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BiBTeX citation export for TUPOST059: PyEmittance: A General Python Package for Particle Beam Emittance Measurements with Adaptive Quadrupole Scans

@inproceedings{miskovich:ipac2022-tupost059,
  author       = {S.A. Miskovich and A.L. Edelen and C.E. Mayes},
  title        = {{PyEmittance: A General Python Package for Particle Beam Emittance Measurements with Adaptive Quadrupole Scans}},
  booktitle    = {Proc. IPAC'22},
% booktitle    = {Proc. 13th International Particle Accelerator Conference (IPAC'22)},
  pages        = {1003--1005},
  eid          = {TUPOST059},
  language     = {english},
  keywords     = {emittance, quadrupole, software, simulation, experiment},
  venue        = {Bangkok, Thailand},
  series       = {International Particle Accelerator Conference},
  number       = {13},
  publisher    = {JACoW Publishing, Geneva, Switzerland},
  month        = {07},
  year         = {2022},
  issn         = {2673-5490},
  isbn         = {978-3-95450-227-1},
  doi          = {10.18429/JACoW-IPAC2022-TUPOST059},
  url          = {https://jacow.org/ipac2022/papers/tupost059.pdf},
  abstract     = {{The emittance of a particle beam is a critically important parameter for many particle accelerator applications. Its measurements guide the initial tuning of an accelerator and are typically done using quadrupole or wire scans. Quadrupole scans are time-intensive, and it can be difficult to determine scan values that provide a good emittance measurement. To address this issue, we describe an adaptive quadrupole scan method that automates the determination of the scan range. With a given initial set of scanning values, our method adapts the range to capture the waist of the beam, and returns the Twiss parameters and a measure of the beam matching at the measurement screen. With the added capability to repeat beam size measurements when needed, this method provides a reliable measurement of the emittance even with sub-optimal initial conditions. To efficiently integrate these measurements into Python-based machine learning optimizations, the method was developed into a Python package, PyEmittance, at the SLAC National Accelerator Laboratory. We present the experimental tests of PyEmittance as performed at the Linac Coherent Light Source (LCLS) and the Facility for Advanced Accelerator Experimental Test (FACET-II).}},
}