Metadata-Version: 2.4
Name: wakis
Version: 0.7.0
Summary: 3D Electromagnetic Time-Domain wake and impedance solver
Home-page: https://wakis.readthedocs.io/
Download-URL: https://pypi.python.org/pypi/wakis
Author: Elena de la Fuente et al.
Author-email: elena.de.la.fuente.garcia@cern.ch
License: Apache 2.0
Project-URL: Bug Tracker, https://github.com/ImpedanCEI/wakis/issues
Project-URL: Documentation, https://wakis.readthedocs.io/en/latest/index.html
Project-URL: Source Code, https://github.com/ImpedanCEI/wakis/wakis
Classifier: Development Status :: 4 - Beta
Classifier: Programming Language :: Python
Classifier: Programming Language :: Python :: 3.9
Classifier: Programming Language :: Python :: 3.10
Classifier: Programming Language :: Python :: 3.11
Classifier: Programming Language :: Python :: 3.12
Classifier: Programming Language :: Python :: 3.13
Classifier: Programming Language :: Python :: 3.14
Classifier: Operating System :: OS Independent
Classifier: Intended Audience :: Science/Research
Classifier: Topic :: Scientific/Engineering :: Physics
Description-Content-Type: text/markdown
License-File: LICENSE
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<img src="https://github.com/ImpedanCEI/wakis/blob/main/docs/img/wakis-logo-pink.png" alt="wakis-logo-light-background" width="240">

> Open-source **Wak**e and **I**mpedance **S**olver

[![Documentation Status](https://readthedocs.org/projects/wakis/badge/?version=latest)](https://wakis.readthedocs.io/en/latest/?badge=latest)
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[![DOI](https://zenodo.org/badge/DOI/10.5281/zenodo.15527405.svg)](https://doi.org/10.5281/zenodo.15527405)


`wakis` is a **3D Time-domain Electromagnetic solver** that solves the Integral form of Maxwell's equations using the Finite Integration Technique (FIT) numerical method. It computes the longitudinal and transverse **wake potential and beam-coupling impedance** from the simulated electric and magnetic fields. It is also a multi-purpose solver, capable of simulating planewaves interaction with nano-structures, optical diffraction, and much more!

## About
🚀 Some of `wakis` features:
* Wake potential and impedance calculations for particle beams with different relativistic $\beta$
* Material tensors: permittivity $\varepsilon$, permeability $\mu$, conductivity $\sigma$. Possibility of anisotropy.
* CAD geometry importer (`STL` & `STEP` format) for definition of embedded boundaries and material regions, based on [`pyvista`](https://github.com/pyvista/pyvista)
* Boundary conditions: PEC, PMC, Periodic, ABC-FOEXTRAP, Perfect Matched Layers (PML)
* Different time-domain sources: particle beam, planewave, gaussian wavepacket
* 100% python, fully exposed API (material tensors, fields $E$, $H$, $J$). Matrix operators based on `numpy` and `scipy.sparse` routines ensure multithreaded calculations using Intel's `mkl-service`.
* 1d, 2d, 3d built-in plotting on-the-fly
* Optimized memory consumption & GPU acceleration using `cupy/cupyx` on double and *single* precision: added in[#v0.6.1](https://github.com/ImpedanCEI/wakis/releases/tag/v0.6.1)
* CUDA-aware MPI parallelization with `mpi4py` and `ipyparallel`: added in[#v0.6.0](https://github.com/ImpedanCEI/wakis/releases/tag/v0.6.0)
* Snappy Smart mesh added in [#v0.6.2](https://github.com/ImpedanCEI/wakis/releases/tag/v0.6.2)

🧩 Other complementary tools in the ecosystem:
* Wakefield extrapolation via broadband resonator fitting with PIML [`iddefix`](https://github.com/ImpedanCEI/IDDEFIX) evolutionary algorithms
* Non-equidistant Filon Fourier integration with [`neffint`](https://github.com/ImpedanCEI/neffint)
* Beam-induced heating estimation due to impedance with [`bihc`](https://github.com/ImpedanCEI/BIHC)

📣 Tag and version changes are decribed in each Wakis [Github Release](https://github.com/ImpedanCEI/wakis/releases)

* For specific needs, please contact the developer 👩‍💻👋: elena.de.la.fuente.garcia@cern.ch

## How to use
📖 Documentation, powered by `sphinx`, is available at [wakis.readthedocs.io](https://wakis.readthedocs.io/en/latest/index.html)

Check 📁 `examples/` and `notebooks/` for different physical applications:
* Planewave interacting with a PEC or dielectric sphere
* Gaussian wavepacket travelling through vacuum / dielectric
* Custom perturbation interacting with PEC geometry
* Wakefield simulation of accelerator cavity on CPU, GPU and with MPI

Check 🌐📁 [`SWAN_tutorial/`](https://github.com/ImpedanCEI/SWAN_tutorial) for hands-on notebook examples ready to run on CERN's SWAN service's GPUs (A100, Tesla T4):

[<img class="open_in_swan" data-path="your_submodule_name" alt="Open this Gallery in SWAN" src="https://swanserver.web.cern.ch/swanserver/images/badge_swan_white_150.png">][gallery_url]

[gallery_url]:https://cern.ch/swanserver/cgi-bin/go?projurl=https://github.com/ImpedanCEI/SWAN_tutorial.git

Check 🌐📁 [`wakis-benchmarks/`](https://github.com/ImpedanCEI/wakis-benchmarks) for beam-coupling impedance calculations & comparisons to the commercial tool *CST® Wakefield solver*:
* PEC cubic cavity below cutoff (mm) and above cutoff (cm)
* Conductive cubic cavity below cutoff
* Lossy pillbox cavity (cylindrical) above cutoff
* Simulations using beams with different relativistic $\beta$

Check 🌐📁 [`BE-Seminar-demo/`](https://github.com/ImpedanCEI/CEI-logo) for a complete demonstration of Wakis usage.

## Installation
Wakis supports `Python 3.9 - 3.14` and can be installed in any `conda` or `venv` environment.

📖 **For a detailed installation guide (GPU, MPI setup, FAQs), check our [documentation](https://wakis.readthedocs.io/en/latest/installation.html).**

### Install via PyPI
For basic usage, simply run:
```bash
pip install wakis
```
For additional features, including **interactive 3D plots in Jupyter notebooks** and Wakis' satellite packages, use:
```bash
pip install wakis['all']
```
To use the *version-frozen* environment specified in `requirements.txt`, with python 3.9-3.11 do:
```bash
conda create --name wakis-env python=3.11
conda activate wakis-env
pip install wakis['notebook']
```

To install Wakis from the source, clone the repository and install it in *editable* mode:
```bash
git clone https://github.com/ImpedanCEI/wakis.git
cd wakis
pip install -e .
```

### Install via Docker
A pre-built [Docker image of Wakis](https://hub.docker.com/r/edelafue/wakis) is available for easy setup and reproducibility.

```bash
sudo docker pull docker.io/edelafue/wakis:latest
sudo docker run --rm -it docker.io/edelafue/wakis:latest /bin/bash
```

💡 **Have a bug, feature request, or suggestion?** Open a [GitHub Issue](https://github.com/ImpedanCEI/wakis/issues) so the community can track it.

🛠️ **Want to contribute?**  To merge your changes into `main`, create a **Pull Request (PR)** following our [PR template](https://github.com/ImpedanCEI/wakis/blob/main/.github/pull_request_template.md).

## Motivation
🎯 The determination of electromagnetic wakefields and their impact on accelerator performance is a significant issue in current accelerator components. These wakefields, which are generated within the accelerator vacuum chamber as a result of the interaction between the structure and a passing beam, can have significant effects on the machine.
These effects can be characterized through the beam coupling impedance in the frequency domain and wake potential in the time domain. Accurate evaluation of these properties is essential for predicting dissipated power and maintaining beam stability.
`wakis` is an open-source tool that can compute wake potential and impedance for both longitudinal and transverse planes for general 3D structures.

* 🌱 `wakis` was firstly presented at the **International Particle Accelerator Conference in 2023** (IPAC23) as a post-processing tool: https://doi.org/10.18429/JACoW-IPAC2023-WEPL170

* 🌳 It has now evolved from a post-processing tool to a full 3D electromagnetic, time domain solver; and has been presented at the **ICAP24: The 14th International Computational Accelerator Physics Conference in 2024**: https://indico.gsi.de/event/19249/contributions/82636/

* 🌸 A dedicated contribution was presented at **IPAC'25: The 16th International Particle Accelerator Conference**: https://inspirehep.net/literature/3101186

## Citing `Wakis`
🔖 Each Wakis release is linked to a [Zenodo](https://zenodo.org/records/15011421) publication under a unique [DOI](https://doi.org/10.5281/zenodo.15011421). If you are using Wakis in your scientific research, please help our scientific visibility by citing this work:

> [1] E. de la Fuente Garcia et. al., “Wakis”. Zenodo, 2025. doi: https://doi.org/10.5281/zenodo.15527405

---
### Tests badges
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