Pith. sign in

REVIEW 3 major objections 5 minor 79 references

Spontaneous stochasticity and anomalous dissipation in collapsing wave turbulence

T0 review · 3 major / 5 minor · reviewed 2026-08-01 · deepseek-v4-flash

Pith's one-line read A focusing fractional NLS equation with finite-time collapse is shown to be spontaneously stochastic in the vanishing-regularization limit: after blowup the inviscid limit is a probability law, not a single solution.

desk verdict Numerically suggestive case for spontaneous stochasticity in collapsing wave turbulence; the main gap is unproven viscous regularization at the exact simulated parameters, and the scaling agreement is partly a consistency check. read the letter →

arxiv 2607.18788 v1 pith:XHZWGSMT submitted 2026-07-21 physics.flu-dyn

classification physics.flu-dyn
keywords spontaneousstochasticitywavecollapsefractionalnonlinearSchrödingerequationanomalousdissipationvanishing-regularizationlimitpost-blowupnonuniquenessturbulenceuncertaintyproduction
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

After a finite-time wave collapse, the focusing fractional NLS equation has no unique classical solution, and this paper provides numerical evidence that the vanishing-regularization limit is genuinely stochastic rather than deterministic. Two collapse-arresting regularizations, viscous diffusion and nonlinear saturation, both recover the same smooth inviscid solution before collapse and both restore finite-time blowup as the regularization vanishes, but they select different post-blowup continuations: the viscous limit dissipates mass at a finite rate while the saturating limit conserves it. Within each regularization, the limit still fails to select a unique continuation: arbitrarily small differences in the regularization parameter or in the initial condition produce order-one post-blowup differences. The paper therefore argues that the singular inviscid limit should be described by a probability law, with collapse events acting as localized sources of uncertainty, and identifies collapsing wave turbulence as a dispersive, potentially table-top optical setting for this phenomenon.

What carries the argument

The carrying object is the one-dimensional focusing fractional NLS equation i∂tψ = Λ^αψ − |ψ|^2ψ on the torus, with Λ^α = |k|^α and α=1/2, a dispersive wave-turbulence model of the Majda–McLaughlin–Tabak type. The argument uses two regularizations, viscous diffusion (ν-fNLS) and saturating nonlinearity (σ-fNLS), whose vanishing-parameter limits are compared through mass gaps and through coarse-grained fluctuation-mass budgets. The central mechanism is wave collapse: the vanishing-regularization limit develops amplitude ∝(t⋆−t)^−1/2 and core width ∝(t⋆−t)^{1/α}, which makes the nonlinear commutator in the filtered mass balance non-vanishing and amplifies infinitesimal parameter or initial-con

What would settle it

A single fixed small ν for which the α=1/2 viscous solution on the torus blows up at finite time, or a numerical run showing that the mass gap G_{ν1,ν2}(t) decays to zero for t>t⋆ as ν1,ν2→0, would overturn the nonselection claim.

Watch

Extended reading notes

Core claim

At dispersion exponent α=1/2 and initial mass 25, the focusing fractional NLS with cubic nonlinearity undergoes wave collapse at a finite time t⋆ ≃ 0.4613. For fixed viscosity ν or saturation σ the regularized equations are globally well posed (proved for saturation; for viscosity proved for α>1/2 and supported by simulations at α=1/2), and both regularizations converge to the same smooth inviscid solution for t<t⋆. After t⋆, the two limits separate: the viscous limit has a finite mass-dissipation rate, hence anomalous mass dissipation, while the saturating limit conserves mass. Moreover, the mass gaps between two nearby regularizations and between two nearby initial conditions remain strict

Load-bearing premise

The claim rests on the assumption that viscous diffusion prevents finite-time blowup exactly at α=1/2 on the torus; the paper proves this only for α>1/2 on the whole line, and at α=1/2 it relies on simulations suggesting that no blowup occurs.

Editorial extensions

If this is right

  • The viscous regularization predicts a dispersive analogue of anomalous dissipation: a finite inviscid mass-loss rate after collapse, despite exact mass conservation in the unregularized equation.
  • Because the viscous and saturating limits are different weak continuations, one dissipative and one conservative, the post-blowup mass balance is not fixed by the inviscid equation alone.
  • Neither regularization provides a deterministic selection rule: the mass gap between two vanishing viscosities or saturations, and the gap from two vanishing initial perturbations, both stay positive after t⋆.
  • If the limit is statistical, collapse events are local sources of randomness: the variance of fluctuations and the uncertainty flux concentrate in collapse cores and persist as ν,σ→0.
  • Saturating regularization, a model of nonlinear optical media, shows the same qualitative behavior, making nonlinear optics a candidate experimental testbed for spontaneous stochasticity.

Reading between the lines

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

  • If the collapse-driven mechanism extends to other focusing dispersive equations, then two-dimensional cubic NLS near the mass-critical case may show a similar statistical singular limit, though with a different collapse law; this is an extrapolation beyond the paper.
  • The viscous mass defect suggests an Onsager-style regularity threshold for mass conservation in fractional NLS: below a critical L4-type control, weak continuations may carry a nontrivial mass flux, analogous to convex-integration flexibility in fluids.
  • The heuristic scaling exponents, −5 for the ν-derivative response and −3 for the σ-derivative response, are sharp quantitative predictions that could be tested analytically or with higher-resolution runs; confirming them would turn numerical nonselection into a more refined statistical law.
  • The saturating case is explicitly qualitative: whether the σ→0 branch reaches a true asymptotic regime remains open, and future work with smaller σ and improved ensemble convergence is needed to close that gap.
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

3 major / 5 minor

Summary. The paper studies a focusing fractional nonlinear Schrödinger equation (fNLS) with α=1/2 on the torus, a one-dimensional dispersive model exhibiting finite-time wave collapse. Two regularizations are considered: viscous diffusion (ν-fNLS) and nonlinear saturation (σ-fNLS). The author provides numerical evidence that, as the regularization parameter vanishes, both recover the same smooth pre-blowup solution; that after blowup the viscous limit dissipates mass while the saturating limit conserves it; and that within each regularization class the vanishing-regularization limit does not select a unique continuation: mass gaps between solutions with different parameters or with slightly randomized initial conditions remain finite after blowup. A coarse-grained fluctuation budget is used to argue that collapse events act as localized sources of uncertainty production. The paper concludes that the inviscid limit is spontaneously stochastic in the sense of a non-Dirac statistical law.

Significance. If the central claims hold, the paper extends spontaneous stochasticity from fluid turbulence to dispersive wave systems and offers a concrete numerical/experimental testbed. It also provides a clean demonstration of anomalous mass dissipation in a fractional NLS setting, and the T1–T3 triptych is a useful organizing framework. Strengths include a clearly described numerical setup, direct diagnostics (mass gaps, variance budgets) rather than reliance on a fitted theory, a rigorous non-blowup proof for the saturating regularization, and honest caveats about the σ-results. The main weaknesses are that the central conclusions are not backed by convergence certificates and that one load-bearing regularity claim is unproved in the exact simulated regime.

major comments (3)
  1. [§IV.B, Appendix A 2, Eq. (8)] The abstract claims 'Both regularizations prevent blowup at fixed parameter,' but the viscous non-blowup bound in Eq. (8) is proved only for α>1/2 on R. All numerical runs use α=1/2 on the torus; the text concedes 'our simulations nevertheless suggest that viscous diffusion still prevents finite-time blowup.' Since T2 requires global well-posedness for every fixed ν, the post-blowup viscous data are interpreted as strong solutions of (ν-fNLS). This missing proof or systematic numerical certification in the exact regime is load-bearing. Please provide a rigorous bound for α=1/2 on T, or a resolution-converged demonstration of boundedness of H_L for fixed ν over long times, and soften the abstract accordingly.
  2. [§VI.C and §VII.C, Figs. 3 and 4] The central quantitative claim is that G_{ν1,ν2}, eG_ν, and M_{ν,χ} have strictly positive limits as ν→0. The paper shows curves for a few discrete values and states that they 'remain finite' or 'do not collapse to zero.' No extrapolation in ν, no liminf estimate bounded away from zero, and no resolution study in N are provided. The local variances in Fig. 4 are admitted to 'still depend visibly on ν,' with accessible viscosities 'not sufficient to claim pointwise convergence.' A slow power-law decay would be consistent with the displayed data. Please supply quantitative lower bounds or convergence tests, or reframe the conclusions as finite-ν evidence.
  3. [§VII.A–B, definition (21) and Section II] The paper's own framework (Section II, T3) defines strong spontaneous stochasticity as convergence of pushforward laws to a non-Dirac probability measure. The paper explicitly does not reconstruct the limiting law and only studies the second moment M_{ε,χ}. Positive variance is necessary but not sufficient for a non-Dirac limiting law: the law may fail to converge, or its mass may concentrate without a limit. The abstract's 'better described in terms probability law' is therefore stronger than the evidence. Either provide evidence on the distribution (histograms, characteristic functions, tightness) or restrict the claims to 'anomalous fluctuations' and 'breakdown of deterministic selection.'
minor comments (5)
  1. [§V.A, Eq. (10) and Appendix C, Eq. (18)] The scaling prediction (18) is derived from the same self-similar collapse law (10) that was used to fit t_*; the observed 'excellent agreement' is therefore a consistency check rather than an independent validation. Appendix C also relies on the uncontrolled replacement of the linearized evolution by the direct Duhamel response. This should be stated more explicitly where (18) is discussed.
  2. [§VII.B, Eq. (28) vs Appendix E] Eq. (28) states a bound with ||Λ^γ ψ(s)||_{L^2}^2, γ>1/2, while Appendix E derives ||ψ(s)||_{H^r}^2 with r>1/2. Also, the appendix says the key closeness estimates 'can be achieved using standard Gronwall lemma and bootstrap argument that we do not detail here,' so the 'we prove' wording in the main text overstates the completeness of the proof.
  3. [§V.C] Typo: 'reamain' should be 'remain.'
  4. [§VI.C] The top panel of Fig. 3 is described qualitatively, but the caption does not specify how the zoom levels are chosen or whether the same spatial window is used for both viscosities. A short description of the normalization would improve reproducibility.
  5. [§VII.C] The statement that intermediate-scale fluxes are 'less sensitive' to the randomization mechanism is not quantified. Please provide a measure of spread (e.g., relative difference between χ=r and χ=i over the intermediate ℓ range).

Circularity Check

1 steps flagged · score 2.0 of 10

No structural circularity: central non-selection and variance results are direct numerical diagnostics; only the auxiliary scaling predictions (18)/(F1) reuse the same fitted collapse law.

  1. fitted input called prediction [Section V.A (blowup-time fit) and Section VI.C / Appendix C, Eq. (18); also Appendix F, Eq. (F1)]
    "The blowup time is estimated using the growth rate of the amplitude of the solution with viscous regularization at the smallest accessible viscosity. Postulating the inverse-square-root behavior (10), we then fit the blowup time. ... In Appendix C we indeed derive such singular behavior using heuristic arguments based on the self similar collapse assumption (10)"

    The same self-similar law (10) is used both to fit t* and to derive the predicted mass-gap scalings (18) and (F1); the numerical comparisons then use that same fitted t*. The agreement is therefore a consistency check of the ansatz rather than an independent prediction. This does not affect the central post-blowup observations (finite mass gaps and variance), which are direct diagnostics, but the scaling 'predictions' are partially self-referential.

full rationale

I find no structural circularity in the paper's central derivation chain. The main claims—that the two regularizations select different post-blowup continuations, that the viscous limit exhibits anomalous mass dissipation, that vanishing perturbations of the regularization parameter or initial condition produce finite post-blowup mass gaps, and that collapse cores are localized sources of uncertainty—are direct numerical diagnostics defined through equations (12), (14), (17) and (21), not outputs of a fitted theory. The only quasi-circular element is the auxiliary pre-blowup scaling: t* is fitted by assuming the inverse-square-root law (10), and the predicted mass-gap growth (18)/(F1) is derived from the same law, making the observed exponent agreement a consistency check rather than an independent prediction. This is a genuine but minor caveat and is not load-bearing for the central non-selection claim, which rests on the direct observation of finite G and variance after t*. The paper also leans on the author's own framework [12] for the measure-theoretic language and the triptych T1–T3, but this self-citation supplies definitions and interpretation, not the empirical evidence; no load-bearing uniqueness theorem is imported from it. Finally, the missing proof that viscous diffusion prevents blowup at alpha=1/2 on the torus (Section IV.B, Eq. (8)) is a real gap in the T2 leg, but it is an unproven assumption, not a circularity, and it does not make the derivation self-referential. Overall, the paper's central result is self-contained numerical evidence, with only the secondary scaling predictions showing mild fit/ansatz overlap.

Assumptions & free parameters 5 free parameters · 5 assumptions · 0 invented entities

The central numerical scenario rests on several unproved or only numerically supported assumptions, listed above; the main load-bearing one is the α=1/2 viscous regularization bound. No new physical entity is introduced; the 'uncertainty flux' and 'fluctuation field' are observables defined from existing quantities.

free parameters (5)
  • initial mass M[ψ0] = 25 (set via normalization factor Z)
    Chosen large enough to trigger several collapse events; all subsequent behavior depends on it.
  • initial spectral band (k1,k2) = (1,10)
    Ad hoc choice of the random Fourier superposition; different bands would change collapse locations and quantitative statistics.
  • quenched random realization {g_k} = not provided
    The realization is drawn once and used for all runs, but no seed or coefficients are given; quantitative results are realization-specific.
  • blowup time t⋆ = ≈0.4613
    Estimated by postulating (t⋆−t)^{-1/2} amplitude scaling and fitting t⋆ (Section V.A); used in all comparisons and heuristic exponents.
  • regularization sequences ν, σ = ν=10^{-5}..10^{-10}; σ=10^{-2.5}..10^{-5}
    Chosen for numerical accessibility; σ values are explicitly not in the asymptotic regime.
assumptions (5)
  • domain assumption Finite-time collapse occurs for focusing fNLS with α≤1 and large mass; for α=1/2 collapse is expected and used to define t⋆.
    Heuristic dimensional analysis in Section III and conjectured/verified behavior from [52]; no rigorous blowup proof for α=1/2.
  • domain assumption Self-similar collapse scaling ∥ψ∥∞∼(t⋆−t)^{-1/2}, L(t)∼(t⋆−t)^{1/α} (Eq. 10).
    Assumed from [52] for single-bump data; used to fit t⋆, derive Eq. (18), and interpret amplitude data (Section V.A, Appendix C).
  • ad hoc to paper Viscous regularization prevents blowup at α=1/2 on T.
    Appendix A 2 proves a bound only for α>1/2 on R; for α=1/2 the paper invokes simulations. This is load-bearing for T2.
  • domain assumption After collapse, fNLS admits weak solutions and nonuniqueness analogous to α=2 NLS [27,28].
    Global existence/nonuniqueness for the fractional focusing equation is stated as open in Section IV; the paper assumes the same flexibility to interpret post-blowup states.
  • domain assumption Ensemble estimates with M=5000 realizations capture low-order statistics.
    Appendix B 2 admits convergence of higher-order statistics is difficult; local σ statistics are not converged (Appendix F).

how reviews work

0 comments
Cite this review

Pith. "Pith review of Spontaneous stochasticity and anomalous dissipation in collapsing wave turbulence." pith.science (2026). https://pith.science/paper/XHZWGSMT

@misc{pith2026260718788,
  author       = {Pith},
  title        = {Pith review of: Spontaneous stochasticity and anomalous dissipation in collapsing wave turbulence},
  year         = {2026},
  howpublished = {\url{https://pith.science/paper/XHZWGSMT}},
  note         = {Machine review of arXiv:2607.18788}
}
read the original abstract

We study a focusing Majda--McLaughlin--Tabak type equation undergoing finite-time wave collapse. This singularity terminates the classical smooth solution and opens a post-blowup regime where infinitely many solutions may exist. To probe this nonunique regime, we regularize the dynamics either by viscous diffusion or by nonlinear saturation and study the corresponding vanishing-regularization limits. Both regularizations prevent blowup at fixed parameter and recover the same inviscid collapse as the parameter vanishes. Before collapse, they converge to the same smooth inviscid solution. After collapse, however, their limits differ. The viscous approximation undergoes anomalous mass dissipation whereas the saturating approximation remains conservative. Moreover, neither regularization selects a unique post-blowup solution. Vanishing perturbations of the regularization parameter or of the initial condition survive the singular limit and generate finite post-blowup uncertainty. This places collapsing wave turbulence in the setting of spontaneous stochasticity, where the inviscid limit is better described in terms probability law on inviscid solutions rather than deterministically. Scale-by-scale fluctuation budgets identify collapse events as localized sources of uncertainty production. While spontaneous stochasticity is usually associated with fluid turbulence, these results provide numerical evidence that it can be applied to a broader class of systems, including dispersive media in which experiments could be conducted.

Figures

Figures reproduced from arXiv: 2607.18788 by the authors.

Figure 1
Figure 1. FIG. 1: Space–time evolution of the modulus of the solutions for the two regularization mechanisms. Left: viscous regularization [PITH_FULL_IMAGE:figures/full_fig_p006_1.png] view at source ↗
Figure 2
Figure 2. FIG. 2: Top left: linear part of the Hamiltonian [PITH_FULL_IMAGE:figures/full_fig_p009_2.png] view at source ↗
Figure 1
Figure 1. In the viscous case, focusing of mass leads to locally extreme events of mass dissipation. In that regard, [PITH_FULL_IMAGE:figures/full_fig_p010_1.png] view at source ↗
Figures from the paper (4 more)
Figure 3
Figure 3. Figure 3: FIG. 3: Top row: amplitude of the viscous solution ( [PITH_FULL_IMAGE:figures/full_fig_p013_3.png]
Figure 4
Figure 4. Figure 4: FIG. 4: In each panel, dashed lines correspond to [PITH_FULL_IMAGE:figures/full_fig_p017_4.png]
Figure 5
Figure 5. Figure 5: FIG. 5: Lack of deterministic selection for the saturating regularization ( [PITH_FULL_IMAGE:figures/full_fig_p028_5.png]
Figure 6
Figure 6. Figure 6: FIG. 6: Same diagnostics as in Fig. 4, for the saturating regularization ( [PITH_FULL_IMAGE:figures/full_fig_p029_6.png]

Discussion (0). Continue with ORCID to comment.

Reference graph

Works this paper leans on

79 extracted references · 3 linked inside Pith

  1. [1]

    From the butterfly effect to spontaneous stochasticity in singular shear flows.Communications Physics, 3(1):122, 2020

    Simon Thalabard, J´ er´ emie Bec, and Alexei A Mailybaev. From the butterfly effect to spontaneous stochasticity in singular shear flows.Communications Physics, 3(1):122, 2020

  2. [2]

    Rayleigh–Taylor turbulence with singular nonuniform initial conditions.Physical Review Fluids, 3(9):092601, 2018

    Luca Biferale, Guido Boffetta, Alexei A Mailybaev, and Andrea Scagliarini. Rayleigh–Taylor turbulence with singular nonuniform initial conditions.Physical Review Fluids, 3(9):092601, 2018

  3. [3]

    Spontaneous stochasticity in the Armstrong–Vicol passive scalar

    Wandrille Ruffenach, Eric Simonnet, and Nicolas Valade. Spontaneous stochasticity in the Armstrong–Vicol passive scalar. arXiv preprint arXiv:2509.15683, 2025

  4. [4]

    Palmer, A

    T.N. Palmer, A. D¨ oring, and G. Seregin. The real butterfly effect.Nonlinearity, 27(9):R123, aug 2014

  5. [5]

    Rotunno and C

    R. Rotunno and C. Snyder. A Generalization of Lorenz’s Model for the Predictability of Flows with Many Scales of Motion. Journal of the Atmospheric Sciences, 65(3):1063–1076, 2008

  6. [6]

    Valade, S

    N. Valade, S. Thalabard, and J. Bec. Anomalous dissipation and spontaneous stochasticity in deterministic surface quasi- geostrophic flow.Annales Henri Poincar´ e, 25:1261–1283, 2024

  7. [7]

    Intermittency and predictability in turbulence.Physical Review Letters, 70(2):166, 1993

    Andrea Crisanti, MH Jensen, A Vulpiani, and G Paladin. Intermittency and predictability in turbulence.Physical Review Letters, 70(2):166, 1993

  8. [8]

    Mailybaev

    Alexei A. Mailybaev. Spontaneous stochasticity of velocity in turbulence models.Multiscale Modeling & Simulation, 14(1):96–112, 2016

Show all 79 references
  1. [9]

    Bandak, A.A

    D. Bandak, A.A. Mailybaev, G.L. Eyink, and N. Goldenfeld. Spontaneous stochasticity amplifies even thermal noise to the largest scales of turbulence in a few eddy turnover times.Phys. Rev. Lett., 132:104002, Mar 2024

  2. [10]

    RG approach to the inviscid limit for shell models of turbulence.Nonlinearity, 38(8):085010, aug 2025

    Alexei A Mailybaev. RG approach to the inviscid limit for shell models of turbulence.Nonlinearity, 38(8):085010, aug 2025

  3. [11]

    Campolina, and Alexei A

    Erika Ortiz, Ciro S. Campolina, and Alexei A. Mailybaev. Spontaneous stochasticity in the fluctuating Navier–Stokes equations on a logarithmic lattice.arXiv preprint arXiv:2507.03196, 2025

  4. [12]

    A Measure-Theoretic Approach to Spontaneous Stochasticity

    Wandrille Ruffenach, Eric Simonnet, and Nicolas Valade. A Measure-Theoretic Approach to Spontaneous Stochasticity. arXiv preprint arXiv:2607.16328, 2026

  5. [13]

    Drivas and A.A

    T.D. Drivas and A.A. Mailybaev. ’Life after death’ in ordinary differential equations with a non-Lipschitz singularity. Nonlinearity, 34:2296, 2021

  6. [14]

    Drivas, A.A

    T.D. Drivas, A.A. Mailybaev, and A. Raibekas. Statistical determinism in non-Lipschitz dynamical systems.Ergodic Theory and Dynamical Systems, 44:1856–1884, 2024

  7. [15]

    Spontaneous stochasticity in a 3d weierstrass-abc flow.Nonlinearity, 39(1):015018, jan 2026

    Antoine Barlet, Adam Cheminet, B´ ereng` ere Dubrulle, and Alexei A Mailybaev. Spontaneous stochasticity in a 3d weierstrass-abc flow.Nonlinearity, 39(1):015018, jan 2026

  8. [16]

    Mailybaev and A

    Alexei A. Mailybaev and A. Raibekas. Spontaneous stochasticity and renormalization group in discrete multi-scale dy- namics.Communications in Mathematical Physics, 401:2643–2671, 2023

  9. [17]

    Eyink and D

    G.L. Eyink and D. Bandak. Renormalization group approach to spontaneous stochasticity.Phys. Rev. Res., 2:043161, Oct 2020

  10. [18]

    Armstrong and V

    S. Armstrong and V. Vicol. Anomalous Diffusion by Fractal Homogenization.Annals of PDE, 11:2, 2025

  11. [19]

    Remarks on regularization by noise, convex integration and spontaneous stochas- ticity.Milan Journal of Mathematics, 92(2):349–370, 2024

    Franco Flandoli and Marco Rehmeier. Remarks on regularization by noise, convex integration and spontaneous stochas- ticity.Milan Journal of Mathematics, 92(2):349–370, 2024

  12. [20]

    Beyond chaos: fluctuations, anomalies and spontaneous stochasticity in fluid turbulence.arXiv preprint arXiv:2512.24469, 2025

    Gregory L Eyink and Nigel Goldenfeld. Beyond chaos: fluctuations, anomalies and spontaneous stochasticity in fluid turbulence.arXiv preprint arXiv:2512.24469, 2025

  13. [21]

    A dissipative random velocity field for fully developed fluid turbulence.Journal of Fluid Mechanics, 794:369–408, 2016

    Rodrigo M Pereira, Christophe Garban, and Laurent Chevillard. A dissipative random velocity field for fully developed fluid turbulence.Journal of Fluid Mechanics, 794:369–408, 2016

  14. [22]

    A spatio-temporal random synthetic turbulent velocity field: The underlying gaussian structure.Journal of Fluid Mechanics, 1030:A23, 2026

    Matthieu Chatelain, J´ ulia Domingues Lemos, Wandrille Ruffenach, Mickael Bourgoin, Charles-Edouard Br´ ehier, Laurent Chevillard, Ilias Sibgatullin, and Romain Volk. A spatio-temporal random synthetic turbulent velocity field: The underlying gaussian structure.Journal of Flui...

  15. [23]

    Geoffrey Beck, Charles-Edouard Br´ ehier, Laurent Chevillard, Ricardo Grande, and Wandrille Ruffenach. Numerical simu- lations of a stochastic dynamics leading to cascades and loss of regularity: Applications to fluid turbulence and generation of fractional gaussian fields.Phy...

  16. [24]

    Springer Science & Business Media, 2011

    Sergey Nazarenko.Wave turbulence, volume 825. Springer Science & Business Media, 2011. 20

  17. [25]

    Majda, David W

    Andrew J. Majda, David W. McLaughlin, and Esteban G. Tabak. A one-dimensional model for dispersive wave turbulence. Journal of Nonlinear Science, 7(1):9–44, 1997

  18. [26]

    Dispersive wave turbulence in one dimension

    David Cai, Andrew J Majda, David W McLaughlin, and Esteban G Tabak. Dispersive wave turbulence in one dimension. Physica D: Nonlinear Phenomena, 152:551–572, 2001

  19. [27]

    Frank Merle. On uniqueness and continuation properties after blow-up time of self-similar solutions of nonlinear Schr¨ odinger equation with critical exponent and critical mass.Communications on Pure and Applied Mathematics, 45(2):203–254, 1992

  20. [28]

    Global existence and uniqueness results for weak solutions of the focusing mass-critical nonlinear Schr¨ odinger equation.Analysis & PDE, 2(1):61–81, 2009

    Terence Tao. Global existence and uniqueness results for weak solutions of the focusing mass-critical nonlinear Schr¨ odinger equation.Analysis & PDE, 2(1):61–81, 2009

  21. [29]

    Nonlinear-damping continuation of the nonlinear Schr¨ odinger equation–a numerical study.Physica D: Nonlinear Phenomena, 241(5):519–527, 2012

    G Fibich and M Klein. Nonlinear-damping continuation of the nonlinear Schr¨ odinger equation–a numerical study.Physica D: Nonlinear Phenomena, 241(5):519–527, 2012

  22. [30]

    Loss of phase of collapsing beams

    Bonggu Shim, Samuel E Schrauth, Alexander L Gaeta, Moran Klein, and Gadi Fibich. Loss of phase of collapsing beams. Physical Review Letters, 108(4):043902, 2012

  23. [31]

    Finite-time localized singularities as a mechanism for turbulent dissipation.Physical Review Fluids, 5(5):054607, 2020

    Christophe Josserand, Yves Pomeau, and Sergio Rica. Finite-time localized singularities as a mechanism for turbulent dissipation.Physical Review Fluids, 5(5):054607, 2020

  24. [32]

    Two-dimensional singularity turbulence.Physica D: Nonlinear Phenomena, 443:133532, 2023

    Juliette Amauger, Christophe Josserand, Yves Pomeau, and Sergio Rica. Two-dimensional singularity turbulence.Physica D: Nonlinear Phenomena, 443:133532, 2023

  25. [33]

    Catherine Sulem and Pierre-Louis Sulem.The nonlinear Schr¨ odinger equation: self-focusing and wave collapse, volume

  26. [34]

    Weak versus strong wave turbulence in the Majda–McLaughlin–Tabak model.Physical Review Fluids, 2(5):052603, 2017

    Sergio Chibbaro, F De Lillo, and M Onorato. Weak versus strong wave turbulence in the Majda–McLaughlin–Tabak model.Physical Review Fluids, 2(5):052603, 2017

  27. [35]

    The impact of frequency bandwidth on a one-dimensional model for dispersive wave turbulence.Journal of Nonlinear Science, 33(5):81, 2023

    Ryan Sh ` ıji´ e D` u and Oliver B¨ uhler. The impact of frequency bandwidth on a one-dimensional model for dispersive wave turbulence.Journal of Nonlinear Science, 33(5):81, 2023

  28. [36]

    Sheffield

    Benno Rumpf and Thomas Y. Sheffield. Transition of weak wave turbulence to wave turbulence with intermittent collapses. Phys. Rev. E, 92:022927, Aug 2015

  29. [37]

    Weak turbulence and collapses in the Majda–McLaughlin–Tabak equation: fluxes in wavenumber and in amplitude space.Physica D: Nonlinear Phenomena, 204(3):188–203, 2005

    Benno Rumpf and Laura Biven. Weak turbulence and collapses in the Majda–McLaughlin–Tabak equation: fluxes in wavenumber and in amplitude space.Physica D: Nonlinear Phenomena, 204(3):188–203, 2005

  30. [38]

    Cascades in the kinetic equation for the Majda–McLaughlin– Tabak model.arXiv preprint arXiv:2606.07763, 2026

    Gregorio Tibone, Giorgio Krstulovic, and Miguel Onorato. Cascades in the kinetic equation for the Majda–McLaughlin– Tabak model.arXiv preprint arXiv:2606.07763, 2026

  31. [39]

    Springer, 2015

    Gadi Fibich.The nonlinear Schr¨ odinger equation, volume 192. Springer, 2015

  32. [40]

    On the growth of Sobolev norms of solutions of the fractional defocusing NLS equation on the circle

    Joseph Thirouin. On the growth of Sobolev norms of solutions of the fractional defocusing NLS equation on the circle. Annales de l’Institut Henri Poincar´ e C, Analyse non lin´ eaire, 34(2):509–531, 2017

  33. [41]

    P. A. Robinson. Nonlinear wave collapse and strong turbulence.Rev. Mod. Phys., 69:507–574, Apr 1997

  34. [42]

    The Kardar–Parisi–Zhang equation and universality class.Random matrices: Theory and applications, 1(01):1130001, 2012

    Ivan Corwin. The Kardar–Parisi–Zhang equation and universality class.Random matrices: Theory and applications, 1(01):1130001, 2012

  35. [43]

    An appetizer to modern developments on the Kardar–Parisi–Zhang universality class.Physica A: Statistical Mechanics and its Applications, 504:77–105, 2018

    Kazumasa A Takeuchi. An appetizer to modern developments on the Kardar–Parisi–Zhang universality class.Physica A: Statistical Mechanics and its Applications, 504:77–105, 2018

  36. [44]

    Linear versus nonlinear dissipation for critical NLS equation.Physica D: Nonlinear Phenomena, 203(3-4):167–184, 2005

    T Passot, C Sulem, and PL Sulem. Linear versus nonlinear dissipation for critical NLS equation.Physica D: Nonlinear Phenomena, 203(3-4):167–184, 2005

  37. [45]

    Dissipation at singularities of the nonlinear Schr¨ odinger equation through limits of regularisations

    Brenton J LeMesurier. Dissipation at singularities of the nonlinear Schr¨ odinger equation through limits of regularisations. Physica D: Nonlinear Phenomena, 138(3-4):334–343, 2000

  38. [46]

    Post-blowup dynamics for the nonlinear Schr¨ odinger equation.Physica D: Nonlinear Phenomena, 456:133944, 2023

    Jos´ e M Escorcia and Alexei A Mailybaev. Post-blowup dynamics for the nonlinear Schr¨ odinger equation.Physica D: Nonlinear Phenomena, 456:133944, 2023

  39. [47]

    Continuations of the nonlinear Schr¨ odinger equation beyond the singularity.Nonlinearity, 24(7):2003, 2011

    G Fibich and M Klein. Continuations of the nonlinear Schr¨ odinger equation beyond the singularity.Nonlinearity, 24(7):2003, 2011

  40. [48]

    Loss of phase and universality of stochastic interactions between laser beams

    Amir Sagiv, Adi Ditkowski, and Gadi Fibich. Loss of phase and universality of stochastic interactions between laser beams. Optics Express, 25(20):24387–24399, 2017

  41. [49]

    Toward the finite-time blowup of the 3D axisymmetric Euler equations: a numerical investigation.Multiscale Modeling & Simulation, 12(4):1722–1776, 2014

    Guo Luo and Thomas Y Hou. Toward the finite-time blowup of the 3D axisymmetric Euler equations: a numerical investigation.Multiscale Modeling & Simulation, 12(4):1722–1776, 2014

  42. [50]

    Chaotic blowup in the 3D incompressible Euler equations on a logarithmic lattice.Physical Review Letters, 121(6):064501, 2018

    Ciro S Campolina and Alexei A Mailybaev. Chaotic blowup in the 3D incompressible Euler equations on a logarithmic lattice.Physical Review Letters, 121(6):064501, 2018

  43. [51]

    Blow-up for the 1D cubic NLS.Communications in Mathematical Physics, 405(1):11, 2024

    Valeria Banica, Renato Luc` a, Nikolay Tzvetkov, and Luis Vega. Blow-up for the 1D cubic NLS.Communications in Mathematical Physics, 405(1):11, 2024

  44. [52]

    Numerical study of fractional nonlinear Schr¨ odinger equations

    Christian Klein, Christof Sparber, and Peter Markowich. Numerical study of fractional nonlinear Schr¨ odinger equations. Proceedings of the Royal Society A: Mathematical, Physical and Engineering Sciences, 470(2172):20140364, 2014

  45. [53]

    Tracking complex singularities of fluids on log-lattices.Nonlinearity, 37(11):115003, 2024

    Quentin Pikeroen, Amaury Barral, Guillaume Costa, Ciro Campolina, Alexei Mailybaev, and B´ ereng` ere Dubrulle. Tracking complex singularities of fluids on log-lattices.Nonlinearity, 37(11):115003, 2024

  46. [54]

    Frisch.Turbulence, The Legacy of A.N

    U. Frisch.Turbulence, The Legacy of A.N. Kolmogorov. Cambridge University Press, Cambridge, 1995

  47. [55]

    Pope.Turbulent Flows

    Stephen B. Pope.Turbulent Flows. Cambridge University Press, Cambridge, 2000

  48. [56]

    The spatio-temporal statistical structure of the turbulent dissipation field and its stochastic representation as a Gaussian multiplicative chaos.Comptes Rendus

    Wandrille Ruffenach and Laurent Chevillard. The spatio-temporal statistical structure of the turbulent dissipation field and its stochastic representation as a Gaussian multiplicative chaos.Comptes Rendus. Physique, 27:275–305, 2026

  49. [57]

    Inertial energy dissipation for weak solutions of incompressible Euler and Navier–Stokes equations.Nonlinearity, 13(1):249–255, 2000

    Jean Duchon and Raoul Robert. Inertial energy dissipation for weak solutions of incompressible Euler and Navier–Stokes equations.Nonlinearity, 13(1):249–255, 2000

  50. [58]

    Constantin, W

    P. Constantin, W. E, and E.S. Titi. Onsager’s conjecture on the energy conservation for solutions of Euler’s equation. Communications in Mathematical Physics, 165(1):207–209, 1994. 21

  51. [59]

    Energy dissipation without viscosity in ideal hydrodynamics I

    Gregory L Eyink. Energy dissipation without viscosity in ideal hydrodynamics I. Fourier analysis and local energy transfer. Physica D: Nonlinear Phenomena, 78(3-4):222–240, 1994

  52. [60]

    Statistical hydrodynamics.Il Nuovo Cimento (1943-1954), 6(Suppl 2):279–287, 1949

    Lars Onsager. Statistical hydrodynamics.Il Nuovo Cimento (1943-1954), 6(Suppl 2):279–287, 1949

  53. [61]

    Onsager’s ideal turbulence theory.Journal of Fluid Mechanics, 988:P1, 2024

    Gregory Eyink. Onsager’s ideal turbulence theory.Journal of Fluid Mechanics, 988:P1, 2024

  54. [62]

    P. Isett. A proof of Onsager’s conjecture.Annals of Mathematics, 188(3):871–963, 2018

  55. [63]

    Buckmaster, C

    T. Buckmaster, C. De Lellis, L. Sz´ ekelyhidi Jr, and V. Vicol. Onsager’s conjecture for admissible weak solutions.Com- munications on Pure and Applied Mathematics, 72(2):229–274, 2018

  56. [64]

    Nonuniqueness of weak solutions to the Navier–Stokes equation.Annals of Mathe- matics, 189(1):101–144, 2019

    Tristan Buckmaster and Vlad Vicol. Nonuniqueness of weak solutions to the Navier–Stokes equation.Annals of Mathe- matics, 189(1):101–144, 2019

  57. [65]

    The predictability of a flow which possesses many scales of motion.Tellus, 21(3):289–307, 1969

    Edward N Lorenz. The predictability of a flow which possesses many scales of motion.Tellus, 21(3):289–307, 1969

  58. [66]

    The production of uncertainty in three-dimensional Navier–Stokes turbulence.Journal of Fluid Mechanics, 977:A17, 2023

    Jin Ge, Joran Rolland, and John Christos Vassilicos. The production of uncertainty in three-dimensional Navier–Stokes turbulence.Journal of Fluid Mechanics, 977:A17, 2023

  59. [67]

    The interscale behaviour of uncertainty in three-dimensional Navier– Stokes turbulence.Journal of Fluid Mechanics, 1017:A29, 2025

    Jin Ge, Joran Rolland, and John Christos Vassilicos. The interscale behaviour of uncertainty in three-dimensional Navier– Stokes turbulence.Journal of Fluid Mechanics, 1017:A29, 2025

  60. [68]

    On blow up for the energy supercritical defocusing nonlinear Schr¨ odinger equations.Inventiones Mathematicae, 227(1):247–413, 2022

    Frank Merle, Pierre Rapha¨ el, Igor Rodnianski, and Jeremie Szeftel. On blow up for the energy supercritical defocusing nonlinear Schr¨ odinger equations.Inventiones Mathematicae, 227(1):247–413, 2022

  61. [69]

    Numerical study of probabilistic well-posedness of one-dimensional fractional nonlinear wave equations.arXiv preprint arXiv:2604.05938, 2026

    Wandrille Ruffenach and Nikolay Tzvetkov. Numerical study of probabilistic well-posedness of one-dimensional fractional nonlinear wave equations.arXiv preprint arXiv:2604.05938, 2026

  62. [70]

    Splitting methods with complex times for parabolic equations.BIT Numerical Mathematics, 49(3):487–508, 2009

    Fran¸ cois Castella, Philippe Chartier, St´ ephane Descombes, and Gilles Vilmart. Splitting methods with complex times for parabolic equations.BIT Numerical Mathematics, 49(3):487–508, 2009

  63. [71]

    SIDUS—the solution for extreme deduplication of an operating system

    Emmanuel Quemener and Marianne Corvellec. SIDUS—the solution for extreme deduplication of an operating system. Linux Journal, 2013(235):3, 2013

  64. [72]

    Hence |ψ|2ψ ℓ − |ψℓ|2ψℓ →0 inL 4/3, and H¨ older’s inequality givesDℓ[ψ]→0

    Indeed, at a fixed time, ifψ∈L 4(T), thenψ ℓ →ψinL 4, whileu7→ |u| 2uis continuous fromL 4(T) toL 4/3(T). Hence |ψ|2ψ ℓ − |ψℓ|2ψℓ →0 inL 4/3, and H¨ older’s inequality givesDℓ[ψ]→0

  65. [73]

    In that case, the regularization fails to act as a selection principle

    asε 1, ε2 ↓0, then the corresponding family of regularized solutions does not converge toward a unique solution of the inviscid problem (fNLS). In that case, the regularization fails to act as a selection principle. Although it produces a unique solution for every fixedν >0 or...

  66. [75]

    Note that the limit does not necessarily exist; one can just replace it by lim inf ε1,ε2→0 Gε1,ε2 Appendix A: Regularizations prevent blowup

  67. [76]

    Using conservation of mass and ln(1 +x)≤ √x, we obtain ∥Λ α 2 ψσ∥2 L2 ≤2H σ[ψ0] + 1 2√σ M[ψ0]

    Saturation prevents blowup With the saturating nonlinearity, the dynamics conserves M[ψσ] = Z T |ψσ(t, x)|2 dx,H σ[ψσ] = Z T 1 2 Λα/2ψσ 2 − 1 4σ ln 1 +σ|ψ σ|4 dx(A1) From the conservation ofH σ, we obtain ∥Λ α 2 ψσ∥2 L2 = 2Hσ[ψ0] + 1 2σ Z T ln 1 +σ|ψ σ|4 dx. Using conservation...

  68. [77]

    Diffusion prevents blowup for large enough dispersion To establish the regularizing effect of diffusion on the whole spaceR, we first recall the mass budget d dt ∥ψν∥2 L2(R) =−2ν∥Λψ ν∥2 L2(R), Z t 0 ∥Λψν(s)∥2 L2(R)ds= 1 2ν h ∥ψ0∥2 L2(R) − ∥ψν∥2 L2(R) i ≤ 1 2ν ∥ψ0∥2 L2(R). 22 T...

  69. [78]

    Because the nonlinearity is cubic, the largest non-dealiased Fourier mode isN/4

    Integration scheme For both regularizations, we solve the dynamics using a fully dealiased pseudo-spectral method withNcollocation points on a periodic domain of lengthL= 2π. Because the nonlinearity is cubic, the largest non-dealiased Fourier mode isN/4. Spatial derivatives a...

  70. [79]

    In each setting, the solution at fixed timetis viewed as a random field, and statistics are estimated from ensembles of independent realizations

    Statistical estimators With the disorder inψ 0 quenched, the statistical behavior studied below arises from randomness introduced either in the regularization parameter, such asνorσ, or through random perturbations (at equal mass) ofψ 0. In each setting, the solution at fixed ...

  71. [139]

    Springer Science & Business Media, 2007

Pith tools

Reviewed August 1, 2026 · model on record in the stance chip above.