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Diffusion and radiation in magnetized collisionless plasmas with small-scale Whistler turbulence

Published online by Cambridge University Press:  22 March 2016

Brett D. Keenan*
Affiliation:
Department of Physics and Astronomy, University of Kansas, Lawrence, KS 66045, USA
Mikhail V. Medvedev
Affiliation:
Department of Physics and Astronomy, University of Kansas, Lawrence, KS 66045, USA
*
Email address for correspondence: bdkeenan@ku.edu
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Abstract

Magnetized high-energy-density plasmas can often have strong electromagnetic fluctuations whose correlation scale is smaller than the electron Larmor radius. Radiation from the electrons in such plasmas – which markedly differs from both synchrotron and cyclotron radiation – is tightly related to their energy and pitch-angle diffusion. In this paper, we present a comprehensive theoretical and numerical study of particle transport in cold, ‘small-scale’ Whistler-mode turbulence and its relation to the spectra of radiation simultaneously produced by these particles. We emphasize that this relation is a superb diagnostic tool of laboratory, astrophysical, interplanetary and solar plasmas with a mean magnetic field and strong small-scale turbulence.

Information

Type
Research Article
Copyright
© Cambridge University Press 2016 
Figure 0

Figure 1. Average square pitch angle versus normalized time. Relevant parameters are ${\it\beta}=0.25$, (number of simulation particles) $N_{p}=5000$, $k_{min}=32{\rm\pi}$, $k_{max}=10k_{kmin}$, $\langle {\it\delta}B^{2}\rangle ^{1/2}/B_{0}=0.1$, ${\it\Omega}_{ce}=1$, ${\it\rho}\approx 400$, ${\it\chi}\approx 0.04$ and ${\it\mu}=4$. The linear nature of the curve (solid, ‘red’) confirms the diffusive nature of the pitch-angle transport. Here, the dashed (‘blue’) line indicates a line of best fit (simple linear regression) with Pearson correlation coefficient: 0.9998.

Figure 1

Figure 2. Average square change in electron energy (in simulation units) versus normalized time. Relevant parameters are ${\it\beta}=0.25$, (number of simulation particles) $N_{p}=5000$, $k_{min}=64{\rm\pi}$, $k_{max}=10k_{kmin}$, $\langle {\it\delta}B^{2}\rangle ^{1/2}/B_{0}=0.1$, ${\it\Omega}_{ce}=1$, ${\it\rho}\approx 400$, ${\it\chi}\approx 0.04$ and ${\it\mu}=4$. The linear nature of the curve (solid, ‘red’) confirms the diffusive nature of the energy transport. Here, the dashed (‘blue’) line indicates a line of best fit (simple linear regression) with Pearson correlation coefficient: 0.9999.

Figure 2

Figure 3. Pitch-angle diffusion coefficient, $D_{{\it\alpha}{\it\alpha}}$ versus the normalized electron velocity, ${\it\beta}$. Relevant simulation parameters include: $N_{p}=5000$, $k_{min}=32{\rm\pi}$, $k_{max}=10k_{kmin}$, $\langle {\it\delta}B^{2}\rangle ^{1/2}/B_{0}=0.1$, ${\it\Omega}_{ce}=1$, ${\it\chi}\approx 0.02$ and ${\it\mu}=4$. The (purple) empty ‘squares’ indicate the $D_{{\it\alpha}{\it\alpha}}$’s obtained directly from simulation data (as the slope of $\langle {\it\alpha}^{2}\rangle$ versus time), while the (green) filled ‘circles’ are the analytical pitch-angle diffusion coefficients, given by (2.8). Numerical error bars (red, lines centred in the ‘squares’) from the standard deviations on each $\langle {\it\alpha}^{2}\rangle$ also appear. Note: that the symbol sizes are much greater than the statistical/numerical error bars.

Figure 3

Figure 4. Energy diffusion coefficient, $D_{WW}$ versus the normalized electron velocity, ${\it\beta}$. Relevant simulation parameters include: $N_{p}=5000$, $k_{min}=32{\rm\pi}$, $k_{max}=10k_{kmin}$, $\langle {\it\delta}B^{2}\rangle ^{1/2}/B_{0}=0.1$, ${\it\Omega}_{ce}=1$, ${\it\chi}\approx 0.02$ and ${\it\mu}=4$. The (blue) empty ‘squares’ indicate the $D_{WW}$’s obtained directly from simulation (as the slope of $\langle {\rm\Delta}W_{e}^{2}\rangle$ versus time), while the (red) filled ‘circles’ are the analytical energy diffusion coefficients, given by (2.40). Numerical error bars (green, lines centred in the ‘squares’) from the standard deviations on each $\langle {\it\alpha}^{2}\rangle$ also appear. Note: that the symbol sizes are much greater than the statistical/numerical error bars.

Figure 4

Figure 5. Pitch-angle diffusion coefficient, $D_{{\it\alpha}{\it\alpha}}$ versus the inverse of magnetic field correlation scale, ${\it\lambda}_{B}^{-1}$. Relevant simulation parameters include: ${\it\gamma}=3$, $N_{p}=1000$, $k_{min}=8{\rm\pi}$, $16{\rm\pi}$, $32{\rm\pi}$, $64{\rm\pi}$ and $128{\rm\pi}$, $k_{max}=10k_{kmin}$ (for each $k_{kmin}$), $\langle {\it\delta}B^{2}\rangle ^{1/2}/B_{0}=0.1$, ${\it\Omega}_{ce}=1$, ${\it\chi}\approx 0.02$ and ${\it\mu}=4$. For each data point, the theoretical and numerical results differ only by a small factor of $O(1)$.

Figure 5

Figure 6. Energy diffusion coefficient, $D_{WW}$ versus the inverse of magnetic field correlation scale, ${\it\lambda}_{B}^{-1}$. Relevant simulation parameters include: ${\it\gamma}=3$, $N_{p}=1000$, $k_{min}=8{\rm\pi}$, $16{\rm\pi}$, $32{\rm\pi}$, $64{\rm\pi}$ and $128{\rm\pi}$, $k_{max}=10k_{kmin}$ (for each $k_{kmin}$), $\langle {\it\delta}B^{2}\rangle ^{1/2}/B_{0}=0.1$, ${\it\Omega}_{ce}=1$, ${\it\chi}\approx 0.02$ and ${\it\mu}=4$. The theoretical and numerical results differ only by a small factor of $O(1)$.

Figure 6

Figure 7. Pitch-angle diffusion coefficient, $D_{{\it\alpha}{\it\alpha}}$ versus the magnetic spectral index, ${\it\mu}$. Relevant parameters are $N_{p}=2000$, $k_{min}=32{\rm\pi}$, $k_{max}=10k_{max}$, $\langle {\it\delta}B^{2}\rangle ^{1/2}/B_{0}=0.1$, ${\it\Omega}_{ce}=1$ and ${\it\chi}\approx 0.05$. Notice that the numerical results have nearly the same functional dependence on ${\it\mu}$ as the analytical squares, as given by (2.8).

Figure 7

Figure 8. Energy diffusion coefficient, $D_{WW}$ versus the magnetic spectral index, ${\it\mu}$. Relevant parameters are $N_{p}=2000$, $k_{min}=32{\rm\pi}$, $k_{max}=10k_{max}$, $\langle {\it\delta}B^{2}\rangle ^{1/2}/B_{0}=0.1$, ${\it\Omega}_{ce}=1$ and ${\it\chi}\approx 0.05$.

Figure 8

Figure 9. Radiation spectrum for a mono-energetic, isotropic distribution of ${\it\gamma}=5$ (${\it\chi}\sim 1$; ${\it\rho}\approx 928$; $\langle {\it\delta}B^{2}\rangle ^{1/2}/B_{0}=0.1$) electrons moving through small-scale Whistler turbulence. The frequency is normalized by ${\it\omega}_{jn}={\it\gamma}^{2}k_{min}{\it\beta}c$ – the relativistic jitter frequency. The solid (‘red’) curve is from simulation data, whereas the dashed (‘blue’) curve is the analytic estimate. Clearly, the spectrum is well represented by a superposition of synchrotron $+$ jitter components. Note the lower-frequency synchrotron component and a higher-frequency power-law component corresponding to the small-angle jitter radiation.

Figure 9

Figure 10. Radiation spectrum for a mono-energetic, isotropic distribution of ${\it\beta}=0.125$ electrons (${\it\chi}\sim 0.04$; ${\it\rho}\approx 160$; $\langle {\it\delta}B^{2}\rangle ^{1/2}/B_{0}=0.2$; ${\it\Omega}_{ce}=2$; $k_{min}=64{\rm\pi}$; $k_{max}=10k_{min}$; ${\it\mu}=5$; $T=50T_{g}$); superimposed with a spectrum given a population of ${\it\gamma}=4$ electrons (${\it\chi}\sim 1$; ${\it\rho}\approx 367$; $\langle {\it\delta}B^{2}\rangle ^{1/2}/B_{0}=0.1$; ${\it\Omega}_{ce}=0.512$; $k_{min}={\rm\pi}$; $k_{max}=10{\rm\pi}$; ${\it\mu}=4$; $T=5T_{g}$). The normalization on the $y$-axis is arbitrary, whereas the $x$-axis is normalized to the ${\it\beta}=0.125$ population’s cyclotron frequency, i.e. ${\it\Omega}_{ce}=2$. The ‘thick’ solid (‘red’) curve is from simulation data for the ${\it\beta}=0.125$ population, the dashed (‘blue’) curve is the corresponding analytic estimate for pure pseudo-cyclotron radiation, the ‘thin’ solid line is the simulation data for the ${\it\gamma}=4$ population and the ‘dot-dashed’ (‘black’) line is the ${\it\gamma}=4$ analytic estimate. Notice, for the ${\it\beta}=0.125$ spectrum, that the spectrum peaks near the cyclotron frequency, ${\it\Omega}_{ce}$ – hence we see the signature of cyclotron radiation. The additional harmonics, which are purely a relativistic effect, are the signature of emerging synchrotron radiation.