Acknowledge pyAMReX

Please acknowledge the role that pyAMReX played in your research.

In Publications

If a project using pyAMReX leads to a scientific publication, please consider citing it. This helps to keep in touch with the community, shows its use and supports the project.

Huebl A, Ananthan S, Grote D P, Sandberg R T, Zoni E, Jambunathan R, Lehe R, Myers A, Zhang W. pyAMReX: GPU-Enabled, Zero-Copy AMReX Python Bindings including AI/ML. software, 2023. DOI:10.5281/zenodo.8408733 github.com/AMReX-Codes/pyamrex

@misc{pyAMReX,
  author       = {Huebl, Axel and
                  Ananthan, Shreyas and
                  Grote, David P. and
                  Sandberg, Ryan T. and
                  Zoni, Edoardo and
                  Jambunathan, Revathi and
                  Lehe, Remi and
                  Myers, Andrew and
                  Zhang, Weiqun},
  title        = {{pyAMReX: GPU-Enabled, Zero-Copy AMReX Python Bindings including AI/ML}},
  year         = 2023,
  publisher    = {Zenodo},
  doi          = {10.5281/zenodo.8408733},
  url          = {https://github.com/AMReX-Codes/pyamrex},
  howpublished = {https://github.com/AMReX-Codes/pyamrex}
}

You can also add an acknowledgement, e.g.,

This research used the open-source code pyAMReX~\cite{pyAMReX}.
We acknowledge all AMReX contributors.

Further pyAMReX References

Myers A, Zhang W, Almgren A, Antoun T, Bell J, Huebl A, Sinn A. AMReX and pyAMReX: Looking Beyond ECP. submitted for review, 2024. arXiv:2403.12179

Works using pyAMReX:

Sandberg R T, Lehe R, Mitchell C E, Garten M, Myers A, Qiang J, Vay J-L and Huebl A. Synthesizing Particle-in-Cell Simulations Through Learning and GPU Computing for Hybrid Particle Accelerator Beamlines. Proc. of Platform for Advanced Scientific Computing (PASC’24), in print, 2024. arXiv:2402.17248
Huebl A et al., Exascale and ML Models for Accelerator Simulations. presentation at the 6th European Advanced Accelerator Concepts workshop (EAAC23), Isola d’Elba, Italy, Sep 17 – 23, 2023. DOI:10.5281/zenodo.8362549
Sandberg R T, Lehe R, Mitchell C E, Garten M, Qiang J, Vay J-L and Huebl A. Hybrid Beamline Element ML-Training for Surrogates in the ImpactX Beam-Dynamics Code. 14th International Particle Accelerator Conference (IPAC’23), WEPA101, in print, 2023. preprint, DOI:10.18429/JACoW-IPAC-23-WEPA101
Huebl A, Lehe R, Mitchell C E, Qiang J, Ryne R D, Sandberg R T, Vay JL. Next Generation Computational Tools for the Modeling and Design of Particle Accelerators at Exascale. 2022 North American Particle Accelerator Conference (NAPAC’22), TUYE2, pp. 302-306, 2022. arXiv:2208.02382, DOI:10.18429/JACoW-NAPAC2022-TUYE2