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On reduced modelling of the modulational dynamics in magnetohydrodynamics

Published online by Cambridge University Press:  19 March 2025

S. Jin*
Affiliation:
Department of Astrophysical Sciences, Princeton University, Princeton, NJ 08543, USA Princeton Plasma Physics Laboratory, Princeton, NJ 08540, USA
I.Y. Dodin
Affiliation:
Department of Astrophysical Sciences, Princeton University, Princeton, NJ 08543, USA Princeton Plasma Physics Laboratory, Princeton, NJ 08540, USA
*
Email address for correspondence: sjin@pppl.gov

Abstract

This paper explores structure formation in two-dimensional magnetohydrodynamic (MHD) turbulence as a modulational instability (MI) of turbulent fluctuations. We focus on the early stages of structure formation and consider simple backgrounds that allow for a tractable model of the MI while retaining the full chain of modulational harmonics. This approach allows us to systematically examine the validity of popular closures such as the quasilinear approximation and other low-order truncations. We find that, although such simple closures can provide quantitatively accurate approximations of the MI growth rates in some regimes, they can fail to capture the modulational dynamics in adjacent regimes even qualitatively, falsely predicting MI when the system is actually stable. We find that this discrepancy is due to the excitation of propagating spectral waves (PSWs) which can ballistically transport energy along the modulational spectrum, unimpeded until dissipative scales, thereby breaking the feedback loops that would otherwise sustain MIs. The PSWs can be self-maintained as global modes with real frequencies and drain energy from the primary structure at a constant rate until the primary structure is depleted. To describe these waves within a reduced model, we propose an approximate spectral closure that captures them and MIs on the same footing. We also find that introducing corrections to ideal MHD, conservative or dissipative, can suppress PSWs and reinstate the accuracy of the quasilinear approximation. In this sense, ideal MHD is a ‘singular’ system that is particularly sensitive to the accuracy of the closure within mean-field models.

Information

Type
Research Article
Creative Commons
Creative Common License - CCCreative Common License - BY
This is an Open Access article, distributed under the terms of the Creative Commons Attribution licence (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted re-use, distribution and reproduction, provided the original article is properly cited.
Copyright
Copyright © The Author(s), 2025. Published by Cambridge University Press
Figure 0

Figure 1. The DNS of modulational dynamics of (2.3) seeded at $\tau =0$ with random noise. (This figure is discussed in detail in later sections. For the notation, see §§ 2.1 and 2.2.) Panels (a,c,e) correspond to a modulationally unstable primary mode (2.17) with $\theta ^\pm =\pm {\rm \pi}/6$, and (b,d,f) correspond to a modulationally stable primary mode with $\theta ^\pm =\pm {\rm \pi}/3$. Panels (a,b) show $z_x^+(t,y)$, (c,d) show $z_y^+(t,x)$ and (e,f) show the corresponding energy breakdown. Specifically, $\mathcal {E}_v$ is the normalized kinetic energy (2.21c), $\mathcal {E}_b = E_b/E_{\text {tot}}$ is the normalized magnetic energy (2.21d), $\mathcal {E}_{\text {mod}}$ is the normalized modulational-mode energy (2.21b) and $\mathcal {E}_{\text {pri}}$ is the normalized primary-mode energy (2.21a). The colour bar shows the field amplitudes normalized to $\mathcal {A}/p$. The spatial coordinates are normalized to $1/p$.

Figure 1

Figure 2. Comparison of the time evolution of various $\psi _n^+$ as predicted by DNS of (2.3) (red dots) and XQLS (numerical simulations of XQLT) (2.28) (black curves) for two representative cases of (a,c,e) the MI ($\theta = {\rm \pi}/6$) and (b,d,f) stable modulational dynamics ($\theta = {\rm \pi}/3$). Nonlinear DNS are seeded with random noise, resulting in a broadband modulational dynamics, but the results shown are for a modulation corresponding to $r = 0.5$, and the XQLS are initialized accordingly. For the $\theta = {\rm \pi}/6$ case, the harmonics shown are (a) $n = 0$, (b) $n = 1$ and (c) $n = 2$. In this case, XQLT adequately approximates the nonlinear dynamics until approximately $\tau \sim 30$. For the $\theta = {\rm \pi}/3$ case, the harmonics shown are (d) $n = 0$, (e) $n = 25$ and (f) $n = 50$. In this case, XQLT adequately approximates the nonlinear dynamics indefinitely.

Figure 2

Figure 3. (a) The growth rate $\varGamma$ (of the most unstable mode) versus the normalized wavenumber $r$ at $\theta = 0$: 4MT (blue); 6MT (red); XQLS (black markers). (b) The same for $\varGamma$ versus $\theta$ at $r = 0.5$. The 4MT predicts identical growth rates at $\theta = 0$ and $\theta = {\rm \pi}$, while the 6MT and XQLS predict that the system is unstable at $\theta = 0$ and stable at $\theta = {\rm \pi}$. (c) The same for $\varGamma$ versus $\phi$ at $r = 0.5$ and $\theta =0$.

Figure 3

Figure 4. The difference between the growth rate predicted by a $Q$MT and that inferred from XQLS, $\varGamma _{Q\text {MT}}-\varGamma _{\text {XQLS}}$, versus $(\theta, r)$ for $\phi = {\rm \pi}/4$: (a) 4MT; (b) 6MT. The dashed curves mark the stability boundary as determined by a parameter scan with XQLS. The preponderance of the red colour, especially outside the instability domain, indicates that truncated models tend to produce false positives for instability.

Figure 4

Figure 5. The growth rates $\varGamma$ obtained through a $Q$MT for $\theta = 0$ (blue markers) and $\theta = {\rm \pi}/2$ (orange markers) versus the number of modes retained, $N$. The solid-coloured lines indicate the corresponding XQLS growth rates, to which the rates predicted by the truncated models converge at large $N$.

Figure 5

Figure 6. Typical structures of eigenmodes, specifically, $|Y_n|$ versus $n$, at $r=0.5$ and $\phi ={\rm \pi} /4$ for various $\theta$: (a) unstable modes supported by VDPMs; (b) oscillatory solutions supported by BDPMs. (The upper index in $|Y_n^\sigma |$ is omitted because $|Y_n^+| = |Y_n^-|$ for the assumed parameters.) Here $|Y_n|$ decreases exponentially with $n$ for the former (notice the logarithmic scale) but asymptote to non-zero constants for the latter. The asymptotes are indicated by the dotted lines. These results are obtained through XQLS using the initial conditions of the form (4.6) and normalized such that $|Y_0| = 1$.

Figure 6

Figure 7. Numerical simulations showing PSW packets propagating (a) down the spectrum ($|n|$ of the packet centre increases with time) and (b) up the spectrum ($|n|$ of the packet centre decreases with time). In both cases, $r = 0.5$ and $\theta = {\rm \pi}/3$. Both packets are initialized using $\psi _n^+(\tau = 0) = \exp [-(n - n_0)^2/\varsigma + \mathrm {i} K^+ n]$ with $n_0 = 200$, $\varsigma = 150$, and (a) $K^+ = -{\rm \pi} /6$, (b$K^+ = {\rm \pi}/2$.

Figure 7

Figure 8. (a) The dependence of the global-mode frequency $\omega > 0$ on $\theta$ for various $r$. The dashed lines are the inferred solutions (4.7). (b) Here $|Y_n^+|$ (blue) and $|Y_n^-|$ (orange) for the mode with $\omega > 0$. The eigenmode amplitudes for the $\omega < 0$ mode are identical with the roles of $|Y_n^+|$ and $|Y_n^-|$ switched.

Figure 8

Figure 9. The XQLS showing global-mode PSWs for $r=0.5$, $\theta = {\rm \pi}/3$ and $\phi = {\rm \pi}/4$: (a$\operatorname {Re} \psi _n^+/\epsilon$ for a PSW seeded by the initial conditions (4.6) with $\xi ^\sigma _d = d\exp (\sigma \mathrm {i} {\rm \pi}/4)$ (colour bar). The dashed lines indicate the fronts propagating at (i) the maximum spectral speed $\sqrt {2}r$ and (ii) the actual group velocity of the mode. The field between these dashed lines consists of transients, which are negligible behind the second front. (b) The total normalized energy of the modulation, $\mathcal {E}_{\text {mod}}/\epsilon ^2$, versus $\tau$ (black), along with its kinetic (red) and magnetic (blue) components. (c) The profiles of the spectral energy density at $\tau =100, 150, 200$, clearly exhibiting left- and right-propagating fronts. The horizontal dashed line indicates the average spectral energy density $\overline {\mathcal {E}_n}$, where the average is taken over the PSW period and over $n$ between the energy fronts.

Figure 9

Figure 10. The global-mode PSW mode with $\omega > 0$, $r = 0.5$ and $\theta = {\rm \pi}/3$; the same as figure 9, but in the real space as opposed to the spectral space. Specifically shown are (a) $z_y^+$ as a function of $(\tau, x)$ at $y = 0$; (b) $z_x^+$ as a function of $(\tau, y)$ at $x = 0$.

Figure 10

Figure 11. (a) The magnitude of the group velocity $|v_g|$ of the global PSW mode (i.e. the speed at which the energy front propagates along the spectrum) versus $\theta$ for various $r$. (b) The same for the average spectral energy density $\overline {\mathcal {E}_n}/\epsilon ^2$. (c) The same for the resulting average drain rate $\gamma /\epsilon ^2$, where $\gamma$ is defined in (4.10). The initial conditions used throughout these figures are given by (4.6), with $\xi _{1}^\sigma =-\xi _{-1}^\sigma =\exp (\sigma \mathrm {i} {\rm \pi}/2)$.

Figure 11

Figure 12. The $\theta$-dependence of the global-mode frequencies derived from truncated models with the closure (5.3) for various $N$: (ac$\operatorname {Re}\omega$ and (df$\operatorname {Im}\omega$. Here (a,d) $N = 2$; (b,e$N = 3$; (c,f$N = 4$. The red and blue curves indicate the branches that are the best match to the, respectively, unstable and stable solutions obtained through XQLS (black dashed lines). The grey curves show the remaining spurious solutions due to finite $N$. Note that MIs exist only for $\theta \in (0, {\rm \pi}/4)$, while PSWs exist in the entire range $\theta \in (0, {\rm \pi}/2)$.

Figure 12

Figure 13. The growth rate $\varGamma$, at $\nu _- = 0$, versus (a$\varLambda \doteq \lambda /\mathcal {A}p^3$ and (b$\mu \doteq \nu _+/\mathcal {A}p^2$. The corresponding ‘centre of energy’ of the unstable eigenmode, $\bar {n}\doteq \sqrt {\sum _n \mathcal {E}_n n^2/\mathcal {E}}$, is shown in (c,d), respectively. In all figures, the colour markers indicate the results obtained through XQLS, while the black solid curves indicate solutions obtained from the 4MT truncation of (6.2). The results are presented for the representative cases $\theta = 0$ and $\theta = {\rm \pi}/2$, both at $r = 0.5$ and $\phi = {\rm \pi}/4$.