Inverse Energy Cascade of Fast Magnetosonic Turbulence in the Heliosheath

Author(s):  
Bertalan Zieger

<p>The solar wind in the heliosheath beyond the termination shock (TS) is a non-equilibrium collisionless plasma consisting of thermal solar wind ions, suprathermal pickup ions (PUI) and electrons. In such multi-ion plasma, two fast magnetosonic wave modes exist: the low-frequency fast mode that propagates in the thermal ion component and the high-frequency fast mode that propagates in the suprathermal PUI component [<em>Zieger et al.</em>, 2015]. Both fast modes are dispersive on fluid and ion scales, which results in nonlinear dispersive shock waves. In this talk, we briefly review the theory of dispersive shock waves in multi-ion collisionless plasma. We present high-resolution three-fluid simulations of the TS and the heliosheath up to 2.2 AU downstream of the TS. We show that downstream propagating nonlinear magnetosonic waves grow until they steepen into shocklets (thin current sheets), overturn, and start to propagate backward in the frame of the downstream propagating wave, as predicted by theory <em>[McKenzie et al</em>., 1993; <em>Dubinin et al.</em>, 2006]. The counter-propagating nonlinear waves result in fast magnetosonic turbulence far downstream of the shock. Since the high-frequency fast mode is positive dispersive on fluid scale, energy is transferred from small scales to large scales (inverse energy cascade). Thermal solar wind ions are preferentially heated by the turbulence. Forward and reverse shocklets in the heliosheath can efficiently accelerate both ions and electrons to high energies through the shock drift acceleration mechanism. We validate our three-fluid simulations with in-situ high-resolution Voyager 2 magnetic field and plasma observations at the TS and in the heliosheath. Our simulations reproduce the magnetic turbulence spectrum with a spectral slope of -5/3 observed by Voyager 2 in frequency domain [<em>Fraternale et al</em>., 2019]. However, since Taylor’s hypothesis is not true for fast magnetosonic perturbations in the heliosheath, the inertial range of the turbulence spectrum is not a Kolmogorov spectrum in wave number domain. </p>

2010 ◽  
Vol 656 ◽  
pp. 448-457 ◽  
Author(s):  
ANDREAS VALLGREN ◽  
ERIK LINDBORG

High-resolution simulations of forced quasi-geostrophic (QG) turbulence reveal that Charney isotropy develops under a wide range of conditions, and constitutes a preferred state also in β-plane and freely decaying turbulence. There is a clear analogy between two-dimensional and QG turbulence, with a direct enstrophy cascade that is governed by the prediction of Kraichnan (J. Fluid Mech., vol. 47, 1971, p. 525) and an inverse energy cascade following the classic k−5/3 scaling. Furthermore, we find that Charney's prediction of equipartition between the potential and kinetic energy in each of the two horizontal velocity components is approximately fulfilled in the inertial ranges.


2020 ◽  
Vol 12 (4) ◽  
pp. 676 ◽  
Author(s):  
Yong Yang ◽  
Wei Tu ◽  
Shuying Huang ◽  
Hangyuan Lu

Pansharpening is the process of fusing a low-resolution multispectral (LRMS) image with a high-resolution panchromatic (PAN) image. In the process of pansharpening, the LRMS image is often directly upsampled by a scale of 4, which may result in the loss of high-frequency details in the fused high-resolution multispectral (HRMS) image. To solve this problem, we put forward a novel progressive cascade deep residual network (PCDRN) with two residual subnetworks for pansharpening. The network adjusts the size of an MS image to the size of a PAN image twice and gradually fuses the LRMS image with the PAN image in a coarse-to-fine manner. To prevent an overly-smooth phenomenon and achieve high-quality fusion results, a multitask loss function is defined to train our network. Furthermore, to eliminate checkerboard artifacts in the fusion results, we employ a resize-convolution approach instead of transposed convolution for upsampling LRMS images. Experimental results on the Pléiades and WorldView-3 datasets prove that PCDRN exhibits superior performance compared to other popular pansharpening methods in terms of quantitative and visual assessments.


1990 ◽  
Vol 15 (2) ◽  
pp. A10 ◽  
Author(s):  
David J. Sahn ◽  
Diana Tasker ◽  
Sandra Hagen-Ansert ◽  
Axel Brisken ◽  
Scott Corbett

Sign in / Sign up

Export Citation Format

Share Document