Author: Mustapha, B.M.
Paper Title Page
WEXB03
The Multi-User Upgrade of the Superconducting Ion Linac, ATLAS  
 
  • B.M. Mustapha
    ANL, Lemont, Illinois, USA
 
  Funding: This work was supported by the U.S. Department of Energy, under Contract No. DE-AC02-06CH11357. This research used the ATLAS facility, which is a DOE Office of Nuclear Physics User Facility.
The recently approved multi-user upgrade of the superconducting ion linac, ATLAS, will enable simultaneous acceleration and delivery of two different ion beams to different experimental areas. In the initial phase, one stable, nearly continuous wave, beam from the ECR ion source and one pulsed radioactive beam from the EBIS charge breeder of the Californium Rare Isotope Beam Upgrade (CARIBU-EBIS) will be interleaved in time via an electrostatic deflector at injection, and accelerated through the first two sections of the linac. At that point, one of the beams is deflected via a pulsed switching magnet to a lower energy experimental area while the other is further accelerated through the third linac stage of ATLAS and delivered to a higher energy experimental area. Details of the proposed implementation and the expected gains from this upgrade will be presented. In addition to enhancing the ATLAS nuclear physics program, this upgrade will also increase the availability of beam time for applications such as material irradiation, isotope production R&D, and radiobiology studies with ion beams. A brief overview and typical results from these applications will be presented.
 
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THPAB123 Pytomic: A Python Tool for Polarized Atomic Beam Tracking 4002
 
  • J.L. Martinez Marin, W. Armstrong, B.M. Mustapha
    ANL, Lemont, Illinois, USA
 
  Funding: This work was supported by the U.S. DOE under Contract No. DE-AC02-06CH11357 through ANL’s LDRD program.
Pytomic is a new tool for the simulation and analysis of atomic beams through magnetic systems. It is written in Python and based on the same fundamentals as other particle tracking codes but for atomic beams instead of charged beams. In this case, the manipulation and control of neutral atomic beams is via a force due to the spin interacting with a magnetic field gradient. An object-oriented tool was developed to aid in the design of a beamline through the manipulation of modular elements. The Python language allowed for a smooth implementation and kept the code clear and simple. The primary purpose of developing this code was to have a tool to design, simulate, and optimize a Breit-Rabi Polarimeter to measure the polarization of an atomic beam. Therefore, different set-ups with different magnets need to be simulated and optimized for direct comparison. In addition to simulation and tracking modules, a new data analysis module was developed to be able to quickly analyze simulation results, gaining insight from each iteration of the simulation, leading to an efficient and rapid design process. Example applications to design polarimeters for atomic beams will be presented.
 
poster icon Poster THPAB123 [7.765 MB]  
DOI • reference for this paper ※ https://doi.org/10.18429/JACoW-IPAC2021-THPAB123  
About • paper received ※ 20 May 2021       paper accepted ※ 21 June 2021       issue date ※ 27 August 2021  
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THPAB181 AI-ML Developments for the ATLAS Ion Linac Facility 4122
 
  • B.M. Mustapha, B.R. Blomberg, C. Dickerson, J.L. Martinez Marin, C.E. Peters
    ANL, Lemont, Illinois, USA
 
  Funding: This work was supported by the U.S. Department of Energy, under Contract No. DE-AC02-06CH11357. This research used the ATLAS facility, which is a DOE Office of Nuclear Physics User Facility.
ATLAS is a DOE/NP User Facility for the study of low-energy nuclear physics with heavy ions. It operates ~6000 hours per year. In addition to delivering any stable beam from proton to uranium, the facility also provides radioactive beams from the CARIBU source or via the in-flight radioactive ion separator, RAISOR. The facility uses 3 ion sources and services 6 target areas at energies from ~1-15 MeV/u. To accommodate the large number and variety of approved experiments, ATLAS reconfigures once or twice per week over 40 weeks of operation per year. The startup time varies from ~12-48 hours depending on the complexity of the tuning, which will increase with the upcoming Multi-User Upgrade to deliver beam to two experimental stations simultaneously. DOE/NP has recently approved a project to use AI/ML to support ATLAS operations. The project aim is to significantly reduce the accelerator tuning time and improve machine performance by developing and deploying artificial intelligence methods. These improvements will increase the scientific throughput of the facility and the quality of the data collected. Our recent developments and future plans will be presented and discussed.
 
poster icon Poster THPAB181 [1.034 MB]  
DOI • reference for this paper ※ https://doi.org/10.18429/JACoW-IPAC2021-THPAB181  
About • paper received ※ 06 June 2021       paper accepted ※ 28 July 2021       issue date ※ 12 August 2021  
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