The Solar Wind Electrons Alphas and Protons (SWEAP) Investigation on SolarProbe Plus is a four sensor instrument suite that provides complete measurements of the electrons and ionized helium and hydrogen that constitute the bulk of solar wind and coronal plasma. SWEAP consists of the Solar Probe Cup (SPC) and the Solar Probe Analyzers (SPAN). SPC is a Faraday Cup that looks directly at the Sun and measures ion and electron fluxes and flow angles as a function of energy. SPAN consists of an ion and electron electrostatic analyzer (ESA) on the ram side of SPP (SPAN-A) and an electron ESA on the anti-ram side (SPAN-B). The SPAN-A ion ESA has a time of flight section that enables it to sort particles by their mass/charge ratio, permitting differentiation of ion species. SPAN-A and -B are rotated relative to one another so their broad fields of view combine like the seams on a baseball to view the entire sky except for the region obscured by the heat shield and covered by SPC. Observations by SPC and SPAN produce the combined field of view and measurement capabilities required to fulfill the science objectives of SWEAP and Solar Probe Plus. SWEAP measurements, in concert with magnetic and electric fields, energetic particles, and white light contextual imaging will enable discovery and understanding of solar wind acceleration and formation, coronal and solar wind heating, and particle acceleration in the inner heliosphere of the solar system. SPC and SPAN are managed by the SWEAP Electronics Module (SWEM), which distributes power, formats onboard data products, and serves as a single electrical interface to the spacecraft. SWEAP data products include ion and electron velocity distribution functions with high energy and angular resolution. Full resolution data are stored within the SWEM, enabling high resolution observations of structures such as shocks, reconnection events, and other transient structures to be selected for download after the fact. This paper describes the implementation of the SWEAP Investigation, the driving requirements for the suite, expected performance of the instruments, and planned data products, as of mission preliminary design review.
Developments in machine learning promise to ameliorate some of the challenges of modeling complex physical systems through neural-network-based surrogate models. High-intensity, short-pulse lasers can be used to accelerate ions to mega-electronvolt energies, but to model such interactions requires computationally expensive techniques such as particle-in-cell simulations. Multilayer neural networks allow one to take a relatively sparse ensemble of simulations and generate a surrogate model that can be used to rapidly search the parameter space of interest. In this work, we created an ensemble of over 1,000 simulations modeling laser-driven ion acceleration and developed a surrogate to study the resulting parameter space. A neural-network-based approach allows for rapid feature discovery not possible for traditional parameter scans given the computational cost. A notable observation made during this study was the dependence of ion energy on the pre-plasma gradient length scale. While this methodology harbors great promise for ion acceleration, it has ready application to all topics in which large-scale parameter scans are restricted by significant computational cost or relatively large, but sparse, domains.
The use of higher-order modes is proposed to control the transverse wakefield structure generated by a laser pulse propagating through a plasma channel. This can be done in the quasilinear regime in both the Laguerre-Gaussian and Hermite-Gaussian bases for appropriate laser-plasma parameters, independently of the longitudinal field. Control of the wake can be achieved by using modes of different mode numbers but with matched phase velocities to generate tunable, matched laser propagation. The wake can be tuned by modifying the initial phase and amplitude of each mode. In addition, it is shown that two different higher order modes can propagate at the same group velocity by appropriately tuning the frequencies. Geometric and frequency tuning of the laser driver allows for greater control of the transverse phase-space of the accelerated electron bunch.
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