Magnetic collimation system for improving ion trap loading efficiency.

This work considers a solenoid-based magnetic collimation system for improving the efficiency of ion trap loading with ions created by laser ablation. We discuss a physical model of ion beam collimation in such a system, provide qualitative analytical estimates of its collimation characteristics, develop a numerical model of ion collimation based on a test-particle approach, and describe a real experimental setup where the proposed approach is effectively employed to collimate 232Th3+ and 88Sr1+ ions. The experimental results are compared with the results of the performed numerical modeling. The observed inconsistencies between the two are discussed, and their possible explanations are suggested.

Kilotesla plasmoid formation by a trapped relativistic laser beam.

A strong quasistationary magnetic field is generated in hollow targets with curved internal surface under the action of a relativistically intense picosecond laser pulse. Experimental data evidence the formation of quasistationary strongly magnetized plasma structures decaying on a hundred picoseconds timescale, with the magnetic field strength of the kilotesla scale. Numerical simulations unravel the importance of transient processes during the magnetic field generation and suggest the existence of fast and slow regimes of plasmoid evolution depending on the interaction parameters. The proposed setup is suited for perspective highly magnetized plasma application and fundamental studies.

Neural network analysis of quasistationary magnetic fields in microcoils driven by short laser pulses.

Optical generation of kilo-tesla scale magnetic fields enables prospective technologies and fundamental studies with unprecedentedly high magnetic field energy density. A question is the optimal configuration of proposed setups, where plenty of physical phenomena accompany the generation and complicate both theoretical studies and experimental realizations. Short laser drivers seem more suitable in many applications, though the process is tangled by an intrinsic transient nature. In this work, an artificial neural network is engaged for unravelling main features of the magnetic field excited with a picosecond laser pulse. The trained neural network acquires an ability to read the magnetic field values from experimental data, extremely facilitating interpretation of the experimental results. The conclusion is that the short sub-picosecond laser pulse may generate a quasi-stationary magnetic field structure living on a hundred picosecond time scale, when the induced current forms a closed circuit.