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Scope/inference is too broad for a single-snapshot study: the manuscript sometimes generalizes from one instantaneous state to global claims about RSG binary mass transfer (e.g., “challenges the traditional RLOF paradigm”), even though convection, pulsation, and orbital-phase effects can strongly modulate morphology (Abstract; Sec. 1; Sec. 3.3.1; Sec. 4.2–4.3).
Recommendation: Systematically localize claims to “this snapshot in this simulation” throughout the Abstract, Sec. 1, Sec. 3.3.1, and Sec. 4.2–4.3. Add explicit time context: snapshot time relative to the orbital period and an estimated convective turnover time, and whether the simulation had reached a statistically steady state. If feasible, analyze even a small ensemble of additional snapshots (e.g., $5$–$10$ across phase/time) to test persistence of (i) the “no L1-crossing streamlines” result and (ii) the force-balance/radiation trends; otherwise, add a clearly titled limitations subsection in Sec. 4.3 emphasizing that morphology and diagnostics may be transient.
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The underlying simulation setup and physics are insufficiently described for readers to judge realism or reproduce results (Sec. 2–2.1 focus on post-processing): code/solver, grid/domain, resolution, boundary conditions, EOS, opacities, radiation closure (FLD/M1, number of groups), binary parameters and frame, run duration, and snapshot selection criteria are unclear.
Recommendation: Add a dedicated “Simulation setup” subsection early in Sec. 2 that concisely lists: numerical code and RHD method; grid geometry, resolution, and domain extents; boundary conditions; EOS and $\gamma$; opacity treatment; radiation closure and groups; gravity (masses, separation, Roche potential) and whether the equations are solved in an inertial or corotating frame; and the snapshot time and selection rationale. Clearly state unit conventions and any mapping to physical units to avoid mixing code radii with ‘solar radii’ (Sec. 2.1–2.1.2). A compact parameter table (masses, separation $rm2$, $\omega$, etc.) would help.
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The headline “no L1 stream” conclusion depends heavily on streamline tracing details that are under-specified and may yield false negatives. Additionally, streamlines are traced for the mass-flux field $J = \rho v$, which is not equivalent to Lagrangian trajectories (Sec. 2.4; Sec. 3.3.1–3.3.2). The crossing diagnostic (0/10,000 cross $x = x(L1)$) depends on seeding strategy, integration tolerances/termination, and the choice of a plane rather than a Roche/L1 nozzle surface.
Recommendation: Expand Sec. 2.4 to specify the streamline integrator (e.g., RK order, step-size control, tolerances), interpolation scheme, maximum integration length/time, termination criteria, boundary handling, and a precise crossing criterion. Justify tracing $J$ rather than $v$, and add a side-by-side test tracing $v$ for a representative subset to show whether the qualitative conclusion changes. Strengthen the L1 claim with at least one independent Eulerian diagnostic: compute the instantaneous surface integral $\dot{M} = \iint J \cdot n\,dA$ through (i) a plane at $x(L1)$, and ideally also (ii) a small control surface around L1 (sphere/cylinder) or an approximate Roche-lobe boundary. Improve seeding robustness by (a) seeding weighted by outward flux $\max(J_r,0)$ on the surface shell and (b) increasing seed density near the substellar point toward the companion. If the result remains “no significant L1 flux in this snapshot”, state it as such rather than as a generic absence of RLOF.
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Region definitions—especially the heuristic “accretion stream” region—risk circularity and sensitivity to ad hoc thresholds ($x1v > 684$, $vel1 > 0.1$, $\rho > 1{\rm e}{-4}$), yet are used to support physical conclusions about outflow/radiation dominance (Sec. 2.1.2; Sec. 3.1.1–3.1.2; Sec. 3.4.1). Similar sensitivity may apply to the surface shell (650–684) and the “L1 vicinity” cube size.
Recommendation: In Sec. 2.1.2, motivate each threshold with physical scales (e.g., fractions of sound speed/escape speed, density relative to a surface/optical-depth criterion). In Sec. 3.1 and Sec. 3.4, provide sensitivity tests varying: (i) surface-shell radius/thickness, (ii) the L1 cube size/location, and (iii) the outflow thresholds, and report how key outputs (Table 1 moments; Table 2 force ratios) change. Consider renaming the “accretion stream” region to a neutral descriptor (e.g., “high-velocity outflow selection”) unless you show it feeds the companion. Add an “unbound/escaping” diagnostic where possible (e.g., Bernoulli parameter or $v$ compared to local escape speed) to demonstrate that selected material plausibly escapes rather than being a transient eddy.
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Coordinate-basis consistency is unclear for vector quantities and is critical for streamlines, fluxes, and $|J|$: the paper uses spherical components (vel1–vel3) while later invoking Cartesian components ($J_x,J_y,J_z$) and Cartesian geometry ($x = x(L1)$ plane), without explicitly defining the conversions and basis assumptions (Sec. 2.2.1; Sec. 2.4; figures/tables using $|J|$/Jmag).
Recommendation: Explicitly state whether streamline integration and flux calculations are performed in Cartesian $(x,y,z)$ or spherical $(r,\theta,\phi)$ coordinates. If Cartesian, provide the explicit conversion from $(vel1,vel2,vel3)$ (and thus $J$) to $(v_x,v_y,v_z)$ using the local spherical basis vectors; likewise define $J_x,J_y,J_z$ only after conversion. If spherical, write the ODEs for $(r,\theta,\phi)$ streamlines and explain the mapping to plotted $(x,y,z)$. Fix the mass-flux magnitude definition so it matches the component basis used (e.g., $\sqrt{J_r^2 + J_\theta^2 + J_\phi^2}$ vs $\sqrt{J_x^2 + J_y^2 + J_z^2}$).
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Force-balance and “radiation-dominated acceleration” interpretation currently relies mainly on ratios of force magnitudes from instantaneous fields, with unclear treatment of rotating-frame/inertial terms and limited connection to acceleration along outflow direction or to escape/unbinding (Sec. 2.5.1–2.5.2; Sec. 3.4.1; Sec. 4.2–4.3). Computing $\nabla \cdot P_r$ in curvilinear coordinates is also easy to implement incorrectly, yet formulas/validation are not given.
Recommendation: In Sec. 2.5.1, specify the frame and the exact momentum-equation decomposition you are comparing (inertial vs corotating). If corotating, include centrifugal and clarify treatment of Coriolis (not representable as $\nabla \Phi$). Provide explicit component formulas for $-\nabla P_g$, $-\rho\nabla\Phi$ (or the effective Roche potential), and $(\nabla\cdot P_r)_i$ in the coordinate basis actually used, including geometric terms. In Sec. 3.4.1, complement magnitude ratios with directional diagnostics: project accelerations along $\hat{v}$ (or streamline tangent), e.g., $a_{\rm rad,\parallel} = (\nabla\cdot P_r)\cdot \hat{v}/\rho$ vs $a_{\rm grav,\parallel}$ and $a_{\rm gas,\parallel}$, to avoid misleading “dominance” when forces are orthogonal. Add a minimal consistency/validation check (e.g., compare net force density to $\rho(v\cdot\nabla)v$ where appropriate; or, if possible, compare to $dv/dt$ from nearby snapshots). Temper language about radiation “unbinding” material unless you provide an order-of-magnitude integration along a path and compare to escape velocity.
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High-order statistics (skewness/kurtosis) and heavy-tail claims may be numerically fragile without clarifying weighting, sample sizes, and uncertainty. On a spherical grid, cell volumes differ; treating each cell equally can bias PDFs/moments. Tail moments are also sensitive to outliers, masking, and binning choices (Sec. 2.2.2–2.2.3; Sec. 3.1; Table 1; Figs. 3–5).
Recommendation: Report, per region, the number of cells and whether statistics/PDFs are volume-weighted, mass-weighted, or unweighted; justify the choice. Specify PDF construction (bin counts/ranges, log vs linear variables, normalization, handling of empty bins/tails). Provide uncertainty estimates for skewness/kurtosis (e.g., bootstrap CIs) and/or show robustness to trimming the most extreme fraction of cells (e.g., top/bottom $0.1\%$). Ensure moments correspond to the same variable whose PDF is shown ($\rho$ vs $\log\rho$, etc.).
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Turbulence and regime-identification methods are introduced but not yet quantitatively or reproducibly supported: correlation/structure-function implementation details are sparse and results are not clearly reported; spectra are discussed qualitatively without fitted slopes/ranges and with unclear boundary/windowing treatment; k-means clustering lacks feature scaling details and quantitative validation of $k=4$ (Sec. 2.2.4; Sec. 2.3.3–2.3.4; Sec. 3.2.1–3.2.2; Fig. 6).
Recommendation: For correlations/structure functions (Sec. 2.2.4), specify sampling strategy (number of pairs, separations, directional sampling), boundary handling, and whether masks break FFT assumptions; then either present the main quantitative outcomes (e.g., correlation lengths, anisotropy measures) or explicitly de-emphasize/remove these methods if inconclusive. For spectra (Sec. 2.3.3; Sec. 3.2.1; Fig. 6), document detrending/windowing/mean subtraction and non-periodic boundary treatment; fit and report approximate slopes over stated $k$-ranges with caveats about limited inertial range. For clustering (Sec. 2.3.4; Sec. 3.2.2), list features, normalization (e.g., z-score), subsampling, explored $k$-range, and show/summarize silhouette/elbow metrics; add cluster mass/volume fractions and typical parameter ranges to substantiate physical interpretation.