Abstract
The influence of space-charge on ion cyclotron resonances and magnetron eigenfrequency in a gas-filled Penning ion trap has been investigated. Off-line measurements with K+39 using the cooling trap of the WITCH retardation spectrometer-based setup at ISOLDE/CERN were performed. Experimental ion cyclotron resonances were compared with ab initio Coulomb simulations and found to be in agreement. As an important systematic effect of the WITCH experiment, the magnetron eigenfrequency of the ion cloud was studied under increasing space-charge conditions. Finally, the helium buffer gas pressure in the Penning trap was determined by comparing experimental cooling rates with simulations.
Highlights
In recent years, Penning ion traps have become established as versatile tools for trapping charged particles in plasma physics, atomic physics, as well as nuclear and particle physics
For estimating the absolute number of ions in the Penning trap, a calibrated, chevron-stacked, 4 cm diameter Micro-Channel Plate (MCP) detector manufactured by Photonis was used
It was shown previously that the area of such a pulse can accurately represent the amount of charge impinging on the detector plates [28], provided special care is taken to avoid saturation effects
Summary
In recent years, Penning ion traps have become established as versatile tools for trapping charged particles in plasma physics, atomic physics, as well as nuclear and particle physics. The Weak Interaction Trap for CHarged particles (WITCH) [7,8], the focus of this work, is a double Penning trap system situated at currents is experimentally ruled out to a precision of only about. Space-charge significantly contributes to systematic effects caused by source properties, i.e. ion cloud dimensions and temperature. Ion clouds of this size and density are still not fully in the plasma régime, and are beyond reach of both single particle and collective motion analytical frameworks. Numerical simulation presently remains the only feasible way of modelling such phenomena For this purpose, the Simbuca [13] simulation package was employed in this work on graphical processor units (GPUs), taking advantage of their intrinsic parallelism
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