Plasma wakefield acceleration of charged particle beams relies on specialized devices for plasma generation and confinement. In both particle-driven wakefield acceleration and beam-focusing experiments, these devices are designed to precisely control plasma properties to optimize beam-plasma interactions. Recent studies employing centimeter-scale, gas-filled discharge plasma sources have demonstrated high accelerating and focusing gradients while preserving electron beam quality, motivating the extension of these techniques to larger structures to achieve higher beam energies. At the SPARC_LAB test facility, multistage accelerating modules based on plasma generation by electrical discharges have been developed to produce tailored longitudinal plasma profiles for simultaneous beam acceleration and focusing. The results presented here show that the longitudinal plasma density within each stage can be independently tuned by modifying the plasma generation conditions, including the applied voltage, current pulse parameters, discharge ignition timing, and plasma recombination dynamics.
We investigate the optimization of nuclear fusion reactivity relative to the choice of energy probability distribution. A single Maxwell-Boltzmann (MB) distribution is found to be optimal in the region where reactivity is a concave function of the average available kinetic energy, specifically near the reactivity peak. Conversely, in regions where the reactivity curve is convex, optimization is achieved through a bimodal MB distribution. We then discuss our results in the context of three classes of generalized energy distributions (superstatistics), which are modeled as a continuum of MB distributions. As expected, in all cases examined, the reactivity gains provided by superstatistics are bounded by the proposed optimal distribution. Finally, we apply these findings to deuterium-deuterium and deuterium-tritium fusion processes using empirical parametrizations of their respective cross sections. For both reactions, employing optimal bimodal MB distributions at low average energies—of particular interest for magnetically confined plasmas—yields a reactivity enhancement of approximately a factor of 2.
Global biochemical cycles of greenhouse gases have received a lot of attention over the past few decades because of their effect on climate and environment. Surprisingly, the turnover of oxygen received considerably less attention in spite of its truly existential importance: Apparently, any significant perturbation to the oxygen cycle may cause serious threat to humans as well as all animal species. Moreover, there is growing empirical as well as theoretical evidence that global warming can perturb the oxygen cycle considerably. In this Perspective, we discuss how this problem can be addressed using a dynamical systems framework. We argue that an insightful approach can consider a family of conceptual mathematical model that couples oxygen dynamics to vegetation (in particular, phytoplankton) and that produces oxygen as a by-product of its primary production and to the state of the global Earth climate. We show that the suggested approach predicts tipping points resulting in oxygen depletion and ocean anoxia as a response to a change in some environmental parameters. This Perspective leads to insights that help to address important issues largely overlooked in the literature and also suggests directions for future research.
