Pith. sign in

REVIEW 4 major objections 4 minor 5 cited by

A cold cloud in a turbulent hot wind survives when its mixed gas cools faster than a turbulence-shortened destruction time; when cooling is fast, turbulence boosts cloud growth by up to an order of magnitude.

Reviewed by Pith at T0; open to challenge. T0 means a machine referee read the full paper against a public rubric. the ladder, T0–T4 →

Challenge this review Re-run · record.json Download PDF Read on arXiv ↗

T0 review · deepseek-v4-flash

2026-08-04 11:38 UTC pith:KYPN5H7N

load-bearing objection First cloud-crushing + driven turbulence study with a plausible but calibration-dependent survival criterion; the qualitative physics is solid, the quantitative boundary needs more work. the 4 major comments →

arxiv 2510.03552 v1 pith:KYPN5H7N submitted 2025-10-03 astro-ph.GA

Woven by the Whirls: The growth and entrainment of cold clouds in turbulent hot winds

Ritali Ghosh , Max Gronke , Prateek Sharma , Alankar Dutta This is my paper
classification astro-ph.GA
keywords turbulent windscold cloudscloud crushingmultiphase gasgalactic windsradiative coolingentrainmentmixing layer
verification ladder T0 review T1 audit T2 compute T3 formal T4 reserved

The pith

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

This paper asks whether the standard criterion for cold cloud survival in a hot wind—cooling of mixed gas must beat the cloud-destruction time—still holds when the wind is turbulent. Through 3D hydrodynamic simulations with external turbulent forcing at Mach numbers 0.1–0.7, it shows that the classic criterion survives in a modified form: clouds survive when t_cool,mix is smaller than a destruction time that folds the turbulent velocity into the wind speed in quadrature, with a fitted fudge factor of about 0.6. In the fast-cooling regime, turbulence stretches the cold gas, increases the mixing surface area by about an order of magnitude, and speeds up cloud growth and entrainment by roughly tenfold. This matters because galactic and circumgalactic winds are turbulent in reality, so laminar cloud-crushing predictions may miss a large fraction of cold-gas mass and momentum transfer.

Core claim

The central claim is that the survival of a cold cloud in a hot wind remains governed by the ratio of the mixed-gas cooling time to a modified cloud-crushing time: t_cool,mix / t_tilde_cc < 1, with t_tilde_cc = t_cc / sqrt(1 + (M_turb/(f_mix M_wind))^2) and f_mix ≈ 0.6. The paper reports that this criterion separates growing from destroyed clouds across simulations spanning t_cool,mix/t_cc from 10^-3 to 10 and subsonic turbulent Mach numbers 0.1–0.7. In the fast-cooling regime, turbulence enhances cold mass growth by up to an order of magnitude, because the mixing surface area grows rather than the mixing velocity (v_mix remains ≈ 0.2 c_s,cl). Consequently, clouds are entrained in roughly 0.

What carries the argument

The key object is the modified destruction time t_tilde_cc = t_cc / sqrt(1 + (M_turb/(f_mix M_wind))^2) (Eq. 5), which treats the wind and turbulent velocities as independent mixing agents combined in quadrature, with a fudge factor f_mix ≈ 0.6 that absorbs uncertainty in the exact scale L_cold at which turbulence acts on the cloud. The underlying mechanism is stretching-enhanced diffusion: turbulence stretches the cloud, increasing the area of the radiative mixing layer through which warm gas cools and condenses onto the cold phase. The mass growth rate then scales as M_turb^(3/2), while the derived mixing velocity v_mix stays close to its laminar value.

Load-bearing premise

The criterion assumes that the turbulent velocity that destroys the cloud is well captured by the rms velocity at the forcing scale, u'(L_cold) ≈ v_rms, even though the paper only constrains L_cold to lie between the cloud radius and the forcing scale; if the cloud-scale turbulent velocity is substantially smaller, the modified destruction time is overestimated and the fudge factor f_mix absorbs a geometry that may not be universal.

What would settle it

A targeted simulation set that varies the ratio L_eddy/R_cl (e.g., from 10 to 200) while holding M_turb fixed would settle the issue: if the growth/destruction boundary in the t_cool,mix/t_cc–M_turb plane shifts, the criterion's universality fails and f_mix must depend on the forcing scale. Observationally, measuring the velocity gradient along cold-gas tails in a starburst wind and comparing to Eq. (7) would also test the entrainment prediction.

Watch this falsifier. Get emailed when new claim-graph text bears on it.

Share X Bluesky LinkedIn Reddit HN

If this is right

  • The survival threshold translates to a minimum cloud size for survival, R_cl ≳ 3.4 pc (chi/100) ... sqrt(1 + (M_turb/M_wind)^2), which is larger than the resolution of many cosmological simulations, so small surviving clouds are likely missing in such runs.
  • In fast-cooling regimes, mass transfer from hot to cold gas is up to an order of magnitude higher in turbulent winds, implying large-scale simulations and subgrid models that neglect this underestimate cold gas loading and metal transport.
  • Entrainment distances shrink roughly as (1 + M_turb)^(-3), predicting velocity gradients along cloud tails of order km/s per pc, which is observable.
  • Turbulence changes absorption signatures: MgII 2796 profiles become broader (EW ≈ 550 mÅ, versus 176 mÅ in laminar winds) with multiple kinematic components, so line profiles carry information about wind turbulence.
  • Long filamentary tails—a common diagnostic of cloud disruption—are suppressed; in turbulent winds, tails are shorter, clumpier, and spread orthogonally.

Where Pith is reading between the lines

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

  • If the modified criterion holds, then the fraction of cold gas that survives in real galactic winds may be much higher than laminar models suggest whenever turbulence is subsonic but non-negligible; this would boost the cold-gas mass loading of outflows and the rate of metal recycling onto the disk.
  • The fitted f_mix absorbs uncertainty in the turbulent scale L_cold; a simulation suite that varies the forcing scale relative to the cloud radius could determine whether f_mix is universal or an artifact of the fixed L_eddy/R_cl = 40 used here. If f_mix depends on L_cold/L_eddy, then the criterion is not fully predictive without specifying the outer scale of turbulence.
  • The observed morphology of high-velocity clouds—droplet-like, without long 21-cm tails—could be direct evidence that the Galactic CGM is turbulent at the level modeled here; a survey correlating HVC tail lengths with local turbulence estimates would test the mechanism.
  • The scaling v_grad ≈ t_drag^(-1) (1 + M_turb)^3 suggests that spatially resolved velocity gradients in cool gas, e.g., in M82 or ram-pressure-stripped galaxies, could be used to infer the hot-phase turbulent Mach number without needing direct X-ray measurements.

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

4 major / 4 minor

Summary. This paper presents 3D hydrodynamic simulations of the classical radiative cloud-crushing problem augmented by continuously driven, subsonic turbulence in the hot wind. The parameter survey covers turbulent Mach numbers M_turb = 0.1–0.7, wind Mach numbers M_wind = 0.5–1.5, and mixing-to-crushing time ratios t_cool,mix/t_cc = 10^-3–10, for a cloud density contrast χ = 100. The central claim is a modified survival criterion: clouds survive when t_cool,mix/t̃_cc < 1, where t̃_cc = t_cc / sqrt(1 + (M_turb/(f_mix M_wind))^2) with a fitted fudge factor f_mix ≈ 0.6 (Eq. 5, Fig. 3). The paper further reports that in the fast-cooling regime turbulence enhances cold-mass growth by up to an order of magnitude through increased surface area, while the entrainment time drops from 2–3 t_drag to ~0.2 t_drag. Qualitative trends, morphology changes, and observational implications for MgII absorption are also discussed.

Significance. If the modified survival criterion holds, the paper provides a useful extension of the classic Gronke & Oh criterion to turbulent winds, with direct implications for cloud survival in galactic outflows, subgrid models, and absorption-line diagnostics. The work combines two previously separate idealized setups—cloud crushing and driven turbulence—and the parameter survey is systematic. Strengths include the public code, the explicit discussion of the fudge factor, and the qualitative regime separation: turbulence accelerates destruction when cooling is weak and accelerates growth when cooling is fast. However, the headline quantitative claim, Eq. (5), is an empirical fit rather than an independent prediction, and the paper itself identifies the unresolved cloud-scale turbulent velocity as a source of uncertainty absorbed into f_mix. The qualitative conclusions are likely robust, but the quantitative boundary needs additional support before being called universal.

major comments (4)
  1. [§3.1, Eq. (5)] The derivation of t̃_cc uses v_rms as the turbulent velocity that destroys the cloud. The paper correctly notes below Eq. (5) that the relevant velocity is u'(L_cold) ≈ v_turb (L_cold/L_eddy)^{1/3}, with only r_cl < L_cold < L_eddy constrained, and then justifies u' ≈ v_rms by the fact that cold gas stretches to tens of r_cl. This is load-bearing: near the destruction boundary the cloud may not have stretched to tens of r_cl, so u' could be 0.4–0.6 v_turb for L_eddy = 40 r_cl, a factor comparable to f_mix ≈ 0.6. Since f_mix is fitted to the same simulations, the fitted value absorbs the unknown L_cold/L_eddy ratio. The criterion is therefore not shown to be universal beyond the simulated L_eddy = 40 r_cl. Please test this by varying the forcing scale, by directly measuring L_cold, or by explicitly reframing Eq. (5) as an empirical fit valid for this L_eddy.
  2. [Fig. 3, Table 1] The boundary in Fig. 3 is obtained by fitting f_mix ≈ 0.6 to the same set of survival/destruction markers that the curve then separates. The paper acknowledges that f_mix absorbs the destruction-time convention as well as the u' uncertainty. This is an honest calibration, but it means the curve is not an independent prediction. The claim of a 'universal survival criterion' is stronger than the evidence supports. An out-of-sample test—for example, withholding part of the parameter space, or simulating a different density contrast or wind geometry—would substantially strengthen the claim. As written, the central quantitative result is a descriptive fit.
  3. [§2.2] The turbulent forcing is applied in a density-weighted manner with F ∝ 1/ρ for cells with T < 3 T_cl, so the cold cloud is not directly accelerated by the turbulent forcing. This is an ad hoc modeling choice that prevents unphysical acceleration of the dense phase, but it also means the study does not include the full coupling of turbulence to the cold gas. Since the paper's conclusions about entrainment and momentum transfer depend on the balance between shear and turbulent mixing, the sensitivity of the results to this forcing ansatz should be discussed or tested. At minimum, please clarify whether a fully coupled forcing would be expected to strengthen or weaken the reported entrainment times.
  4. [§4.5, Fig. 5] The paper states that the estimated mixing area A_turb is 'not converged' in these simulations, while the mass growth rate is claimed to be converged because only the outer mixing scale must be resolved. The order-of-magnitude mass-growth enhancement is attributed to the area increase, so the non-convergence of A_turb is a relevant caveat for the quantitative interpretation of Figs. 4 and 5. Please clarify how sensitive the reported mass-growth enhancement and the derived v_mix are to resolution, or explicitly state that the area-based interpretation is approximate and that v_mix may be an upper limit, as noted in the text.
minor comments (4)
  1. [Abstract] The phrase 'f_mix ∼ 0.6 is a fudge factor' is unusually candid but also signals that the criterion is calibrated. Consider using 'calibration factor' or 'empirical factor' in the abstract and conclusions.
  2. [§2.1, Table 1] The table uses symbols ✓, ✗, and ? without a legend in the caption; this makes the table hard to read. Please add a legend or spell out 'growth', 'destruction', and 'ambiguous'.
  3. [Fig. 2 caption] There is a grammatical error: 'similar to those in the left panel' appears twice and the second occurrence is redundant. Also, the colorbar labels are inconsistent with the text (e.g., 'turb' vs 'M_turb').
  4. [§4.4, Eq. (7)] The scaling δv/δd ∼ t_drag^{-1}(1+M_turb)^3 is dimensionally consistent, but the numerical prefactor should be justified. The order-of-magnitude estimate of 1 km/s/pc for fiducial parameters is useful; please state whether it is derived from the simulations or an analytic estimate.

Circularity Check

1 steps flagged

Central survival criterion Eq. (5) is calibrated to the same simulations it then presents as a universal finding; f_mix absorbs the unresolved cloud-scale turbulent velocity.

specific steps
  1. fitted input called prediction [Section 3.1, Eq. (5), Fig. 3; recast in Section 4.3, Eq. (6)]
    "Note that in Eq. (5), we used v_rms as a proxy for the turbulent velocity v_turb. More precisely, this should be u'(L_cold) ≈ v_turb(L_cold/L_eddy)^{1/3}, where L_cold is the scale of the cold gas that turbulence is acting upon. While we can constrain this scale to lie within r_cl < L_cold < L_eddy, its exact value remains uncertain. ... This uncertainty of the relevant u' as well as the fact that destruction usually occurs at a few t_cc (e.g. Scannapieco & Brüggen 2015) are absorbed in the fudge factor f_mix."

    The modified destruction time in Eq. (5) is not derived from a first-principles model of turbulent destruction; f_mix is a free parameter chosen so that the resulting curve separates the simulated growing and destroyed clouds in Fig. 3. Because the paper explicitly places the unknown u'(L_cold) into f_mix, the boundary t_cool,mix/tilde_t_cc < 1 is a calibration of the same survival/destruction data it is then used to 'predict.' The later critical-radius formula Eq. (6) merely rearranges this calibrated criterion, so the headline quantitative claim reduces to a fit with a fudge factor, not an independent test.

full rationale

The paper's main non-circular content is its simulation measurements: enhanced cold-mass growth by up to an order of magnitude, increased mixing surface area, faster entrainment, and morphological changes are all direct simulation outputs, not consequences of the fitted formula. These results are self-contained and do not rely on f_mix. However, the central claim advertised as the 'universal survival criterion' (Eq. 5 and Fig. 3) is constructed by fitting f_mix ~ 0.6 to the very same set of growing/destroyed runs, and the admitted absorption of the uncertain cloud-scale turbulent velocity into f_mix means the boundary is not an independent prediction. The paper is honest about the fudge factor, but the presentation of the fitted curve as the key finding and its use to derive Eq. (6) constitute partial circularity. No load-bearing self-citation chain was found; cited prior results (cloud-crushing, mixing-layer scalings) are independent published work.

Axiom & Free-Parameter Ledger

2 free parameters · 7 axioms · 0 invented entities

The central criterion rests on one fitted parameter (f_mix) and several domain assumptions: the equilibrium Cloudy cooling curve, the laminar mixed-gas survival criterion it extends, a density-weighted forcing prescription that shields the cloud from direct turbulent acceleration, the approximation that the driving-scale rms velocity acts on the cloud, 8-cells-per-cloud-radius resolution sufficiency, and the artificial prevention of wind cooling. No new physical entities (particles, forces, or dimensions) are introduced.

free parameters (2)
  • f_mix = ≈0.6
    Fudge factor in the modified destruction time (Eq. 5, Fig. 3) fitted to separate surviving from destroyed runs; absorbs the uncertain turbulent velocity at the cloud scale and the destruction-time normalization.
  • Power-law index of \dot{M}_cl vs M_turb = 3/2
    The scaling \dot{M}_cl ∝ M_turb^{3/2} (§4.2, Fig. 9) is fitted to the simulation points and presented as a scaling, not derived from the criterion.
axioms (7)
  • domain assumption Cloudy equilibrium cooling curve with solar metallicity, Haardt & Madau (2012) UVB at z=0, and a 4×10^4 K temperature floor
    Adopted in §2 to define the radiative loss function; the central growth/survival results depend on this cooling curve.
  • domain assumption The laminar mixed-gas cooling criterion t_cool,mix/t_cc < 1 (Gronke & Oh 2018) is the correct baseline that turbulence modifies
    The paper extends rather than re-derives this criterion (§1, §3.1); if the baseline itself fails, the modified criterion inherits the failure.
  • ad hoc to paper Density-weighted turbulent forcing keeps the cold cloud from being accelerated by the forcing (F ∝ 1/ρ for T < 3T_cl)
    Introduced in §2.2 (footnote 3) to avoid 'unphysical acceleration' of the dense cloud; this restricts turbulence to act on the cloud only through shear in the hot phase, which could bias the entrainment and mixing results.
  • domain assumption u'(L_cold) ≈ v_rms at the driving scale in the survival criterion
    Stated below Eq. (5) in §3.1: the relevant turbulent velocity for cloud destruction is approximated by the forcing-scale rms velocity although L_cold is only known to lie between r_cl and L_eddy; the uncertainty is then absorbed into f_mix.
  • domain assumption R_cl/Δ = 8 cells is sufficient for converged cold-mass growth rate
    Used in §2.1 and defended in §4.5 via prior convergence studies (Gronke & Oh 2019; Dutta et al. 2025); the paper admits the surface area entering the growth mechanism is not converged (§3.2).
  • domain assumption Wind cooling is switched off in unmixed cells (tracer C < 10^-4), approximating background heating that keeps the wind hot
    Introduced in §2.1 to maintain a quasi-static hot reservoir; the physical nature of the assumed background heating is unspecified.
  • domain assumption Periodic boundary conditions with continuously driven turbulence represent a galactic wind over the simulated times
    Assumed in §2.1; the periodic box and homogeneous forcing are idealizations relative to stratified, expanding galactic winds, as acknowledged in §4.5.

pith-pipeline@v1.3.0-alltime-deepseek · 27954 in / 18926 out tokens · 140219 ms · 2026-08-04T11:38:05.318640+00:00 · methodology

0 comments
Cite this review

Pith. "Pith review of Woven by the Whirls: The growth and entrainment of cold clouds in turbulent hot winds." pith.science (2026). https://pith.science/paper/KYPN5H7N

@misc{pith2026251003552,
  author       = {Pith},
  title        = {Pith review of: Woven by the Whirls: The growth and entrainment of cold clouds in turbulent hot winds},
  year         = {2026},
  howpublished = {\url{https://pith.science/paper/KYPN5H7N}},
  note         = {Machine review of arXiv:2510.03552}
}
Share X Bluesky LinkedIn Reddit HN
read the original abstract

Galactic and intergalactic flows often exhibit relative motion between the cold dense gas and the hot diffuse medium. Such multiphase flows -- involving gas at different temperatures, densities, and ionization states -- for instance, galactic winds, are frequently turbulent. However, idealized simulations typically model the winds and driven turbulence separately, despite their intertwined roles in galaxy evolution. To address this, we investigate the survival of a dense cloud in a hot wind subject to continuous external turbulent forcing. We perform 3D hydrodynamic simulations across a range of turbulent Mach numbers in the hot phase $\mathcal{M}_{\rm turb}=v_{\rm turb}/c_{\rm s, wind}$ from 0.1 to 0.7 ($c_{\rm s, wind}$ and $v_{\rm turb}$ being the sound speed and the turbulent velocity in the hot phase, respectively). We find that in spite of the additional subsonic turbulence, cold clouds can survive if the cooling time of the mixed gas $t_{\rm cool, mix}$ is shorter than a modified destruction time $\tilde{t}_{\rm cc}$, i.e., $t_{\rm cool,mix}/\tilde{t}_{\rm cc}<1$ where $\tilde{t}_{\rm cc}=t_{\rm cc}/(1+\left(\mathcal{M}_{\rm turb}/\left(f_{\rm mix}\mathcal{M}_{\rm wind}\right)\right)^2)^{1/2}$, where $f_{\rm mix}\sim0.6$ is a fudge factor. Moreover, in the `survival regime', turbulence can enhance the growth of cold clouds by up to an order of magnitude because of more efficient stretching and an associated increase in the surface area. This increase in mass transfer between the phases leads to significantly faster entrainment of cold material in turbulent winds. In contrast to the narrow filamentary tails formed in laminar winds, turbulence stretches the cold gas orthogonally, dispersing it over a larger area and changing absorption line signatures.

Figures

Figures reproduced from arXiv: 2510.03552 by Alankar Dutta, Max Gronke, Prateek Sharma, Ritali Ghosh.

Figure 1
Figure 1. Figure 1: Projected column density of a cloud moving through a turbulent wind at various strengths of turbulent Mach number Mturb (increasing from top to bottom). The [left column] shows the cloud evolution in the weak cooling regime (𝑡cool,mix/𝑡cc = 10−1 ), while the [right column] shows the state in the strong cooling regime (𝑡cool,mix/𝑡cc = 10−3 ). All the snapshots are taken at 8𝑡cc, where 𝑡cc ∼ 𝜒 1/2𝑅cl/𝑣rel is… view at source ↗
Figure 2
Figure 2. Figure 2: [Left panel]: Evolution of the cold mass 𝑀cl (normalized by the initial cloud mass 𝑀cl,0) in units of cloud crushing time 𝑡cc at various turbulent Mach numbers Mturb = 𝑣turb/𝑐s,wind and the ratio of the cooling time of the mixed gas to the cloud crushing time 𝑡cool,mix/𝑡cc. [Right panel]: The relative velocity between the cloud and wind along the x-direction 𝑣cl − 𝑣wind in units of the initial relative vel… view at source ↗
Figure 3
Figure 3. Figure 3: provides an overview of the parameter space explored in our cloud crushing simulations (cf [PITH_FULL_IMAGE:figures/full_fig_p007_3.png] view at source ↗
Figure 5
Figure 5. Figure 5: Derived mixing velocity 𝑣mix (in units of 𝑐s,cl/(𝑡cool,cl/𝑡sc,cl) −1/4 ) as a function of turbulent Mach number Mturb in various cooling regimes 𝑡cool,mix/𝑡cc (indicated in the colormap). The triangles indicate the average mixing velocity between 10 − 20 𝑡cc, with error bars showing its range within the specified time. The derived mixing velocity is therefore close to ∼ 0.2, as found in standard cloud crus… view at source ↗
Figure 4
Figure 4. Figure 4: [Top panel]: Mass growth rate for the fast and moderate cool￾ing regimes with different strengths of turbulent forcing. Different linestyles are for different 𝑡cool,mix/𝑡cc. The line colors mark the evolution at different strengths of turbulent driving, as indicated in the colorbar. [Bottom panel]: area as a function of time for an isosurface considered at temperature threshold 𝑇thres = 2 × 𝑇cl). Continuou… view at source ↗
Figure 6
Figure 6. Figure 6: Correlation between mass enhancement time versus the entrainment time. A highly turbulent wind (higher Mturb) can entrain the cold clouds in a short time, while the mass is enhanced by an ever increasing area (see [PITH_FULL_IMAGE:figures/full_fig_p009_6.png] view at source ↗
Figure 8
Figure 8. Figure 8: Evolution of cold gas spread and tail length in the presence of continuous turbulent forcing in cloud crushing simulations. [Top panel]: Orthogonal spread of cold gas (in units of the initial cloud radius 𝑅cl) per￾pendicular to the wind direction (𝑅ˆ) for simulations with varying turbulent forcing, as indicated by the Mach number Mturb in the colormap. The extent of cloud is determined from the lateral spr… view at source ↗
Figure 10
Figure 10. Figure 10: Relation between cloud area 𝐴cl(in units of 𝑅 2 cl) and cold gas mass 𝑀cl (in units of initial cloud mass 𝑀cl,0) for simulations with varying turbulent forcing, as indicated by the turbulent Mach number in the colorbar. Thick cyan and orange lines show reference scalings 𝐴cl ∝ 𝑀𝛿 cl . For most runs with driven turbulence, the evolution follows a slope of 𝛿 ≈ 2/3, indicating that the area available for coo… view at source ↗
Figure 11
Figure 11. Figure 11: The column of MgII through a randomly chosen line of sight for 𝑡cool,mix/𝑡cc = 10−1 and Mturb = 0.2. The top-left panel (a) shows the volume-rendered view with the chosen sightline intersecting three cloud complexes (visible as overdensities in panel b). Panel (b) shows the Hydrogen number density (in blue) along with that of MgII in magenta. The velocity field along the direction of the line of sight (𝑧ˆ… view at source ↗
Figure 12
Figure 12. Figure 12: Effective entrainment distance defined as the distance the cloud travel when the relative velocity reaches Δ𝑣/𝑣wind ∼ 0.1 against turbulent Mach number. The different symbols indicate different cooling efficiencies and the blue band marks the scaling ∝ (1 + Mturb ) −3 which the numerical results seem to follow. High-velocity clouds (HVCs), which are observed close to the Galactic disk, are also going to b… view at source ↗

discussion (0)

Sign in with ORCID, Apple, or X to comment. Anyone can read and Pith papers without signing in.

Forward citations

Cited by 5 Pith papers

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

  1. Survival is not Enough: Dust Sputtering, Growth, and H$_2$ Formation in Galactic Winds

    astro-ph.GA 2026-07 conditional novelty 7.5

    Entrained clouds form high H2 fractions only with dust growth at densities ≳10–30 times the cloud-survival critical density; without growth, DGR dilution and sputtering keep them atomic.

  2. XMAGNET -- Stir before serving: a Lagrangian perspective on mixing-driven condensation in the intracluster medium

    astro-ph.GA 2026-05 unverdicted novelty 6.0

    Lagrangian tracers show mixing with low-entropy seeds drives most condensation in cluster cores; magnetic fields cause earlier divergence, higher vorticity, lower Mach numbers, and slower cold-cloud motion via tension.

  3. XMAGNET -- Stir before serving: a Lagrangian perspective on mixing-driven condensation in the intracluster medium

    astro-ph.GA 2026-05 conditional novelty 6.0

    In cool-core cluster simulations, mixing with pre-existing cold gas, not direct radiative cooling, dominates condensation; magnetic fields stretch the pre-condensation history to ~150 Myr and brake infalling clouds th...

  4. Cold gas formation triggered by active galactic nuclei jet feedback in galaxy cluster cores

    astro-ph.GA 2026-01 conditional novelty 6.0

    In simulations, cold clumps condense in situ from hot cluster gas within ~30 Myr in high-compression, low-vorticity zones stirred by laterally expanding AGN jets, most efficiently when the hot-gas turbulent Mach numbe...

  5. Multiphase gas in Circumgalactic cloud complexes: Insights from kiloparsec-scale Magnetohydrodynamic Turbulence Simulations

    astro-ph.GA 2025-10 conditional novelty 6.0

    Cold-gas survival in the circumgalactic medium is set by t_cool/t_mix; small-scale cold gas requires dense, quiescent regions, not turbulent cascade patches.

Reference graph

Works this paper leans on

122 extracted references · 13 canonical work pages · cited by 4 Pith papers

  1. [1]

    write newline

    " write newline "" before.all 'output.state := FUNCTION fin.entry write newline FUNCTION new.block output.state before.all = 'skip after.block 'output.state := if FUNCTION new.sentence output.state after.block = 'skip output.state before.all = 'skip after.sentence 'output.state := if if FUNCTION not #0 #1 if FUNCTION and 'skip pop #0 if FUNCTION or pop #1...

  2. [2]

    W., Bryan G

    Abruzzo M. W., Bryan G. L., Fielding D. B., 2022, @doi [ ] 10.3847/1538-4357/ac3c48 , https://ui.adsabs.harvard.edu/abs/2022ApJ...925..199A 925, 199

    doi:10.3847/1538-4357/ac3c48 2022

  3. [3]

    Antolin P., 2019, @doi [Plasma Physics and Controlled Fusion] 10.1088/1361-6587/ab5406 , 62, 014016

    doi:10.1088/1361-6587/ab5406 2019

  4. [4]

    K., Prochaska J

    Armillotta L., Fraternali F., Werk J. K., Prochaska J. X., Marinacci F., 2017, @doi [ ] 10.1093/mnras/stx1239 , https://ui.adsabs.harvard.edu/abs/2017MNRAS.470..114A 470, 114

    doi:10.1093/mnras/stx1239 2017

  5. [5]

    Audit E., Hennebelle P., 2010, @doi [A&A] 10.1051/0004-6361/200912695 , 511, A76

    doi:10.1051/0004-6361/200912695 2010

  6. [6]

    Banerjee N., Sharma P., 2014, @doi [ ] 10.1093/mnras/stu1179 , https://ui.adsabs.harvard.edu/abs/2014MNRAS.443..687B 443, 687

    doi:10.1093/mnras/stu1179 2014

  7. [7]

    A., et al., 2020, @doi [The Astrophysical Journal] 10.3847/1538-4357/abb376 , 902, 154

    Barger K. A., et al., 2020, @doi [The Astrophysical Journal] 10.3847/1538-4357/abb376 , 902, 154

    work page doi:10.3847/1538-4357/abb376 2020

  8. [8]

    C., Fabian A

    Begelman M. C., Fabian A. C., 1990, , https://ui.adsabs.harvard.edu/abs/1990MNRAS.244P..26B 244, 26P

    1990

  9. [9]

    Bordoloi R., et al., 2014, @doi [ ] 10.1088/0004-637X/794/2/130 , https://ui.adsabs.harvard.edu/abs/2014ApJ...794..130B 794, 130

    doi:10.1088/0004-637x/794/2/130 2014

  10. [10]

    N., Fabian A

    Bregman J. N., Fabian A. C., Miller E. D., Irwin J. A., 2006, @doi [The Astrophysical Journal] 10.1086/501112 , 642, 746

    doi:10.1086/501112 2006

  11. [11]

    Br \"u ggen M., Scannapieco E., 2016, @doi [ ] 10.3847/0004-637X/822/1/31 , https://ui.adsabs.harvard.edu/abs/2016ApJ...822...31B 822, 31

    doi:10.3847/0004-637x/822/1/31 2016

  12. [12]

    Dover Publications, Incorporated

    Chandrasekhar S., 1981, Hydrodynamic and Hydromagnetic Stability. Dover Publications, Incorporated

    1981

  13. [13]

    Chen H., et al., 2020, @doi [ ] 10.1093/mnras/staa1868 , https://ui.adsabs.harvard.edu/abs/2020MNRAS.496.4654C 496, 4654

    doi:10.1093/mnras/staa1868 2020

  14. [14]

    Chen H.-W., et al., 2023, @doi [ ] 10.3847/2041-8213/acf85b , https://ui.adsabs.harvard.edu/abs/2023ApJ...955L..25C 955, L25

    doi:10.3847/2041-8213/acf85b 2023

  15. [15]

    G., 2013, @doi [Monthly Notices of the Royal Astronomical Society] 10.1093/mnras/sts439 , 429, 1922

    Creasey P., Theuns T., Bower R. G., 2013, @doi [Monthly Notices of the Royal Astronomical Society] 10.1093/mnras/sts439 , 429, 1922

    work page doi:10.1093/mnras/sts439 2013

  16. [16]

    K., Gronke M., 2024, @doi [ ] 10.1093/mnras/stad3125 , https://ui.adsabs.harvard.edu/abs/2024MNRAS.527..991D 527, 991

    Das H. K., Gronke M., 2024, @doi [ ] 10.1093/mnras/stad3125 , https://ui.adsabs.harvard.edu/abs/2024MNRAS.527..991D 527, 991

    doi:10.1093/mnras/stad3125 2024

  17. [17]

    K., Gronke M., Weinberger R., 2024, @doi [arXiv e-prints] 10.48550/arXiv.2412.03751 , https://ui.adsabs.harvard.edu/abs/2024arXiv241203751D p

    Das H. K., Gronke M., Weinberger R., 2024, @doi [arXiv e-prints] 10.48550/arXiv.2412.03751 , https://ui.adsabs.harvard.edu/abs/2024arXiv241203751D p. arXiv:2412.03751

    Pith/arXiv arXiv doi:10.48550/arxiv.2412.03751 2024

  18. [18]

    H., Appleby S., 2019, @doi [Monthly Notices of the Royal Astronomical Society] 10.1093/mnras/stz937 , 486, 2827

    Davé R., Anglés-Alcázar D., Narayanan D., Li Q., Rafieferantsoa M. H., Appleby S., 2019, @doi [Monthly Notices of the Royal Astronomical Society] 10.1093/mnras/stz937 , 486, 2827

    doi:10.1093/mnras/stz937 2019

  19. [19]

    T., 2011, Physics of the Interstellar and Intergalactic Medium

    Draine B. T., 2011, Physics of the Interstellar and Intergalactic Medium . Princeton University Press, 2011

    2011

  20. [20]

    J., Pfrommer C., 2008, @doi [The Astrophysical Journal] 10.1086/529371 , 677, 993

    Dursi L. J., Pfrommer C., 2008, @doi [The Astrophysical Journal] 10.1086/529371 , 677, 993

    doi:10.1086/529371 2008

  21. [21]

    Dutta A., Sharma P., Nelson D., 2022, @doi [ ] 10.1093/mnras/stab3653 , https://ui.adsabs.harvard.edu/abs/2022MNRAS.510.3561D 510, 3561

    doi:10.1093/mnras/stab3653 2022

  22. [22]

    S., Sharma P., Ghosh R., Roy M., Nath B

    Dutta A., Bisht M. S., Sharma P., Ghosh R., Roy M., Nath B. B., 2024, @doi [Monthly Notices of the Royal Astronomical Society] 10.1093/mnras/stae977 , 531, 5117

    doi:10.1093/mnras/stae977 2024

  23. [23]

    arXiv:2506.08545

    Dutta A., Sharma P., Gronke M., 2025, @doi [arXiv e-prints] 10.48550/arXiv.2506.08545 , https://ui.adsabs.harvard.edu/abs/2025arXiv250608545D p. arXiv:2506.08545

    doi:10.48550/arxiv.2506.08545 2025

  24. [24]

    A., Lazarian A., Cho J., Leitner S

    Esquivel A., Benjamin R. A., Lazarian A., Cho J., Leitner S. N., 2006, @doi [ ] 10.1086/505338 , https://ui.adsabs.harvard.edu/abs/2006ApJ...648.1043E 648, 1043

    doi:10.1086/505338 2006

  25. [25]

    Eswaran V., Pope S., 1988, @doi [Computers & Fluids] https://doi.org/10.1016/0045-7930(88)90013-8 , 16, 257

    doi:10.1016/0045-7930(88)90013-8 1988

  26. [26]

    C., 1994, @doi [ ] 10.1146/annurev.aa.32.090194.001425 , https://ui.adsabs.harvard.edu/abs/1994ARA&A..32..277F 32, 277

    Fabian A. C., 1994, @doi [ ] 10.1146/annurev.aa.32.090194.001425 , https://ui.adsabs.harvard.edu/abs/1994ARA&A..32..277F 32, 277

    arXiv 1994

  27. [27]

    F., 2017, @doi [The Astrophysical Journal] 10.3847/1538-4357/835/1/52 , 835, 52

    Faerman Y., Sternberg A., McKee C. F., 2017, @doi [The Astrophysical Journal] 10.3847/1538-4357/835/1/52 , 835, 52

    doi:10.3847/1538-4357/835/1/52 2017

  28. [28]

    J., Gronke M., 2021, @doi [Monthly Notices of the Royal Astronomical Society] 10.1093/mnras/stab3412 , 510, 551

    Farber R. J., Gronke M., 2021, @doi [Monthly Notices of the Royal Astronomical Society] 10.1093/mnras/stab3412 , 510, 551

    doi:10.1093/mnras/stab3412 2021

  29. [29]

    Roman-Duval, J

    Federrath, C. Roman-Duval, J. Klessen, R. S. Schmidt, W. Mac Low, M.-M. 2010, @doi [A&A] 10.1051/0004-6361/200912437 , 512, A81

    doi:10.1051/0004-6361/200912437 2010

  30. [30]

    J., et al., 2017, @doi [ ] 10.48550/arXiv.1705.10877 , https://ui.adsabs.harvard.edu/abs/2017RMxAA..53..385F 53, 385

    Ferland G. J., et al., 2017, @doi [ ] 10.48550/arXiv.1705.10877 , https://ui.adsabs.harvard.edu/abs/2017RMxAA..53..385F 53, 385

    Pith/arXiv arXiv doi:10.48550/arxiv.1705.10877 2017

  31. [31]

    B., Bryan G

    Fielding D. B., Bryan G. L., 2022, @doi [The Astrophysical Journal] 10.3847/1538-4357/ac2f41 , 924, 82

    doi:10.3847/1538-4357/ac2f41 2022

  32. [32]

    Fielding D., Quataert E., Martizzi D., Faucher-Giguère C.-A., 2017, @doi [Monthly Notices of the Royal Astronomical Society: Letters] 10.1093/mnrasl/slx072 , 470, L39

    doi:10.1093/mnrasl/slx072 2017

  33. [33]

    B., Ostriker E

    Fielding D. B., Ostriker E. C., Bryan G. L., Jermyn A. S., 2020, @doi [ ] 10.3847/2041-8213/ab8d2c , https://ui.adsabs.harvard.edu/abs/2020ApJ...894L..24F 894, L24

    doi:10.3847/2041-8213/ab8d2c 2020

  34. [34]

    B., et al., 2025, @doi [Monthly Notices of the Royal Astronomical Society] 10.1093/mnras/staf363 , 538, 3068

    Fisher D. B., et al., 2025, @doi [Monthly Notices of the Royal Astronomical Society] 10.1093/mnras/staf363 , 538, 3068

    doi:10.1093/mnras/staf363 2025

  35. [35]

    J., Savage B

    Fox A. J., Savage B. D., Wakker B. P., 2006, @doi [The Astrophysical Journal Supplement Series] 10.1086/504800 , 165, 229

    doi:10.1086/504800 2006

  36. [36]

    J., et al., 2014, @doi [The Astrophysical Journal] 10.1088/0004-637X/787/2/147 , 787, 147

    Fox A. J., et al., 2014, @doi [The Astrophysical Journal] 10.1088/0004-637X/787/2/147 , 787, 147

    doi:10.1088/0004-637x/787/2/147 2014

  37. [37]

    J., Richter P., Ashley T., Heckman T

    Fox A. J., Richter P., Ashley T., Heckman T. M., Lehner N., Werk J. K., Bordoloi R., Peeples M. S., 2019, @doi [The Astrophysical Journal] 10.3847/1538-4357/ab40ad , 884, 53

    doi:10.3847/1538-4357/ab40ad 2019

  38. [38]

    Fumagalli M., Fossati M., Hau G. K. T., Gavazzi G., Bower R., Sun M., Boselli A., 2014, @doi [Monthly Notices of the Royal Astronomical Society] 10.1093/mnras/stu2092 , 445, 4335

    doi:10.1093/mnras/stu2092 2014

  39. [39]

    Girichidis P., 2021, @doi [ ] 10.1093/mnras/stab2157 , https://ui.adsabs.harvard.edu/abs/2021MNRAS.507.5641G 507, 5641

    doi:10.1093/mnras/stab2157 2021

  40. [40]

    W., Beckwith K., 2020, The Astrophysical Journal, 889, 19

    Grete P., O’Shea B. W., Beckwith K., 2020, The Astrophysical Journal, 889, 19

    2020

  41. [41]

    P., 2018, @doi [ ] 10.1093/mnrasl/sly131 , https://ui.adsabs.harvard.edu/abs/2018MNRAS.480L.111G 480, L111

    Gronke M., Oh S. P., 2018, @doi [ ] 10.1093/mnrasl/sly131 , https://ui.adsabs.harvard.edu/abs/2018MNRAS.480L.111G 480, L111

    doi:10.1093/mnrasl/sly131 2018

  42. [42]

    P., 2019, @doi [Monthly Notices of the Royal Astronomical Society] 10.1093/mnras/stz3332 , 492, 1970

    Gronke M., Oh S. P., 2019, @doi [Monthly Notices of the Royal Astronomical Society] 10.1093/mnras/stz3332 , 492, 1970

    doi:10.1093/mnras/stz3332 2019

  43. [43]

    P., Ji S., Norman C., 2021, @doi [Monthly Notices of the Royal Astronomical Society] 10.1093/mnras/stab3351 , 511, 859

    Gronke M., Oh S. P., Ji S., Norman C., 2021, @doi [Monthly Notices of the Royal Astronomical Society] 10.1093/mnras/stab3351 , 511, 859

    doi:10.1093/mnras/stab3351 2021

  44. [44]

    Gr nnow A., Tepper-Garc \' a T., Bland-Hawthorn J., 2018, @doi [ ] 10.3847/1538-4357/aada0e , https://ui.adsabs.harvard.edu/abs/2018ApJ...865...64G 865, 64

    work page doi:10.3847/1538-4357/aada0e 2018

  45. [45]

    Grønnow A., Tepper-García T., Bland-Hawthorn J., Fraternali F., 2021, @doi [Monthly Notices of the Royal Astronomical Society] 10.1093/mnras/stab3452 , 509, 5756

    doi:10.1093/mnras/stab3452 2021

  46. [46]

    Haardt F., Madau P., 2012, @doi [ ] 10.1088/0004-637X/746/2/125 , https://ui.adsabs.harvard.edu/abs/2012ApJ...746..125H 746, 125

    doi:10.1088/0004-637x/746/2/125 2012

  47. [47]

    M., Baum S

    Heckman T. M., Baum S. A., van Breugel W. J. M., McCarthy P., 1989, @doi [ ] 10.1086/167181 , https://ui.adsabs.harvard.edu/abs/1989ApJ...338...48H 338, 48

    doi:10.1086/167181 1989

  48. [48]

    Heckman T., Borthakur S., Wild V., Schiminovich D., Bordoloi R., 2017, @doi [The Astrophysical Journal] 10.3847/1538-4357/aa80dc , 846, 151

    doi:10.3847/1538-4357/aa80dc 2017

  49. [49]

    Heitsch F., Hartmann L., 2008, @doi [The Astrophysical Journal] 10.1086/592491 , 689, 290

    work page doi:10.1086/592491 2008

  50. [50]

    J., Gronke M., 2023, @doi [Monthly Notices of the Royal Astronomical Society] 10.1093/mnras/stad3069 , 527, 135

    Hidalgo-Pineda F., Farber R. J., Gronke M., 2023, @doi [Monthly Notices of the Royal Astronomical Society] 10.1093/mnras/stad3069 , 527, 135

    doi:10.1093/mnras/stad3069 2023

  51. [51]

    Hillier A., Snow B., Arregui I., 2023, @doi [ ] 10.1093/mnras/stad234 , https://ui.adsabs.harvard.edu/abs/2023MNRAS.520.1738H 520, 1738

    work page doi:10.1093/mnras/stad234 2023

  52. [52]

    H., Peeples M

    Huang S., Katz N., Scannapieco E., Cottle J., Davé R., Weinberg D. H., Peeples M. S., Brüggen M., 2020, @doi [Monthly Notices of the Royal Astronomical Society] 10.1093/mnras/staa1978 , 497, 2586

    work page doi:10.1093/mnras/staa1978 2020

  53. [53]

    B., et al., 2019, @doi [The Astrophysical Journal] 10.3847/1538-4357/ab378f , 882, 156

    Hummels C. B., et al., 2019, @doi [The Astrophysical Journal] 10.3847/1538-4357/ab378f , 882, 156

    doi:10.3847/1538-4357/ab378f 2019

  54. [54]

    P., Masterson P., 2019, @doi [Monthly Notices of the Royal Astronomical Society] 10.1093/mnras/stz1248 , 487, 737

    Ji S., Oh S. P., Masterson P., 2019, @doi [Monthly Notices of the Royal Astronomical Society] 10.1093/mnras/stz1248 , 487, 737

    doi:10.1093/mnras/stz1248 2019

  55. [55]

    Kanjilal V., Dutta A., Sharma P., 2021, @doi [ ] 10.1093/mnras/staa3610 , https://ui.adsabs.harvard.edu/abs/2021MNRAS.501.1143K 501, 1143

    doi:10.1093/mnras/staa3610 2021

  56. [56]

    Kim J.-G., Kim W.-T., 2013, @doi [ ] 10.1088/0004-637X/779/1/48 , https://ui.adsabs.harvard.edu/abs/2013ApJ...779...48K 779, 48

    doi:10.1088/0004-637x/779/1/48 2013

  57. [57]

    C., 2018, @doi [ ] 10.3847/1538-4357/aaa5ff , https://ui.adsabs.harvard.edu/abs/2018ApJ...853..173K 853, 173

    Kim C.-G., Ostriker E. C., 2018, @doi [ ] 10.3847/1538-4357/aaa5ff , https://ui.adsabs.harvard.edu/abs/2018ApJ...853..173K 853, 173

    doi:10.3847/1538-4357/aaa5ff 2018

  58. [58]

    I., McKee C

    Klein R. I., McKee C. F., Colella P., 1994, @doi [ ] 10.1086/173554 , https://ui.adsabs.harvard.edu/abs/1994ApJ...420..213K 420, 213

    doi:10.1086/173554 1994

  59. [59]

    Koyama H., Inutsuka S.-i., 2004, @doi [The Astrophysical Journal] 10.1086/382478 , 602, L25

    doi:10.1086/382478 2004

  60. [60]

    Krishnarao D., et al., 2022, @doi [ ] 10.1038/s41586-022-05090-5 , https://ui.adsabs.harvard.edu/abs/2022Natur.609..915K 609, 915

    doi:10.1038/s41586-022-05090-5 2022

  61. [61]

    L., 2010, @doi [ ] 10.1088/0004-637X/719/1/523 , https://ui.adsabs.harvard.edu/abs/2010ApJ...719..523K 719, 523

    Kwak K., Shelton R. L., 2010, @doi [ ] 10.1088/0004-637X/719/1/523 , https://ui.adsabs.harvard.edu/abs/2010ApJ...719..523K 719, 523

    doi:10.1088/0004-637x/719/1/523 2010

  62. [62]

    Lakhchaura K., et al., 2018, @doi [ ] 10.1093/mnras/sty2565 , https://ui.adsabs.harvard.edu/abs/2018MNRAS.481.4472L 481, 4472

    work page doi:10.1093/mnras/sty2565 2018

  63. [63]

    Lewiner T., Lopes H., Vieira A., Tavares G., 2003, @doi [Journal of graphics tools] 10.1080/10867651.2003.10487582 , 8, 1

    arXiv 2003

  64. [64]

    F., Squire J., Hummels C., 2020a, @doi [ ] 10.1093/mnras/stz3567 , https://ui.adsabs.harvard.edu/abs/2020MNRAS.492.1841L 492, 1841

    Li Z., Hopkins P. F., Squire J., Hummels C., 2020a, @doi [ ] 10.1093/mnras/stz3567 , https://ui.adsabs.harvard.edu/abs/2020MNRAS.492.1841L 492, 1841

    doi:10.1093/mnras/stz3567

  65. [65]

    Li Y., et al., 2020b, @doi [ ] 10.3847/2041-8213/ab65c7 , https://ui.adsabs.harvard.edu/abs/2020ApJ...889L...1L 889, L1

    doi:10.3847/2041-8213/ab65c7 2041

  66. [66]

    A., Mathur S., Nguyen D

    Lopez L. A., Mathur S., Nguyen D. D., Thompson T. A., Olivier G. M., 2020, @doi [The Astrophysical Journal] 10.3847/1538-4357/abc010 , 904, 152

    doi:10.3847/1538-4357/abc010 2020

  67. [67]

    Luo R., et al., 2023, @doi [ ] 10.1093/mnras/stad1003 , https://ui.adsabs.harvard.edu/abs/2023MNRAS.521.6266L 521, 6266

    work page doi:10.1093/mnras/stad1003 2023

  68. [68]

    P., 2025, @doi [arXiv e-prints] 10.48550/arXiv.2504.15345 , https://ui.adsabs.harvard.edu/abs/2025arXiv250415345M p

    Marin-Gilabert T., Gronke M., Oh S. P., 2025, @doi [arXiv e-prints] 10.48550/arXiv.2504.15345 , https://ui.adsabs.harvard.edu/abs/2025arXiv250415345M p. arXiv:2504.15345

    Pith/arXiv arXiv doi:10.48550/arxiv.2504.15345 2025

  69. [69]

    M., Madigan A.-M., Quataert E., 2015, @doi [Monthly Notices of the Royal Astronomical Society] 10.1093/mnras/stv355 , 449, 2

    McCourt M., O'Leary R. M., Madigan A.-M., Quataert E., 2015, @doi [Monthly Notices of the Royal Astronomical Society] 10.1093/mnras/stv355 , 449, 2

    doi:10.1093/mnras/stv355 2015

  70. [70]

    McDonald M., Veilleux S., Rupke D. S. N., 2012, @doi [ ] 10.1088/0004-637X/746/2/153 , https://ui.adsabs.harvard.edu/abs/2012ApJ...746..153M 746, 153

    doi:10.1088/0004-637x/746/2/153 2012

  71. [71]

    McQuinn K. B. W., van Zee L., Skillman E. D., 2019, @doi [ ] 10.3847/1538-4357/ab4c37 , https://ui.adsabs.harvard.edu/abs/2019ApJ...886...74M 886, 74

    doi:10.3847/1538-4357/ab4c37 2019

  72. [72]

    Mignone A., Bodo G., Massaglia S., Matsakos T., Tesileanu O., Zanni C., Ferrari A., 2007, @doi [ ] 10.1086/513316 , https://ui.adsabs.harvard.edu/abs/2007ApJS..170..228M 170, 228

    doi:10.1086/513316 2007

  73. [73]

    Mohapatra R., Sharma P., 2019, @doi [Monthly Notices of the Royal Astronomical Society] 10.1093/mnras/stz328 , 484, 4881

    doi:10.1093/mnras/stz328 2019

  74. [74]

    Mohapatra R., Jetti M., Sharma P., Federrath C., 2022, @doi [ ] 10.1093/mnras/stab3603 , https://ui.adsabs.harvard.edu/abs/2022MNRAS.510.3778M 510, 3778

    doi:10.1093/mnras/stab3603 2022

  75. [75]

    Mohapatra R., Sharma P., Federrath C., Quataert E., 2023, @doi [ ] 10.1093/mnras/stad2574 , https://ui.adsabs.harvard.edu/abs/2023MNRAS.525.3831M 525, 3831

    doi:10.1093/mnras/stad2574 2023

  76. [76]

    Morganti R., Fogasy J., Paragi Z., Oosterloo T., Orienti M., 2013, @doi [Science] 10.1126/science.1240436 , 341, 1082

    doi:10.1126/science.1240436 2013

  77. [77]

    A., Oort J

    Muller C. A., Oort J. H., Raimond E., 1963, Academie des Sciences Paris Comptes Rendus, https://ui.adsabs.harvard.edu/abs/1963CRAS..257.1661M 257, 1661

    1963

  78. [78]

    Mutchler M., et al., 2007, @doi [Publications of the Astronomical Society of the Pacific] 10.1086/511160 , 119, 1

    doi:10.1086/511160 2007

  79. [79]

    Nelson D., et al., 2020, @doi [Monthly Notices of the Royal Astronomical Society] 10.1093/mnras/staa2419 , 498, 2391

    doi:10.1093/mnras/staa2419 2020

  80. [80]

    D., Thompson T

    Nguyen D. D., Thompson T. A., Schneider E. E., Lopez S., Lopez L. A., 2023, @doi [ ] 10.1093/mnrasl/slac141 , https://ui.adsabs.harvard.edu/abs/2023MNRAS.518L..87N 518, L87

    work page doi:10.1093/mnrasl/slac141 2023

Showing first 80 references.