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Laser wakefield accelerators generate ultrashort electron bunches with the capability to produce γ-rays. Here, we produce focused laser wakefield acceleration electron beams using three quadrupole magnets. Electron beams are then focused into a 3 mm lead converter to generate intense, focused bremsstrahlung γ beams. Experimental results demonstrate the generation and propagation of focused γ beams to a best focus spot size of 2.3 ± 0.1 × 2.7 ± 0.2 mm 2 using a copper stack calorimeter. Monte Carlo simulations conducted using GEANT4 are in good agreement with experimental results and enable detailed examination of γ-ray generation. Simulations indicate that the focused γ beams contained 2.6 × 10 9 photons in the range of 100 keV to 33 MeV with an average energy of 6.4 MeV. A γ-ray intensity of 7 × 10 10 W/cm 2 was estimated from simulations. The generation of focused bremsstrahlung γ-ray sources can have important applications in medical imaging applications and laboratory astrophysics experiments. 

While nearly all investigations of high order harmonic generation with relativistically intense laser pulses have taken place at 800 or 1053 nm, very few experimental studies have been done at other wavelengths. In this study, we investigate the scaling of relativistic high harmonic generation towards longer wavelengths at intensities ofa₀ ∼ 1. Longer driver wavelengths enable enhanced diagnostics of the harmonic emission, as multiple orders lie in the optical regime. We measure the conversion efficiency by collecting the entire harmonic emission as well as the divergence through direct imaging. We compare the emission with 2D particle-in-cell simulations to determine the experimental target conditions. This new regime of high order harmonic generation also enables relativistic scaling as well as improved discrimination of harmonic generation mechanisms.

 

Abstract Laser wakefield accelerators promise to revolutionize many areas of accelerator science. However, one of the greatest challenges to their widespread adoption is the difficulty in control and optimization of the accelerator outputs due to coupling between input parameters and the dynamic evolution of the accelerating structure. Here, we use machine learning techniques to automate a 100 MeV-scale accelerator, which optimized its outputs by simultaneously varying up to six parameters including the spectral and spatial phase of the laser and the plasma density and length. Most notably, the model built by the algorithm enabled optimization of the laser evolution that might otherwise have been missed in single-variable scans. Subtle tuning of the laser pulse shape caused an 80% increase in electron beam charge, despite the pulse length changing by just 1%.