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MHD turbulence: a biased review

Published online by Cambridge University Press:  12 October 2022

Alexander A. Schekochihin*
Affiliation:
Rudolf Peierls Centre for Theoretical Physics, Clarendon Laboratory, University of Oxford, Parks Road, Oxford OX1 3PU, UK Merton College, Oxford OX1 4JD, UK
*
Email address for correspondence: alex.schekochihin@physics.ox.ac.uk
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Abstract

This review of scaling theories of magnetohydrodynamic (MHD) turbulence aims to put the developments of the last few years in the context of the canonical time line (from Kolmogorov to Iroshnikov–Kraichnan to Goldreich–Sridhar to Boldyrev). It is argued that Beresnyak's (valid) objection that Boldyrev's alignment theory, at least in its original form, violates the Reduced-MHD rescaling symmetry can be reconciled with alignment if the latter is understood as an intermittency effect. Boldyrev's scalings, a version of which is recovered in this interpretation, and the concept of dynamic alignment (equivalently, local 3D anisotropy) are thus an example of a physical theory of intermittency in a turbulent system. The emergence of aligned structures naturally brings into play reconnection physics and thus the theory of MHD turbulence becomes intertwined with the physics of tearing, current-sheet disruption and plasmoid formation. Recent work on these subjects by Loureiro, Mallet et al. is reviewed and it is argued that we may, as a result, finally have a reasonably complete picture of the MHD turbulent cascade (forced, balanced, and in the presence of a strong mean field) all the way to the dissipation scale. This picture appears to reconcile Beresnyak's advocacy of the Kolmogorov scaling of the dissipation cutoff (as $\mathrm {Re}^{3/4}$) with Boldyrev's aligned cascade. It turns out also that these ideas open the door to some progress in understanding MHD turbulence without a mean field – MHD dynamo – whose saturated state is argued to be controlled by reconnection and to contain, at small scales, a tearing-mediated cascade similar to its strong-mean-field counterpart (this is a new result). On the margins of this core narrative, standard weak-MHD-turbulence theory is argued to require some adjustment – and a new scheme for such an adjustment is proposed – to take account of the determining part that a spontaneously emergent 2D condensate plays in mediating the Alfvén-wave cascade from a weakly interacting state to a strongly turbulent (critically balanced) one. This completes the picture of the MHD cascade at large scales. A number of outstanding issues are surveyed: imbalanced turbulence (for which a new, tentative theory is proposed), residual energy, MHD turbulence at subviscous scales, and decaying MHD turbulence (where there has been dramatic progress recently, and reconnection again turned out to feature prominently). Finally, it is argued that the natural direction of research is now away from the fluid MHD theory and into kinetic territory – and then, possibly, back again. The review lays no claim to objectivity or completeness, focusing on topics and views that the author finds most appealing at the present moment.

Information

Type
Review Article
Copyright
Copyright © The Author(s), 2022. Published by Cambridge University Press
Figure 0

Figure 1. IK and GS (photo of R. S. Iroshnikov courtesy of N. Lipunova and K. Bychkov, Sternberg Astronomical Institute; photo of R. H. Kraichnan courtesy of the AIP Emilio Segrè Visual Archives).

Figure 1

Figure 2. A visualisation of numerical RMHD turbulence, courtesy of A. Beresnyak (run R5 from Beresnyak 2012a, $1536^3$). The shades of grey represent the absolute value of $\boldsymbol {Z}_{\perp }^+ = \boldsymbol {u}_{\perp } + \boldsymbol {b}_{\perp }$ (see § 3).

Figure 2

Figure 3. (Decaying) MHD simulation of transition from weak to strong turbulence by Meyrand, Galtier & Kiyani (2016): the upper panel shows the magnetic spectrum vs. $k_{\parallel }$ and $k_{\perp }$ (where $k_{\parallel }$ is along the global mean field), the lower one the same integrated over $k_{\parallel }$ and normalised by $k_{\perp }^{3/2}$ (see § 6 for why $k_{\perp }^{-3/2}$ rather than $k_{\perp }^{-5/3}$). A transition manifestly occurs from a $k_{\perp }^{-2}$ to a $k_{\perp }^{-3/2}$ spectrum and, simultaneously, from a state with no $k_{\parallel }$ cascade (and a relatively narrow-band parallel spectrum) to one consistent with a CB cascade (2D spectra of CB turbulence are worked out in Appendix C). (Reprinted with permission from Meyrand et al.2016, copyright (2016) by the American Physical Society.)

Figure 3

Figure 4. Kinetic ($E$, solid lines) and magnetic ($M$, dotted lines with crosses) energy spectra for $k_{\parallel }=0$ (red), $k_{\parallel }=2\pi /L_{\parallel }$ (blue) and $k_{\parallel }=4\pi /L_{\parallel }$ (green) from an unpublished weak RMHD turbulence simulation by Yousef & Schekochihin (2009). The box size was $(L_{\perp },L_{\parallel })$ in the perpendicular and parallel directions, respectively, and the forcing was narrow-band, at $k_{\parallel }=2\pi /L_{\parallel }$ and $k_{\perp } = (1,2)\times 2\pi /L_{\perp }$, deep in the WT regime ($L_{\perp }\gg \lambda _{\mathrm {CB}}$). WT spectra for the case of broad-band forcing can be found in Perez & Boldyrev (2008) and Boldyrev & Perez (2009) and are discussed in Appendix A.4.

Figure 4

Figure 5. Critical balance in a ($2+1$)D system supporting both nonlinearity and waves (RMHD).

Figure 5

Figure 6. Refined critical balance: this figure, taken from Mallet et al. (2015), shows the probability density function (PDF) of the ratio $\chi ^+=\tau _{\mathrm {A}}/\tau _{\mathrm {nl}}^+$ with $\tau _{\mathrm {nl}}^+$ defined by (6.4). In fact, 17 PDFs are plotted here, taken at different scales within an approximately decade-wide inertial range (this was a $1024^3$ RMHD simulation) – the corresponding lines are in colour shades from blue (smaller scales) to red (larger scales), but this is barely visible because the PDFs all collapse on top of each other. The inset shows that the self-similarity does not work if $\tau _{\mathrm {nl}}^+$ is defined without the alignment angle (see § 6). (Reprinted from Mallet et al.2015 by permission of the Royal Astronomical Society.)

Figure 6

Figure 7. (a) Parallel ($P_\parallel$) and perpendicular ($P_\perp$) spectra (Fourier and wavelet) of the magnetic fluctuations in the solar wind, measured by the Ulysses spacecraft and computed by Wicks et al. (2010), with frequencies $f$ converted to wavenumbers $k$ using the Taylor hypothesis (reprinted from Wicks et al.2010 by permission of the Royal Astronomical Society). (b) An earlier (historic, the first ever) measurement by Horbury, Forman & Oughton (2008) of the spectral index of these spectra as a function of angle to the local mean field (reprinted with permission from Horbury et al.2008, copyright (2008) by the American Physical Society).

Figure 7

Figure 8. Measuring correlations along local vs. global mean field. True parallel correlations cannot be captured by a measurement along the global field $\boldsymbol {B}_0$ if the distance $\varDelta l_\perp$ (see (5.7)) by which the point-separation vector ${\boldsymbol {l}}$ along $\boldsymbol {B}_0$ ‘slips’ off the exact field line ($\boldsymbol {B}_0+\boldsymbol {b}_{\perp }$) is greater than the perpendicular decorrelation length $\lambda$ between ‘neighbouring’ field lines.

Figure 8

Figure 9. Cartoon of a GS95 eddy (a) vs. a Boldyrev (2006) aligned eddy (b). The latter has three scales: $l_{\parallel }\gg \xi \gg \lambda$ (along $\boldsymbol {B}_0$, along $\boldsymbol {b}_{\perp }$, and transverse to both). This picture is adapted from Boldyrev (2006) (reprinted with permission from Boldyrev 2006, copyright (2006) by the American Physical Society). In the context of my discussion, the fluctuation direction should, in fact, be thought of as along $\boldsymbol {Z}_{\perp }^+$ or $\boldsymbol {Z}_{\perp }^-$ (see figure 38).

Figure 9

Figure 10. The best-resolved currently available spectra of RMHD turbulence. (a) From simulations by Perez et al. (2012) (their figure 1), with Laplacian viscosity and resolution up to $2048^2\times 512$. (b) From simulations by Beresnyak (2014b) (his figure 1, © AAS, reproduced with permission), with Laplacian viscosity (a) and with fourth-order hyperviscosity (b); the resolution for the three spectra is $1024^3$, $2048^3$ and $4096^3$. His spectra are rescaled to Kolmogorov scale (6.11) (which he denotes $\eta$). He finds poorer convergence (see his figure 2) when he rescales to Boldyrev's scale (6.24). Perez et al. (2012) appear to get a somewhat better outcome (see their figure 8) if they plot their spectra vs. $k_{\perp }\lambda _{\eta }$ where $\lambda _{\eta }$ is given by (6.24) with $\lambda _{\mathrm {CB}}$ computed in each simulation as the normalisation constant in the scaling (6.22) of $\sin \theta _\lambda$ (in their analysis, however, this is the angle between velocity and magnetic perturbations, not the Elsasser fields).

Figure 10

Figure 11. (a) Probability distribution of $l_{\parallel }/\lambda ^{1/2}$ in a $1024^3$ RMHD simulation (the shades of colour from blue to red correspond to PDFs at increasing scales within the inertial range). This plot is taken from Mallet & Schekochihin (2017) (where the reader will find a discussion – somewhat inconclusive – of the slope of this PDF) and illustrates how good (or otherwise) is the assumption that $l_{\parallel }/\lambda ^\alpha$ has a scale-invariant distribution (the assumption is not as good as RCB, illustrated in figure 6 based on data from the same simulation). (b) Joint probability distribution for the length $l_{\parallel }$ and width $\xi$ (in my notation) of the most intense dissipative structures (adapted from Zhdankin, Boldyrev & Uzdensky 2016b). This shows that $\xi \propto l _{\parallel }$, in line with (6.29). (Reprinted from Zhdankin et al.2016b with the permission of AIP Publishing.) Independent simulations by J. M. Stone (private communication, 2018) support this scaling.

Figure 11

Figure 12. Locally 3D-anisotropic structures in the (a) solar wind (from Verdini et al.2018 © AAS, reproduced with permission) and (b) numerical simulations (here $l_{\parallel }$ is normalised to $L_{\parallel }/2\pi$ and $\lambda$ and $\xi$ to $L_{\perp }/2\pi$, hence apparent isotropy at the outer scale). These are surfaces of constant second-order structure function of the magnetic field (a) or one of the Elsasser fields (b). The three images correspond to successively smaller fluctuations and so successively smaller scales (only the last of the three is firmly in the universal inertial range). In both cases, the emergence of statistics with $l_{\parallel }\gg \xi \gg \lambda$ is manifest. In the solar wind, the route that turbulence takes to this aligned state appears to depend quite strongly on the solar-wind expansion, which distorts magnetic-field component in the radial direction compared to the azimuthal ones (Verdini & Grappin 2015; Vech & Chen 2016). The data shown in panel (a) was carefully selected to minimise this effect; without such selection, one sees structures most strongly elongated in the $\xi$ direction at the larger scales ($\xi >l_{\parallel }>\lambda$), although they too tend to the universal aligned regime at smaller scales (see Chen et al.2012, where 3D-anisotropy plots like ones shown here first appeared).

Figure 12

Figure 13. Scaling exponents of the structure functions in RMHD turbulence simulated by Mallet et al. (2016) (the plot is reproduced from Mallet & Schekochihin 2017). (a) Structure functions of the Elsasser-field increments (5.6): by definition, $\langle |\delta \boldsymbol {Z}_{\boldsymbol {l}}^+|^n\rangle \propto l^{\zeta _n}$ and $\zeta _n^\perp$, $\zeta _n^\mathrm {fluc}$, $\zeta _n^\parallel$ are exponents for $l=\lambda$, $\xi$, $l_{\parallel }$, respectively (i.e., all structure functions are conditional on the point separation being in one of the three directions of local 3D anisotropy; see §§ 5.3 and 6.5). The solid lines are for a $1024^3$ simulation (with hyperviscosity), the dashed ones are for a $512^3$ simulation, indicating how converged, or otherwise, the exponents are, and the dotted lines, in both (a) and (b), are the theoretical model by Mallet & Schekochihin (2017). (b) Similarly defined structure functions of the velocity (solid lines) and magnetic-field (dashed lines) increments from the same $1024^3$ simulation. The magnetic field is ‘more intermittent’ than the Elsasser fields and the latter more so than velocity. An early (possibly first) numerical measurement of this kind, highlighting the differences between scalings of different fields and in different local directions, was done by Cho, Lazarian & Vishniac (2003).

Figure 13

Figure 14. Spectrum of MHD turbulence and transition to tearing-mediated cascade (see (7.15)) (adapted from Mallet et al.2017b). The width of the tearing-mediated range is, of course, exaggerated in this cartoon. The spectral slopes of the ‘mini-cascades’ between $\lambda _n^{-1}$ and $\lambda _{n+1}^{-1}$ are all $k_{\perp }^{-3/2}$, but the overall envelope is $k_{\perp }^{-11/5}$. Note that, modulo $\mathrm {Pm}$ dependence, the disrupted aligned cascade and a putative unaligned GS95 $k_{\perp }^{-5/3}$ spectrum, starting at $\lambda _{\mathrm {CB}}$, terminate at the same, Kolmogorov, scale (7.19).

Figure 14

Figure 15. A snapshot of current density ($j_z$) from a 2D, $\mathrm {Rm}=10^6$ (64,000$^2$) MHD simulation by Dong et al. (2018) (reprinted with permission from Dong et al.2018, copyright (2018) by the American Physical Society; I am grateful to C. Dong for letting me have the original figure file). Zoomed areas show sheets broken up into plasmoids. The 3D versions of these visualisations reported by Dong et al. (2021) look generally messier, with islands less clearly delineated (they look a bit like the flux ropes in figure 50), but not, at first glance, qualitatively different in a paradigm-changing way.

Figure 15

Figure 16. (a) Distribution of normalised cross-helicity ($\sigma _{\mathrm {c}}$) and residual energy ($\sigma _{\mathrm {r}}$) (defined in (B4)) in an interval of fast-solar-wind data taken by Wind spacecraft and analysed by Wicks et al. (2013b), from whose paper both plots in this figure are taken (© AAS, reproduced with permission). (b) Structure functions corresponding to the total energy (sum of kinetic and magnetic) conditioned on values of $\sigma _{\mathrm {c}}$ and $\sigma _{\mathrm {r}}$ and corresponding to Regions 1 (balanced), 2 (Elsasser-imbalanced), and 3 (Alfvénically imbalanced towards magnetic perturbations), indicated in panel (a). The $f^{-2/3}$ slope corresponds to a $k_{\perp }^{-5/3}$ spectrum, the $f^{-1/2}$ slope to a $k_{\perp }^{-3/2}$ one.

Figure 16

Figure 17. Cosine of the angle between increments $\delta \boldsymbol {u}_{\boldsymbol {\lambda }}$ and $\delta \boldsymbol {b}_{\boldsymbol {\lambda }}$ in the $(x,y)$ plane, for $\lambda = L_{\perp }/6$ (left) and $\lambda = L_{\perp }/12$ (right, corresponding to the region demarcated by the white square within the left panel) in a balanced RMHD simulation by Perez & Boldyrev (2009) (reprinted with permission from Perez & Boldyrev 2009, copyright (2009) by the American Physical Society). Since $\delta \boldsymbol {u}_{\boldsymbol {\lambda }}\cdot \delta \boldsymbol {b}_{\boldsymbol {\lambda }} =\left (|\delta \boldsymbol {Z}^+_{\boldsymbol {\lambda }}|^2 - |\delta \boldsymbol {Z}^-_{\boldsymbol {\lambda }}|^2\right )/4$, this is an illustration of patchy local imbalance, as well as of local alignment between the velocity and magnetic field.

Figure 17

Figure 18. A typical MHD simulation with large imbalance: (a) spectra, (b) anisotropy, $l_{\parallel }^\pm$ vs. $\lambda$. These plots are adapted from Beresnyak & Lazarian (2009b) (© AAS, reproduced with permission). Mallet & Schekochihin (2011) and Meyrand & Squire (2020) have qualitatively similar results (although the difference in slopes between the weaker and the stronger fields’ spectra is much smaller in the higher-resolution simulations of Meyrand & Squire 2020 – see an example of that in figure 35c, taken from Meyrand et al.2021).

Figure 18

Figure 19. Scalings found in (unpublished) $512^3$ RMHD numerical simulations by Mallet & Schekochihin (2011): perpendicular (parallel) spectral indices $\mu _\perp$ ($\mu _\parallel$) (inferred from structure functions calculated as explained in § 5.3) for both fields, denoted by the $\pm$ superscripts. In terms of the scaling exponents $\gamma ^\pm _{\perp,\parallel }$ of the field increments ($\delta Z^\pm _\lambda \propto \lambda ^{\gamma ^\pm _\perp }$, $\delta Z^\pm _{l_{\parallel }}\propto l _{\parallel }^{\gamma ^\pm _\parallel }$), these are $\mu ^\pm _{\perp,\parallel } = -2\gamma ^\pm _{\perp,\parallel } - 1$. The last column shows the overall Elsasser ratio $R_{\mathrm {E}}=\langle |\boldsymbol {Z}_{\perp }^+|^2\rangle /\langle |\boldsymbol {Z}_{\perp }^-|^2\rangle$. The parallel scalings of the weaker field were converged with resolution, while the perpendicular scalings of the stronger (weaker) field at $\varepsilon ^+/\varepsilon ^- = 10$ became shallower (steeper) as resolution was increased from $256^3$ to $512^3$ to $1024^2\times 512$; the parallel scaling of the stronger field also appeared to become shallower. Simulations with $\varepsilon ^+/\varepsilon ^- = 100, 1000$ should be viewed as numerically suspect.

Figure 19

Figure 20. Cartoon of the spectra of imbalanced turbulence. The interactions are shown by arrows: red (advection of the weaker field by the stronger field, non-local in $\lambda$ but local in $l_{\parallel }$) and blue (advection of the stronger field by the weaker field, local in $\lambda$ but non-localin $l_{\parallel }$). The inset shows the parallel scales $l_{\parallel }^\pm$ vs. the perpendicular scale $\lambda$.

Figure 20

Figure 21. Spectra of magnetic (red), kinetic (blue), total (black) and residual (green) energies measured by Chen et al. (2013) (figures taken from Chen 2016): (a) typical spectra; (b) average spectral indices vs. normalised cross-helicity $\sigma _{\mathrm {c}}$ (defined in (B4)).

Figure 21

Figure 22. Spectra of total, magnetic, kinetic ((a), solid, dashed and dot-dashed lines, respectively, compensated by $k_{\perp }^{3/2}$) and residual energy ((b), compensated by $k_{\perp }^{1.9}$) in an RMHD simulation by Boldyrev et al. (2011) (© AAS, reproduced with permission). Beresnyak (2014b) does a convergence study by rescaling to the dissipative cutoff and finds instead a $k_{\perp }^{-1.7}$ scaling to be the best fit to the residual-energy spectrum (see his figure 3), so it is possible that what is displayed here is a large-scale transient.

Figure 22

Figure 23. Joint probability distribution of Elsasser vorticities $\omega ^\pm = \hat {\boldsymbol {z}}\cdot (\boldsymbol {\nabla }_{\perp }\times \boldsymbol {Z}_{\perp }^\pm )$ in an RMHD simulation by Zhdankin et al. (2016b) (reprinted from Zhdankin et al.2016b with the permission of AIP Publishing). The contours are elongated in the SE-NW direction, indicating $\langle \omega ^+\omega ^-\rangle <0$ and thus a preponderance of current sheets over shear layers.

Figure 23

Figure 24. (a) Spectra of magnetic and kinetic energy for subviscous turbulence, taken from Cho et al. (2003). (b) Magnetic-field strength for the filtered $k>20$ part of the field in the same simulation (from Cho et al.2002a; both figures © AAS, reproduced with permission). Stripy field structure is manifest.

Figure 24

Figure 25. A snapshot of $|\boldsymbol {B}|$ from a decaying 2D MHD turbulence simulation, courtesy of D. Hosking. This run had the resolution of $4608^2$ and used $n=4$ equal hyperviscosity and hyperresistivity (the run with $\nu _4=\eta _4=2\times 10^{-11}$ from Hosking & Schekochihin 2021).

Figure 25

Figure 26. A cross-section of helicity density $H=\boldsymbol {A}\cdot \boldsymbol {B}$ (in Coulomb gauge, $\boldsymbol {\nabla }\cdot \boldsymbol {A}=0$) from a decaying 3D MHD turbulence simulation ($512^3$) with zero net helicity, taken from Hosking & Schekochihin (2022a). Red is $H>0$, blue is $H<0$. The superimposed grey scale shows the magnitude of the current density $J=|\boldsymbol {\nabla }\times \boldsymbol {B}|$, so the black patches are strong currents between, and on the edges of, local blobs of non-zero helicity – presumably, these are reconnection sites where decay occurs, at constant Hosking invariant (12.25), i.e., conserving the mean square helicity fluctuations.

Figure 26

Figure 27. Numerical probe of the conservation of the Hosking invariant $I_H$, defined by (12.20) with $\psi = \boldsymbol {A}\cdot \boldsymbol {B}$. This plot, reproduced from Hosking & Schekochihin (2021), is of the mean square helicity density over a cubic volume $V = (2R)^3$, at different times in a decaying, non-helical, 3D MHD turbulence simulation started in a magnetically dominated state – red-to-blue curves correspond to earlier-to-later times. The simulation box is periodic, which is why $I_H$ is only non-zero in a range of $R$ intermediate between the energy-containing scale $L$ and the box size ($2R = 2\pi$). The inset shows the near-constancy of $I_H$ (calculated over the interval of $R$ indicated by vertical dashed lines).

Figure 27

Figure 28. Spectra of kinetic (blue) and magnetic (red) energies in decaying turbulence: (a) pure hydrodynamic, (b) MHD with no mean field and zero helicity, (c) MHD with no mean field and finite helicity. The time evolution is from right to left (always towards larger scales). These plots are from Brandenburg & Kahniashvili (2017).

Figure 28

Figure 29. Snapshots of vertical ($z$) current density in the $(x,y,0)$ (top row) and $(x,0,z)$ (bottom row) planes, taken at a series of subsequent times in a decaying RMHD simulation by Zhou et al. (2020). This illustrates growth of $L_{\perp }\propto \sqrt {t}$ and $L_{\parallel }\propto t$ (the scalings confirmed quantitatively in their paper) and the presence of numerous current sheets.

Figure 29

Figure 30. Stretching/shearing a field line produces direction reversals (cartoon from Schekochihin & Cowley 2007).

Figure 30

Figure 31. From unpublished work by Iskakov & Schekochihin (2008): a $512^3$ incompressible-MHD simulation of saturated fluctuation dynamo, $\mathrm {Pm}=1$, $\mathrm {Re}=1360$ (defined $=u_{\mathrm {rms}}/\nu k_0$, where $k_0=2\pi$ is the forcing wavenumber, corresponding to the box size; this is the same numerical set up as in Iskakov et al.2007 and Schekochihin et al.2007). These are 2D cuts from instantaneous snapshots of absolute values of (a) velocity, (b) magnetic field. Panel (c) is a cut out from these snapshots, zooming in on the horizontal fold just down towards the left from the centre of the snapshot. Stream lines are in black and field lines are in red. A reconnecting-sheet structure, with field reversal, inflows and outflows is manifest. Very pretty 3D visualisations of this kind of reconnecting structure extracted from an MHD turbulence simulation can be found in Lalescu et al. (2015).

Figure 31

Figure 32. From unpublished work by Beresnyak (2012b) (reproduced with the kind permission of the author): snapshot of the absolute value of magnetic field in a $\mathrm {Pm}=10$ and $\mathrm {Re}\approx 500$ simulation at $1024^3$ (the same numerical set up as in Beresnyak & Lazarian 2009a and Beresnyak 2012c; note that Beresnyak defines his $\mathrm {Re}$ in terms of the ‘true’ integral scale of the flow calculated from its spectrum). Plasmoids/fold corrugations galore. In his other simulations within this sequence, there are even more plasmoid-like-looking features at $\mathrm {Pm}=1$ and $\mathrm {Re}\approx 6000$, with some sign of them breaking up into even smaller structures (cf. § 13.3.3). In contrast, they start disappearing at $\mathrm {Pm}=10^2$ and $\mathrm {Re}\approx 80$ and are gone completely in the ‘Stokes’regime $\mathrm {Pm}=10^4$ and $\mathrm {Re}\approx 2$. Very similar results have been found by Galishnikova, Kunz & Schekochihin (2022).

Figure 32

Figure 33. (a) Spectra of saturated MHD dynamo: kinetic-energy (red, compensated by $k^{5/3}$) and magnetic-energy (blue) spectra from a series of incompressible-MHD simulations with $\mathrm {Pm}=10$ and increasing $\mathrm {Re}$ by Iskakov & Schekochihin (2008). The numerical set up is the same as in Schekochihin et al. (2007); the resolution is $512^3$ (so the highest-$\mathrm {Re}$ run may be numerically suspect). (b) A summary plot from Grete et al. (2021) (© AAS, reproduced with permission) of their and several other numerical studies, viz., from top to bottom, Bian & Aluie (2019); Grete et al. (2021); Porter et al. (2015); Eyink et al. (2013); Haugen et al. (2004). The kinetic-energy (solid lines) and magnetic-energy (dot-dashed lines) spectra are all compensated by $k^{4/3}$ to highlight the shallow kinetic-energy spectrum at small scales. Galishnikova et al. (2022) report very similar spectra and find also the magnetic spectrum steepening at even smaller scales, perhaps vindicating the prediction of § 13.3.3.

Figure 33

Figure 34. Spectrum of isotropic MHD turbulence, which is the saturated state of small-scale dynamo. The universal cascade below the fold-reversal scale $\lambda _{\mathrm {R}}$ (see (13.9)) is described in § 13.3.3. Various options for the spectrum at $k\lambda _{\mathrm {R}} < 1$ are discussed in § 13.4; in particular, the $k^{-1}$ magnetic spectrum is (13.18). The velocity spectrum may well be steeper than $k^{-5/3}$ at the largest scales and then shallower at smaller ones (see § 13.2), before steepening again at $k\lambda _{\mathrm {R}}\gtrsim 1$. The disruption ($\lambda _{\mathrm {D}}$) and dissipation ($\lambda _{\eta }$) scales are given by (13.15) and (13.16), respectively. Whether the $k^{-11/5}$ spectrum starts at $\lambda _{\mathrm {R}}$ (§ 13.4.1) or at $\lambda _{\mathrm {D}}$ (§ 13.3.3) is not obvious because how the spectra at scales below and above $\lambda _{\mathrm {R}}$ are connected remains an open question.

Figure 34

Figure 35. Spectra of Elsasser field for (c) heavily imbalanced RMHD turbulence ($\varepsilon ^+/\varepsilon ^-\approx 16$), (a) similarly imbalanced turbulence in an RMHD-like model of a low-beta collisionless plasma with FLR effects, and (b) balanced turbulence in the same model. Purple-to-yellow colour scale shows time evolution of the spectra. The spectrum of the stronger Elsasser field in (a) does not reach a steady state, with spectral break moving to larger scales. Measurement of energy fluxes in these simulations shows that (a) is not a constant-flux solution, whereas (b) is. These results are from Meyrand et al. (2021).

Figure 35

Figure 36. Cartoon of the 2D spectrum of broad-band-forced weak turbulence. Schematic contour lines of $E_{\mathrm {2D}}(k_{\perp },k_{\parallel })$ are the brown dotted lines. Red arrows are energy fluxes: $\varPi (k_{\perp },k_{\parallel })\sim \varepsilon L _{\parallel }$ arriving from the forcing wavenumbers to the ‘2D condensate’ at each $k_{\parallel }$, $\varepsilon L _{\parallel }\varDelta k _{\parallel }$ flowing through the condensate (see (A26)), and $\varepsilon = \mathrm {const}$ after the transition to critically balanced cascade (cf. figure 40a).

Figure 36

Figure 37. (a) The 2D spectrum, $E_{\mathrm {res,2D}}(k_{\perp },k_{\parallel })/E_{\mathrm {res,2D}}(k_{\perp },0)$ and (b) the 1D, $k_{\perp }^{-1}$- compensated spectrum of residual energy from WT simulations by Wang et al. (2011) ($512^3$, broad-band forced at $k_{\parallel } = 1,\ldots,16$ and $k_{\perp }=1,2$; © AAS, reproduced with permission).

Figure 37

Figure 38. Geometry of velocity, magnetic and Elsasser fields ($\boldsymbol {B}_0$ is perpendicular to the page). All four fields are aligned: the angles $\theta$, $\theta ^{ub}$, $\theta ^\pm$ are all small (although they do not have to be). Also shown are the axes along which the $\lambda$ and $\xi$ scales in (6.4) are meant to be calculated (along and across $\boldsymbol {Z}_{\perp }^+$, respectively). The angle between these axes is $\phi = \pi /2 - \theta$ and so $\cos \phi = \sin \theta$.

Figure 38

Figure 39. A direct test of the relations (B6) in globally balanced ($\varepsilon ^+/\varepsilon ^-=1$, panels (a,c)) and imbalanced ($\varepsilon ^+/\varepsilon ^-=10$, panels (b,d)) RMHD simulations by Mallet & Schekochihin (2011) (these are the same unpublished simulations as tabulated in figure 19). The plots show histograms of $4\sin ^2\theta /R_{\mathrm {E}}\sin ^2\theta ^{ub}$ (a,b) and $(1-R_{\mathrm {A}})^2R_{\mathrm {E}}/16\cos ^2\theta$ (c,d) vs. perpendicular point separation $\lambda$. Note that the first relation in (B6) is reasonably well satisfied even in the globally balanced simulation.

Figure 39

Figure 40. Sketch of the 2D spectra (C23) of RMHD turbulence: (a) in the 2D wave-number plane; (b) at constant $k_{\perp }$; (c) at constant $k_{\parallel }$. Note that $k_{\parallel }$ here is measured along the perturbed field, not the $z$ axis (see discussion in § 5.3).

Figure 40

Figure 41. The outer solution for a tearing mode in a large-aspect-ratio sheet (adapted from Loureiro et al.2007). $\varDelta '$ measures the discontinuity of $\partial _x\psi$ at $x=0$ (see (D9)).

Figure 41

Figure 42. Tearing growth rate $\gamma$ vs. $k_y$: the Coppi et al. (1976) solution (D36) for $k_y\ll k_*$, where $k_*$ is given in (D32), and the FKR solution (D34) at $k_y\gg k_*$. The viscous version of the latter takes over at $k_y\gg k_\mathrm {visc}$, where $k_\mathrm {visc}\lambda \sim S_\lambda ^{-1/4}\mathrm {Pm}^{-5/8}$. This cartoon is for $\mathrm {Pm}\ll 1$; if $\mathrm {Pm}\gg 1$, the viscous-FKR scaling starts at $k_*$.

Figure 42

Figure 43. (a) An $X$-point, shown during the nonlinear stage of tearing mode, (b) SP current sheet, formed later on, upon collapse of that $X$-point (adapted from a 2D RMHD numerical simulation by Loureiro et al.2005). The black lines are magnetic-field lines (constant-flux contours). The in-plane field reverses direction along the middle of the domain that is shown. In the notation of Appendix D.4.1, the length of the sheet is $\ell$ and its width is $\delta$.

Figure 43

Figure 44. Plasmoid instability in current sheets with, from top to bottom, $S_\xi =10^4, 10^5, 10^6, 10^7, 10^8$. The domain shown is $0.12$ of the full length of the sheet. This plot is adapted from Samtaney et al. (2009), who confirmed the scalings (D52) numerically. (Reprinted with permission from Samtaney et al.2009, copyright (2009) by the American Physical Society.)

Figure 44

Figure 45. Formation of a sheet from an $X$-point in the MRX experiment at Princeton (reprinted from Yamada et al.1997 with the permission of AIP Publishing).

Figure 45

Figure 46. This is a plot from Huang et al. (2017) (© AAS, reproduced with permission) illustrating the evolution of tearing perturbations of an evolving sheet in a 2D MHD simulation with $S_\xi \sim 10^6$ and $\mathrm {Pm}\ll 1$. Their $(x,y,z)$ are my $(y,z,x)$, their $L$ is my $\xi$ (sheet length), their $a$ is my $\lambda$ (sheet width), their $\tau _\mathrm {A}$ is my $\varGamma ^{-1}\sim \xi /v_{\mathrm {A}}$ (characteristic time of the sheet evolution), their $\delta$ is my $\delta _{\mathrm {in}}$ (width of the tearing inner layer). The colour in the upper halves of their panels shows out-of-page current (colour bar ‘$J_y$’) and in the lower halves the outflow velocity along the sheet (colour bar ‘$v_x$’). The solid magenta lines are separatrices demarcating two ‘global’ coalescing islands that they set up to form the sheet. The four snapshots are (a) at the moment when the tearing mode goes nonlinear ($w\sim \delta _{\mathrm {in}}$; see Appendix D.2), (b) a little later, showing formation of secondary sheets (and so collapse of inter-island $X$-points), (c) later on, with a secondary instability of these sheets manifesting itself as more plasmoids appear (cf. Appendix D.5.2), and (d) in saturation, which for them is the period of stochastic but statistically steady and fast (with a rate independent of $S_\xi$) reconnection and which obviously also corresponds to islands reaching the width of the sheet and starting to form a stochastic chain, moving and coalescing (see Appendix D.6). Note that all of this evolution happens within one Alfvén time, although the initial-growth stage does need a few Alfvén times to get going.

Figure 46

Figure 47. A plot, adapted from Tenerani et al. (2015b) (© AAS, reproduced with permission), of the $b_x=-ik_y\psi (x)$ profiles (cf. figure 41) for nested tearing modes: primary (black), secondary (red) and tertiary (blue). They extracted these from a direct numerical simulation of a recursively tearing sheet. This is a remarkably clean example of the similarity of tearing at ever smaller scales.

Figure 47

Figure 48. Contour plot of the magnetic flux function illustrating the open flux. This is taken from a section of a 2D MHD simulation of a plasmoid chain; the centre of the sheet is somewhere far away on the left. (Reprinted with permission from Uzdensky et al. (2010), copyright (2010) by the American Physical Society.)

Figure 48

Figure 49. (a) Reconnection rate (blue squares), normalised, in my notation, to $u_yv_{\mathrm {A}y}$, in 2D MHD $\mathrm {Pm}=1$ simulations by Loureiro et al. (2012). Transition at $S_\ell \sim 10^4$ from the SP scaling to the fast-reconnection regime (D81) is manifest. (b) Plasmoid-width distribution function in the same simulations, from the same paper, confirming the scaling predicted by Uzdensky et al. (2010) (see Appendix D.6.1). (Reprinted from Loureiro et al. (2012) with the permission of AIP Publishing.)

Figure 49

Figure 50. A 3D, turbulent plasmoid (flux-rope) chain obtained in the simulations of Huang & Bhattacharjee (2016) (© AAS, reproduced with permission).

Figure 50

Figure 51. Simulations of stochastic reconnection by Kowal et al. (2009): (a) arrows are magnetic fields, colour shows (turbulent) currents; (b) reconnection rate $V_\mathrm {rec}$ vs. injected power $P_\mathrm {inj}$, which, in my notation, are $u_x$ and $\varepsilon$, respectively – this plot, taken from Lazarian et al. (2015), shows $u_x\propto \varepsilon ^{1/2}$, in accordance with (D111).