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arXiv · 2404.14401

A Python GPU-accelerated solver for the Gross-Pitaevskii equation and applications to many-body cavity QED

Lorenzo Fioroni·Luca Gravina·Justyna Stefaniak·Alexander Baumgärtner·Fabian Finger·Davide Dreon·Tobias Donner
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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.

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Lorenzo Fioroni, Luca Gravina, Justyna Stefaniak, Alexander Baumgärtner, Fabian Finger, Davide Dreon, Tobias Donner. 2024-04-22. A Python GPU-accelerated solver for the Gross-Pitaevskii equation and applications to many-body cavity QED. https://doi.org/10.21468/scipostphyscodeb.38

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