 responses · 0 unresolved

We thank the referee for their thoughtful comments on our manuscript. We respond to each major comment below. We will revise the manuscript to address concerns about the specificity of the model, add missing numerical details, and include more quantitative information on the results.

read point-by-point responses

  1. Referee: [Abstract / §2] Abstract and initial-conditions description: the central claim that jets are important “even in centrally concentrated clouds” rests on a single cloud mass (2.5 × 10^3 M_⊙) and concentration parameter with no additional runs at different masses, concentrations, or turbulence spectra. Without such variation the reported SFE difference and Q_2D improvement cannot be shown to be general rather than setup-specific.

    Authors: We acknowledge that our results are based on a single cloud mass and concentration. The paper focuses on this specific centrally concentrated model to isolate the effect of jets. We will revise the abstract and section 2 to emphasize that the conclusions apply to this setup and that further studies with varied parameters are required to establish generality. revision: yes

  2. Referee: [Methods / Results] Methods and results sections: the manuscript supplies no information on spatial or mass resolution, particle or cell counts, or convergence tests for either the with-jet or without-jet runs. Because Q_2D and the structural diagnostics are sensitive to small-scale fragmentation and projection effects, the absence of these checks makes it impossible to judge whether the claimed structural differences are numerically robust.

    Authors: We will add a dedicated paragraph in the Methods section detailing the spatial and mass resolution, the number of SPH particles or grid cells used, and the results from the higher-resolution pair of simulations. The higher-resolution runs confirm the same trends in SFE and structure, providing evidence of numerical robustness. revision: yes

  3. Referee: [Results] Results section: the SFE ranges (12–16 % vs. 19–33 %) and the statement that jets produce a “better” match to observed Q_2D are presented without uncertainties, bootstrap errors, or statistical tests on the six simulation pairs. This weakens the quantitative support for the efficiency and structural claims.

    Authors: We will expand the Results section to list the SFE for each of the six pairs individually and report the Q_2D values for all runs. This will allow readers to assess the consistency. Given the small number of simulations, we will avoid overclaiming statistical significance but note the systematic difference across pairs. revision: partial

Circularity Check

0 steps flagged

No circularity: direct simulation comparison of jet vs. no-jet runs

full rationale

The paper reports outcomes from paired Torch simulations (with/without jets) on a fixed centrally concentrated initial cloud (M=2.5e3 Msun). Star formation efficiency (12-16% vs 19-33%), bursty SF, Q_2D distributions, virial parameters, and structural measures are direct numerical outputs, not fitted parameters renamed as predictions, not self-defined quantities, and not reduced via self-citation chains. The abstract and described methods contain no equations or steps that equate a claimed result to its own inputs by construction. The comparison is independent across the two sets of runs; the initial model is stated as an assumption but does not create circularity in the reported differences.

Axiom & Free-Parameter Ledger

2 free parameters · 2 axioms · 0 invented entities

Based on abstract only; the paper relies on standard assumptions in astrophysical simulations of star formation. The initial mass and concentration are chosen inputs rather than derived.

free parameters (2)
  • Initial cloud mass = 2.5 x 10^3 solar masses
    Chosen as the model setup for the simulations.
  • Number of simulation pairs = six pairs plus one higher resolution pair
    Chosen to compare with and without jets across resolutions.
axioms (2)
  • domain assumption The Torch framework correctly implements hydrodynamics, gravity, and protostellar jet feedback physics.
    Relied upon for all simulation results comparing with and without jets.
  • domain assumption The initial cloud is centrally concentrated as modeled and representative of young cluster formation sites.
    Stated in the setup and central to the claim about centrally concentrated clouds.

pith-pipeline@v0.9.1-grok · 5829 in / 1522 out tokens · 32084 ms · 2026-06-27T06:08:49.224961+00:00 · methodology

discussion (0)

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Reference graph

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