pymultipact
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Low similarity (11.9%) to scientific vocabulary
Repository
Basic Info
- Host: GitHub
- Owner: Dark-Elektron
- License: mit
- Language: Jupyter Notebook
- Default Branch: origin
- Size: 33.5 MB
Statistics
- Stars: 1
- Watchers: 1
- Forks: 0
- Open Issues: 0
- Releases: 0
Metadata Files
README.md
PyMultipact
Multipacting is a phenomenon arising from the emission and subsequent multiplication of charged particles in accelerating radiofrequency (RF) cavities, which can limit the achievable RF power. Predicting field levels at which multipacting occurs is crucial for optimising cavity geometries. This paper presents an open-source Python code (PyMultipact) for analysing multipacting in 2D axisymmetric cavity structures. The code leverages the NGSolve framework to solve the Maxwell eigenvalue problem (MEVP) for the electromagnetic (EM) fields in axisymmetric RF structures. The relativistic Lorentz force equation governing the motion of charged particles is then integrated using the calculated fields within the domain to describe the motion of charged particles. Benchmarking against existing multipacting analysis tools is performed to validate the code's accuracy.
Workflow
The workflow begins by defining the domain using geometry_writer.py.
Next, the Maxwell eigenvalue problem (MEVP) is solved with the NGSolve finite element method (FEM)
framework via domain.compute_field. Collision detection and handling are performed in Python.
The multipacting metrics currently defined are the counter and enhanced counter functions.
To analyse the domain for multipacting, domain.analyse_multipacting is used.
Example - TESLA Cavity Geometry (Jupyter)
To get started, import the Project and Domain classes from domain. A Project object is used to define the project folder
and required to initialise a Domain object. A Domain object contains every object that can be found in
the domain. For example, a Particles object can be added to the Domain object. Certain physics
can also be defined in a Domain object. For example, the eigenmodes of the domain can be computed
by calling the <domain_object>.compute_field(). A Domain object also contains the necessary methods for
making plots and post-processing.
```python from pymultipact.domain import Project, Domain
create project
proj = Project() proj.createproject('<projectfolder>/TESLA')
define domain
domain = Domain(proj) ```
The defined domain contains, by default, the TESLA cavity geometry (mid-cell) [1]. One possible parameterisation of the mid-cell of an elliptical cavity geometry is given in the figure below.

The default elliptical cavity geometry installed with PyMultipact is the TESLA cavity mid-cell geometry. The following line of code can be used to define a new elliptical geometry boundary,
```python
import numpy as np
format: cell = [A, B, a, b, Ri, L, Req] in meters.
midcell = np.array([42, 42, 12, 19, 35, 57.7, 103.3])*1e-3 domain.defineellipticalcavity(midcell=mid_cell) ```
The geometry can be visualised using
```python
domain.draw() ```
A Domain object is meshed automatically with a default size if no specification
for the mesh is given after definition. The mesh can be regenerated for a specific mesh resolution and visualised
using
python
domain.mesh_domain(<maxh>)
domain.draw_mesh()
Next, compute and visualise the fields using
python
domain.compute_fields()
domain.draw_fields(mode=1, which='E')
where the which keyword is used to specify if the electric (E) or magnetic (H) field should be plotted.
The mode keyword specifies for which mode the field should be plotted. Mode indexing starts from 1.
Multipacting analysis is then carried out using
python
domain.analyse_multipacting()
The currently implemented multipacting metrics are the counter and enhanced counter functions. Results from multipacting can be plotted with the following lines of code.
python
domain.plot_cf() # to plot counter function
domain.plot_Ef() # to plot final impact energy
domain.plot_ef() # to plot enhanced counter function
The results can be compared with the result obtained in [2].
References
[1] Aune, Bernard, et al. "Superconducting TESLA cavities." Physical Review special topics-accelerators and beams 3.9 (2000): 092001.
[2] Zhu, Feng, et al. "High field multipacting of 1.3 GHZ Tesla cavity." This Workshop, TuP51. 2003.
Owner
- Name: Sosoho-Abasi Udongwo
- Login: Dark-Elektron
- Kind: user
- Repositories: 2
- Profile: https://github.com/Dark-Elektron
Computational scientist
Citation (CITATION.cff)
# This CITATION.cff file was generated with cffinit.
# Visit https://bit.ly/cffinit to generate yours today!
cff-version: 1.2.0
title: PyMultipact
message: >-
If you use this software, please cite it using the
metadata from this file.
type: software
authors:
- given-names: Sosoho-Abasi
family-names: Udongwo
email: soskey94@gmail.com
affiliation: University of Rostock
identifiers:
- type: url
value: 'https://github.com/Dark-Elektron/PyMultipact'
repository-code: 'https://github.com/Dark-Elektron/PyMultipact.git'
abstract: >-
Multipacting is a phenomenon arising from the emission and
subsequent multiplication of charged particles in
accelerating radiofrequency (RF) cavities, which can limit
the achievable RF power. Predicting field levels at which
multipacting occurs is crucial for optimising cavity
geometries. This paper presents a new open-source Python
code for analysing multipacting in 2D axisymmetric cavity
structures. The code leverages the NGSolve framework to
solve the MEVP for the cavity's resonant modes'
electromagnetic (EM) fields. The relativistic Lorentz
force equation governing the motion of charged particles
is then integrated using the fields within the cavity.
Benchmarking against existing multipacting analysis tools
is performed to validate the code's accuracy.
keywords:
- '#multipacting'
- '#ngsolve'
- '#cavity'
- '#radiofrequency'
license: MIT
version: 05.05.2024
date-released: '2024-05-05'
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Dependencies
- PyQt5 *
- icecream *
- matplotlib *
- mpi4py *
- networkx *
- numpy *
- numpydoc *
- oapackage *
- openpyxl *
- pandas *
- plotly *
- ply *
- psutil *
- pyparsing *
- pyqtgraph *
- pyvista *
- pyvistaqt *
- qtpy *
- qtvscodestyle *
- scikit-learn *
- scipy *
- seaborn *
- setuptools *
- swig-4.1.1 *
- sympy *
- termcolor *
- tqdm *
- vtk *