Dhrubaditya Mitra

only search my website

On Magnetic Reconnection and Energization of Charged Particles.

The Solar Corona is a fascinating object. From spectral observations the temperature of the corona is estimated to be more than a million Kelvins. But the temperature of the inner regions of the sun, e.g., the photosphere is much less. Hence the corona must have its own heating mechanism. This mechanism is believed to be dominated by the coronal magnetic field. The physics of the corona is determined by the equations that determine motions of plasma. The equations of magnetohydrodynamics may be a reasonable approximation. The resistivity of the corona is very low. In this regime, it is useful to consider the coronal physics in the limit (but not equal to) of zero resistivity. This is the limit where the topology of magnetic field lines are almost a conserved quantity. Then the topology of the magnetic field lines are supposed to change suddenly giving rise to sudden dissipation of energy. A phenomenon known as magnetic reconnection. The aim of this project is to understand this phenomenon. In addition, let us also ask the question, where does the dissipated energy go ? Normally, the answer is that the dissipated energy goes into the thermal modes of the plasma (the kinetic energy of the electrons and the ions). But it could also happen that the electrons (and ions) exited by the dissipative process cannot be described by a thermal distribution. The second aim of this project is to study this possibility.

Our first paper on this topic is submitted to the ArXiv.

Introduction

Let us first look at the problem in the spirit of a numerical experiment. We study the same setup as used by Loureiro et al but in three dimensions.

Numerical Experiments

Our domain is a periodic box of size $2\pi$ in each direction. We solve for the equations of isothermal magnetohydrodynamics, \begin{eqnarray} \partial_t (\rho U_i) + {\rm div}(\rho U_iU_j) &=& -{\rm grad}(p) + \nu\nabla^2 U_i + \frac{1}{\mu_0}({\bf J}\times{\bf B}) + {\bf f} \\ \partial_t \rho + {\rm div}({\bf U}\rho) &=& 0 \\ c^2_s &=& \gamma \frac{p}{\rho} = {\rm constant}\\ \partial_t {\bf B} &=& {\rm curl}({\bf U}\times{\bf B} -\eta {\bf J} + \eta {\bf J}_{\rm ini}) \end{eqnarray} where ${\bf J} = {\rm curl}({\bf B})$. Of particular interest is the last term in the induction equation. This is a term with negative (magnetic) diffusivity. We interpret it as a term that injects energy in to the induction equation. The function ${\bf J}_{\rm ini}$ is a function of only one coordinate ($x$ in the present case) given by \begin{equation} {\bf J}_{\rm ini} = \frac{d^2}{dx^2} [\tanh(x)]^2 \end{equation} Initially both the velocity field and the magnetic fields are taken to be zero. After about one diffusive time, we reach a statistically stationary state. The first thing we want to do is to calculate the reconnection rate. A suggestion from Kowal et al to measure the reconnection rate is the following:

  1. Calculate the line integral of the Electric field \begin{equation} {\bf E} = {\bf u}\times {\bf B} \end{equation} along a closed contour enclosing the reconnection region, in the following fashion \begin{equation} \oint ({\rm sign} B_y){\vec E}\cdot d{\vec \ell} \end{equation} In our code we implement it by first calculating line averages of the electric field along the $z$ direction. \begin{equation} \langle{\bf E}\rangle_{z} \equiv \int_{L_z} {\vec E}\cdot d{\vec \ell} \end{equation} Then the contour integral is given by \begin{equation} \oint ({\rm sign} B_y){\vec E}\cdot d{\vec \ell} = \langle{\bf E}\rangle_{z}(-A,0) + \langle{\bf E}\rangle_{z}(A,0) \end{equation}
  2. The reconnection speed is given by \begin{equation} V_{\rm rec} \equiv \frac{1}{\mid {\bf B}_{\rm max} \mid} \oint ({\rm sign} B_y){\vec E}\cdot d{\vec \ell} \end{equation} In the movie below we show how our simulation evolves.

In this movie we show four different quantities, in the $x-y$ plane: (clockwise from top left) (a) $\langle{\bf E}\rangle_{z}$; (b) $\langle B_y \rangle_z$; (c) $\langle{\bf E}\rangle_{z}$ (black) , $\langle B_y\rangle_z$ (blue) and $\langle J_z \rangle_z$ (red) as a function of $x$ at $y=0$; and (d) $\langle J_z \rangle_z$.

Dimensionaless parameters

To understand energization, let us now look at the dimensionless parameteters of the problem. For the fluid, we solve the isothermal MHD equations which takes the following dimensionless form \begin{eqnarray} \partial_t (\rho U_i) + {\rm div}(\rho U_iU_j) &=& -\frac{1}{{\rm M}^2}{\rm grad}(p) + \frac{1}{{\rm Re}}\nabla^2 U_i + \frac{1}{\varepsilon}\frac{1}{{\rm Ma}^2}({\bf J}\times{\bf B}) + {\bf f} \\ \partial_t \rho + {\rm div}({\bf U}\rho) &=& 0 \\ c^2_s &=& \gamma \frac{p}{\rho} = 1.\\ \partial_t {\bf B} &=& {\rm curl}({\bf U}\times{\bf B} -\frac{1}{\varepsilon}\frac{1}{{\rm Re}_{\rm M}} \left[ {\bf J} + {\bf J}_{\rm ini} \right] \end{eqnarray} where
  1. The Mach number: \begin{equation} {\rm Ma} = \frac{u_{\rm rms}}{c_{\rm s}} \end{equation}
  2. The Alfvenic Mach number: \begin{equation} {\rm Ma}_{\rm A} = \frac{u_{\rm rms}}{v_{\rm A}} \end{equation}
  3. The Alfven velocity \begin{equation} v_{\rm A} = \frac{B_{\rm max}}{\sqrt{\rho_0\mu_0}} \end{equation}
  4. The Reynolds number \begin{equation} {\rm Re} = \frac{u_{\rm rms}L}{\nu } \end{equation}
  5. The magnetic Reynolds number \begin{equation} {\rm Re}_{\rm M} = \frac{u_{\rm rms}L}{\eta } \end{equation}
where $L$ is an integral length of the system, e.g., the length of the current sheet and and $\lambda$ is the width of the current sheet. To non-dimensionalize the current we have used \begin{equation} J \approx \frac{1}{\lambda} B_{\rm max} \end{equation} and \begin{equation} \varepsilon = \frac{\lambda}{L} \end{equation} The dimensional form of the equation of motion for the charged particles (in the test particle approximation) is given by \begin{eqnarray} \dot{{\bf x}} &=& {\bf v} \\ \dot{{\bf v}} &=& \frac{q}{m}\left[ -{\bf u}\times{\bf B} + {\bf v}\times B + \eta {\bf J} \right] \end{eqnarray} Non-dimensional form of this equation looks like: \begin{eqnarray} \dot{{\bf x}} &=& \frac{1}{{\rm Ma}}{\bf v} \\ \dot{{\bf v}} &=& {\rm Lo}\left[ -{\rm Ma}{\bf u}\times{\bf B} + {\bf v}\times B + \frac{{\rm Ma}}{\varepsilon{\rm Re}_{\rm M}}{\bf J} \right] \end{eqnarray}
  1. Where the Lorentz number is \begin{equation} {\rm Lo} = \tau_{\rm L}\omega_{\rm c} \end{equation}
  2. The integral time scale of turbulence, \begin{equation} \tau_{\rm L} = \frac{L}{u_{\rm rms}} \end{equation}
  3. The cyclotron frequency, \begin{equation} \omega_{\rm c} = \frac{q B_{\rm max}}{m} \end{equation}
  4. We have also assumed that the characteristic scale of the speed of the particles is set by the thermal motion, hence \begin{equation} \left[ \mid{\bf v}\mid \right] \approx c_{\rm s} \end{equation}
In the table below we try to estimate what these dimensionless parameters are in various circumstances.
${\rm Ma}$ ${\rm Ma}_{\rm A}$ ${\rm Re}$ ${\rm Re}_{\rm M}$ ${\rm Lo}$ $\varepsilon$
MHD simulations $\approx 0.1$ $10$-$0.1$ $100$-$500$ $100$-$500$ ${\rm Lo}$ $\approx 1/6$
Solar Corona $\approx 0.1$ $\approx 0.1$ $10^6$ $??$ $\approx 10^{16}$ (electron) $??$
ISM $??$ $??$ $??$ $??$ $??$ (electron) $??$
Laboratory Plasma $??$ $??$ $??$ $??$ $??$ (electron) $??$
The Lorentz number is always huge in astrophysical situation. This implies that simulating such a situation in a computer is hopeless. If we resolve the time scale over which the electron/ion makes one gyro-rotation we would never be able to run the simulations so long as to meaningfully evolve any turbulent velocity/magnetic field. There are two ways out of this connundrum. One is to choose a much smaller ${\rm Lo}$ somethings of the order of $100$, this is indeed possible. But this would not correspond to any fundamental particle but maybe charged dust.
The other one, which is the more interesting one is to average the equations over the very short time scale of one-over-gyrofrequency and write effective equations at larger time scales. This would be the guided center approximation. We now need to write down the equations of a charged particle in guiding center approximation.

Collaobrators

This is very much a work in progress, done jointly with Rohit Sharma and Divya Oberoi at NCRA, Pune.

Computational Resources

We use the pencil-code, which is a open-source MPI parallelized solver the partial differential equations (PDEs) that are relevant to fluid and magnetohydrodynamic turbulence. The code shows (weak) linear scaling up to 70, 000 cores. I am one of the core developers of this code. As part of other SNIC projects the code has been ported and ran in abisko.

Last modified: Wed Apr 25 22:28:34 CEST 2012