Abstract

Magnetic fields are ubiquitous in universe, space, and laboratory plasmas. Especially, self-generated magnetic fields are important to know the mind of nature. The formation of Weibel-mediated collisionless shock is studied theoretically as a structure formation by the linear plasma wave growth, nonlinear saturation, and mode–mode coupling. Following a series of computer simulations and experimental studies of the physics, a simple model equation is proposed here to describe the time evolution of magnetic turbulence. Weibel instability is saturated by magnetic pressure, and thicker filaments continue to be generated by current coalescence (magnetic reconnection) mechanism. The model equation concludes the fact that the filament spacing increases linearly in time, and the magnetic energy power spectrum is given as Bk2 ∝ k−2. The time evolution of the turbulence is characterized with the cascade toward smaller k. Such inverse cascade is well-known in 2D hydrodynamic turbulence such as a typhoon or hurricane formation and is known to have Kolmogorov spectrum k−5/3. Although only a small difference in power, the physics of inverse cascades is very different as shown in the present paper. With use of Alfvén current limit condition, the criteria of collisionless shock formation are evaluated. The present theory is compared to corresponding experiments done with Omega and NIF lasers and a variety of PIC simulations. The theory is also applied to evaluate the strength of magnetic field near the shock front of the supernova remnant SN1006. The enhancement of magnetic field of about 25 μG is concluded in the present theory. Finally, a universality of the model equation is shown by applying the theory to the turbulent mixing due to Rayleigh–Taylor instability at the contact surface of two fluids in a gravitational or inertial force, which is very important in compressing plasma such as inertial confinement fusion by implosion. It is shown that the well-known evolution physics, mixing layer of the two fluids grows in proportion to (time)2, can be explained with the same model equation.

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