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  1. Plasma-based acceleration has emerged as a promising candidate as an accelerator technology for a future linear collider or a next-generation light source. We consider the plasma wakefield accelerator (PWFA) concept where a plasma wave wake is excited by a particle beam and a trailing beam surfs on the wake. For a linear collider, the energy transfer efficiency from the drive beam to the wake and from the wake to the trailing beam must be large, while the emittance and energy spread of the trailing bunch must be preserved. One way to simultaneously achieve this when accelerating electrons is to use longitudinally shaped bunches and nonlinear wakes. In the linear regime, there is an analytical formalism to obtain the optimal shapes. In the nonlinear regime, however, the optimal shape of the driver to maximize the energy transfer efficiency cannot be precisely obtained because currently no theory describes the wake structure and excitation process for all degrees of nonlinearity. In addition, the ion channel radius is not well defined at the front of the wake where the plasma electrons are not fully blown out by the drive beam. We present results using a novel optimization method to effectively determine a current profile for the drive and trailing beam in PWFA that provides low energy spread, low emittance, and high acceleration efficiency. We parameterize the longitudinal beam current profile as a piecewise-linear function and define optimization objectives. For the trailing beam, the algorithm converges quickly to a nearly inverse trapezoidal trailing beam current profile similar to that predicted by the ultrarelativistic limit of the nonlinear wakefield theory. For the drive beam, the beam profile found by the optimization in the nonlinear regime that maximizes the transformer ratio also resembles that predicted by linear theory. The current profiles found from the optimization method provide higher transformer ratios compared with the linear ramp predicted by the relativistic limit of the nonlinear theory. 
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    Free, publicly-accessible full text available May 1, 2024
  2. We employ two machine learning techniques, i.e., neural networks and genetic-programming-based symbolic regression, to examine the dynamics of the electron-positron pair creation process with full space–time resolution inside the interaction zone of a supercritical electric field pulse. Both algorithms receive multiple sequences of partially dressed electronic and positronic spatial probability densities as training data and exploit their features as a function of the dressing strength in order to predict each particle’s spatial distribution inside the electric field. A linear combination of both predicted densities is then compared with the unambiguous total charge density, which also contains contributions associated with the independent vacuum polarization process. After its subtraction, the good match confirms the validity of the machine learning approach and lends some credibility to the validity of the predicted single-particle densities.

     
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  3. null (Ed.)
  4. We examine the effect of a frequency-chirped external force field on the final energy that has been absorbed by two classical mechanical oscillators, by quantum mechanical two- and three-level systems, and by electron-positron pairs that were created from the quantum field theoretical Dirac vacuum. By comparing the final dynamical responses to the original force field with that associated with the corresponding time-reversed field, we can test the sensitivity of each of these five systems to the temporal phase information contained in the field. We predict that the linear oscillator, the two-level atom, and the pair-creation process triggered by a spatially homogeneous field are remarkably immune to this phase, whereas the quartic oscillator, the three-level atom, or the pair-creation process caused by a space-time field absorb the provided energy differently depending on the temporal details of the external field.

     
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