Shocks in unmagnetized plasma with a shear flow: Stability and magnetic field generation

A pair of curved shocks in a collisionless plasma is examined with a two-dimensional particle-in-cell (PIC) simulation. The shocks are created by the collision of two electron-ion clouds at a speed that exceeds everywhere the threshold speed for shock formation. A variation of the collision speed along the initially planar collision boundary, which is comparable to the ion acoustic speed, yields a curvature of the shock that increases with time. The spatially varying Mach number of the shocks results in a variation of the downstream density in the direction along the shock boundary. This variation is eventually equilibrated by the thermal diffusion of ions. The pair of shocks is stable for tens of inverse ion plasma frequencies. The angle between the mean flow velocity vector of the inflowing upstream plasma and the shock's electrostatic field increases steadily during this time. The disalignment of both vectors gives rise to a rotational electron flow, which yields the growth of magnetic field patches that are coherent over tens of electron skin depths.Comment: 10 pages, 10 figures accepted for publication in Physics of Plasma

Surfatron and stochastic acceleration of electrons in astrophysical plasmas

Electron acceleration by large amplitude electrostatic waves in astrophysical plasmas is studied using particle-in-cell (PIC) simulations. The waves are excited initially at the electron plasma frequency $\omega_{\rm pe}$ by a Buneman instability driven by ion beams: the parameters of the ion beams are appropriate for high Mach number astrophysical shocks, such as those associated with supernova remnants (SNRs). If $\omega_{\rm pe}$ is much higher than the electron cyclotron frequency $\Omega_{\rm e}$, the linear phase of the instability does not depend on the magnitude of the magnetic field. However, the subsequent time evolution of particles and waves depends on both $\omega_{\rm pe}/\Omega_{\rm e}$ and the size of the simulation box $L$. If $L$ is equal to one wavelength, $\lambda_0$, of the Buneman-unstable mode, electrons trapped by the waves undergo acceleration via the surfatron mechanism across the wave front. This occurs most efficiently when $\omega_{\rm pe}/\Omega_{\rm e} \simeq 100$: in this case electrons are accelerated to speeds of up $c/2$ where $c$ is the speed of light. In a simulation with $L=4\lambda_0$ and $\omega_{\rm pe}/\Omega_{\rm e} = 100$, it is found that sideband instabilities give rise to a broad spectrum of wavenumbers, with a power law tail. Some stochastic electron acceleration is observed in this case, but not the surfatron process. Direct integration of the electron equations of motion, using parameters approximating to those of the wave modes observed in the simulations, suggests that the surfatron is compatible with the presence of a broad wave spectrum if $\omega_{\rm pe}/\Omega_{\rm e}> 100$. It is concluded that a combination of stochastic and surfatron acceleration could provide an efficient generator of mildly relativistic electrons at SNR shocks

Interactive Visualization of 3D Histopathology in Native Resolution

We present a visualization application that enables effective interactive visual analysis of large-scale 3D histopathology, that is, high-resolution 3D microscopy data of human tissue. Clinical work flows and research based on pathology have, until now, largely been dominated by 2D imaging. As we will show in the paper, studying volumetric histology data will open up novel and useful opportunities for both research and clinical practice. Our starting point is the current lack of appropriate visualization tools in histopathology, which has been a limiting factor in the uptake of digital pathology. Visualization of 3D histology data does pose difficult challenges in several aspects. The full-color datasets are dense and large in scale, on the order of 100,000 × 100,000× 100 voxels. This entails serious demands on both rendering performance and user experience design. Despite this, our developed application supports interactive study of 3D histology datasets at native resolution. Our application is based on tailoring and tuning of existing methods, system integration work, as well as a careful study of domain specific demands emanating from a close participatory design process with domain experts as team members. Results from a user evaluation employing the tool demonstrate a strong agreement among the 14 participating pathologists that 3D histopathology will be a valuable and enabling tool for their work

Particle-in-cell simulation study of a lower-hybrid shock

The expansion of a magnetized high-pressure plasma into a low-pressure ambient medium is examined with particle-in-cell simulations. The magnetic field points perpendicular to the plasmas expansion direction and binary collisions between particles are absent. The expanding plasma steepens into a quasi-electrostatic shock that is sustained by the lower-hybrid (LH) wave. The ambipolar electric field points in the expansion direction and it induces together with the background magnetic field a fast E cross B drift of electrons. The drifting electrons modify the background magnetic field, resulting in its pile-up by the LH shock. The magnetic pressure gradient force accelerates the ambient ions ahead of the LH shock, reducing the relative velocity between the ambient plasma and the LH shock to about the phase speed of the shocked LH wave, transforming the LH shock into a nonlinear LH wave. The oscillations of the electrostatic potential have a larger amplitude and wavelength in the magnetized plasma than in an unmagnetized one with otherwise identical conditions. The energy loss to the drifting electrons leads to a noticeable slowdown of the LH shock compared to that in an unmagnetized plasma. Published by AIP Publishing.Funding Agencies|EPSRC [EP/N022696/1]</p

Interaction for Immersive Analytics

International audienceIn this chapter, we briefly review the development of natural user interfaces and discuss their role in providing human-computer interaction that is immersive in various ways. Then we examine some opportunities for how these technologies might be used to better support data analysis tasks. Specifically, we review and suggest some interaction design guidelines for immersive analytics. We also review some hardware setups for data visualization that are already archetypal. Finally, we look at some emerging system designs that suggest future directions

Kinetic simulation of electron injection by electrostatic waves

Radio-synchrotron emission is evidence for relativistic electrons at supernova remnant shocks. These electrons may have been accelerated by Fermi acceleration at perpendicular shocks which requires them to have initial energies above 100 keV. Such electrons cannot be found in the interstellar medium. Previous particle-in-cell (PIC) simulations have shown that the transport of electrons across a magnetic field by an electrostatic wave can, in principle, accelerate electrons to such energies. However, there it was also shown that the wave is unstable and that the resulting acceleration is shortlived. Here we compare results obtained from PIC with those from Vlasov simulations for identical plasma parameters. We show that the life-time of the wave in the Vlasov simulations substantially exceeds previous findings, in principle allowing for electron acceleration to relativistic speeds

Connecting shock velocities to electron-injection mechanisms

Electrons can be accelerated by their interaction with nonlinearly saturated electrostatic waves up to speeds with which they can undergo diffusive acceleration across supernova remnant shocks. Here, we model this wave-electron interaction by particle-in-cell and Vlasov simulations. We find that the lifetime of the saturated wave is considerably longer in the Vlasov simulation, due to differences in how these simulation methods approximate the plasma. Electron surfing acceleration which requires a stable saturated wave may thus be more important for electron acceleration at shocks than previously thought. For beam speeds above a critical value, which we estimate here, both simulation codes exclude surfing acceleration due to a rapid wave collapse

Deriving and Visualizing Uncertainty in Kinetic PET Modeling

Kinetic modeling is the tool of choice when developing new positron emission tomography (PET) tracers for quantitative functional analysis. Several approaches are widely used to facilitate this process. While all these approaches are inherently different, they are still subject to uncertainty arising from various stages of the modeling process. In this paper we propose a novel approach for deriving and visualizing uncertainty in kinetic PET modeling. We distinguish between intra- and inter-model uncertainties. While intra-model uncertainty allows us to derive uncertainty based on a single modeling approach, inter-model uncertainty arises from the differences of the results of different approaches. To derive intra-model uncertainty we exploit the covariance matrix analysis. The inter-model uncertainty is derived by comparing the outcome of three standard kinetic PET modeling approaches. We derive and visualize this uncertainty to exploit it as a basis for changing model input parameters with the ultimate goal to reduce the modeling uncertainty and thus obtain a more realistic model of the tracer under investigation. To support this uncertainty reduction process, we visually link abstract and spatial data by introducing a novel visualization approach based on the ThemeRiver metaphor, which has been modified to support the uncertainty-aware visualization of parameter changes between spatial locations. We have investigated the benefits of the presented concepts by conducting an evaluation with domain experts. 1