Ion motion in the wake driven by long particle bunches in plasmas

We explore the role of the background plasma ion motion in self-modulated plasma wakefield accelerators. We employ J. Dawson's plasma sheet model to derive expressions for the transverse plasma electric field and ponderomotive force in the narrow bunch limit. We use these results to determine the on-set of the ion dynamics, and demonstrate that the ion motion could occur in self-modulated plasma wakefield accelerators. Simulations show the motion of the plasma ions can lead to the early suppression of the self-modulation instability and of the accelerating fields. The background plasma ion motion can nevertheless be fully mitigated by using plasmas with heavier plasmas.Comment: 23 pages, 6 figure

Magnetically assisted self-injection and radiation generation for plasma based acceleration

It is shown through analytical modeling and numerical simulations that external magnetic fields can relax the self-trapping thresholds in plasma based accelerators. In addition, the transverse location where self-trapping occurs can be selected by adequate choice of the spatial profile of the external magnetic field. We also find that magnetic-field assisted self-injection can lead to the emission of betatron radiation at well defined frequencies. This controlled injection technique could be explored using state-of-the-art magnetic fields in current/next generation plasma/laser wakefield accelerator experiments.Comment: 7 pages, 4 figures, accepted for publication in Plasma Physics and Controlled Fusio

Transverse self-modulation of ultra-relativistic lepton beams in the plasma wakefield accelerator

The transverse self-modulation of ultra-relativistic, long lepton bunches in high-density plasmas is explored through full-scale particle-in-cell simulations. We demonstrate that long SLAC-type electron and positron bunches can become strongly self-modulated over centimeter distances, leading to wake excitation in the blowout regime with accelerating fields in excess of 20 GV/m. We show that particles energy variations exceeding 10 GeV can occur in meter-long plasmas. We find that the self-modulation of positively and negatively charged bunches differ when the blowout is reached. Seeding the self-modulation instability suppresses the competing hosing instability. This work reveals that a proof-of-principle experiment to test the physics of bunch self-modulation can be performed with available lepton bunches and with existing experimental apparatus and diagnostics.Comment: 8 pages, 8 figures, accepted for publication in Physics of Plasma

Astrometry of mutual approximations between natural satellites. Application to the Galilean moons

Typically we can deliver astrometric positions of natural satellites with errors in the 50-150 mas range. Apparent distances from mutual phenomena, have much smaller errors, less than 10 mas. However, this method can only be applied during the equinox of the planets. We developed a method that can provide accurate astrometric data for natural satellites -- the mutual approximations. The method can be applied when any two satellites pass close by each other in the apparent sky plane. The fundamental parameter is the central instant $t_0$ of the passage when the distances reach a minimum. We applied the method for the Galilean moons. All observations were made with a 0.6 m telescope with a narrow-band filter centred at 889 nm with width of 15 nm which attenuated Jupiter's scattered light. We obtained central instants for 14 mutual approximations observed in 2014-2015. We determined $t_0$ with an average precision of 3.42 mas (10.43 km). For comparison, we also applied the method for 5 occultations in the 2009 mutual phenomena campaign and for 22 occultations in the 2014-2015 campaign. The comparisons of $t_0$ determined by our method with the results from mutual phenomena show an agreement by less than 1-sigma error in $t_0$, typically less than 10 mas. This new method is particularly suitable for observations by small telescopes.Comment: 13 pages, 11 figures and 8 tables. Based on observations made at the Laborat\'orio Nacional de Astrof\'isica (LNA), Itajub\'a-MG, Brazi

SAMplus: adaptive optics at optical wavelengths for SOAR

Adaptive Optics (AO) is an innovative technique that substantially improves the optical performance of ground-based telescopes. The SOAR Adaptive Module (SAM) is a laser-assisted AO instrument, designed to compensate ground-layer atmospheric turbulence in near-IR and visible wavelengths over a large Field of View. Here we detail our proposal to upgrade SAM, dubbed SAMplus, that is focused on enhancing its performance in visible wavelengths and increasing the instrument reliability. As an illustration, for a seeing of 0.62 arcsec at 500 nm and a typical turbulence profile, current SAM improves the PSF FWHM to 0.40 arcsec, and with the upgrade we expect to deliver images with a FWHM of $\approx0.34$ arcsec -- up to 0.23 arcsec FWHM PSF under good seeing conditions. Such capabilities will be fully integrated with the latest SAM instruments, putting SOAR in an unique position as observatory facility.Comment: To appear in Proc. SPIE 10703 (Ground-based and Airborne Instrumentation for Astronomy VII; SPIEastro18

Machine learning controlled laser wakefield acceleration simulations

One of the most promising technologies to form the next generation of compact particle accelerators is plasma acceleration. Plasmas have the ability to sustain waves with electric fields that can be three orders of magnitude higher than those in radio frequency (RF) cavities.The ultimate goal of plasma-based acceleration is to produce relativistic, high quality electron and positron bunches for scientific and societal applications. The recent progress has been tremendous but improving beam quality still remains as a grand-challenge in the field.The fundamental aspects and properties of these accelerators are accessible through simplified analytical models, but the self-consistent dynamics of the laser in the plasma can only be captured by numerical simulations. Search for optimised parameters to improve beam quality can be based on systematic parameter scans. However, because numerical calculations can be very computationally intensive, it is important to investigate more efficient techniques to scan over the entire parameter range currently available. In this work, we propose a machine learning approach to optimize this search based on genetic algorithms.Recent experiments have employed genetic algorithms to control plasma based accelerators[1]. Here, instead, we will employ this technique to control the outputs and optimise plasma-based accelerators in particle-in-cell (PIC) simulations. We implemented a genetic algorithm in ZPIC, a fully relativistic PIC educational code[2]. The genetic algorithm is fully automated: it receives an initial set of input parameters, launches several simulations in parallel using MPI, and ends automatically once given convergence criteria are reached. The algorithm can thus take full advantage of large-scale super-computers. We present results from 1D simulations.We focus on plasmas with non-uniform density and lasers with variable longitudinal envelope profiles.info:eu-repo/semantics/publishedVersio