SciPost Submission Page
A Python GPU-accelerated solver for the Gross-Pitaevskii equation and applications to many-body cavity QED
by Lorenzo Fioroni, Luca Gravina, Justyna Stefaniak, Alexander Baumgärtner, Fabian Finger, Davide Dreon, Tobias Donner
Submission summary
| Authors (as registered SciPost users): | Davide Dreon · Lorenzo Fioroni |
| Submission information | |
|---|---|
| Preprint Link: | https://arxiv.org/abs/2404.14401v1 (pdf) |
| Code repository: | https://github.com/qo-eth/TorchGPE |
| Date submitted: | 2024-04-23 18:36 |
| Submitted by: | Dreon, Davide |
| Submitted to: | SciPost Physics Codebases |
| Ontological classification | |
|---|---|
| Academic field: | Physics |
| Specialties: |
|
| Approach: | Computational |
Abstract
TorchGPE is a general-purpose Python package developed for solving the Gross-Pitaevskii equation (GPE). This solver is designed to integrate wave functions across a spectrum of linear and non-linear potentials. A distinctive aspect of TorchGPE is its modular approach, which allows the incorporation of arbitrary self-consistent and time-dependent potentials, e.g., those relevant in many-body cavity QED models. The package employs a symmetric split-step Fourier propagation method, effective in both real and imaginary time. In our work, we demonstrate a significant improvement in computational efficiency by leveraging GPU computing capabilities. With the integration of the latter technology, TorchGPE achieves a substantial speed-up with respect to conventional CPU-based methods, greatly expanding the scope and potential of research in this field.