Speaker
Description
We present recent results from a proof-of-principle laser-plasma acceleration experiment that reveal a unique synergy between a laser-driven and particle-driven accelerator: a high-charge laser-wakefield accelerated electron bunch can drive a wakefield while simultaneously drawing energy from the laser pulse via direct laser acceleration. This process continues to accelerate electrons beyond the usual decelerating phase of the wakefield, thus reaching much higher energies. We find that the 10-centimeter-long nanoparticle-assisted wakefield accelerator can generate 340 pC, 10.4±0.6 GeV electron bunches with 3.4 GeV RMS convolved energy spread and 0.9 mrad RMS divergence. The nanoparticles control the amount of charge injected in the wakefield. This synergistic mechanism and the simplicity of the experimental setup represent a step closer to compact tabletop particle accelerators suitable for applications requiring high charge at high energies, such as radiation sources producing muon and positron beams.
Acknowledgments
BM Hegelich, C Aniculaesei, T Ha, L Labun, OZ Labun, and E McCary have been supported by the Air Force Office of Scientific Research Grant No. FA9550-17-1-0264. DOE Office of Science supported the laser facility, Fusion Energy Sciences, under Contract No. DE-SC0019167, the LaserNetUS initiative at the Texas Petawatt Laser facility.
The contributions of A Hannasch, R Zgazdaj, I Pagano, JA Franco, and MC Downer were supported by the U.S. Department of Energy grant DE-SC0011617. DA Jarozynski, E Brunetti, B Ersfeld, and S Yoffe would like to acknowledge support from the U.K. EPSRC (EP/J018171/1, EP/N028694/1) and the European Union's Horizon 2020 research and innovation program under grant agreements no 871124 Laserlab-Europe and EuPRAXIA (653782). Simulation results were obtained using the ARCHIE-WeSt High-Performance Computer (www.archie-west.ac.uk) based at the University of Strathclyde, and the facilities of the N8 Centre of Excellence in Computationally Intensive Research (N8 CIR) provided and funded by the N8 research partnership and EPSRC (grant number EP/T022167/1), coordinated by the Universities of Durham, Manchester, and York.
Many thanks to Rémi Lehe of Lawrence Berkeley National Laboratory for his support in deploying and optimizing the FBPIC code.
