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Tidal disruption events in the local universe are dominated by cuspy satellite galaxies in cluster outskirts, not by cluster cores.

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load-bearing objection First environment-resolved TDE rate map from constrained simulations, with a novel spatial prediction that hinges on an unverified cusp/core proxy. the 4 major comments →

arxiv 2607.29454 v1 pith:PTABLVJW submitted 2026-07-31 astro-ph.HE astro-ph.GA

Rates of tidal disruption events from constrained cosmological simulations of the local Universe: population properties and implications for transient surveys

Julian S. Sommer , Ildar Khabibullin , Klaus Dolag , Luca Sala , Benjamin Seidel , Jenny G. Sorce , Alice Damiano This is my paper
classification astro-ph.HE astro-ph.GA
keywords tidal disruption eventssupermassive black holescosmological simulationsgalaxy clusters and superclusterscusp/core galaxy structuretransient surveysloss-cone dynamicslocal universe
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 uses a constrained cosmological simulation of the local universe, with zoom-in volumes around six real galaxy clusters and superclusters, to compute how often supermassive black holes tidally disrupt stars. It reports an average volumetric TDE rate of about 600 events per cubic gigaparsec per year and an average per-black-hole rate of about 4.5e-5 per year, numbers that sit near the upper end of observed estimates. The paper's central claim is spatial: after removing dynamically unstable black holes and applying a relativistic correction for direct capture, cluster cores contribute little, and the TDE budget is overwhelmingly produced by cuspy satellite galaxies in the extended cluster halos. The authors argue that yields are set by black hole demographics and spatial concentration rather than total cluster mass, which matters for where future transient surveys should look.

Core claim

The central discovery is that the simulated absolute TDE rate matches earlier literature estimates while the spatial distribution does not. In the cluster centers, low-mass galaxies have merged away or been stripped, and the massive black holes that remain swallow stars directly rather than producing visible flares, so central rates are strongly reduced. The budget is instead dominated by low-mass, high-spin black holes in cuspy dwarf satellites spread through the outer halos, where the relativistic efficiency for producing a visible flare is high. Environmental efficiency per black hole is therefore driven by the black hole mass distribution: Fornax, the least massive environment, retains m

What carries the argument

The argument is carried by three coupled pieces. First, a filter chain (offset from subhalo center, velocity relative to local dispersion, velocity-anisotropy, and dark-matter-to-stellar-mass ratio) isolates dynamically stable, pressure-supported 'main-sequence' black holes for which the loss-cone formalism applies. Second, each host galaxy is classified cuspy or cored from the 3D stellar density slope measured within 1 kpc, a proxy for the unresolved nuclear profile that sets loss-cone refilling. Third, the baseline TDE rate for each class is multiplied by the Kesden efficiency, the fraction of the loss cone that yields a visible flare instead of direct capture, computed from the Kerr geome

Load-bearing premise

The cusp/core classification, and therefore the conclusion that cuspy satellites dominate the TDE budget, rests on treating the 3D stellar density slope measured at 1 kpc as a faithful proxy for the unresolved sub-parsec nuclear structure that actually controls loss-cone refilling.

What would settle it

Measure the resolved nuclear stellar density profiles of the dwarf galaxies that dominate the simulated budget, in observed Coma, Virgo, and Fornax counterparts, at sub-parsec to few-parsec scales. If the 1 kpc slope fails to predict whether a steep nuclear cusp is present — for instance, if 'cored' dwarfs host steep nuclear star clusters — the cusp/core split and the predicted satellite-dominated spatial distribution would be invalid.

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

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If this is right

  • Observed optical and X-ray TDE rates around 1-3e-5 per galaxy per year are consistent with the simulated complete budget of about 4.5e-5 per black hole per year once survey selection and obscuration are accounted for.
  • Traditional 2D extrapolations that concentrate dwarf galaxies in cluster cores overestimate central surface TDE rates by roughly an order of magnitude; the same total yield is instead spread over the extended halo and outskirts.
  • A single universal volumetric TDE rate is not supported: the six environments span roughly 300-790 Gpc^-3 yr^-1, with the spread set by black hole number density and demographics, not cluster mass.
  • For surveys, the paper implies that wide-area coverage of supercluster outskirts is at least as important as deep monitoring of cluster centers for catching TDEs.
  • Because the simulation may overproduce low-mass dwarf galaxies, the quoted rate should be read as a robust theoretical upper limit for survey forecasts.

Where Pith is reading between the lines

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

  • If the 1 kpc density slope does not trace the unresolved sub-parsec stellar cusp — for example because nuclear star clusters or feedback flatten the inner profile — the satellite-dominance conclusion would need revision; resolved nuclear photometry of nearby dwarf satellites could test this directly.
  • The same simulation machinery could be extended to higher redshift, where merger activity peaks, to predict how the TDE rate and its environmental mix evolve toward the redshift peak seen in other work.
  • The comparison with efficiency set to unity in the paper suggests that relativistic capture is not the main cause of the central surface-density shortfall; if that holds, survey corrections should focus on dynamical depletion and dwarf-galaxy survival rather than spin-dependent prescriptions.
  • One could also use the simulated host-galaxy population to predict the offset distribution of TDEs from galactic nuclei, connecting to rare offset events noted in the paper.

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. The manuscript estimates tidal disruption event (TDE) rates in six constrained cosmological zoom-in environments (Coma, Hercules, Shapley, Virgo, Perseus, Fornax) from the SLOW/LOWER DECKS simulations. It extracts black hole masses, spins, and local stellar environments, applies four kinematic and structural filters, classifies host galaxies as cuspy (g≥2) or cored (g≤1) using the 3D stellar density slope within 1 kpc as a proxy for unresolved nuclear structure, applies the Kesden relativistic efficiency correction, and sums the Stone & Metzger (2016) empirical baseline rates (Eqs. 6–8). The paper reports a mean volumetric rate of ≈600 Gpc⁻³ yr⁻¹ and a per-black-hole rate of ≈4.5×10⁻⁵ yr⁻¹, and argues that the TDE budget is dominated by cuspy satellite galaxies in extended cluster halos rather than by central core galaxies. It further concludes that TDE yields are controlled by black hole demographics and spatial concentration rather than by total cluster mass.

Significance. If the central spatial-distribution claim holds, this is a useful step beyond 2D analytic extrapolations: it gives concrete, falsifiable predictions for the radial and environmental distribution of TDE hosts, and it connects cluster assembly state to per-black-hole TDE efficiency. The use of constrained simulations of observed structures is a strength, as is the inclusion of black hole spin and the relativistic efficiency correction. The paper is also commendably transparent about its main limitation (the 1 kpc slope proxy) and about the dwarf-overproduction caveat. However, because the absolute normalization is inherited from SM16 fits and the qualitative dominance claim rests on an unvalidated proxy, the significance is conditional on additional validation.

major comments (4)
  1. [§2.3, Fig. A.1] The classification of all hosts into cusps (g≥2) and cores (g≤1) uses the 3D stellar density slope measured in a 1 kpc aperture as a proxy for unresolved nuclear structure. The text explicitly states that the inner parsecs are not resolved and that the choice is justified by the 'macroscopic structure reflects global assembly history' paradigm. This proxy is load-bearing: Eqs. (6)–(7) differ by a factor of about 5.4, and Fig. 5's conclusion that cuspy satellites dominate the TDE budget follows directly from this classification. Fig. A.1 shows only that the 1 kpc slope is bimodal and scale-dependent; it does not validate that the 1 kpc bimodality tracks the sub-parsec cusp/core dichotomy. Nuclear star clusters, dissipative gas inflow, or AGN feedback could decouple the two. I request either a validation against resolved nuclear profiles (e.g., the Hannah et al. sample) or a robustness tes
  2. [Table 1, §3.2–3.3 and §2.3 filters] All rates are quoted as point values with no statistical or systematic uncertainties. Each environment is represented by one simulation realization, and Table 1 quotes Γ_vol to several significant figures (e.g., 777.65 vs. 794.22 Gpc⁻³ yr⁻¹) and Γ_norm differs by about 10% across environments. It is therefore not possible to tell whether Fornax's higher per-black-hole efficiency or Hercules's high volumetric rate is significant relative to cosmic variance. The four filters in §2.3 involve thresholds (1.5 kpc offset, FA<0.4, DM-to-stellar mass ratio >1, N_neigh≥10) that are not varied. Please add bootstrap/jackknife errors and a sensitivity analysis of the filter thresholds; without these, the environmental comparisons that constitute a main result are not quantitatively supported.
  3. [§2.5, Eqs. (6)–(8)] Because Γ_vol in Eq. (8) is the volume-normalized sum of the SM16 empirical fits, the reported ≈600 Gpc⁻³ yr⁻¹ and 4.5×10⁻⁵ yr⁻¹ per black hole are not independent theoretical predictions; they inherit the observed normalization already encoded in Eqs. (6)–(7). The abstract's statement that the absolute rates 'match early literature estimates' is therefore partly by construction. The genuinely new information is the spatial and environmental redistribution of these baseline rates. Please reframe the absolute-rate claims accordingly and, where possible, present environmental contrasts as ratios to the homogeneous extrapolation (as in Fig. 6) rather than as absolute predictions.
  4. [§4.3, §3.3] The text states that the simulation overproduces low-luminosity dwarf galaxies and that the derived volumetric yield is a 'robust theoretical upper limit.' These dwarfs are precisely the population that, by the paper's own analysis, dominates the TDE budget in the extended halos. The caveat therefore cuts deeper than a normalization factor: it may amplify the central claim that cuspy satellite galaxies dominate. Please quantify the sensitivity to the dwarf population (e.g., by rescaling or by comparing to observed dwarf luminosity functions) or, at minimum, soften the claim that the spatial distribution is robust while only the normalization is an upper limit.
minor comments (4)
  1. [Fig. 2] Axis labels such as 'log10(σ⋆/km s□1)' contain a placeholder box; the LaTeX/math rendering should be fixed.
  2. [Fig. 7 caption] The numbers '0.018 0.012' and '0.030 0.016' in the legend are not explained; define what they represent.
  3. [Table 1] The quantity f_cusp/core is listed as a fraction, but values near 1.0 (e.g., Coma 0.98, Hercules 1.00) are ambiguous: is this the ratio of cusp to core, or the fraction of cusps? Please define explicitly.
  4. [§4.1] When comparing Γ_norm = 4.5×10⁻⁵ yr⁻¹ to observed rates, note that the observational values are per galaxy with different selection functions; a brief reminder in the text would avoid confusion.

Circularity Check

1 steps flagged

Absolute volumetric and per-BH rates are inherited from the empirical SM16 baseline rates summed in Eq. 8; the spatial-distribution claim is not circular.

specific steps
  1. fitted input called prediction [Section 2.5, Eqs. 6-8; Section 3.2; Abstract]
    "SM16 empirically found that the trend of the TDE rate depends on whether the black hole is located in a core or cusp environment: Γg≤1 =1.2×10−5 (M•/10^8 M⊙)^−0.247 yr−1 gal−1 (6) Γg≥2 =6.5×10−5 (M•/10^8 M⊙)^−0.223 yr−1 gal−1 (7). ... Γvol = 1/Vz Σ Γi ηi (8). ... The resulting mean volumetric TDE rate Γvol,g≈606 Gpc−3 yr−1 ... Although our absolute TDE rates match early literature estimates, the underlying spatial distribution fundamentally differs."

    The paper's quoted 'prediction' of ~600 Gpc^-3 yr^-1 and 4.5e-5 yr^-1 per BH is the volume-normalized sum of the SM16 baseline rates (Eqs. 6-7), which the paper itself labels as empirical ('SM16 empirically found'). Those empirical rates were calibrated to observed TDE rates, so the abstract's statement that the simulation's absolute rates 'match early literature estimates' is inherited from the fitted input, not derived from the 3D simulation. Changing the baseline calibration would shift the 'prediction' nearly proportionally. The spatial-distribution conclusion (cuspy satellites dominate extended halos) is independent and not circular.

full rationale

The paper's main new physical claim—that TDE yields are dominated by cuspy satellite galaxies in extended cluster halos, with central core rates suppressed by dynamical depletion and direct-capture constraints, and that yields trace BH demographics and concentration rather than M500—is not circular. It follows from the simulated BH positions, masses, spins, and 1 kpc density-slope classification, combined with the SM16 cusp/core baseline split and the Kesden efficiency. The only reduction-by-construction step is the absolute normalization: Eq. 8 sums Eqs. 6-7, which the paper itself calls empirical fits, so the quoted agreement of absolute rates with early literature is carried by those fitted inputs rather than predicted independently. The 1 kpc cusp/core proxy is an unvalidated modeling assumption and a genuine correctness risk, but it is not a circular step. The self-citations to SLOW, LOWER DECKS, and the authors' spin/dynamical-friction models are simulation infrastructure and are not load-bearing for the circularity assessment.

Axiom & Free-Parameter Ledger

6 free parameters · 5 axioms · 0 invented entities

The central results rest on six tunable or adopted parameters (search radius, three filter thresholds, the SM16 baseline fits, and a fiducial stellar type) and on four domain assumptions about how unresolved nuclear structure and loss-cone dynamics behave in the simulations. No new physical entities are introduced.

free parameters (6)
  • r_search = 1 kpc
    Chosen from stability map (Fig. A.1); sets the radial envelope for the density slope fit and hence the cusp/core classification that selects SM16 baseline rates.
  • offset cut threshold = 1.5 kpc (~4 epsilon_*)
    Assumed maximum distance of a BH from subhalo center; excludes offset TDE hosts (acknowledged in Section 2.3).
  • FA cut threshold = 0.4
    Chosen to keep only approximately isotropic velocity ellipsoids so that SM16 loss-cone prescriptions apply; affects sample size.
  • DM-to-stellar mass ratio cut = >1
    Used to remove tidally stripped bare stellar nuclei; choice affects which BHs are kept.
  • SM16 cusp/core normalizations and slopes = 1.2e-5 and 6.5e-5 yr^-1 gal^-1 with exponents -0.247/-0.223
    Empirical fits from Stone & Metzger (2016) adopted as input baselines; the paper's absolute rates scale linearly with these values.
  • Fiducial star for Kesden efficiency = 1 M_sun, 1 R_sun
    The relativistic efficiency eta is computed for a solar-type star rather than the full Kroupa IMF used in SM16; the paper argues the mass dependence is weak.
axioms (5)
  • domain assumption SM16 empirical TDE rates (Eqs 6,7) apply to every simulated BH at face value
    The volumetric rate is a sum over these baselines; if real loss-cone dynamics in simulated galaxies deviate (e.g., due to unresolved nuclear star clusters or non-two-body relaxation), the rates shift.
  • domain assumption The 1 kpc stellar density slope is a valid proxy for the unresolved sub-parsec nuclear cusp/core profile
    Section 2.3, used to assign cusp vs core baseline rates; the paper cites the macroscopic-structure/assembly-history paradigm but does not verify it against resolved profiles.
  • domain assumption Loss-cone refilling in these galaxies is driven by two-body relaxation as in the SM16 framework
    Section 2.5: the calculation does not include gas-induced dynamical friction or other mechanisms; stated explicitly.
  • domain assumption The four main-sequence filters isolate the dynamically stable BH population for which SM16 applies
    Section 2.3: offset/velocity/FA/DM cuts are applied with thresholds chosen by the authors; the completeness and representativeness of the filtered sample is not validated externally.
  • standard math Kerr geodesic equations for r_mb, r_td and eta
    Eqs 2-5; standard GR, no free parameters.

pith-pipeline@v1.3.0-daily-deepseek · 24228 in / 13379 out tokens · 136170 ms · 2026-08-03T06:40:14.974822+00:00 · methodology

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Cite this review

Pith. "Pith review of Rates of tidal disruption events from constrained cosmological simulations of the local Universe: population properties and implications for transient surveys." pith.science (2026). https://pith.science/paper/PTABLVJW

@misc{pith2026260729454,
  author       = {Pith},
  title        = {Pith review of: Rates of tidal disruption events from constrained cosmological simulations of the local Universe: population properties and implications for transient surveys},
  year         = {2026},
  howpublished = {\url{https://pith.science/paper/PTABLVJW}},
  note         = {Machine review of arXiv:2607.29454}
}
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read the original abstract

(abridged) Motivated by upcoming surveys like LSST, we estimate tidal disruption event (TDE) rates using the constrained cosmological Simulation of the LOcal Web (SLOW) to test the limitations of traditional 2D analytical extrapolations within a fully 3D framework. We aim to provide reliable TDE budgets extracted from the simulated zoom-in volumes of the digital counterparts of the Coma, Hercules, Shapley, Virgo, and Perseus supercluster environments, and the Fornax galaxy cluster. From the zoom-in boundary volumes of the six environments, reaching radial extents of $55-92\,$Mpc, we extracted black hole demographics (including spin) and their host galaxy properties to establish a filter scheme that strictly preserves dynamically stable "main-sequence" black holes. We further classified host galaxies as cuspy or cored based on the slope of their 3D stellar density profile measured within $1\,$kpc as a proxy for unresolved nuclear structure and applied the relativistic Kesden efficiency correction to the filtered sample. We find an average volumetric and per black hole TDE rate of $\approx 600\,$Gpc$^{-3}\,$yr$^{-1}$ and $\approx 4.5\times 10^{-5}\,$yr$^{-1}$ across all six environments, respectively. Although our absolute TDE rates match early literature estimates, the underlying spatial distribution fundamentally differs. Central core rates are heavily reduced by dynamical depletion and direct capture constraints, meaning the total TDE budget is overwhelmingly dominated by cuspy satellite galaxies in the extended cluster halos. TDE yields are driven by black hole demographics and spatial concentration rather than total cluster mass. Actively assembling superclusters (e.g., Hercules) reduce per-black-hole TDE efficiencies via merger-driven black hole mass growth, whereas low-mass environments (e.g., Fornax) are highly efficient due to unmerged, low-mass black holes.

Figures

Figures reproduced from arXiv: 2607.29454 by Alice Damiano, Benjamin Seidel, Ildar Khabibullin, Jenny G. Sorce, Julian S. Sommer, Klaus Dolag, Luca Sala.

Figure 1
Figure 1. Figure 1: Distribution of stellar density slope g for each valid black hole in the six simulated structures (Shapley, Coma, Perseus, Hercules, Virgo, and Fornax). A distinct bimodal distribution, separating core (g ≤ 1) and cusp (g ≥ 2) environments, is clearly observed across all environ￾ments [PITH_FULL_IMAGE:figures/full_fig_p004_1.png] view at source ↗
Figure 2
Figure 2. Figure 2: Population of black holes before (top row) and after the main-sequence-filters were applied (bottom row). Each column is color￾coded by the median black hole mass (M•), stellar subhalo mass (M⋆,sub) and fractional anisotropy (FA). The population in σ⋆-∆r pa￾rameter space shows the velocity dispersion within the inner 1 kpc versus the offset of the black hole to its closest subhalo. with K = (L − aE) + Q, w… view at source ↗
Figure 3
Figure 3. Figure 3: Combined volumetric probability density function of the filtered black hole population in the ˜a-M• parameter space across all simulated structures. To account for varying boundary sizes, the individual dis￾tributions were normalized by their respective zoom-in volumes before combination. proximation from Kesden (2012): Γiso = 4.8 × 10−4 [PITH_FULL_IMAGE:figures/full_fig_p007_3.png] view at source ↗
Figure 4
Figure 4. Figure 4: Mean volumetric TDE density taken from all six environments in this sample in ˜a-M• parameter space. The dashed line represents the an￾alytical maximum black hole mass M•,max capable of producing a TDE. all galaxies, the SM16 framework systematically lowers the ex￾pected flux. This reduction comes not only from explicit sep￾aration of cusp and core galaxies, but also from the adoption of a more realistic K… view at source ↗
Figure 5
Figure 5. Figure 5 [PITH_FULL_IMAGE:figures/full_fig_p009_5.png] view at source ↗
Figure 7
Figure 7. Figure 7: presents a 2D surface projection depicting the cu￾mulative surface rate density. To provide a direct comparison of the influence of the Kesden efficiency parameter η, the fig￾ure shows the surface rate density with true η values and with η = 1 only. Both peak at approximately 10−2 Mpc−2 yr−1 with minimum differences in peak values reached. Since the surface rate densities are normalized by the respective e… view at source ↗

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