PyECLOUD was originally developed as a tool for the simulation of electron cloud build-up in particle accelerators. Over the last five years the code has become part of a wider set of modular and scriptable Python tools that can be combined to study different effects of the e-cloud in increasingly complex scenarios. The Particle In Cell solver originally included in PyECLOUD later developed into a stand-alone general purpose library (PyPIC) that now includes advanced features like a refined modeling of curved boundaries and optimized resolution based on the usage of nested grids. The effects of the e-cloud on the beam dynamics can be simulated interfacing PyECLOUD with the PyHEADTAIL code. These simulations can be computationally very demanding due to the multi-scale nature of this kind of problems. Hence, a dedicated parallelization layer (PyPARIS) has been recently developed to profit from parallel computing resources in order to significantly speed up the computation.

EVOLUTION OF PYTHON TOOLS FOR THE SIMULATION OF ELECTRON CLOUD EFFECTS / Iadarola, Giovanni; Belli, Eleonora; Li, Kevin; Mether, Lotta; Romano, Annalisa; Rumolo, Giovanni. - (2017), pp. 3803-3806.

EVOLUTION OF PYTHON TOOLS FOR THE SIMULATION OF ELECTRON CLOUD EFFECTS

Eleonora Belli;
2017

Abstract

PyECLOUD was originally developed as a tool for the simulation of electron cloud build-up in particle accelerators. Over the last five years the code has become part of a wider set of modular and scriptable Python tools that can be combined to study different effects of the e-cloud in increasingly complex scenarios. The Particle In Cell solver originally included in PyECLOUD later developed into a stand-alone general purpose library (PyPIC) that now includes advanced features like a refined modeling of curved boundaries and optimized resolution based on the usage of nested grids. The effects of the e-cloud on the beam dynamics can be simulated interfacing PyECLOUD with the PyHEADTAIL code. These simulations can be computationally very demanding due to the multi-scale nature of this kind of problems. Hence, a dedicated parallelization layer (PyPARIS) has been recently developed to profit from parallel computing resources in order to significantly speed up the computation.
2017
python, python tools, electron cloud, PyECLOUD, collider, CERN, FCC, LHC
04 Pubblicazione in atti di convegno::04b Atto di convegno in volume
EVOLUTION OF PYTHON TOOLS FOR THE SIMULATION OF ELECTRON CLOUD EFFECTS / Iadarola, Giovanni; Belli, Eleonora; Li, Kevin; Mether, Lotta; Romano, Annalisa; Rumolo, Giovanni. - (2017), pp. 3803-3806.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11573/1023535
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