A Python GPU-accelerated solver for the Gross-Pitaevskii equation and applications to many-body cavity QED
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.
Keywords
Cite
@article{arxiv.2404.14401,
title = {A Python GPU-accelerated solver for the Gross-Pitaevskii equation and applications to many-body cavity QED},
author = {Lorenzo Fioroni and Luca Gravina and Justyna Stefaniak and Alexander Baumgärtner and Fabian Finger and Davide Dreon and Tobias Donner},
journal= {arXiv preprint arXiv:2404.14401},
year = {2024}
}