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Abstract Collisionless plasma shocks are a common feature of many space and astrophysical systems. They are sources of high-energy particles and nonthermal emission, channeling as much as 20% of the shock’s energy into nonthermal particles. The generation and acceleration of these nonthermal particles have been previously studied and shown to affect shock hydrodynamics to the zeroth order. In this work, we use self-consistent hybrid particle-in-cell simulations to examine the effect of self-generated nonthermal ion populations on the nature of collisionless, quasi-parallel shocks. Accelerated nonthermal particles downstream of the shock diffuse into the upstream region, taking energy away from the shock, which increases the compression ratio, slows the shock down, and flattens the nonthermal population’s spectral index for lower-Mach-number shocks. We show that this enhances shock compressibility when the heat flux is included in the Rankine–Hugoniot jump conditions, results that are roughly consistent with previous theories of “cosmic-ray-modified shocks.” Additionally, the simulation data show that heat flux and enthalpy flux cancels out in the upstream region, yielding a relatively simple, alternative closure for the jump conditions which accurately predict for the shock speed and compression ratio. The results have the potential to explain discrepancies between predictions and observations in a wide range of systems, such as inaccuracies in predictions of the arrival times of coronal mass ejections and the conflicting radio and X-ray observations of intracluster shocks. These effects will likely need to be included in fluid modeling to predict shock evolution accurately. 

Abstract Thermalization and heating of plasma flows at shocks result in unstable charged-particle distributions that generate a wide range of electromagnetic waves. These waves, in turn, can further accelerate and scatter energetic particles. Thus, the properties of the waves and their implication for wave−particle interactions are critically important for modeling energetic particle dynamics in shock environments. Whistler-mode waves, excited by the electron heat flux or a temperature anisotropy, arise naturally near shocks and foreshock transients. As a result, they can often interact with suprathermal electrons. The low background magnetic field typical at the core of such transients and the large wave amplitudes may cause such interactions to enter the nonlinear regime. In this study, we present a statistical characterization of whistler-mode waves at foreshock transients around Earth’s bow shock, as they are observed under a wide range of upstream conditions. We find that a significant portion of them are sufficiently intense and coherent (narrowband) to warrant nonlinear treatment. Copious observations of background magnetic field gradients and intense whistler wave amplitudes suggest that phase trapping, a very effective mechanism for electron acceleration in inhomogeneous plasmas, may be the cause. We discuss the implications of our findings for electron acceleration in planetary and astrophysical shock environments. 

Accepted, not yet published 

The current state of the art thermal particle measurements in the solar wind are insufficient to address many long standing, fundamental physical processes. The solar wind is a weakly collisional ionized gas experiencing collective effects due to long-range electromagnetic forces. Unlike a collisionally mediated fluid like Earth’s atmosphere, the solar wind is not in thermodynamic or thermal equilibrium. For that reason, the solar wind exhibits multiple particle populations for each particle species. We can mostly resolve the three major electron populations (e.g., core, halo, strahl, and superhalo) in the solar wind. For the ions, we can sometimes separate the proton core from a secondary proton beam and heavier ion species like alpha-particles. However, as the solar wind becomes cold or hot, our ability to separate these becomes more difficult. Instrumental limitations have prevented us from properly resolving features within each ion population. This destroys our ability to properly examine energy budgets across transient, discontinuous phenomena (e.g., shock waves) and the evolution of the velocity distribution functions. Herein we illustrate both the limitations of current instrumentation and why higher resolutions are necessary to properly address the fundamental kinetic physics of the solar wind. This is accomplished by directly comparing to some current solar wind observations with calculations of velocity moments to illustrate the inaccuracy and incompleteness of poor resolution data. 

An important question that is being increasingly studied across subdisciplines of Heliophysics is “how do mesoscale phenomena contribute to the global response of the system?” This review paper focuses on this question within two specific but interlinked regions in Near-Earth space: the magnetotail’s transition region to the inner magnetosphere and the ionosphere. There is a concerted effort within the Geospace Environment Modeling (GEM) community to understand the degree to which mesoscale transport in the magnetotail contributes to the global dynamics of magnetic flux transport and dipolarization, particle transport and injections contributing to the storm-time ring current development, and the substorm current wedge. Because the magnetosphere-ionosphere is a tightly coupled system, it is also important to understand how mesoscale transport in the magnetotail impacts auroral precipitation and the global ionospheric system response. Groups within the Coupling, Energetics and Dynamics of Atmospheric Regions Program (CEDAR) community have also been studying how the ionosphere-thermosphere responds to these mesoscale drivers. These specific open questions are part of a larger need to better characterize and quantify mesoscale “messengers” or “conduits” of information—magnetic flux, particle flux, current, and energy—which are key to understanding the global system. After reviewing recent progress and open questions, we suggest datasets that, if developed in the future, will help answer these questions.