Author: Mitchell, C.E.
Paper Title Page
MOPA72 Preliminary Tests and Beam Dynamics Simulations of a Straight-Merger Beamline 206
 
  • A.A. Al Marzouk, P. Piot, T. Xu
    Northern Illinois University, DeKalb, Illinois, USA
  • S.V. Benson, K.E. Deitrick, J. Guo, A. Hutton, G.-T. Park, S. Wang
    JLab, Newport News, Virginia, USA
  • D.S. Doran, G. Ha, P. Piot, J.G. Power, C. Whiteford, E.E. Wisniewski
    ANL, Lemont, Illinois, USA
  • C.E. Mitchell, J. Qiang, R.D. Ryne
    LBNL, Berkeley, California, USA
  
  Funding: NSF award PHY-1549132 to Cornell University and NIU, U.S. DOE contract DE-AC02-06CH11357 with ANL and DE-AC05-06OR23177 with JLAB.
Beamlines capable of merging beams with different energies are critical to many applications related to advanced accelerator concepts and energy-recovery linacs (ERLs). In an ERL, a low-energy "fresh" bright bunch is generally injected into a superconducting linac for acceleration using the fields established by a decelerated "spent" beam traveling on the same axis. A straight-merger system composed of a selecting cavity with a superimposed dipole magnet was proposed and recently test at AWA. This paper reports on the experimental results obtained so far along with detailed beam dynamics investigations of the merger concept and its ability to conserve the beam brightness associated with the fresh bunch. 		 
poster icon Poster MOPA72 [1.659 MB]  
DOI • reference for this paper ※ doi:10.18429/JACoW-NAPAC2022-MOPA72  
About • Received ※ 11 August 2022 — Accepted ※ 13 August 2022 — Issue date ※ 02 October 2022  
Cite • reference for this paper using ※ BibTeX, ※ LaTeX, ※ Text/Word, ※ RIS, ※ EndNote (xml)  
 
TUYE2 Next Generation Computational Tools for the Modeling and Design of Particle Accelerators at Exascale 302
 
  • A. Huebl, R. Lehé, C.E. Mitchell, J. Qiang, R.D. Ryne, R.T. Sandberg, J.-L. Vay
    LBNL, Berkeley, California, USA
  
  Funding: Work supported by the Exascale Computing Project (17-SC-20-SC), a collaborative effort of the U.S. DOE SC and the NNSA, resources of NERSC, and by LBNL LDRD under DOE Contract DE-AC02-05CH11231.
Particle accelerators are among the largest, most complex devices. To meet the challenges of increasing energy, intensity, accuracy, compactness, complexity and efficiency, increasingly sophisticated computational tools are required for their design and optimization. It is key that contemporary software take advantage of the latest advances in computer hardware and scientific software engineering practices, delivering speed, reproducibility and feature composability for the aforementioned challenges. A new open source software stack is being developed at the heart of the Beam pLasma Accelerator Simulation Toolkit (BLAST) by LBNL and collaborators, providing new particle-in-cell modeling codes capable of exploiting the power of GPUs on Exascale supercomputers. Combined with advanced numerical techniques, such as mesh-refinement, and intrinsic support for machine learning, these codes are primed to provide ultrafast to ultraprecise modeling for future accelerator design and operations.
[1] J.-L. Vay, A. Huebl, et al, Phys. Plasmas 28, 023105 (2021)
[2] J.-L. Vay, A. Huebl, et al, J. Instr. 16, T10003 (2021)
[3] A. Myers, et al (incl. A. Huebl), Parallel Comput. 108, 102833 (2021) 		 
slides icon Slides TUYE2 [9.399 MB]  
DOI • reference for this paper ※ doi:10.18429/JACoW-NAPAC2022-TUYE2  
About • Received ※ 13 July 2022 — Revised ※ 02 August 2022 — Accepted ※ 08 August 2022 — Issue date ※ 11 August 2022
Cite • reference for this paper using ※ BibTeX, ※ LaTeX, ※ Text/Word, ※ RIS, ※ EndNote (xml)