We use one-dimensional measurements to reconstruct the four-dimensional phase space of an ion beam at the Argonne Tandem Linac Accelerator System (ATLAS) using maximum entropy tomography. This was accomplished with a novel algorithm that directly reconstructs 4D from 1D. The results were compared against a quadrupole scan measurement of the phase space. Finally, an error analysis method employing statistical analysis was used to estimate the errors.

Beam instabilities and resonances affect the transverse dynamics in particle accelerators and, when encountered, can trigger emittance growth and beam loss. Resonance lines originate from nonlinear elements and effects in the lattice,and impose strict constraints on the choice of working points and narrow the available tune space. Circular modes—intrinsically coupled, flat-round eigenmodes—provide an alternative beam motion and dynamics. In this study we derive the third-order sextupole resonance conditions in the coupled (normal-mode) parametrization and show that, with circular-mode lattice design and beam operation, most of these resonance lines are naturally suppressed thanks to the mode’s inherent flatness.

The RF beam sweeper is a crucial component for radioactive ion beam production, which enhances the purity of in-flight produced rare isotope beams by introducing a time-of-flight separation. The current sweeper operates at ATLAS’s subharmonic frequency of 6 MHz using 1-meter-long electrode plates and a maximum deflecting voltage of 55 kV, which is sufficient for the separation of certain beams. However, the new capabilities, enabled by the recently commissioned in-flight radioactive beam separator RAISOR demand higher voltages and higher frequency operation. To address these needs, we are developing an advanced RF sweeper capable of switching between 6 MHz and 12 MHz, depending on the beam, with a maximum deflecting voltage of 150 kV. The design is based on a resonant circuit with electrode plates and an adjustable coil, along with a sliding contact switch for frequency switching. This talk presents the sweeper design and fabrication progress.

We have developed a browser-based user interface for AI-ML applications at Argonne’s ATLAS ion linac facility. The new interface is named the “ATLAS AI-ML Dashboard”, it is based on the web application package, Dash, and customized to easily include any ATLAS beamline and select from several beam tuning options and optimization algorithms. The interface is being introduced to the operators and their feedback will be used to further improve its capabilities. Among the features that are being added is the extraction of the initial beam parameters, from pepper-pots and quad scans, to use as input for the optimization procedure. In addition to presenting the main features of the ATLAS AI-ML interface, we will also present the first online experience of the operators.

Beam instabilities and resonances affect the transverse dynamics in particle accelerators and, when encountered, can trigger emittance growth and beam loss. Resonance lines originate from nonlinear elements and effects in the lattice,and impose strict constraints on the choice of working points and narrow the available tune space. Circular modes—intrinsically coupled, flat-round eigenmodes—provide an alternative beam motion and dynamics. In this study we derive the third-order sextupole resonance conditions in the coupled (normal-mode) parametrization and show that, with circular-mode lattice design and beam operation, most of these resonance lines are naturally suppressed thanks to the mode’s inherent flatness.

Studying nuclear reactions to develop new medical isotopes requires the measurement of production cross sections at varying beam energies. To do this efficiently without wasting beam time available for experimentation, the energy needs to be changed rapidly over a very wide range. We present recent experimental results, employing machine learning methods for rapid tuning of 16O &136Xe beams following manual energy change. For the 16O beam energy is changed from a base value of 106 MeV to 71 MeV and for the 136Xe beam energy is changed from the base energy of 803 MeV to 671 MeV and 525 MeV. Re-tuning from the base energy took ~15 minutes compared to ~30 minutes for operator tuning. The collected data is then used to validate the same procedure in a virtual model of ATLAS running the TRACK simulation code with error ~6% across energies. Preliminary virtual model error is corrected by considering quadrupole misalignments and real values of input beam parameters obtained by Bayesian inference.

We use one-dimensional measurements to reconstruct the four-dimensional phase space of an ion beam at the Argonne Tandem Linac Accelerator System (ATLAS) using maximum entropy tomography. This was accomplished with a novel algorithm that directly reconstructs 4D from 1D. The results were compared against a quadrupole scan measurement of the phase space. Finally, an error analysis method employing statistical analysis was used to estimate the errors.

A virtual machine model that seamlessly integrates with the online accelerator system would highly benefit the operators to test and evaluate beam tuning scenarios and apply them online. As part of this effort, the code TRACK is wrapped with control system architectures and a custom-made graphic user interface based on the Dash web application package. Customizability and task visualization are prioritized based on end user feedback. More important is how well the model agrees with the real machine. A recent effort to account for beam steering and misalignment effects has reduced the error between simulation and measurements from ~ 50% to ~ 10%. More work to reduce this error and further close the gap is currently underway. The concurrent execution of simulation with experiment for troubleshooting and parallel optimizations to quickly determine ideal element settings for the desired beam parameters are some of the features to be highlighted. Previously published AI-ML capabilities are incorporated to this extent. Simulation-based surrogate models benchmarked against collected data are being developed to speed up the process and reproduce the operating conditions in a timely manner.