Searcharxiv⌕ Search

arXiv subjects

Joaquim Pereira

Publications and source records attributed to Joaquim Pereira.

2 recordsLinked to original sources

Space-time beams with tunable orbital group velocity toward plasma superradiance

Light springs are space-time beams that have a helical wavepacket. Due to this special property, light springs result into a rotating pulse when intercepting a plane lying orthogonal to their propagation direction. Associated to this, we introduce here the orbital group velocity, an additional tunable property of light springs. The orbital group velocity quantifies the speed of the light spring intensity rotation, distinctly from the conventional longitudinal group velocity, which describes the motion of the wavepacket envelope along its propagation axis. We demonstrate experimentally by tunable Fourier synthesis that the orbital group velocity can assume sub- and superluminal values, thus becoming a new platform for synthetic motion studies and control of laser-matter interactions. Particularly, in the superluminal regime, when interacting with a thin overdense plasma, we reveal by particle-in-cell simulations that the light spring unlocks superradiant radiation, due to the coherent excitation of the electrons in the plasma acting as a quasiparticle. This superradiant source inherits the ultrafast temporal dynamics of the light springs while emitting in the terahertz region, thus creating a new source of terahertz radiation controlled by the properties of spatiotemporal coupling of the laser. Therefore, spatiotemporal tuning of light springs is at the frontier of controlling laser-matter interaction and generating new tunable sources of radiation.

physics.optics↗

Bayesian Optimization and Convolutional Neural Networks for Zernike-Based Wavefront Correction in High Harmonic Generation

High harmonic generation (HHG) is a nonlinear process that enables table-top generation of tunable, high-energy, coherent, ultrashort radiation pulses in the extreme ultraviolet (EUV) to soft X-ray range. These pulses find applications in photoemission spectroscopy in condensed matter physics, pump-probe spectroscopy for high-energy-density plasmas, and attosecond science. However, optical aberrations in the high-power laser systems required for HHG degrade beam quality and reduce efficiency. We present a machine learning approach to optimize aberration correction using a spatial light modulator. We implemented and compared Bayesian optimization and convolutional neural network (CNN) methods to predict optimal Zernike polynomial coefficients for wavefront correction. Our CNN achieved promising results with 80.39% accuracy on test data, demonstrating the potential for automated aberration correction in HHG systems.

physics.optics↗