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The star-formation response of a simulated major merger is set by which stellar-feedback recipe the code uses.

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 →

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In nine matched cosmological simulations of a Milky Way-progenitor major merger at z≈4.5, the timing and strength of the merger-induced starburst depend on whether the code uses kinetic, thermal, or delayed-cooling stellar feedback.

T0 review reviewed 2026-08-01 challenge →

load-bearing objection A useful, visually rich AGORA comparison of one major merger across nine codes; the SFR-feedback grouping is plausible and mechanistically supported, but one run per code and a biased baseline method leave the central causal claim suggestive rather than decisive. the 3 major comments →

arxiv 2607.21709 v1 pith:LD5TOEKE submitted 2026-07-23 astro-ph.GA

The AGORA High-resolution Galaxy Simulations Comparison Project. IX - Part 1: Effects of a Major Galaxy Merger on Star Formation of a Milky Way-mass Galaxy Progenitor

Thinh Huu Nguyen , Kirk S. S. Barrow , Minyong Jung , Ram\'on Rodr\'iguez-Cardoso , Santi Roca-F\`abrega , Ji-hoon Kim , Joel R. Primack , Kentaro Nagamine
show 18 more authors
Renyue Cen Daniel Ceverino Weiguang Cui Anna Genina Hyeonyong Kim Yuri Oku Johnny W. Powell Yves Revaz Pablo Granizo Alessandro Lupi Ikkoh Shimizu H\'ector Vel\'azquez Tom Abel Oscar Agertz Avishai Dekel Boon Kiat Oh Thomas R. Quinn the AGORA Collaboration
This is my paper
classification astro-ph.GA
keywords galaxy mergersstar formationstellar feedbackcosmological simulationszoom-in simulationsburst fractionhigh redshift galaxiescode comparison
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.

The reading

The paper asks whether the star-formation response of a Milky-Way-mass galaxy to a major merger at z≈4.5 is a robust prediction of cosmological hydrodynamics or a product of the subgrid stellar-feedback model chosen by each code. Using nine calibrated zoom-in simulations of the same galaxy and merger, it reports that the answer is strongly feedback-dependent: kinetic feedback (momentum injection) produces a pronounced merger-induced starburst that begins to subside before coalescence; thermal-only feedback produces prolonged star-formation growth past coalescence; and delayed-cooling or radiation-pressure recipes produce strongly fluctuating SFR. The paper also traces gas particles to show that kinetic feedback funnels gas from the secondary onto the primary galaxy between first periapsis and first apoapsis, enabling the earlier burst, and finds an inverse correlation between the burst fraction and the pre-merger gas fraction that holds across all feedback models. If correct, the result means galaxy mergers are a sharp testbed for stellar feedback prescriptions rather than a settled prediction.

Core claim

The central discovery is a three-way split in the star-formation history of the same major merger when the only systematic change is the stellar feedback prescription. Simulations whose supernova feedback includes a kinetic channel (momentum injected into surrounding gas) form an extended starburst that peaks between first periapsis and first apoapsis and declines before the galaxies coalesce; simulations using only thermal feedback (heat injection) continue to increase their SFR after coalescence; and simulations adding delayed cooling or radiation pressure to thermal feedback show strong short-timescale SFR fluctuations superimposed on either trend. Gas particle tracking shows the kinetic-

What carries the argument

The organizing object is the feedback type, in particular whether a code's supernova scheme injects momentum (kinetic feedback) or only heat (thermal feedback), and whether it adds delayed cooling or radiation pressure. The suite provides nine calibrated simulations of one halo and one merger, so the feedback recipe is the main controlled variable. The analysis then uses orbit definitions (infall, first passage, coalescence, post-coalescence based on stellar-core distance and velocity) and tracks pre-star gas particles in Lagrangian codes to expose the causal path: kinetic feedback, possibly aided by momentum kicks opposite to infall, lets gas from the secondary collapse into the primary cen

Load-bearing premise

The paper attributes the spread in star-formation behavior to the feedback type while running only one simulation per code, so uncontrolled run-to-run chaotic divergence could in principle masquerade as a feedback effect.

What would settle it

Concrete: rerun one thermal-only code with a kinetic channel enabled and one kinetic code with it disabled, keeping all other settings fixed; if the SFR pattern does not flip accordingly, the central claim is falsified. Also, multiple seeded runs per code would test the chaos contamination.

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

If this is right

  • Merger-triggered starburst timing and amplitude are not converged predictions of cosmological galaxy formation; they vary by roughly an order of magnitude in SFR depending on the feedback recipe.
  • Kinetic feedback codes form their burst early, before coalescence, while thermal-only codes keep forming stars long after the remnant relaxes, so merger-stage classification alone does not fix the expected SFR response.
  • Delayed cooling and radiation pressure produce episodic, small-amplitude SFR fluctuations that can masquerade as merger-driven bursts on short timescales.
  • The inverse burst-fraction–gas-fraction correlation, found independently of feedback model, gives a candidate scaling relation that can be compared with observational burst-efficiency estimates.
  • Because the response is so feedback-sensitive, observed post-merger SFR histories could constrain which feedback modes operate at high redshift.

Where Pith is reading between the lines

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

  • If the grouping holds in larger samples, the timing of the post-merger SFR peak relative to coalescence could be used as an observational diagnostic of the dominant feedback channel in high-redshift galaxies.
  • The paper's own caveat that identical runs can diverge chaotically by factor-of-two stellar mass implies the true test requires multiple realizations per code; ensemble runs would separate feedback-driven trends from run-to-run stochasticity.
  • A code whose superbubble scheme expels gas shows its strongest starburst about 550 Myr after coalescence, implying surveys selecting mergers by morphological disturbance will miss a fraction of merger-driven star formation since the peak burst can occur after the remnant has relaxed.
  • One testable extension: rerun the same feedback model with kinetic feedback added or removed within a single code, holding everything else fixed, to confirm the causal claim without cross-code confounding.
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Editorial analysis

A structured set of objections, weighed in public.

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

Referee Report

3 major / 6 minor

Summary. This AGORA IX Part 1 paper uses the nine-code CosmoRun cosmological zoom-in suite to study a major galaxy merger at z≈4.5 in a Milky Way-mass progenitor. The authors define merger stages with a new coalescence criterion, track gas particles in particle-based codes, and compare the resulting SFR evolution across codes. Their central claim is that the merger-induced star formation response is strongly shaped by the stellar feedback prescription: codes with kinetic feedback show a pronounced pre-coalescence starburst; codes with thermal-only feedback show prolonged SFR growth into the post-coalescence stage; and codes with delayed cooling or radiation pressure show short-timescale SFR fluctuations. They also introduce a method to compute a burst fraction without an isolated control sample and report a feedback-independent anti-correlation between burst fraction and gas fraction.

Significance. If the central claim holds, the paper would demonstrate that the star formation response to major mergers is not a robust prediction of cosmological hydrodynamics but depends sensitively on subgrid stellar feedback prescriptions. This is an important and timely result, as it would imply that observed merger-induced starbursts can be used as a discriminating testbed for feedback models. The paper has notable strengths: the initial conditions and calibration are shared across codes, the halo finder and merger-stage definitions are carefully described, the gas-particle tracking provides a physical mechanism, and the authors are transparent about their caveats, including the lack of repeat runs. The new burst-fraction estimator is a useful methodological contribution, even if its assumptions need validation. The significance is conditional: the qualitative patterns are clear from the figures, but the causal attribution to feedback type is not fully secured by the current experimental design.

major comments (3)
  1. [§4.3 (second caveat) and §2.1] The paper's headline result—that feedback type 'strongly shapes' the SFR evolution—rests on one realization per code, with no repeat runs or chaos experiments. The authors themselves cite Keller et al. (2019), who found factor-of-two stellar-mass scatter between otherwise identical runs, with divergence amplified during mergers. With n=1 per code, the observed grouping of SFR curves could in principle be a stochastic realization effect rather than a causal consequence of feedback type. The within-group agreement across different code architectures is encouraging, but it does not replace replication. To make the causal claim load-bearing, the authors should either provide repeat runs for at least a subset of codes, or explicitly soften the language to 'correlated with' and present the feedback-type attribution as a plausible interpretation rather than a demonstrated cause.
  2. [§3.3, Eq. (2), Figs. 10–11] The burst-fraction method assumes that sSFR remains constant over the ~0.6–0.8 Gyr merger timescale in the absence of mergers with μ>1:10. This is an unvalidated assumption, and the baseline sSFR is chosen as the minimum sSFR in a 100-Myr pre-infall window. Taking the minimum rather than, say, the mean or median maximizes the inferred excess star formation and therefore the burst fraction. No sensitivity test is provided to show how f_sb or the R²=0.74 gas-fraction anti-correlation depends on this baseline choice. Since the gas-fraction correlation is claimed to be feedback-independent and is a key secondary result, the robustness of f_sb to alternative baseline definitions and window lengths should be demonstrated. At minimum, the authors should report how much f_sb and the correlation change under reasonable variations of the baseline definition.
  3. [§3.1 and §3.2.4] The three-way classification into 'kinetic', 'thermal-only', and 'delayed cooling/radiation pressure' feedback groups is not a clean partition: ART-I and GADGET-3 appear in both the kinetic group and the delayed-cooling/radiation-pressure group. The short-timescale 'bursty' behavior is asserted from visual inspection of Fig. 4, but no quantitative burstiness metric is provided. Additionally, the gas-particle tracking that directly supports the kinetic-feedback mechanism is limited to GADGET-3, GADGET-4, and GIZMO; ART-I's inclusion in the kinetic group is inferred from its SFR curve and phase plots, not from direct particle tracing. The authors should quantify the short-timescale variability (e.g., a scatter or burstiness parameter) and explicitly state which parts of the mechanistic explanation are directly traced versus inferred from the SFR morphology.
minor comments (6)
  1. [§3.1, third bullet] Typo: 'RASMES' should be 'RAMSES'.
  2. [§3.2.4] Typo: 'GAGDET-3' should be 'GADGET-3'.
  3. [§2.3 / Fig. 2] The phrase 'top 10%-bound star particles' is unclear; consider 'the 10% most bound star particles'.
  4. [§3.3 / Fig. 11] The gas-fraction correlation is based on only seven codes, with GEAR evaluated at a different time and GADGET-3/GADGET-4 excluded. A brief statement of the effective n and the sensitivity to those choices would help the reader calibrate the strength of the R² values.
  5. [§4.1] The comparison with Ferreira et al. (2025) uses one merger per code against a sample-averaged observational result; the authors note this, but the point could be made more prominently when interpreting the 'six out of nine' agreement.
  6. [Table 1 / Table 3] The naming of codes is inconsistent (e.g., 'Art-I' vs 'ART-I', 'Gadget-3' vs 'GADGET-3' in various places). Please normalize to the table style throughout.

Circularity Check

0 steps flagged

No circular derivation; central SFR-feedback comparison is independent of its inputs.

full rationale

The paper's central claim is that SFR evolution during the target merger groups by stellar feedback type. The feedback type is an a priori property of each code setup (Table 1), not a parameter fit to the SFR patterns; the SFR evolution is the measured output, not an input. The nine-code suite shares initial conditions and calibration targets from earlier AGORA papers, but those citations are legitimate methodological references and do not smuggle in the conclusion. The baseline sSFR used to define the burst fraction (Section 3.3) is chosen as the minimum pre-merger sSFR and is explicitly a counterfactual assumption; the resulting baseline stellar mass is the integral of that assumed constant sSFR, not an independent prediction, so the burst fraction is a defined metric rather than a fitted parameter renamed as a prediction. The acknowledged n=1 stochasticity caveat (Section 4.3) is an underdetermination and correctness-risk concern, not circularity. No equation reduces to itself, and no load-bearing uniqueness claim is imported from the authors' prior work. Score 1 reflects only minor self-referential methodological framing, not actual circularity.

Axiom & Free-Parameter Ledger

5 free parameters · 6 axioms · 0 invented entities

The paper introduces no new physical entities. Its explanatory burden is carried by the subgrid prescription parameters (feedback energies, delay times, star formation efficiency) and by analysis choices (baseline sSFR, coalescence thresholds). The key unexamined item is the isolation assumption — that the nine runs differ only in feedback — along with the constant-sSFR baseline used for the burst fraction.

free parameters (5)
  • baseline sSFR per code = quoted per code in Fig. 10 (order 1e-9/yr)
    Chosen as the minimum sSFR over the 100-Myr window before infall (§3.3). The min-selection systematically lowers the baseline and inflates f_sb.
  • coalescence thresholds in Eq. 1 = 0.025 R200c; vrel/σv < 0.1
    Hand-chosen thresholds defining t_cls and thus the merger-stage boundaries that organize the SFR pattern classification (§2.4, Appendix A).
  • subgrid feedback energies/delays per code = e.g., E_SN from 4e49 erg/Msun to 5e52 erg/SN; T_delay 5-10 Myr (Table 1)
    Calibrated so that the main halo stellar mass at z≈4 matches semi-empirical predictions within ~0.7 dex (Paper III); the central claim's grouping is defined by these prescriptions.
  • star formation efficiency epsilon = 0.01
    Common subgrid parameter assumed in the star formation law dρ*/dt = ε ρ_gas / t_ff (§2.1); controls the overall SFR scale.
  • SFR averaging timescale = 10 Myr
    Chosen for all SFR curves (§3.1); affects the classification of short-timescale burstiness vs. the long-timescale merger trend.
axioms (6)
  • ad hoc to paper Constant sSFR baseline: in the absence of mergers with μ>1:10, a galaxy's sSFR remains constant over ~0.6-0.8 Gyr
    Stated in §3.3 and used to predict baseline stellar mass for f_sb; only qualitatively justified and explicitly fails for GADGET-3 and GADGET-4.
  • domain assumption Very minor mergers (1:100<μ<1:10) contribute negligibly to SFR changes compared to the target merger
    Assumed in §4.3; the authors themselves find a counterexample in Appendix B where a μ=0.032 merger may trigger the GADGET-3/4 pre-merger starburst.
  • domain assumption The nine CosmoRun simulations differ essentially only in hydro solver and stellar feedback; shared initial conditions, cosmology, cooling, and calibration make discrepancies attributable to feedback
    Foundation of the AGORA method (§2.1, §5); not tested with controlled feedback toggling, leaving code architecture as a potential confound.
  • domain assumption Numerical stochasticity and chaotic divergence are subdominant to feedback-type differences
    Explicitly neglected in §4.3 (second caveat), citing Keller et al. 2019 where identical runs vary by a factor of two in stellar mass. One realization per code.
  • domain assumption The subgrid star formation recipe dρ*/dt = ε ρ_gas / t_ff with n_H > 1 cm^-3 is an adequate description of star formation
    Standard but unproven subgrid model shared by all codes (§2.1).
  • standard math WMAP7/9+SNe+BAO cosmological parameters and MUSIC initial conditions are the correct background
    Input cosmology from Komatsu et al. 2011 and Hinshaw et al. 2013 (§2.1).

reviewed 2026-08-01 · how reviews work

0 comments
Cite this review

Pith. "Pith review of The AGORA High-resolution Galaxy Simulations Comparison Project. IX - Part 1: Effects of a Major Galaxy Merger on Star Formation of a Milky Way-mass Galaxy Progenitor." pith.science (2026). https://pith.science/paper/LD5TOEKE

@misc{pith2026260721709,
  author       = {Pith},
  title        = {Pith review of: The AGORA High-resolution Galaxy Simulations Comparison Project. IX - Part 1: Effects of a Major Galaxy Merger on Star Formation of a Milky Way-mass Galaxy Progenitor},
  year         = {2026},
  howpublished = {\url{https://pith.science/paper/LD5TOEKE}},
  note         = {Machine review of arXiv:2607.21709}
}
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abstract

Given their highly nonlinear dynamics and sensitivity to initial conditions, galaxy mergers are a compelling area to conduct a simulation code comparison. We perform a comparative study of a major galaxy merger at $z \approx 4.5$ in cosmological zoom-in hydrodynamic simulations of a Milky Way-mass galaxy progenitor. The comparison employs the AGORA CosmoRun suite of nine well-calibrated, state-of-the-art numerical codes, each adopting a different stellar feedback scheme. We find that the evolution of the star formation rate (SFR) during the interaction is strongly shaped by the stellar feedback type. Using kinetic feedback in the feedback model drives a pronounced merger-induced starburst that starts to subside before coalescence; using thermal feedback without kinetic feedback yields prolonged SFR growth even after coalescence; and using delayed cooling or radiation pressure results in highly fluctuating SFR. Tracking gas particles in particle-based codes reveals that kinetic feedback facilitates gas inflow from the secondary galaxy onto the primary galaxy between the first periapsis and apoapsis, thus producing an earlier and more prominent starburst. In contrast, thermal feedback, augmented by superbubble or delayed-cooling feedback, suppresses gas cooling, creates a more extended gas distribution, and hinders strong starbursts during the merger. We also observe an inverse correlation between burst fraction and pre-merger gas fraction that is independent of feedback models. Overall, these results highlight the sensitivity of simulated galaxy mergers' star formation response to stellar feedback prescriptions. This study indicates that galaxy mergers may serve as a good testbed for stellar feedback processes in cosmological simulations.

Figures

Figures reproduced from arXiv: 2607.21709 by Alessandro Lupi, Anna Genina, Avishai Dekel, Boon Kiat Oh, Daniel Ceverino, H\'ector Vel\'azquez, Hyeonyong Kim, Ikkoh Shimizu, Ji-Hoon Kim, Joel R. Primack, Johnny W. Powell, Kentaro Nagamine, Kirk S. S. Barrow, Minyong Jung, Oscar Agertz, Pablo Granizo, Ram\'on Rodr\'iguez-Cardoso, Renyue Cen, Santi Roca-F\`abrega, The Agora Collaboration, Thinh Huu Nguyen, Thomas R. Quinn, Tom Abel, Weiguang Cui, Yuri Oku, Yves Revaz.

Figure 1
Figure 1. Figure 1: The merger history of the main halo (dashed black line) when the target merger happens at z ≈ 4.5. The subhalos are shown by solid lines and coloured by their DM mass ratio with respect to the main halo. For clearer vi￾sualization, we only plot subhalos with µDM > 0.005 that form outside the main halo and then merge with it within the plotting period. The target merger (µDM > 0.45) clearly appears in all n… view at source ↗
Figure 2
Figure 2. Figure 2: The orbital trajectory of the secondary galaxy relative to the primary during the target merger. The time axis is set to zero at the time of the first periapsis. The dis￾tance is computed by using the top 10%-bound star particles (stellar cores) from both galaxies at the beginning of infall. Notably for this merger, mesh-based codes predict a larger first-apoapsis distance compared to particle-based codes.… view at source ↗
Figure 3
Figure 3. Figure 3: Left: The four merger stages in our analysis: infall stage, passage stage, coalescence stage, and post-coalescence stage (or post-merger stage). The orbital trajectory of RAMSES’s target merger is used as an example. Right: The duration of the target merger in each code, from the beginning of the infall stage to the end of the coalescence stage. The vertical coloured lines separate the merger timescale int… view at source ↗
Figure 4
Figure 4. Figure 4: The evolution of the primary galaxy’s stellar mass, SFR, gas mass, star-forming gas mass (nH > 1 cm−3 ), and gas mass fraction, within 1 Gyr after the beginning of the infall. The names of codes with kinetic feedback are labeled in blue, the asterisk sign (*) denotes codes with delayed cooling and/or radiation pressure feedback, and the dagger sign (†) denotes codes with superbubble feedback. The gas prope… view at source ↗
Figure 5
Figure 5. Figure 5: The gas phase plot showing the density-temperature distribution of all gas elements within the primary halo’s convex hull at different times in the merging interaction. From top to bottom, we show the phase plots at tstart, at the end of the infall stage, at the end of the first passage stage (tmax), and at the timestep 0.6 Gyr after the first passage ("Cls/Post-cls"). For all codes but GEAR, this timestep… view at source ↗
Figure 6
Figure 6. Figure 6: Similar to [PITH_FULL_IMAGE:figures/full_fig_p013_6.png] view at source ↗
Figure 7
Figure 7. Figure 7: Tracking the gas particles from the pre-infall secondary halo that turn into star particles within ≈ 1 Gyr after tstart. The plot origin (red cross) is at the primary galaxy’s centre. Top row: the trajectories of each gas particle, coloured by elapsed time since tstart. The scatter points show where gas particles turn into star particles, with colours denoting the star formation time relative to tstart. Mi… view at source ↗
Figure 8
Figure 8. Figure 8: The time evolution of total mass (solid lines) and total radial momentum (dashed lines) of pre-star gas parti￾cles from the secondary galaxy with vr < 0. We focus this plot on the first passage stage and on gas within a 20-kpc radius from the primary galaxy’s centre, as the starbursts in codes with kinetic feedback begin in this stage and within that radius (first row of [PITH_FULL_IMAGE:figures/full_fig_… view at source ↗
Figure 9
Figure 9. Figure 9: The stellar mass (top row), SFR (middle row), and sSFR (bottom row) of the main galaxy before and shortly after the infall of the target merger. The vertical grey band represents the range of tstart in all nine codes. Except for GADGET-3 and GADGET-4, the SFR and sSFR in the other codes remain relatively low and stable right before the target merger, allowing us to reliably calculate the baseline sSFR and … view at source ↗
Figure 10
Figure 10. Figure 10: The sSFR (top row), stellar mass (bottom row, solid coloured line), and SFR (bottom row, gray solid line) of the primary galaxy, computed after excluding all stars that are at any time more bound to the secondary galaxy than the primary. The constant baseline sSFR (the sSFR assuming that the main galaxy evolves in isolation) is computed as the lowest sSFR over the 100-Myr period before the target merger’s… view at source ↗
Figure 11
Figure 11. Figure 11: The relationship between the burst fractions (fsb) and the system’s gas fraction (fgas, left) as well as the total mass ratio (µtotal, right). The R 2 value of a simple linear regression is shown for each subplot. We find that the burst fraction is negatively correlated with the gas fraction and very weakly correlated with the total mass ratio. At sufficiently small fgas, however, fsb may also be suppress… view at source ↗
Figure 12
Figure 12. Figure 12: The time evolution of the variables used to define coalescence in Equation 1. From top to bottom, the rows show the ratio between the distance between the two galaxies and the primary galaxy’s R200c radius, the relative velocity between the two galaxies, the velocity dispersion of the primary (solid lines) and secondary galaxy (dotted lines), the ratio between the relative velocity magnitude and the veloc… view at source ↗
Figure 13
Figure 13. Figure 13: The gas mass (first row), gas metallicity (sec￾ond row), fast-collapsing gas mass (third row), and average collapse time of the fast-collapsing gas (fourth row) within the main halo’s convex hull before the target merger. The vertical grey band represents the range of the target merger’s tstart across the nine codes. A fast-collapsing gas element is defined as one with a negative radial velocity and a col… view at source ↗
Figure 14
Figure 14. Figure 14: The gas density and gas metallicity projection plots, overlaid with HASKAP PIE’s non-spherical halos, showing the very minor merger (mass ratio ≈ 3:100, indicated by the red boundary) that may cause the z ≈ 6 starburst of GADGET-3 (top row) and GADGET-4 (bottom row) before the target merger. The white boundary marks the main halo. Two timesteps are shown for each code: one approximately at the infall and … view at source ↗
Figure 15
Figure 15. Figure 15: The CHANGA’s delayed starburst that happens more than 500 Myr after coalescence. Even though this burst is delayed, it is the largest burst due to the target merger across all simulations. The two dashed black lines mark the burst period that will be used to plot [PITH_FULL_IMAGE:figures/full_fig_p028_15.png] view at source ↗
Figure 16
Figure 16. Figure 16: The trajectories and thermal evolution of gas particles that form stars during the merger timescale (top row) and during the delayed starburst (bottom row) in CHANGA. The left and right columns show the same type of plots as the top and middle rows of [PITH_FULL_IMAGE:figures/full_fig_p029_16.png] view at source ↗

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This paper was first reviewed by deepseek-v4-flash on August 1, 2026.