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BiBTeX citation export for THPDP060: Beam Instrumentation Simulation in Python

@inproceedings{gonzalez-berges:icalepcs2023-thpdp060,
  author       = {M. Gonzalez-Berges and D. Alves and A. Boccardi and V. Chariton and I. Degl’Innocenti and S. Jackson and J. Martínez Samblas},
% author       = {M. Gonzalez-Berges and D. Alves and A. Boccardi and V. Chariton and I. Degl’Innocenti and S. Jackson and others},
% author       = {M. Gonzalez-Berges and others},
  title        = {{Beam Instrumentation Simulation in Python}},
% booktitle    = {Proc. ICALEPCS'23},
  booktitle    = {Proc. 19th Int. Conf. Accel. Large Exp. Phys. Control Syst. (ICALEPCS'23)},
  eventdate    = {2023-10-09/2023-10-13},
  pages        = {1454--1459},
  paper        = {THPDP060},
  language     = {english},
  keywords     = {simulation, electron, electronics, instrumentation, framework},
  venue        = {Cape Town, South Africa},
  series       = {International Conference on Accelerator and Large Experimental Physics Control Systems},
  number       = {19},
  publisher    = {JACoW Publishing, Geneva, Switzerland},
  month        = {02},
  year         = {2024},
  issn         = {2226-0358},
  isbn         = {978-3-95450-238-7},
  doi          = {10.18429/JACoW-ICALEPCS2023-THPDP060},
  url          = {https://jacow.org/icalepcs2023/papers/thpdp060.pdf},
  abstract     = {{The design of acquisition electronics for particle accelerator systems relies on simulations in various domains. System level simulation frameworks can integrate the results of specific tools with analytical models and stochastic analysis. This allows the designer to estimate the performance of different architectures, compare the results, and ultimately optimize the design. These simulation frameworks are often made of custom scripts for specific designs, which are hard to share or reuse. Adopting a standard interface for modular components can address these issues. Also, providing a graphical interface where these components can be easily configured, connected and the results visualised, eases the creation of simulations. This paper identifies which characteristics ISPy (Instrumentation Simulation in Python) should fulfill as a simulation framework. It subsequently proposes a standard format for signal-processing simulation modules. Existing environments which allow script integration and an intuitive graphical interface have then been evaluated and the KNIME Analytics Platform was the proposed solution. Additionally, the need to handle parameter sweeps for any parameter of the simulation, and the need for a bespoke visualisation tool will be discussed. Python has been chosen for all of these developments due to its flexibility and its wide adoption in the scientific community. The ensuing performance of the tool will also be discussed. }},
}