<p align="center"><img src="docs/pygpe.png" alt="logo" ></p>
<h4 align="center">A fast and easy to use Gross-Pitaevskii equation solver.</h4>
## Description
PyGPE is a CUDA-accelerated Python library for solving the Gross-Pitaevskii equations for use in simulating
Bose-Einstein condensate systems.
- Documentation: https://wheelermt.github.io/pygpe-docs/
### Supported features
- Scalar, two-component, spin-1, and spin-2 BEC systems.
- 1D, 2D, and 3D grid lattices.
- GPU support.
- HDF5 data saving system.
- Method for generating vortices within the system.
### Requirements
- Python (3.10 and above),
- [h5py](https://github.com/h5py/h5py) (^3.6.0),
- [numpy](https://numpy.org/) (^2.0.0),
- Matplotlib (^3.8.2)
If using a GPU:
- CUDA Toolkit (>=11.2)
- [CuPy](https://github.com/cupy/cupy) (>=10.2.0).
## Installation
The simplest way to begin using PyGPE is through pip:
pip install pygpe
By default, PyGPE will use the CPU to perform calculations.
However, if a CUDA-capable GPU is detected, PyGPE will automatically utilise it for drastic
speed-ups in computation time.
## Examples
See [examples](examples) folder for various examples on the usage of the library.
Below is an animation of superfluid turbulence in a scalar BEC simulated using PyGPE on a $512^2$ lattice
for $N_t=200000$ time steps taking **~5 minutes** to complete on an RTX 2060.
<p align="center"><img src="docs/animation.gif" alt="logo" > </p>
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"description": "<p align=\"center\"><img src=\"docs/pygpe.png\" alt=\"logo\" ></p>\n\n<h4 align=\"center\">A fast and easy to use Gross-Pitaevskii equation solver.</h4>\n\n## Description\n\nPyGPE is a CUDA-accelerated Python library for solving the Gross-Pitaevskii equations for use in simulating\nBose-Einstein condensate systems.\n\n- Documentation: https://wheelermt.github.io/pygpe-docs/\n\n### Supported features\n\n- Scalar, two-component, spin-1, and spin-2 BEC systems.\n- 1D, 2D, and 3D grid lattices.\n- GPU support.\n- HDF5 data saving system.\n- Method for generating vortices within the system.\n\n### Requirements\n\n- Python (3.10 and above),\n- [h5py](https://github.com/h5py/h5py) (^3.6.0),\n- [numpy](https://numpy.org/) (^2.0.0),\n- Matplotlib (^3.8.2)\n\nIf using a GPU:\n - CUDA Toolkit (>=11.2)\n - [CuPy](https://github.com/cupy/cupy) (>=10.2.0).\n\n## Installation\n\nThe simplest way to begin using PyGPE is through pip:\n\n pip install pygpe\n\nBy default, PyGPE will use the CPU to perform calculations.\nHowever, if a CUDA-capable GPU is detected, PyGPE will automatically utilise it for drastic\nspeed-ups in computation time.\n\n## Examples\n\nSee [examples](examples) folder for various examples on the usage of the library.\nBelow is an animation of superfluid turbulence in a scalar BEC simulated using PyGPE on a $512^2$ lattice\nfor $N_t=200000$ time steps taking **~5 minutes** to complete on an RTX 2060.\n\n<p align=\"center\"><img src=\"docs/animation.gif\" alt=\"logo\" > </p>\n",
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