Pith. sign in

REVIEW 4 major objections 4 minor 1 cited by

Superfast amplification and superfast nonlinear saturation of perturbations as the mechanism of turbulence

T0 review · 4 major / 4 minor · reviewed 2026-08-14 · deepseek-v4-flash

Pith's one-line read This paper reports that fully developed turbulence amplifies initial perturbations according to $e^{\sigma\sqrt{Re}\sqrt{t}+\sigma_1 t}$ — faster than exponential — and that direct numerical simulations up to Reynolds number 6210 confirm…

desk verdict Real DNS effort and a legitimate visual check of the superfast amplification idea, but the confirmation claim outruns the evidence: no error bars, an unresolved Re^0.38 vs √Re ambiguity in the paper's own Figure 3, and no test of the predicted constants. read the letter →

arxiv 1908.04838 v1 pith:PVTRADLI submitted 2019-08-13 physics.flu-dyn math.APnlin.CDphysics.ao-ph

classification physics.flu-dynmath.APnlin.CDphysics.ao-ph PACS 47.27.Gs05.45.-a47.27.ek
keywords turbulencemechanismsuperfastamplificationperturbationgrowthNavier-StokesequationsdirectnumericalsimulationLyapunovexponentnonlinearsaturationhomogeneousisotropic
verification ladder T0 review T1 audit T2 compute T3 formal

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 proposes a mechanism for fully developed turbulence: ever-present small perturbations are amplified superfast, growing as $e^{\sigma\sqrt{Re}\sqrt{t}+\sigma_1 t}$ in the early stage, and this growth drives a superfast nonlinear saturation. Such growth is faster than the exponential growth that characterizes deterministic chaos, matching the intuition that turbulence is more violent than chaos. The authors run direct numerical simulations of the three-dimensional Navier-Stokes equations in homogeneous isotropic turbulence, with resolution up to $2048^3$ and Reynolds numbers up to 6210, and report that the measured amplification follows the predicted $\sqrt{t}$ dependence in time and $\sqrt{Re}$ dependence in Reynolds number until nonlinear saturation. If correct, the result identifies the generation, development, and persistence of turbulence with this superfast amplification rather than with classical Lyapunov chaos.

What carries the argument

The load-bearing object is the explicit growth law $e^{\sigma\sqrt{Re}\sqrt{t}+\sigma_1 t}$, a prediction the authors derive from rigorous analysis of the Navier-Stokes equations and previously tested at low resolution. The verification mechanism is the Eulerian perturbation-tracking setup: a statistically steady turbulent field is duplicated, one copy has the forcing skipped for one time step, and the linear and nonlinear perturbation evolutions are followed by subtracting fields. Matching the measured amplification curves to the predicted $\sqrt{t}$ plateaus and the $\sqrt{Re}$ scaling at fixed $0.3T_0$ is what carries the confirmation. The relation $\sigma_1=(\sqrt{e}/2)\sigma$ fixes the relative size of the exponential correction term.

What would settle it

Run the same linear perturbation setup at Reynolds number around 6000 and fit $\ln(\delta u(t)/\delta u(0))/\sqrt{t}$ over $0.1T_0$ to $0.5T_0$; if the plateau tilts or drifts systematically with the fit window, or if the amplification at fixed $t=0.3T_0$ scales as $Re^{0.38}$ rather than $e^{c\sqrt{Re}}$, the predicted superfast law is not confirmed.

Watch

Extended reading notes

Core claim

On the paper's own terms, the central discovery is that perturbation amplification in fully developed homogeneous isotropic turbulence is governed by $e^{\sigma\sqrt{Re}\sqrt{t}+\sigma_1 t}$, with $\sigma_1=(\sqrt{e}/2)\sigma$, so the early-time amplification is much faster than exponential. The numerical evidence is the key claim: for Reynolds numbers 130, 805, 1450, and 2520, plots of $[\ln(\Delta(t)/\Delta(0))]t^{-1/2}$ show horizontal plateaus over an extended interval, indicating $e^{c\sqrt{t}}$ growth, and the amplification at $0.3T_0$ grows with Reynolds number roughly as $e^{c\sqrt{Re}}$. The same superfast growth is argued to lead naturally to superfast nonlinear saturation, so turbulence is generated, developed, and maintained by the relentless amplification of perturbations that already exist in the flow.

Load-bearing premise

The entire confirmation rests on the assumption that the time window over which the fits are made (roughly up to $0.3$–$0.5$ large-eddy turnover times) lies entirely inside the superfast $e^{c\sqrt{t}}$ regime, and that the constants $\sigma$ and $\sigma_1$, including $\sigma_1=(\sqrt{e}/2)\sigma$, are universal; if the window mixes growth regimes or the constant relation is wrong, the observed plateaus do not confirm the prediction.

Editorial extensions

If this is right

  • If the growth law is correct, fully developed turbulence amplifies perturbations several times faster than low-dimensional chaos, since chaos gives at most exponential growth.
  • Predictability windows shrink superfast: errors grow like $e^{c\sqrt{t}}$, so the time to reach a given error level scales roughly as $(\text{error}/\sigma\sqrt{Re})^2$, much shorter than in exponential growth.
  • Nonlinear saturation time drops as Reynolds number rises, so higher-Re flows saturate perturbations sooner, consistent with the observed violence of developed turbulence.
  • The authors state the theory should guide turbulence engineering and ensemble weather forecasting, where initial-condition uncertainty must be tracked.

Reading between the lines

Editorial extensions of the paper, not claims the author makes directly.

  • A natural testable extension is to measure the finite-time Lyapunov exponent $\Lambda(t)=\ln(\delta u(t)/\delta u(0))/t$; the superfast law predicts $\Lambda(t)\sim \sigma\sqrt{Re}/\sqrt{t}$ at early times, so the standard long-time Lyapunov exponent may not exist or may be dominated by the $\sigma_1$ term.
  • The predicted universality of $\sigma$ and $\sigma_1$ could be checked by varying the forcing band $k_f$ and the initial perturbation band; the paper fixes $k_f=2.5$ and injects the perturbation in that band, so it does not test whether the constants are truly universal.
  • If the $\sqrt{Re}$ scaling holds up to very high Reynolds numbers, then Kolmogorov-based dimensional estimates of Lyapunov exponents need revision, because the relevant time scale is the combination $1/(\sigma^2 Re)$ from the superfast term rather than the Kolmogorov time.
Share X Bluesky LinkedIn Reddit HN

Editorial analysis

A structured set of objections, weighed in public.

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

Referee Report

4 major / 4 minor

Summary. The manuscript reports a numerical verification of the authors' earlier prediction that the maximal amplification of perturbations in fully developed homogeneous isotropic turbulence grows as e^{σ√Re√t + σ1 t}, i.e. faster than exponential, with σ1 = (√e/2)σ. Direct numerical simulations of forced Navier-Stokes turbulence at resolutions up to 2048^3 and Reynolds numbers up to 6210 are used. The evidence is presented as: (i) in Figure 2, plots of [ln(Δ(t)/Δ(0))] t^{-1/2} versus t for four Reynolds numbers, whose horizontal segments are interpreted as demonstrating the √t growth in the exponent; and (ii) in Figure 3, a plot of ln(Δ(0.3T0)/Δ(0)) versus Re with a fit to ~√Re, alongside a competing Re^0.38 fit. The paper concludes that superfast amplification and superfast nonlinear saturation of ever-present perturbations constitute the mechanism for generation, development, and persistence of turbulence.

Significance. If the predicted law (1) were convincingly confirmed and the constants σ and σ1 quantitatively matched, this would be a significant result: it would place turbulence in a regime more violent than low-dimensional chaos, contradicting Ruelle's exponential Lyapunov scaling, and would offer a mechanistic explanation for turbulence persistence. The computational effort is a genuine strength: DNS up to 2048^3 with Re up to 6210 is a substantial campaign, and the manuscript carefully distinguishes nonlinear amplitude Δ(t) from linear amplitude δu(t), an important conceptual point. However, the verification as presented is qualitative rather than quantitative. The confirmation claims rest on visual plateaus in Figure 2 over less than one large-eddy turnover time, and on a single-time Reynolds-number plot in Figure 3 that includes a visually comparable Re^0.38 fit, with no error bars, residuals, or model-selection statistics. Because the central claim is precisely a specific functional form with specific constants, the lack of quantitative fitting is a load-bearing gap. The result may well be correct, but the evidence in this manuscript does not yet establish it.

major comments (4)
  1. [Figure 2 and surrounding text] The evidence for the e^{c√t} behavior is only the visual flatness of [ln(Δ(t)/Δ(0))] t^{-1/2} over roughly 0 ≤ t ≤ 1 (about half a large-eddy turnover time, since T0 ≈ 2). No error bars, no goodness-of-fit measure, and no comparison against alternative growth laws such as e^{λt} or t^p with p near 1/2 are provided. Over such a short window, many functional forms produce nearly flat segments, especially after excluding the t→0 region. The paper should report quantitative fits to log-amplitude versus t for each Re, with parameter uncertainties and a model-selection statistic (e.g., AIC or a chi-square ratio) that discriminates √t from exponential or other powers. Without this, the plateau observation does not by itself confirm the √t scaling.
  2. [Figure 3 and surrounding text] The Reynolds-number scaling is examined at a single time t = 0.3T0, and the figure itself displays two fits, one ~√Re and one ~Re^0.38. The text asserts that the data fit well with e^{c√Re}, but no residuals, parameter uncertainties, or statistical comparison between the two fits are given. Visually, the two curves are close over the plotted range, so the data do not discriminate the predicted √Re dependence from a slower power law. A quantitative fit with confidence intervals, or a plot of ln(amplification) versus √Re with the Re^0.38 curve and residuals, is needed to support the central claim.
  3. [Equations (1), (5)-(6) and Figures 2-3] Prediction (1) is for the linear amplification δu(t), while the verification plots use the nonlinear amplitude Δ(t). The paper states that during the early stage the linear amplification is a good approximation of the nonlinear one, but no quantitative evidence is given that t = 0.3T0 is within the pre-saturation linear regime for all Reynolds numbers shown. Since saturation occurs sooner at higher Re (as the text itself notes), the high-Re points in Figure 3 may already be in the nonlinear saturation regime, in which case the observed amplitude reflects saturation rather than superfast linear growth. The authors should show, for each Re, the divergence time between δu(t) and Δu(t) and confirm that the fitting window lies before it, or present linear-amplification data directly.
  4. [Equation (1) and the constants σ, σ1] The prediction (1), including the relation σ1 = (√e/2)σ, is imported from the authors' prior work [19-22] and is not rederived in this manuscript. The numerical tests, however, use a generic constant c and never compare the fitted coefficient with the predicted σ or σ1. Consequently, the verification is only of the functional form with free parameters, not of the quantitative prediction. To claim confirmation, the manuscript should either derive the constants within the present framework or explicitly test whether the measured prefactor matches the predicted value within uncertainties. As it stands, the functional-form test alone is a weaker statement than the paper's conclusion.
minor comments (4)
  1. [Introduction (paragraph 1)] There are typographical errors: 'meterology' should be 'meteorology' and 'undertaining' should be 'understanding'.
  2. [References] Reference [23] is cited as an arXiv preprint (arXiv:1702.02993, 2018); if it has been published in a journal, the published version should be cited, and if not, the manuscript should indicate that the verification builds on an unpublished preprint.
  3. [Figure 2 caption and text] The phrase 'Except in t→0+ limit' is vague: the excluded region is not precisely defined. For reproducibility, the authors should specify the time interval over which the fits are performed and how the initial transient is excluded.
  4. [Figure 3] The figure uses both a dashed curve and a red/grey curve but the caption does not explicitly state which is which; adding labels directly in the figure or a clear legend would improve clarity.

Circularity Check

2 steps flagged · score 6.0 of 10

Prediction (1) is imported from the authors' own prior work and then "confirmed" by fits with a generic constant c, leaving the predicted constants σ and σ1 untested.

  1. self citation load bearing [Introduction, around Eq. (1)]
    "We predicted that the maximal amplification of perturbations in fully developed turbulence is faster than exponential [19]-[2], eσ√Re√t+σ1t, (1) where σ and σ1 are two positive constants, σ1=√e 2σ. Our prediction is based on rigorous analysis on the Navier-Stokes equations [19]-[22]."

    The analytical prediction (1), including the constant relation σ1=√e/2 σ, is not derived in this paper; it is delegated to refs [19]-[22], which are the authors' own prior work (Y. Li, and Inci and Y. Li). The subsequent numerical verification never recovers σ or σ1, so the cited self-work is load-bearing for the claim that (1) is an analytical prediction. The prediction is therefore not independently established within this manuscript.

  2. fitted input called prediction [Discussion of Figures 2 and 3]
    "Except in t→0+ limit, we clearly observed the amplifications of ec√t in t as we predicted in (1). We use c to represents a generic constant in this paper. The data fit well with ec√Re as we predicted in (1)."

    The verification replaces the fixed constants σ and σ1 of prediction (1) with a fitted generic constant c and then calls the resulting curve fit a confirmation of (1). Because c is free, the fit cannot test the predicted constants or the relation σ1=√e/2 σ. Figure 3 itself shows a comparable ~Re^0.38 fit, with no residuals, error bars, or model-selection statistics, so the e^{c√Re} shape is not uniquely identified. The 'predicted' scaling is thus in part determined by the fitted curve rather than by an independent parameter-free test.

full rationale

The paper performs a large and real DNS campaign, and the t-dependence plateau plots do provide some independent evidence for a growth shape of the form e^{c√t}. However, the specific analytical claim, prediction (1) with constants σ and σ1 and the relation σ1=√e/2 σ, is not re-derived here; it is imported from the authors' own prior references. The numerical 'verification' then tests only the functional form with a generic fitted constant c, and the Reynolds-number plot also displays both √Re and Re^0.38 fits without model-selection statistics. Thus the confirmation is partly a curve fit with a free parameter rather than a parameter-free test of the cited prediction. Because the data could in principle have failed to show the plateau, the work is not fully circular, but the central claim's distinguishing constants are never confronted with the simulation data, so a score of 6 reflects substantial partial circularity.

Assumptions & free parameters 2 free parameters · 3 assumptions · 0 invented entities

The central prediction (1) is assumed from the authors' prior work, the near-t=0 numerical data is excluded by fiat, and the L2 energy norm is chosen as the amplification measure; none of these are independently justified in this paper.

free parameters (2)
  • sigma (σ) in the amplification exponent = not estimated in this paper
    The predicted growth law (1) contains σ as a positive constant. The numerics only verify the functional form e^{c√t} with a generic constant c; σ is never measured or predicted independently.
  • sigma1 (σ1) with σ1 = (√e/2)σ = not estimated
    The linear-in-t term in (1) is asserted to have the coefficient σ1 = (√e/2)σ, but this paper does not verify the t-linear term or the relation; it is an unexamined part of the prediction.
assumptions (3)
  • domain assumption The analytical prediction (1), e^{σ√Re√t + σ1 t} with σ1=(√e/2)σ, from Li's prior rigorous analysis [19-22], is correct.
    The paper cites [19-22] for the prediction and does not rederive it; the numerical 'confirmation' tests this assumed functional form.
  • domain assumption The t→0+ behavior of the DNS perturbation is numerically unreliable and can be discarded.
    Stated in the text near Figure 2: 'in the t→0+ limit, numerical resolution can never be sufficient and generates false results as shown by an explicit example in [23]'. This exclusion shapes the verification window.
  • domain assumption The energy norm (5)-(6) is the appropriate measure of perturbation amplification.
    The paper defines amplification through the L2 energy norm of the perturbation and uses it for the fits; no alternative norms or error measures are considered.

how reviews work

0 comments
Cite this review

Pith. "Pith review of Superfast amplification and superfast nonlinear saturation of perturbations as the mechanism of turbulence." pith.science (2026). https://pith.science/paper/PVTRADLI

@misc{pith2026190804838,
  author       = {Pith},
  title        = {Pith review of: Superfast amplification and superfast nonlinear saturation of perturbations as the mechanism of turbulence},
  year         = {2026},
  howpublished = {\url{https://pith.science/paper/PVTRADLI}},
  note         = {Machine review of arXiv:1908.04838}
}
abstract

Ruelle predicted that the maximal amplification of perturbations in homogeneous isotropic turbulence is exponential $e^{\sigma \sqrt{Re} t}$ (where $\sigma \sqrt{Re}$ is the maximal Liapunov exponent). In our earlier works, we predicted that the maximal amplification of perturbations in fully developed turbulence is faster than exponential $e^{\sigma \sqrt{Re} \sqrt{t} +\sigma_1 t}$. That is, we predicted superfast initial amplification of perturbations. Built upon our earlier numerical verification of our prediction, here we conduct a large numerical verification with resolution up to $2048^3$ and Reynolds number up to $6210$. Our direct numerical simulation here confirms our analytical prediction. Our numerical simulation also demonstrates that such superfast amplification of perturbations leads to superfast nonlinear saturation. We conclude that such superfast amplification and superfast nonlinear saturation of ever existing perturbations serve as the mechanism for the generation, development and persistence of fully developed turbulence.

Figures

Figures reproduced from arXiv: 1908.04838 by the authors.

Figure 2
Figure 2. FIG. 2: The nonlinear amplifications of perturbations for dif [PITH_FULL_IMAGE:figures/full_fig_p003_2.png] view at source ↗
Figure 1
Figure 1. FIG. 1: The divergence of the linear amplification and the [PITH_FULL_IMAGE:figures/full_fig_p003_1.png] view at source ↗
Figure 3
Figure 3. FIG. 3: The Reynolds number dependence of the nonlinear [PITH_FULL_IMAGE:figures/full_fig_p003_3.png] view at source ↗

Discussion (0). Continue with ORCID to comment.

Forward citations

Cited by 1 Pith paper

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

  1. Fluctuations of Lyapunov Exponents in homogeneous and isotropic turbulence

    physics.flu-dyn 2019-09 conditional novelty 6.0 of 10

    Finite-time Lyapunov exponents from DNS are robust, quickly converging measures of chaos in homogeneous isotropic turbulence, and a Reynolds-dependent dissipation correction resolves the prior alpha discrepancy.

Reference graph

Works this paper leans on

27 extracted references · 22 canonical work pages · cited by 1 Pith paper

  1. [1]

    Li, Dynamics of PDE 10, 379 (2013)

    Y. Li, Dynamics of PDE 10, 379 (2013)

  2. [2]

    Li, Notices of the AMS 65, 1255 (2018)

    Y. Li, Notices of the AMS 65, 1255 (2018)

  3. [3]

    Ruelle and F

    D. Ruelle and F. Takens, Comm. Math. Phys. 20, 167 (1971)

  4. [4]

    T. Bohr, M. H. Jensen, G. Paladin, and A. Vulpiani, Dynamical Systems Approach to Turbulence (Cambridge University Press, 2005)

  5. [5]

    Kawahara and S

    G. Kawahara and S. Kida, J. Fluid Mech. 449, 291 (2001)

  6. [6]

    Viswanath, J

    D. Viswanath, J. Fluid Mech. 580, 339 (2007)

  7. [7]

    J. F. Gibson, J. Halcrow, and P. Cvitanovi´ c, J. Fluid Mech. 611, 107 (2008)

  8. [8]

    van Veen and G

    L. van Veen and G. Kawahara, Phys. Rev. Lett. 107, 114501 (2011)

Show all 27 references
  1. [9]

    Kawahara, M

    G. Kawahara, M. Uhlmann, and L. van Veen, Ann. Rev. Fluid Mech. 44, 203 (2012)

  2. [10]

    Kreilos and B

    T. Kreilos and B. Eckhardt, Chaos 22, 047505 (2012)

  3. [11]

    Lucas and R

    D. Lucas and R. Kerswell, Phys. Fluids 27, 045106 (2015)

  4. [12]

    Ruelle, Phys

    D. Ruelle, Phys. Lett. 72A, 81 (1979)

  5. [13]

    Crisanti, M

    A. Crisanti, M. H. Jensen, A. Vulpiani, and G. Paladin, Phys. Rev. Lett. 70, 166 (1993)

  6. [14]

    Aurell, G

    E. Aurell, G. Boffetta, A. Crisanti, G. Paladin, and A. Vulpiani, Phys. Rev. Lett. 77, 1262 (1996)

  7. [15]

    Aurell, G

    E. Aurell, G. Boffetta, A. Crisanti, G. Paladin, and A. Vulpiani, J. Phys. A 30, 1 (1997)

  8. [16]

    Boffetta, M

    G. Boffetta, M. Cencini, M. Falcioni, and A. Vulpiani, Phys. Rep. 356, 367 (2002)

  9. [17]

    Boffetta and S

    G. Boffetta and S. Musacchio, Phys. Rev. Lett. 119, 054102 (2017)

  10. [18]

    Berera and R

    A. Berera and R. Ho, Phys. Rev. Lett. 120, 024101 (2018)

  11. [19]

    Li, Electronic Journal of Differential Equations 2014, 104 (2014)

    Y. Li, Electronic Journal of Differential Equations 2014, 104 (2014)

  12. [20]

    Li, Nonlinearity 30, 1097 (2017)

    Y. Li, Nonlinearity 30, 1097 (2017)

  13. [21]

    Inci, Dynamics of Partial Differential Equations 12, 97 (2015)

    H. Inci, Dynamics of Partial Differential Equations 12, 97 (2015)

  14. [22]

    Inci and Y

    H. Inci and Y. Li, arXiv preprint, arXiv:1805.06507 (2018)

  15. [23]

    Feng and Y

    Z. Feng and Y. Li, arXiv preprint, arXiv:1702.02993 (2018)

  16. [24]

    S. R. Yoffe, Ph.D. Thesis, University of Edinburg (2012), arXiv: 1306.3408

  17. [25]

    Machiels, Phys

    L. Machiels, Phys. Rev. Lett. 79, 3411 (1997)

  18. [26]

    Kaneda and T

    Y. Kaneda and T. Ishihara, J. of Turbulence 7, N20 (2006)

  19. [27]

    M. F. Linkmann and A. Morozov, Phys. Rev. Lett. 115, 134502 (2015)

Pith tools

Reviewed August 14, 2026 · model on record in the stance chip above.