An accurate physics simulation model is key to accelerator operation because all beam control and optimization algorithms require good understanding of the accelerator and its elements. For the AGS Booster, discrepancies between the real physical system and online simulation model have been a long-standing issue. Due to the lack of a reliable model, the current practice of beam control relies mainly on empirical tuning by experienced operators, which may be inefficient or sub-optimal. In this work, we investigate two main factors that can cause discrepancies between simulation and reality in the AGS Booster: magnet misalignments and magnet transfer functions. We developed a orbit response measurement script that collects real machine data in the Booster for model calibration. By matching simulated data with real data, we can develop a more accurate simulation model for future polarization optimizations, and build the foundation for a fully functional digital-twin.

Slow resonant extraction plays a crucial role in delivering a high-quality continuous beam to experiments. Simulating extraction and transport of charged particle beams require a process of careful modeling and experimentation. There are various particle tracking simulation tools available to use. Each has its merits and deficiencies. In this work we have used long-term tracking based on the Bmad toolkit to run third integer resonant extraction simulations of beams of various ion species in the booster synchrotron at Brookhaven National Laboratory. In this paper, we will present results of detailed slow extraction, multi-particle tracking simulations, and we will describe the features that make Bmad a useful tool for this work. We will show comparisons to other simulation tools of our results.

The RHIC heavy ion program relies on a series of RF bunch merge gymnastics to combine individual source pulses into bunches of suitable intensity. Intensity and emittance preservation during these gymnastics require careful setup of the voltages and phases of RF cavities operating at several different harmonic numbers. The optimum setting tends to drift over time, degrading performance and requiring operator attention to correct. We describe a reinforcement learning approach to learning and maintaining an optimum configuration, accounting for the relevant RF parameters and external perturbations (e.g., a changing main dipole field) using a physics-based simulator at Brookhaven Alternating Gradient Synchrotron (AGS).

The AGS Booster synchrotron at Brookhaven National Laboratory delivers resonant slow extracted beams to a fixed target beamline called the NASA Space Radiation Laboratory (NSRL). Experimenters at the NSRL require uniformly distributed radiation fields over large area to simulate the cosmic ray space radiation environment. The facility generates the uniform distribution using a pair of octupole magnets in the transport line. The beamline is designed to produce a achromatic optics through the octupoles and to the target. However, the dispersion function depends on the trajectory of the beam as it is transported out of the booster and into the NSRL beamline. The dependence on this trajectory has not been previously studied. In this paper, we describe a new model we have developed to study this effect and show measurements to compare to our simulations.

An accurate physics simulation model is key to accelerator operation because all beam control and optimization algorithms require good understanding of the accelerator and its elements. For the AGS Booster, discrepancies between the real physical system and online simulation model have been a long-standing issue. Due to the lack of a reliable model, the current practice of beam control relies mainly on empirical tuning by experienced operators, which may be inefficient or sub-optimal. In this work, we investigate two main factors that can cause discrepancies between simulation and reality in the AGS Booster: magnet misalignments and magnet transfer functions. We developed a orbit response measurement script that collects real machine data in the Booster for model calibration. By matching simulated data with real data, we can develop a more accurate simulation model for future polarization optimizations, and build the foundation for a fully functional digital-twin.

Beam emittance plays the crucial role in a Beam transportation system. At a fixed-target beamline off the AGS Booster Synchrotron, beam emittance is determined through measuring the beam width via a segmented multi-wire ion chamber (SWIC) and varying quadrupole strength. The width of the beam signal (as Full Width Half Max) on the SWIC passes through a minimum value and the resulting dataset of FWHM per magnet current is used to fit a function. Using this technique, new controls software has been developed to set up measurements, acquire data, and perform analysis through a python-based scripts to calculate the emittance along the NASA Space Radiation Laboratory (NSRL) beamline. Initial results of the program are presented to for various points along the beamline in a variety of conditions.